1. business and industrial
2. agriculture and forestry
3. organic farming

A Characteristic-Approach to Adoption: The Case of
Irnprovcd Rice Varieties in S~~ther~lSenegal
bY
SAMBA SALL
B. S., University of Abidjan, tvory Coast, 1975
Agronomy Degree, ENSA, Abidjan, ivory Coast, 1977
M. S., University of Laval, Quebec, Canada, 1980
A OISSERTATION
Submitted in partial fuffiilment of the
requirements for the degree
DOCTOR OF PHILOSOPHY
Department of AgricuItural Economies
College of Agriculture
KANSAS STATE UNIVERSITY
Manhattan, Kansas
1997
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Abstract
This study apptieda technology-characteristic approach to the adoption of improved
rice vaneties in Southem Senegal. The objective was to test the hypothesis that both farm,
farmers’ characteristics, and farmers’ perceptions of technology-specific characteristics
signi~~ntty condition the technology adoption decision. Earlier studies bave not incorporated
the characteristics of the technology in the analysis of adoption. Different measures of
performance were used to evatuate the behavior of the improved varieties, and seven
characteristios eticitedfrom farmers were used to measure the extent to which the improved
varieties meet the expectations of farmers. A Tobit mode1was used to test the hypothesis,
using a stratified random sample of 400 farmers, The results reveal that the application of
fertilizer is the major determinant of the Yield Gap. Most of the improved varieties are
superior to the focal in better environments, but do not perform well in poor environments.
One of the causes of slow progress in rice production is the undue attention given to
deveioping technologies for physical favorable environments. fmproved and local varieties
have different responses to fertilizer, and under the fann levelconditions, response curve
cross-over does occur for many varieties. Hence, the ordering of varieties with respect to
yield wili vary at high and low management levels. The resuits also show that famers use
different criteria to discriminate among varieties. Farmers demandtice varieties with short
maturation period, tait stature, good resistance to soii-related constraints, and good cooking
quaiity. The study fînds that farmer-specific variables (info~ation, participation in villagelevef organization, acoess to credit, age) and technology-specific factors (cycle, resistance
to stress, height, cooking quality) are significant in explaining farmers’ adoption of improved
varieties.
\
The mode1results show that farmer perceptions of the tech~o~ogy-specj~c attributes of the
varieties are the major factors determining adoption. The response to changes in these
attributes is relatively more elastic than the response to changes in the farmer-specifïc
factors. Therefore, research and extension that shape the adoption of improved
technologies, need to consider farmers’ perceptions of technology-speciftc attributes in their
pfograms.
Table of CuiPtents
........................................................................................................................
Table of Contents ................................................................................................
tist of Figures ......................................................................................................
tist of Tables ........................................................................................................
A~kno~~edgments................................................................................................
List of Acronyms .................................................................................................
l.Introduction .................................................
1.1 NeedfortheStudy .......................................
1.2 Objectives of the Study ...................................
1.3 Organization of the Study .................................
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vii
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4
5
2. Southern SenegaLState of the Art, Previous Research and Extension Work.. 7
2.1 The Casamance Region in the Senegalese Economy . . . . . . . . . . . . 7
2.2 Physical Environment and Crop Production , . . . . . . . , . . . . . . . . . . 9
2.3 Social Organization of Labor and Farm Size . . . . . . . . . . . . . . . , , 12
2.4 Rural Credit, input Availability and Farm Equipment . . . . . . . . . . . . 17
2.5 Farm fncome and Food Availability . . . . . . . . . . . . . . , . . . . . . . . . . 19
2.6 Measures of Farm Performance in Lower Casamance . . . . . . . . . . 20
2.7 Agricuitura~Research and Technology Choices
31
2.7.1 Rice Research in Casamance . . . . . . . . . . . . . . . . . . . . . . 32
2.7.2 Farming Systems Research in Lower Casamance
. . . , 35
2.7.2.1 Agricultural Zones and Research Priorities . . . . . 35
2.7.2.2 Major Achievements of FSR in Lower Casamance 38
2.8 Agricultural Extension . . . . . . . . . . . . . . . . . . <. . . . . . . . . . . . . . . . 43
2.9 Adoption of fmproved Technology in Lower Casamance . . , . . . . . 45
3. Framework for Technology Adoption Analysis . . . . . . . . . . . . . . , . . . . . . , . 49
3.1 Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...49
3.2 Models of the Adoption of Individual Farms , . . . . . . . . . . . . . . . , . . 50
3.3 Models of Aggregate Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.4 Empirical Studies of Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . , 54
3.5 The Approach Used in the Study . . . . . . . . . . . . . . . . . . , . . . . . . . . 58
3.51 The Yield Gap between On-Station and
On-Farm Conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.5.2 Adaptability Analysis . . . . . . . . . , . . . . . . . . . . . . . . . . . . . 65
3.5.3 Response to Improved Management . . , . . . , . . . . . , . . . . 67
3.5.4 Farmers’ Quantitative Assessment of Rice Varieties . . . . . 68
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3.5.5 Theory of Farmer Choice Behavior . . . . . . . . . . I . . . . . . . 73
4, The Data and Variable Definition Procedures . . . . . . . . . . . I . . . . . . , , . .
4.1 Secondary Data Sources . . . . . , . . . . . . . . . 1. . . . .
4.2 Primat-y Data Collection and Survey ~ethodology .
4.3 Rice Varie@ Categories . . . . . . I . . . . . . . . . . . . . . .
4.3 Variables Definition I . . . . ~ . . . . . . . , . . . . . . , . . . .
4.4 Main So~~oe~onorn~c
Characteristics of Sample
Farms and Farmers . . . . . . . . . . . . . . . . , . . . . . . . . . < .
79
79
82
86
87
5. Measures of Rice Variety Performance ............................
5.1 The Station -to-Farmer Yield Gap ..........................
5.1 .l Farmers’ Practices and Rice Yield ..................
5.2 Adaptability of Rice Varieties .............................
5.3 Response to Fertilizer and the Issue of Response Curve ......
5.4 Farmers’ Evaluation of Rice Varieties ......................
5.4.1 Farmers’ Perceptions About Rice Varieties ...........
54.2 Quantitative Assessment of Rice Variety Performance . .
97
97
1OI
107
110
114
1I4
119
6. Determinants of Adoption: Empirioat Results and fmplications . . . . . . . . .
6.1 Farm, Farmer-Specific Factors and the Adoption
of Improved Rice Varieties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2 Technology-Specific Factors and Adoption . . . . . . . . . . . , . . . . . .
6.3 Farm, and Farmer Specific Factors, Technology-Specific
Variabfes and Adoption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.4 Quantitative implications for Research
and Devefopment Strategies . . . . . . . . . . . . . . . . . . . . . . , . . . . . .
6.5 Future Directions in Rice Breeding . . . . , . . . . . . . . . . . . . . . <. . .
127
141
154
7. Conclusions, Jmpkations and Suggestions for Future Research .......
7.1 Summary of Results ....................................
7.2 Policy Implications .....................................
7.3 Limitations of this Study .................................
7.4 Needs for Further Research .............................
158
160
165
171
172
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128
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140
References .. . .. . .... .. .. ... <. .. ... .. .. .. .. .. ... . .. .. ... .. .. .. .. .. . .. ... .. .. . .. .. . .. .. .. .. .. .. .. . .. .. .. . .. .. .. .. .. .176
Appendices .. .. . ... .. ... .. ....a.... .. .. .. ... .. .. .. .. .. .. .. .. ... . .. .. .. .. .. .. . .. .. .. .. .. . ... .. .. . .. .. . .. .. .. .. .. . .. 189
hist of Figures
Figure .............................................................................................................
Page
2.1: Map of Senegal and Agricul~uralzones in Lower Casamance ................. .JG
4.1: Location Map of Sample Area in Lower Casamance ...............
85
5.1: Yields of Varieties Plotted on El................................................................
“rO8
5.2:
Stability Type C ........................................................................................
.108
5.3:
Stability Type A ........................................................................................
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List of Tables
2.1
Area Cultivated (‘000 ha) and Production ~IOOO~T) for the
Major Crops in the Casamance Region (198589). , . . . . . . , , , . , . . , , . . 9
2.2
Rainfalf Pattern {mm), Area Cultivated (ha) and Yieid Level in
Lower Casamance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , , ~. . . . . . .l 1
2.3
Family Labor Organization, Cropping System, and Labor Utilization
According to Location..,...*. ~~...........................<......<,...<..,.....,..,....<.......,.. 14
2.4
Average Yield (kglha) of Paddy by Position in the Toposequence , . , . . 17
2.5
Resource use, Costs and Income per Farm in Lower Casamance
. .. ....<....20
(1982-86)............................................................................,.,......
2.6
Descriptive Statistics of Efficiency Measures for a Sample
of Farmers in Casamance (1983-1984) . . . . . . . . . . , , , , . . , . , . . . , , . . 24
2.7
Distribution of the Efficiency Measures for a Sample of Farmers
across the Three Major Farming Systems in Casamance . . . . . . . . . . . . 25
2.8
Tobit Results Relating Efficiency Measures to Farm Characteristics . . . 27
2.9
Rates of Adoption 1% of farmers) of Three Major Technical Components
for Groundnut (P), Maize (Mf and Millet (Mi) in Casamance (1991-1994). 46
2.10 Rates of Adoption (% of farmers) of Three Major Technical Components
for Rainfed Rice (RR), Phreatic Rice (PR} and Aquatic Rioe (AR) in
Casamance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.1
Treatments Included in the Factorial Experiment . . . . . . . . . , . . . . . . . . 63
3.2
The Response Matrix . . I . . . I . . . . . . . . . . . . . . . . . . . . +. . . . . I . . , . . 69
3.3
The Weighting Matrix, . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
4.1
Expected Sign for the Relationship between Farm and Farmer
Characteristics and the Adoption of Improved Rice Varieties. . . . . . , . . 88
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4.2
Expected Sign for the Relationship between Technology Characteristics
and the Adoption of fmproved Rice Varietjes in Casamance . , . . , . . . , 91
4.3
Descriptive Statistics on the Variables Used in the Empirical Mode1 . . 92
4.4
Distribution of Rice Area and Improved Variety Use in the Sample
5.1
Total Yield Gap in kglha for Rice Varieties Setween Tria!s at Djibel-r
Station and ISRA Farmers’ Tests in Casamance, 1982-87. . . , . . . . , , 98
5.2
Yield Gap II and Contribution of each Factor in kglha . . . . . . . . . . , . . 99
5.3
Expected Sign of the Relationship between Farmers’ Practices
and the Yield of Rice Varieties. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
5.4
Double Log ResuEtsof Yield Determinants . . . . . . . . . . . . . . . . . . . . . 105
5.5
Stabiiity Analysis for Improved Rice Varieties at Zero Fertilizer . . . . . . 110
5.6
Stability Analysis for lmproved Rice Vafieties at IOON Fertilizer Level 1‘IO
5.7
Estimates of Response Functions for Rice Varieties . . . . . . . . . , . . . . 1q2
5.8
Results of Hypothesis Testing for Response Curve . . . . . . . . . . . . . . . 113
5.9
Adoption Level and Experience with Improved Varieties in
Casamance(l996) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ...115
. . . 95
5.70 Sources of Farmers’ information (Percent of Farmers) in
Casamance (1996) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . , , . 115
5. II
Farmers’ Ranking of Varietal Characteristics (Percent of Farmers) . , . 118
5.12 Ranges of indices for the Sets of Weights . . . . . . . . . . . . . . . . . . . . . . 120
5.13 Pearson Correlation Coefficients for Attainment indexes
. . . . . . . 121
5.14 Spearman Correlation Coefficients for Attainment Indexes 1. . . . . . . . 121
5.15 Attainment Indices for the Main Six Varieties . . . . . . . . . . . . . . , . , . . . 122
5.16 Demand Indices for the Main Six Varieties . . . . . . . . . . . . . . , . . , . . . . 123
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5.17 Suppfy Indices for the Main Six Varieties . . . . . . . . . . . . . . . . . , . . . ~. 123
5.18 Gycle(days), H~ight(~m), and Tiilering Ga~acity(pan/m*)
for the 5 Varieties. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
6.1
Estimated Results for Farmer Adoption Mode1Using Fat-m
and Farmer Specific Factors . . . . . . . . . . . . . . . . . . . . . . . . , . . . , . , 129
6.2
Estimated Resuits for Farmer Adoption Mode1Using
Technology-Specific Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
6.3
Estimated Results for Farmer Adoption Mode1Using Farm
and Farmer Specific Factors and Technology-Specific Variables. . , . 142
6.4
Tobit Total Effects for Changes in the Farmer-Gharacteristics and
Technology-Specific Gharacteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 144
6.5
Prioritization of Breeding Objectives Among
Researchers and Farmers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
vi
I am much indebted to Dr David Norman, my major professor, for his daily
invatuable guidance, assistance and enthusiastic support during this thesis. L-lis
experience on Senegalese agr~~ulturairesearch and development policies has
been resourceful to me.
f wish to express thanks to Dr Allen Featherstone, 5~ f3ryan Schurte, and Dr
Len Bloomquist,my committee members, for their help and encouragement during
this thesis preparation,
My thanks go to the Department of Agricultural Economies, Kansas State
University, for the invaluable education that I received during my training.
My gratitude goes to ISf?Aand USAID, for giving me a graduate scholarship.
~ithout the schoiarship, I would not have been able to complete this work.
I am thankful for my colleagues and friends: Dr Mulumba Kamuanga, 5r
Joshua Posner, Dr Yamar Mbodj, Alphonse Faye, Mamadou Lo, Afioune Fall,
Lamine Sonko, Boubacar Barry, Souleymane Dialfo, Souleye Badiane, Ibrahima
Thomas, Saliou Djiba, MamadouCamara, Marcel Diatta, Lansana Sonko, Ousmane
Mane, Jean Pierre Malou, Magatte Diouf, Daro Niang, and 8ole Tamba.
I am indebtedto my parents, my spouse Fatou Gueye Sali, and my children,
Mamy, Cheikh, Lobe and Awa.
Samba Sali
t
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LIIIs,”
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List of Acronyms
CNCAS
Senegalese
AgriculturalCredit Bank
CNRA
NationalCenterfor AgriculturalResearch
CIMMYT
Tnernational
Maize andWheatImprovementCenter
DERBAC
Projet de DeveloppementRural de la Casamance
FSR
FarmingSystem Research
GP
ProducersGroup
CIE
Groupementd’Interet Economique
GOS
Governmentof Senegal
HYV
High YieldingVariety
ISRA
Senegalese
Institute for AgriculturalResearch
IRAT
FrenchInstitute for TropicalAgriculturalResearch
IRRI
InternationalRice Researchfnstitute
XITA
InternationalInstitute for TropicalAgriculture
LIC
Low IncomeCountry
NPA
New AgriculturalPolicy
NGO
Non-GovemmentalOrganization
PAPEM
Point d’Appui pour L’ExperimentationMultilocale
PNVA
NationalAgriculturalExtensionProject
USAID
United StatesAgencyfor InternationalDevelopment
UE
UnitesExperimentales
RDA
RegionaiDevelopmentAgency
SONED
SocieteNationaled’Etudeset de Development
SOMIVAC
RegionalParastatalfor Developmentof the Casamance
WARDA
West African Rice DevelopmentAssociation
I
iX
Chapter
1
Technology may be broadly defined as the “skiils, knowledge and
procedures for making, using, and doing useful things” (Henry, 1987). Technology
has had a considerabfe impact on the growth of output of the more developed
countries. But in recent years, there have been inereasingconcerns that agriculture1
technology has not been adequatelybenefiting the world’s smalt-soalefarmers. One
argument is that extensionhas been ineffective in reaching small farmers. Another
is that small farmers are SOtraditional that they do not want to change their habits.
Finally another major concerns have arisen that research and extension are
produ~ing technologies not appropriate to the conditions of small farmers.
This study Willaddress the factors affecting the adoption of new technology
in a subset of the agricuttural sector in Senegal. The study is focused on the
adoption of high yielding varieties of rice. The research Will investigate the
determinants of adoption of the WWS of rice. More specificalty, the study
hypothesizes that both socioeconomic(e,g., age, education, family size, farm sire),
physicai (Le., productionconditions)faetors, and specific technology characteristics
detetmine whether a farmer will or Will not adopt a new rice technology.
t
1
1.1 Need for the Study
Although vast regional differences exist, rice is an important source of
nutrition in Senegal. Rice is by far the main staple food consumed in large
quantities, particularly for the noon time meal. Nationally, rice accounts for 34
percent of the volume of cereal consumption,making up 54 percent and 24 percent
of the volume of oereals consumedamong urban and rural populations, respectively
(L%AID, 1991). National annual per capita consumption averaged 62.7 kg in 1990
(USAID, 1991). imports accounted by 84.5% of the national rice consumption in
1990 while the remaining was produced domesticly. This domestic production is
located in two major areas:
(1)
The Northern region where large irrigation schemes are being operated.
(2)
The Southern region (Casamance region), a traditional rain-fed growing rice
region.
The organizationof rice production in the Casamance region is closely tied
to the social and religious stratificationof the cummunity (Linares, i 983). Compared
to the rest of the country, it has the highest annual per capita consumption of rice,
averaging 82 kg (SCNED, 1983). About 30 percent of the domestic production
takes place in the swamps and phreatic lands of the Casamance (USAID, 1991).
However since 1973, the rice cropping systems have faced some physical
constraints; persistent patterns of drought, salt intrusion, and local varieties
progressive~yless adapted to the changing environment.
In 1984, as a result of the deteriorating food situation in the country, the
*
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Govert~ment stated in a plan its intentions to increase food self-sufficiency by the
year 2000. For rice, this could be achieved by enhancing domestic production. In
the region of Casamance the strategy was to increase rice production mainly
through the introduction of modern technologies. The building blocks were
improved seeds, chemical fertilizers, pest control, and land improvements. Unless
domestic rice production increases rapidly, rising demand for rice Will lead to
increased dependency on imports. For this reason, the Introduction of new rice
cuttivars with high yields and short duration Will become increasingly important. A
growing number of research programs (ISRA in collaboration with WARDA, IlTA )’
and extension projects (PIDAC, DERBAC)* have focused on the development and
diffusion of improved rice varieties. From 1982 to 1994, different varieties, for
different parts of the toposequencehave been tested by researchers and extension
agençies through multitocational, on-farm and adoption Mals.
ISRA’s role is to diagnose farm-level constraints, to develop and validate
technologies, and to deiiver these extension re~mmendations to the extension
services. While ISRA has developed and tested varieties and cultural
recommendations for rice production, most of these technologies do not reach
farmers. TO date, linkages between research and extension have been seen as the
major weakness in improving agricultural production in Senegal (UASID, 1991). lt
‘Institut Senegalais
de RecherchesAgricoles(ISRA); West Aftican RiceDevelopment
Association(WARDA); InternationalInstitute for TropicalAgriculture(IITA)
2ProjetIntegre de DevelopementAgricoIede la Casamance
(PIDAC); Projet Autonome
de DevekopmentAgricole de la BasseCasamnce(DEMAC).
3
is also possible that this weakness lies within ISRA and between ISRA and farmers,
Despite the obvious importance of these research programs and extension
projccts in the devetopment of rice production, there are relatively few detailed
studios of improved rice variety use at the farm tevel, and atmoçt none that examine
the rates of adoption and the factors that affect this adoption. Information and
analysis provided by such studies could be used to examine the poficy orientations
and the adoption issues outlined above, They should help ISRA rice breeders
judiciously Selectobjectives,criteria, and design innovations with a high probab~~ity
of being adopted by a large number of rice fafmers in the region. The study could
be an important step for the proposed impact study that ISRA is committed ta
conducting.
A.2 Objectives
of the Study
Therefore the research Willfocus on the fofluwing general questions:
What cari we learn from pas2 experiences with the development and
diffusion of improved rice varieties that are relevant to improving the design
of agriculturaf poticy and future research programs?
What are the main factors that affect farmers’ decision making in selecting
innovationsthat Willhelp tSRA better understand farmer’s effective demand
of new technotogy?
In the fight of those general questions, five speciflc objectives cari be delineated:
,IV
Describe and evaluate the performance of research pragtams, and projects
#
4
that shaped the development and diffusion of improved rice varieties from
1982 to 1994.
(2)
Present an analysis of agr~norni~data using yield gap analysis, ~daptabiljty
analysis, and response curves.
(3)
Measure the observed rates of adoption of improved rice varieties by
farmers involved in different programs3.
(4
Determine the factors that affect the probability and intensity of adoption of
improved rice varieties.
(5)
Draw some implicationsfor the design and impt~mentatio~~
of future research
ptograms and development projects relating to rice.
1.3 Urganization
of the Study
The organization of the study is as foilows. Chapter 2 discusses the
problems and circumstances faced by rice producers in Southern Senegaf. It also
highlights the main results coming out of research and extension programs in the
study area. Chapter 3 discusses the approaches and major findings in light of the
existing Iiterature on adoption, and develops the framework for adoption anaiysis
for the study. Chapter 4 discusses the survey methodology and the data from the
five agriculturai situations of Southern Senegal. The samplingframe, characteristies
of the respondents and descriptions of the variables used, are also included. In
31SRAresearchprograms(FarmingSystemResearch,Rice program);PIDAL and
DERBAf frice intensificationprograms).
5
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Chapter 5, data on responses to improved praçtice under farmers’ conditions
obtained from the analysis of on-farm experimentk conducted by ISRA in the area
are used to assess the performance of the new rice varieties. Different indexes,
measuringthe importance of different varietal characteristics, and the quality of the
varieties with respect to the given characteristics, are computed. Chapter 6
discusses the major determinants of rice varieties adoption in Southern Senegal,
and provides some implicationsfor research and devetopment. It also compares the
empirical results of the study to ather low income country (LIC) studies. The last
chapfer of the study gives conclusions, poficy implications for the design and
~mplernentati~f~of future research programs and development projects relating to
rice production.
Chapter 2
Research and Extension Work
The purpose of this chapter is to briefly discuss the current resoutce base,
çharacteristics, performance, problems and prospects of rice producers in Southern
Senegal which provide a background for the environment in which fat-mers make
production decisions. Major achievsments of research and extension programs in
the study area are aiso included.
2.1 The Casamance Region in the Senegafese Economy
Senegalcovers 196,722 square kiiometers. The national territory is divided
into ten administrative regions, each with three departments. The ?988 census of
the population counted 6.9 million peopie, 39 percent of whom lived in urban areas.
Senegal’s economy is agriculturally based. In spite of poor soils and irregular
rainfall which renders agricuftural production risky, this sector dominates the entire
economy. Although the primary sector has declined in importance relative to the
other sectors (from 26.5 percent of real EDP during 196046 to 21.3 percent during
#
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the 198589 period), it continues to generate much of the variation in economic
growth, a large part, but not all, of which cari be attributed to rainfall variation. The
rural sector accounts for two-thirds of Senegal’s total active popul~tjon, Millet,
sorghum, maize, rice and cowpeas are the main food crops while groundnuts and
Lotton constitute the cash crops. The country is administratively divided into ten
regions: Cap-Vert in the west; Diourbel, Thies, Louga and Kaolack in the centerwest or Groundnut Basin; the Fleuve along the Senegal River; Tambacounda in the
east; Kolda and the Casamance regions in the south.
The Casamance (Region of Ziguinchor, or Lower Casamance) is one of the
regions with the greateçt potential for expanded rainfed agriculture in the country
(Table 2.1). The total land area represents 14 percent of the country land area,
while 15 percent of the cropped and fallow land in the country is located in the
Casamance region. It possesses a wide range of development alternatives when
efforts are taken to improve the marketing~transpo~ation sector and the
management of natural resourGes, especially lands susceptible to erosion. The
region also has the largest forest area, but pressure from “mining” newly cfeared
land for trop production and to provide woodfuel continues to place more and more
land at risk. The region provides an environment under which a wide variety of
crops cari be grown. Because of its relatively high productive potential, the region
has been selected by the Government of Senegal (GOS) as a priority development
area with emphasis on expanding rice and maize production. Recfaiming and
protecting soils from salt intrusion by the construction of anti-salt dikes is the major
Ir
8
strategy to ensure rice production. Total population amounts to 398,000 with 62
percent still living in the rural area (Senegat’ 1988 population census).This
represents 18.4 percent of the rural population in the countty. USAID (1991>
projecststhat in 1996 the populationWillamount to 490,000 and that only 58 percent
Will stilt live in rural areas. The age pyramid in Casamance is particularly skewed
toward the very ofd and very Younggroups.
Table 2.1: Area Cultivated (‘000 ha) and Production ~I~O~~T) for the Major Crops
in the Casamance Region (198589).
1
-,
Casamance region
Senegal
1
Millet
Maire
Paddy Rice
24.9 (32.76)
32.6 (22.08)
1
Groundnut
Source: GOSIMDRWDS
76
I
1 25.5 (3.23)
1 28.5 (3.57)
1 788
-.--l
and USAID (1991). Numbersin parenthesesare the percentof the
national figures.
The Diola (85%) and the ~anding(5O~)constitute the major ethnie groups. Althoug~
numerically inferior, the Manding have historically had a strong cultural and
religious inftuence north of the Casamance River.
2.2 Physical Environment
and Crop Production
The Casamanca Region is situated in Southern Senegal, in the maritime part
of the natural region of Casamance,lying between the Gambia and Guinea Bissau.
The region is subdivided into three departments: Bignona, Ziguinchor and
The climate is classified as dry Guinean savanna with two distinct seasons:
a rainy seasonfrom June to November and a very long dry season . As a result of
the droughts in the 1973-I 980 period, the rainy season has been reduced from 5
% months to 4 months and average annual rainfallfor Basse Casamance was about
11~~rnrn during the period 1980-84, 25% lower than its long-term average
(152Omm, 1960-1964).This low rainfall has had a serious effect on rice production
in this region. The deciine in cultivated rice lands between 1980-84 cari be
attributed to the high proportion of rice fields that have been abandoned as a result
of salt intrusionon the lower fields and drought stress on the Upper paddies (Table
2.2). The rainfall deficit and reduced area under rice have resulted in a high rate of
out-migration of rural Casamance youths for the cities (Van Loo, 1973; de Jonge
et al., i976; Harza, 1984). It has also led farmers to begin changing their approach
to farming. An expansionof dryland crops such as groundnuts, millet and corn has
been apparent over the course of the last few years.
The figures in Table 2.2 indicate the area covered by the three main crops
has decreased during the period 1991-I 993. The lack of seeds and lands suitable
for rice production (more rice lands are affected by salt intrusion) cari explain that
trend. According to DERBAC (1995) plateau crops in 1994 across the area
accounted for 62.4 percent of the total land cultivated. The resident Farming
System Research (FSR) team in 1982 found that plateau crops accounted for 50
t
10
percent of the total land cuitivated per household
Table 2.2: Rainfall Pattern (mm) , Area Cultivated (ha) and Yield tevel in Lourer
xamance
Source : GO! IDGPA
About 60 percent of the cultivated plateau land was reclaimed from bush fa/lows.
This means that the region farmers, as a result of the drought, were attempting to
increase labor productivity by clearing iands for groundnuts, millet, sorghum and
maize. Rice remains the major cereal trop in the region. Compared the situation in
the 1982-1986 period groundnut production has decreased subs~an~iallyin the
region. The percentage of land devoted to groundnut production was respectively
49.5%, 59.7%, and 55.5% in 1982, 1983, and 1984 (FSR, 1985). Rice production
for the same period accounted for 31.9%, II .7%1,and 21 .l%. Two main reasons
given for these trends are: the improvement in the rainfall pattern in the last year
(1984) which was more favorable to rice production, and the difficulty for farmers
to acquire groundnut seeds in the region since the government’s disengagement
of the seed sector.
Maize production for which the region has a good potential has been
i!
11
increasing since the period 1981-85 with the help of the ma~ze-j~~tensÎfi~tion
program developed by PIDAC. However for the last period 1991 to 1994 the area
in maize production has been declining due ta the fack of seeds and fertilizer, and
various marketing problems faced by farmers in selling their production. Since
maize consumption is not popular in the area, farmers have become convinced that
it could be a good cash trop for them.
2.3 Social Organization of tabsr and Farm Size
Studies (Linares, 1983) revealed profound differences in the organization of
production and the land tenure system with impartant implications for both
technslogy development and the adoption of improved practices.
South of the Casamance River, the Kassa-Diola Iive in households
csomposedof conjugal families which are autonomous in economic matters. The
area has an intensive aquatic rice production system with an equitable sexual
division of labor by task: the heavywork of dike building and ridging Esdone by men
while women transplant and harvest rice. Land is nominally owned by patrifilial
groups, but usufruct rights over it lie with the conjugal unit under the direct
responsibîlity of the head. Women as a rule do not own rice land.
Northeast of the river, the Fogny-Diola have adapted many aspects of their
Manding neighbors’ culture including the Islam religion. Sexual division of labor is
oomplete with women growing only rice in the low lands for subsistence, and men
on upland growing groundnut for cash and coarse cereals fur local consumption.
*
12
Social status here favors the original settlers and founders of the villages which are
exogamous. Residential units are quite large. IndividuaI households respond to the
head of the compound and, as a general rule, control of elders over youth and
dependents as sources of labor is very firm. Rice land is owned by patrilineal
groups, but unlike in the south resident females cari gain access to rice land
through lending by close family members.
TO the northwest, the Fogny-Combo Diola display a type of social
organjzation of production that is intermediatebetween the first two. Sexual division
of labor like in the south is complementary. Women help men in their groundnut
fields for sowing, weeding and harvesting whiie at the same time they are still
exclusively responsible for aquatic rice production Individual residential units are
large with a similar interna1structure as in the northeast area, but many individual
households within the family compound remain economically independent.
Those subtle differences in the organization of the production are associated
with variation in the use of resource, agricultural practicos and performances (Table
2.3). Farm sizes are larger in the northeast (3.3 hectares) because production is
organired at the compound level with the possibility of mobilizing a much targer
work force than in the southwestern zone. The use of oxen and moldboard plows
makes it possible to cuttivate greater areas of land on the plateau. Groundnut
production accounted for 76 percent of total cultivated tanci. Rice is the second
most important c-ropfollowed by dryland cereafs such as maize, and mjlle~sorghum,
Labor contribution to rice production is significant (25 percent of total family labor).
t
13
Female tabor contributed for 17 percent to total tabor in the farm.
Table 2.3: Family Labor Organization, Cropping System, and Labor Utilization
Northeast
Northwest
3.28
3.70
0.49
0.39
Groundnut
2.51
3.13
Dryland cereals
0.27
0.16
Family size (Nos)
15
10
Family labor (Nos)
10
8
Family labor in rice (%)
25
16.4
Female labor (%)
17
9.5
Non family labor (%)
19
7.5
trop.
Source:Numberswere computedfrom FSR data file: surveys 1982-1986.
In this system nonfamily iabor plays an important role (29% of total farm labor).
Most of that iabor is composed by labor exchange between farms usually during the
peak tabor periods (planting and harvest periods).
Farm size in the south is an average 1.82 hectares with 5 agricultural
workers. For the majority of farms production is organized at the level of a conjugal
family with timitation on manpower avaifability when the using traditional technique
of manual land preparation. Rice is still the main trop in this part of the region. Rice
production accounted for 43 percent of the total labor time. Female labor
contributed for 37 percent of the labor. This important share is related to the
importance of aquatic rice and the heavy invo~vementof women in every step of the
t
14
production process.
In terms of cropping system and farm siie the northwest presents many
similaritieswith the northeast. Farm size is largerthat is 3 to 4 hectares on average.
Groundnut production acoounted for 85 percent of the total farmiand. Oniy 16
percent of the iabor was devoted to rice production.
Three major features cari be outlined following this description:
(1)
Farm size increases from south to north of the river.
(2)
The contribution of women in agricultural production decreases from norht
to south.
(3)
The importance of rice production decreases from south to north while
groundnut production increases.
Rioe production in the Casamance region has been severeiy hampered by
salinizationof the food plain along the Casarnance river. Successful growth of rice
under tidal conditions is determined by the low concentration of the salt in the
tributaries of the river, This limits the supply of land available for lowland rice,
Posner (1991) identified three fowland rice production systems in the Basse
Casamanoe:
(1)
Systems based exclusivefyon transpfanted rice, very labor intensive. In this
system farmers do not have suff~oientuptand areas suited to the cultivation
of other crops. Thus their main responseto the drought is through modifying
their efforts to aquatic rioe cultivation according to the rainfall pattern each
year. Off-farm activities such as fishing are found.
t
15
(2)
The system in which direct seeding of rice is dominant. Shifting from
transpfanted to direct-seeded rice and cultivating more upland crops is the
main adaptation to the drought in such a rice production system.
(3)
Systems that combinethe two first systems. 80th Salt-affected and non-salty
areas are cultivated.
In terms of the classification of the types of rice fields common in the area, three
types cari be distinguished:rainfed rice with no water accumulation with short cycle
varieties, phreatic rice (nappe) which benefits in August from a short rise in the
water table, and deep flooded rice fields (aquatic rice).
Land preparation techniques vary according to the type of equipment and
often the type of social organizationof labor. Ridging using the cayendo (local toof)
is the most common pradice in rice cultivation. In 1985, 58 percent of the lowland
area was ridged. Ridging facilitates weed control and allows better control of the
depth of flooding. Flat Mage, using a local tool (fanting) and ox-drawn plow is the
second type of land preparation.
A wide range of local varieties are used and one cari find several of those
varieties planted on all types of rice fields. The length of the growing cycle varies
from 91 days to more than 133 days in phreatic rice and from 105 days to more than
161 days in aquatic rice (Posner, 1991).
Yields at the farm level vaty from year to year and are highly dependent on
the rainfall profile (Table 2.4). Yields of transpianted rice are higher in the lower
paddies than in the Upper when they are not affected by salinity or iron toxicity.
t
16
.------
-------
--.--.-
_--. --- . ._l-.--l._.__.- - _-._
-..:
‘_
F,.
1
),,’
.____ __..___ .__
,“
‘_
L
Table 2.4: Average Yield (kglha) of Paddy by Position in the Toposequence
s,u,e:
DERBAC(1995)
Despite the numerous constraints they face in rice production, the farmers
of the Lower Casamance are still culturally attached to their rice cropping system.
The increase in rice production in the country (4 percent per year, USAID, 1991) for
the period 1989-I 990 seems to be iargely ~ttributed to the development of irrigation
in the north. In Casamance, any improvementWilldepend on the availabiiity and the
adoption of more productive te~hnoiogies,and soif reclamation efforts to secure the
supply of land available for lowland rice.
2.4 Rural Credit, Input Availabifity and Farm Equipment
The government program under which the majority of farmers, particularly
north of the Casamance river, acquired farm equipment has been halted since
1980. it was abandoned largely because it contributed to enormous governmental
deficits. The New Agricultural Policy (NPA) has centered on state disengagement
and privatization. It has Ied to the elimination of “modem” input subsidies. Private
input distributors located in big Mies are inaccessible to farmers and are less
willing to extend credit to farmers. In Casamance, in 4990, only two private
%
17
agricultural input distributors were identified for the whole region. Jhe obvious
impli~t~on is that farmers now demand Iower quantities of modern inputs. Fertitizer
use by the region in 1989-90 was 1.2 percent of the total fertilizer use in the
country. The problem most frequently mentioned is the difficulty of obtaining credit.
GNGAS (Caisse Nationale Gredit Agricole du Senegal) has begun to rebuild the
farm credit system, but like many previous credit programs, GNGAS has
encountered credit repayment problems.
fnput distribution is mainly carried out by projects which provide credit to
farmers. In Gasamance this function is carried out by the DERBAG project. This
credit is designed for farmers organized in GIE (Economie Inter-est Groups).Jhey
were established to comptement the cooperatives and to serve as a vehicle for
advancing some of the policy’s major objectives: the withdrawal of the state from
commercialfunctions, and the “responsabilization” of farmers. GIEs offer a form of
organization which relies on participants’ initiative and involves minimal state
intervention. GlEs may be formed by two or more farmers and the project hefps
farmers in doing the necessary paper work. The GIE is a legai entity which may
incur debt and may be capitalized at the discretion of their membership. In 1992,
150 GIEs were created under the project with 4 to 50 members per GEE,depending
on the village. Each GlE’s president is responsibte for contracting the short term
credit with the GNGAS. A down payment is required for each type of credit as a
percentage of the amount of the credit. For farm equipment the down payment is
20% for a two-year period, and for divisible inputs the down payment is 15% for a
t
18
njne~nlonth period. In contrast to the former ctedit program, the DERBAC çredit
program has a high repayment rate. In 1993, fhree months after the harvest the rate
was 82 percent (ISRA-DERBAC, +I993).Nevertheless two main problems arise with
the program:
(1)
lts lack of diversity because farmers are more interested in consumptian
credit and credit in kind to developalternative activities (local stores, fishing
activities).
(2)
The low level of demand for inputs especially fertilizer.
Income differences are mainly attributed to diffarences in farm fevel resource
endowments between the north and the south. Larger farmers, especiafly those
located in the north who cultivate more groundnuts, have higher income. The use
of animal traction makes it possible to cultivate more land. This situation is totally
reversed in the south where farms are smail and heavily oriented toward rlce
production with manual land preparation. Thus fat-mers cari only be compared on
the basis of their labor productivity and net income per unit of land (Table 2.5 ).
Labor productivity is also higher in the north than in the south. But in terms of offfarrn activities, farms in the south rely heavily on income generated from such
activities. In 1985, off-farm income accounted for 59% of total farm income in the
south and only 20% in the north.
Food grain deficits occurred in many villages of rural BasseCasamance in
*
19
1984. Measured against the FAO consumption standard of 200 kglpersonlyear, in
the south the level of cefeal availability was on average 140 kg and 316 kg in the
north. it is important to note that villages north of the Casamance river with
important plateau crops and where animal traction cultivation has been adopted are
the villages that have the lowest food grain deficits. At the other extreme, the
villages south of the river where aquatic rice is cultivated, have the highest cereals
deficits. In 1994, 77 percent of the regional cereal needs were covered by local
production (Direction Agriculture, ‘l994).
Table 2.5: Resource use, Costs and Income per Farm in Lower Casamance
(19824986)
r
Variables
North
Farm area (ha)
1.78
Total labor used-mandayska
145
108
Vatue of production (CFA)
98,422
506,262
Variable costs (CFA)
4,107
26,192
FDted costs (CFA)
1,800
3,470
Net farm income (CFA)
92,515
476,600
Net income (CFAIha)
51,948
66,471
Net income (CFA/man-day)
358
Source:ISRA, 1982-1986surveys.
2.6 Measures of Fat-mPerformance in Lower Casamance
Four efficiency parameters proposed by Fare, Grrisskopf and Lowel (1985),
Farell (1957) are used to measure the performance of farmers in Lower
Casamance:
t
20
(1)
The concept of pure technical efficiency (PTE) relates to the question of
whether a farm uses the best availabletechnology in its production process.
In general, 0~ PTEcl, where PTE = 1 impfies that the farm is producing on
the production frontier and is said to be technically efficient. Alternatively,
PTE < 1 impliesthat the farm is net technically efficient. In this case (1 ?TE)
is the largest proportionai reduction in inputs that cari be achieved in the
production of a given output level.
(2)
The concept of allocative efficiency (AE) also called “price efficiency” is
related to the ability of the farm to choose its inputs in a cost minimizing way.
It reflects whether a technicallyefficient farm produces at the lowest possible
cost. In general, 0~ AE<l, where AE = ‘l corresponds to cost minimizing
behavior where the farm is said to be allocatively efficient. AE < 1 implies
allocative inefficiency. In this case, (6AE)
measures the maximum
proportion of cost, the farrn cari save by behaving in a cost minimizing way.
(3)
The scale efficiency (SE) measures whether the farm is producing at the
most efftcient size. Clearfy, O<SE<1 and if SE=l, the output level indicates
an efficient scale of operation corresponding to the smallest ray average
cost.
(4)
The concept of scope economies (SCT) or “economies of diversification”
addresses the issue of why some farmers choose to produce more than one
produçt. Economies of scope refers to the percentage cost savings
attributable to joint production. The larger the economy of scope, the more
%
21
cost efficient the farmers will become by diversifying their product lines.
A nonparametric approach was used to derive the different efficiency measures and
Tobit regression was used to identifYthe sources of farm inefficiencies (Chavas and
Aliber, 1993; Fare et al, 1985; Farrell, 1957).
The data used in the analysis were collected in 1983 and 1984 by a FSR
team operating in the area. The team used an input-output data collection
framework on a master sample of 235 households in 10 villages. The master
sample was also used to conduct a cost-route input-output survey on 32
representative farms and a year long study of off-farm activities and incomes.
Detailed and comprehensive resource-flow data were coliected on the
representative farms. The efficiency analysis is done using the data on 120 farms
for which desegregated data for labor inputs were cotlected. The data for each
includes both inputs and outputs. The output used in the analysis inciudes the
following crops (peanut, rice, maize, sorghum). The inputs include female family
labor, male family labor, non-family labor, and trop inputs such as seeds and
fertiiizers. All quantity measurementswere annual flow variables. Farm levef prices
were not coilected since all farmers in the same region face the same relative
prices, because prices are fixed by government authorities. Thus the faw of one
price does hold in that prices differ across regions only by the transportation costs.
In the efficiency analysis, outputs were converted into monetary value using officia1
prkes. This allows us to account for the differences that exist in the prkes of the
different crops grown by the farmers in the sample.
i
22
I
. ~
x
_ , “ .
.
_
. -
- - -
- -
- . - .
^ . . .
-
. . -
- . . _ - -
- .
.
.
- _ _ - - ~
_ _ _ _ _ _ - .
~ _ .
Farm income and off-farm income were exprsssed in local currency CFA
(IUS dollar- 500 CFA). Labor was expresscd in hours, farm size was the number
of hectares, and seeds were measured in kilograms.
Although measuring inefficienciesis of interest by itself, it is of more interest
to identify the sources of such inefficiency. We examined the refationship between
the efficiency measures, farm characteristics and envif~nm~ntal faotors. The
expianatory variables used in the mode1 were the number of years of farming by
the househotd head, as a measure of experience, the percentage of total income
coming from onfarm activities used as a measure of specialization in agriculture, the
size of the farm in number of hectares cultivated, the percentage of land farmed that
was devoted to upland trop production, whether or not the farmer used animal
traction, and the type of sexual organization of labor.
The efficiency resuits and their distribution across the region of Casamance
for the sample of farmers are shown in Tables2.6 and 2.7. The mean technicat
efficiency index (PTE) is 0.80, meaningthat farmers could increase their production
by 20 percent by producing on the frontier. Roughly 55 percent of the farms were
produ~~ngon the frontier. This index does not vary very much across the area. The
south and the northeast have the highest level of technical eficiençy.
The northeast part is close to the two main cities Ziguinchor and Bignona
and has had greater expasure tu extension programs. The level of speciafization
in agriculture was found to be positively related to the efficiency index. Farmers
devoting more time to agricultural activities were more efficient.
%
23
Table 2.6: Descriptive Statistics of Efficiency Measures for a Sample of Fat-mers in
-y-Pure technical (PTE)
AIlocative (AE)
Scale (SE)
Economie (EE)’
Scope economies (SCT)
’ Ecanomic
effkiency
is the
productof alfocative
and pure technical
efficiency.
Farmers in the south and the northeast spent much time in off-farm activities (Palm
wine harvest) from January to August before the flooding of the rice fields. Such
activities are more confined and do not compete with agricultural activities.
Farmers in the northwest are less technically efficient (Table 2.7). They
cultivate cereals and groundnut in large areas using animal traction, but for ptanting
and weeding they do not use animal traction and rely heavily on family labor. In
many cases only one weeding is done and in other cases the fiefds are not
harvested due to a lack of weeding. The problem in this area is the fack of
appropriate equipment. Farmers are only equipped with ox-drawn plows ( i.e., 1 oxdrawn plow for 16 hectares and 50 percent of farmers in fact own this type of
equipment). Because of their proximity to the Gambia, farmers have developed
more off-farm activities (Palm oil harvest, illegal activities such as smuggling) that
often compete with agricultural activities (planting and weeding).
24
--
Table 2.7: Distribution of the Effieiency Measures for a Sample of Farmers across
the Three Major Farming Systems in Casamance
--Te-
Efficiency
-----II_
South
Mean
-Sd
-Sd
Min
Pure tec:hnical
0.94
0.10
0.26
0.27
Min
-0.24
Allocative
0.45
0.14
0.29
0.18
0.16
Scale
0.77
0.18
0.18
0.48
0.85
Economie
0.42
0.15
0.31
0.10
0.13
Scope
-----
0.19
--
0.10
0.10
0
0
--
Since, the level of technical efficiency appeared to be inluenced by the level
of specialization in agriculture (Table 2.8), research and extension activities
intended to increase the technical efficiency of farmers should focus on themes
such as diversification of the cropping system by introducing new crops that Will not
compete for labor at peak season. Late-seeded crops such as cowpea, sorghum
and/or millet might be important crops to consider. The emphasis on late-seeded
crops was due to the general lack of mechanization and changing rainfall patterns
and the expectation that these could serve as catch-trop alternatives should the
first pîanting fail. The initial idea that farmers involved in off-farm activities woufd be
better-off because they have additionalincome and would be more willing to invest
in the farming business by acquiring improved inputs, and hiring labor does not
always seem to be the case in practice.
Quite often, the contribution of total factor productivity is interpreted as the
contribution of technical progress. Such an interpretation implies that the
i~provement in productivity anses from technical progress only. This assumption
25
_> . ..- -. ,r.___C_<X,l..-.. -
.1
_ .”
is valid only if farmers operate on theit production frontiers producing the maximum
possible output or realizing the full potentiai of the technofogy. Operation on the
front& cari be achieved if farmers follow the best practice methods of application
of the technology commonly referred to as “technical efficiency”. SO far as farmers
do not operate on their frontier due to various nonprice and organizational factors
but somewhere below the frontiers, technical progress cannot be the only source
of total factor productivity growth. A substantial increase in total factor productivity
under these circumstances still cari be realired by improving the method of
application of the given technology.
The mean allocative efficiency (AE) was 0.53 with a coefficient of variation
of 45 percent (Table 2.6). Only few farms (7 percent) were found to be allocatively
efficient. By improving aflooetiveeficiency, farms could reduce production costs by
47 percent. On average farms situated south of the river were less efficient than
those situated north of the river (Table 2.7). Allooative efficiency was found to be
explained by three main factors: experience in farming, the use of animal traction,
and the ratio of upland crops to the total area cultivated (Table 2.8).
Experiencewas positively related to allooativeefficiency, indicating skills and
knowledge over time help in adjusting strategies to differences in the production
environment concerning which they hâve intimate first-hand experience. Farmers
cultivating a high ratio of upland crops were less allocatively efficient. They were
technically efficient but they were not producing at the lowest possible cost.
Table 2.8: Tobit Results Refating Efficiency Measures to Farm Characteristics
c
Pararneter
--.Constant
--
1 PTE
I
] AE
I
SE
EE
I SCT
Ratio of upland trop
I--------Yearsin farming
Farm six in ha
0.0007
(0.05)
0.0008
(0.77)
O.OU
(0.46)
0.0008
(0.84)
Note: T-statisticsare in parentheses.One asteriskdenotessignificanceat th;lO
percent level. Two astetisksdenote significanceat the 5 percentlevel, Three asterisks
denote signifkance
at the 1 percentlevel.
Most of the upland crops (65 percent) consist of groundnut production which
requires more Iabor espeoiallyduring the weeding periods. Allocative eff iciency was
positively explained by the use of animal traction. The cost reduction here is
essentially in terms of labor for ploughing and planting, enabling better timeliness
in terms of these operations.
The mean scale ef?iciency(SE) was 0.85 with a coefficient of variation of 21
percent. On average, size seemed to be less important. This suggests that the
gains from attaining an efficient scale appear to be moderate relative to allocative
efficiency. The average cost function (the inverse of the scale index following
Chavas, 1993) had a general L-shape. It is a declining function of output under
increasing returns to scale, and an increasing function under decreasing returns to
scale. Oniy few farms were found to exhibit diseconomies of scale. The scale
efficiency index ranges from 0.77 for farms in the south to 0.95 for farms in the
north. The gain from size improvement was bigger in the south. Farms in this part
of the region are usually small in size due to the fact that the cropping system is
concentrated on rice. Few farms hâve extended into upland crops. The possibility
of aquiring new land is very limited because of the high population density. Sçaie
efficiency was found to be explained by the type of labor organization and the
percentage of upland crops (Table 2.8). The sexual division of labor and, in
particular, the traditional Diola system was positively refated to scale efficiency. The
system aflowing for a labor division established by task seems to be more efficient.
The advantage of that division of labor is that it makes possible for all active family
members to prepare the land and get the season off to a good star-t in May-June.
tabor represents an important share of all the value of nonland resources used in
agricultural production. Besides land, it is the predominant input. Traditionai
societies are poor becausetheir labor productivity is low. The specialization of labor
by task, positively related to scale efficiency, shoufd be encouraged through the
development and diffusion of technologies. Farms cultivating more plateau crops
are more scale efficient. In fact as a result of low rainfall and the intrusion of saline
tidal water, many lowlandfields were abandoned. The only possibility for increasing
farm size is through the cultivation of more upland orops. This practice has led to
the destruction of much of the forest land in the area.
I
28
The mean economic efficiency index (EE) was 0.42 meaning that farms are
both techrtieatlyand allocatively inefficient.High proportional reductions in average
cost exist through farms, becoming more technicaliy and allocatively efficient.
Economieefficiency was found to be related to the percentage of upland crops, the
use of animal traction, the farmer’s experience in farming and the physical size of
the farms. Animal traction is more common in the northern part of the region with
a wide use of ox-drawn plow, mechanicat seeders, moidboard ploughs. Animal
traction suffers from a lac-kof consistent government support policies, particufarly
with respect to veterinary services and research on animal technologies. To be
efficient the use of animal traction must Lover the peak periods of the cropping
season during which labor bottlenecks are azur. This implies that farmers shoutd
be able to use the animal traction for ploughing, planting and weeding. Farmers
faced many constraints such as the availability of the machines, spare parts and
local expertise in undertaking repairs. Measures required to improve the viability of
animal traction include provision of additional credit to complete the purchase of
additional
equipment, to facilitate greater use of oxen. Also equipment repair
centers need to be installed and local blacksmiths need to be trained, to provide
spare parts and facilitate the adaptation of equipment to local conditions,
The analysis of economies of scope @CT) showed that, on average, farms
enjoyed positive economies of scope of 20 percent with a maximum of 42 percent.
By producing the different crops, rice, dryiand cereals (maire, mille#sorghum) and
groundnut in a multi-product framework, farmers cari decrease their costs by on
%
29
._. __
average 20 percent. The gain from diversification was higher in the northeast with
a mean of 24 percent and a maximum of 42 percent. Most of those economies
resulted from combiningmore rain-fed cereals, rice and groundnut production. The
northwest had the lowest level of
smpe
economies. In this zone the diversification
is more in terms of increase in groundnut production. The importance of groundnuts
in Casamance raises some concerns because of various negative aspects
attributabfe to the erratic pattern of rainfall, and agronomiclecological threats
caused by overcropping. The government 1985 diversification policy was aimed at
reversing the path t-esultingfrom a drought-stricken agriculture. During the period
1980-90 farmers did not increase substantialtythe area cultivated in cereals as had
been expected from implementationof the policy. The diversification policy focused
mainly on promoting cereal production but little had been done to facilitate the
marketing of cereals. The whole marketing system was tied to groundnut
production.
The different efficiency measures vary between zones, indicating the need
ta recognize the heterogeneity in the farming population and the need to adapt
strategies aocording to the local situation. The different measures of efficiency and
their relation to farmers’ characteristics improve the understanding of the existing
agricultural system and help in designing the optimal path of development. They
could be used further to categorize the different farming systems existing in
Southern Senegal. Furthermore, policy recommendations, and targeted research
and extension interventions based on those factors coutd more effective.
1
30
.- ._.---.
-_.
Historically, agricultural research under the responsibifity of the French
lnstitute for Tropical Agriculture (IRAT) was oarried out from the Center National de
la Recherche Agronomique (CNRA), in Bambey with a network of regional stations,
along commodity and disciplinaryfthematic lines. Crop research focused on variety
improvement and plant protection. Much of the research on rice was conducted at
the Dijbelor (Casamance) and Fanaye stations. Traditional trop research in
par-ticularhas had several flaws in the past, It had poor or no links with agricultural
extension and was mostly concentrated on agricultural stations with little research
undertaken at the farm ievel to ascertain the fat-mers’ environment and constraints.
fncreasing awareness of the significance of the socioeconomic dimension
of rural change led IRAT in 1969 to embark on an experiment: the Unites
Experimentales (UE) in the Kaolack Groundnut Basin. The objective of the UE
projed was ta assess the relevancy of technologiesdeveloped on research stations
for farmers. The UE, later taken over by ISRA, produced a considerable amount of
knowfedge and a better understanding of the process of transferring technology
from the research tenter to the farmer. lnteresting findings on the technical and
economic feasibility of the intensification were obtained. However, the cost of
extending the improved technical package and maintaining the momentum of the
intensification process at the farm or village level constituted a serious flaw in the
project.
In 1982 the GOS opted to reorient agricultural research in order to focus on
*
31
the problems faced by farmers and herders in the countty’s major agro-ecoiogical
zones. In August 1982, ISRA was officially reorganized. The reorganization was
aimed at improving tSRA’s efficiency in carrying out applied research and in helping
the EOS achieve its investment objectives in agriculture.
TO reach this broad objective, ISRA endorsed a new research strategy with
three important aspects: (1) decentralization (regionalization) of agricuitural
research; (2) replacement of the fragmented disciplinary research approach by a
coordinated multidiscjplina~ team approach along commodity lines, and (3)
it~pl~mentation of production systems research (FSR) in the four agro-ecological
zones of Senegal.
As part of the decentralization of agricultural research in Senegal, fSRA set
up two programs in Lower Casamance: The Rice Research Program and the
Farming Systems Research Program.
2.7.1 Rice Research in Casamanm
A major characteristic of rice production in the region is the diversity in rice
fieids associated with a diversified cropping system. This variability is linked both
to toposequence position with different constraints and differences in input use.
The ISRA station at Djibelor, established in 1967, was mainly concerned with
aquatic rice. Research focused on breeding, soii fertility, cultural practices, plant
pathology and weeds control. The rice program was designed to identify and
classify the different rice-based cropping systems and their respective constraints
and design rice varieties that are appropriate to the different systems.
i
32
_. _
-
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The research program, a multidisciplina~ team, had two generai rice
improvement goals: (1) yield potential at high management and (2) yieid stability
through enhanced resistance to environmental stress factors. In collaboration with
iRAT, WARDA and IRRI, using on-station triais and mult~io~tionai on-fat-m trials,
different varieties for different types of rice fieids were tested in the Casamance
Region:
Varieties that are resistant to rice blast and P.o-zae. Three varieties were
released for rainfed rice DJ8-341, IRAT 10 and IRAT 144, three varieties
DJ12519, IRAT 133 and TOX 728 were released for phreatic rice, and four
more varieties were refeased for aquatic rice, DJ6840, ITA 123, BW241 .l
and IR 442.
(2)
Varieties resistant to different stresses such as iron toxicity and satinity. Bath
constraints became very important in the area with the rainfall deficit. With
respect to salinity the varieties ROCKS, DJ6840, WAR77 and WARI 15 were
found to tolerate a certain level of salinity during the beginning and the end
of the cropping season. Sylla (1994) found that salinity stress was the
dominant factor limiting rice production in the Casamance River Basin. In dry
environments, rice yield was well correlated with the spatial variabiiity of soi1
satinity. In terms of iron toxicity more work needs to be done.
Weed control is one of the major constraints in phreatic rice cultivation.
Weeding is difficult and time-consuming especialfy when it is done manually. The
difficulty rises in refation with the type of seeding, The quality of weed control is
z
33
also retated to the type of land preparation apptied on the rice fields. Studies
(Riallo, Fall, 1988) compared three types of land preparation combined with
different methods of seeding, and showed that flat plowing followed by broadcast
seeding is superior in controlling weeds. With the implementation of projects in the
area promoting the use of improved inputs especially herbicides, farmers close to
the main city of Ziguinchor were further found to be interested in the use in
herbicides to tut down their weeding requirements. Sevefal types of herbicides
were tested by the program. The studies showed that one application of Ronstar
250 CE (either pre-or post-emergence) could replace two manual or mechanical
weedings. But to be more efficient, the application of the herbicide shoufd be
complemented by one manual or mechanical weeding.
Recently the focus of the rice program in the area has been to test the most
promising varieties in a mu~ti~o~tional framework in collaboration with the
development project and the World Bank Extension Program (PNVA), and to
continue the screening of varieties that are more suited to the constraints of satinity
and iron toxicity. The testing of those varieties wifl hetp researchers identify better
techniques for production that will fit into the existing farming systems. The
screening of varieties resistant to stresses such as salinity and acidity witl require
changes in water management. It is critically important to protect the rice fields from
salinization.The construction of small anti-salt dams, hand-made by the population,
has been supported with external finances {USAl~~S~~~VAC/lS~,
1985). They
consist of earthen dikes with water control structures. Some of those dams have
%
34
been efficient, but watet management was not well-adapted in other cases. Thus
the rehab~tjtationof the degraded lands remains an acute probtem, which still needs
resolution. Reclaiming those lands in a cost effective way wilt facilitate varietal
screening by removing most of the constraints in these tands (salinity, acidity), and
increasing the suppfy of lowlands in the area.
2.7.2 Farming Systems Research in Lower Casamance
The FSR program was initiated in late 1981. The objectives were to conduct
adaptative on-farm research and study the production system currentty in use and
how they were evolving in the face of prolonged rainfalf deficits.
Qver the course of the work program, it became evident that agro-ecological
and socio-cuftural heterogeneity in Basse Casamance was an important factor.
Accordingly, an applied research program was developed in order to account for
that heterogeneity from the outset. Thus the area was delineated into farming zones
on the basis of three criteria: the sexual divisionof labor, the extent to which animal
traction had been adopted, and the importance of transplanted rice versus other
cereals in the cropping system. These criteria resulted in five zones being identified
(Figure 2.1).
2.7.2.1 Agricultural Zones and Research Priorities
According to the first criterion, sexual division of fabor, two main systems
were identified: in the Diola system, men do ail land preparation while women plant,
weed and harvest the crops (Zones 1, Il, V); in the Manding system, labor division
is estabiished by trop with rice production under the soie responsibifity of women,
\
35
Figure 2.1: Map of Senegal and Agricultural Zones in Lower Casamance
..*
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. . .
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.
.
.
.
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36
.
.
and men accomplish all the tasks associated with upfand crops (Zones Ill, IV).
The importance of animal traction permiited a further subdivision of the
D~o~a/~anding systems. The north shore viflages close to the Gambia and the
Middle Casamance to the east have benefited from a longer history of animal
traction (Zones IV, V).
The third criterion was important in the delineation of major farming systems.
Land elevation rises steadily from the southwest to the northwest along with a
decreasing rainfall gradient. This results in a greater emphasis on upiand crops
(Zones II, IV and V). The effect of this transition on the cropping calendar is quite
marked. While in the not-theast (Zone IV) major agricuitural activities take place in
June-July with the plantingof maize, groundnuts, millet and direct seeded rice, the
peak tabor demand in the southwest (Zone 1)does not occur until late August or
early September as the land is being plowed and rice transplanted.
Previouszoning of the Basse Casamance region into agricuftural zones was
undertaken mainly by SOMIVAC, since it was established in 1975. More recent
work was prepared for SOMIVAC by HARZA (a consulting firm under a USAID
contract) in 1982. It delineatedthe Basse Casamance into nine intervention zones,
each with a particular development potential especialfy in reference to the type of
watershed managementprograms to be designed. Intervention zones are useful as
a guide in regional development planning. However, they do not constitute a
practical basis for the work ieading to the identification of appropriate
research\extension programs that would be economically viable and sociaîly
t
37
acceptable. That type of zoning used criteria that characterize morpho~edotogi~l
and agio-ecological units rather than oriteria that describe how farmers exploit their
natural environment.
The resident FSR team identified three research priorities:
(1)
The intensification of production in good lands especiaily in lowland areas
for rice cultivation. This involved the use of improved varieties, fertitizer and
better weed control.
(2)
The diversificationof the cropping system by introducing late seeded crops
(sweet potatoes, cowpea) that would net compete for labor at labor
bottleneck periods. This strategy was due to the general lack of
meohanizationand changing rainfall patterns and the expectation that these
would serve as catch-trop alternatives should the first seedings failed.
(3)
The reclamationof abandoned lands. Higher rice land in the village proximity
had been abandoned due to the failing water table, Those areas, marginal
for rice production, could be used for maize production.
2.7.2.2 Major Achievements of FSR in Lower Casamance
In addition to the generation of improved, adapted technologies, the
FSR team helped reinforoe linkagesthat were weak within the regional agricufturalextension system, thus allowing more relevant research to be undertaken.
Specific technology components that better fit into farmers’ circumstances
came out of the FSR research were:
(1)
%
The introduction of oxen drawn rice seeders in women fields. Animals and
38
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equipment beiong to men. In most areas the use of animai traction is
confined to upiand crops and women cannai access it for preparing their rice
fieids. TO improvethe use of animai traction and the productivity of womenlabor, men were asked to prepare rice fiel& with oxen and moidboard
ptoughs. it was indeed possiblefor men to piough their wives’ rice fieids with
oxen and proceed with direct sowing using mechanicai seeders within 2-3
days. The time saved by women was productiveiy used by many to cultivate
more lowland rice fields.
(2)
Mechanical weeding of maize (i.e., fiat pioughing folfowed by combined
ridging-weeding with the moldboard plough) was found to be three times
faster than the traditionai method of ridge-pfoughing foiiowed by hand
pianting and weeding. The probiem for that practice is the fact that row
pianting is required to facilitate the mechanicaf weeding.
(3)
The introduction of a second trop (sweet potatoes) after rice harvest, that
would mature on residuai moisture. There was wide adoption in villages
without cattle or where men were willing to help build fentes around
harvested rice fields to prevent their use as dry season pasture.
(4)
The land rehabiiitationshowed that crops, other than rice, cari be grown on
the Upper river terraces that rarely show wateriogging. The advantage of
maize, is that it is less iabor intensive than rice and has a short growing
cycle SO it replenishes the family granary during the crucial months of
September and October (“hungry season”), prior to the harvest of other
39
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The research paradigm developed by the FSR team, resulted in onfy three
types of adaptive research output (Le., adoption of improved technologies directly
acquired by collaborating farmers, recommendations reieased to PIDAC, and
feedback to on-station researchers). This difference in approach brought criticisms
from on-station researchers on one major point: the informa1 survey phase waç
regarded and criticized as being an attempt to “rediscover the wheel” in a region
with nearly 50 years of confirmed research results. Another point of distord was
that the conduct of farmer managed trials was incorrectly perceived as lacking
scientific rigor. Over the 1982-85 period, however, the dialogue between the FSR
team and on-station researchers improved gradually. Two main factors çontributed
to this. First, the team’s initial approach and open minded attitude toward other
scientists facilitated discussions and progressivefy cleared major misperceptions
about FSR objectives and methodology. As a result of this better dialogue, some
station-based researchers committed part of their time to probfems raised by the
FSR team. For example, the weed control specialist moved from a single minded
concern with chemical control of weeds affecting rice to an examination of how
different land preparation techniques practiced by farmers cari be cost effective in
controlling weed growth. Second, prier to the implementat~on of the FSR,
economists and social scientists were never viewed as part of the research system
especially in the technology design process. In leading the FSR, economists began
to become more involved in the research process and for the first time agronomists
*
40
felt the need to work with economists when designing, testing and evaluating
technologies.
Bridging the gap between research and extension is the most serious
institutional problem in developing an effective research-extension system.
Numerous unsuccessful attempts were made in the past to establish a dialogue
between researchers and extensionists in Lower Casamance, each side trying to
plaoe the responsibility for failure on the other side. Extensionists argued that the
recommendationsfrom researchers are usually complex, unrealistic, and ifficult to
implement at the farm level. The signing of a protocol agreement in 1983 between
ISRA and SOMIVAC was a turning point in collaboration between the two
institutions, The agreement committed both parties to joint efforts in adapting
agricultural research and extension programs to the problems and needs of
Casamance farmers. Joint trials at the farm level and field visits with other farmers
and village leaders, were organized.
SOMIVAC’s acceptance of the FSR team’s zoning as its future extension
framework represented an important step in reinforcing research-extension
linkages. This represented a real move away from the traditional extension
approach of the same message for every farmer, with no reference to farmers’
circumstances and real needs. Now the message could vary from one group to
another. Researchers and extensionists using the same work setting encouraged
interaction, and helped formalize the data collection process. As a result some
modifications in the zoning resufted following the discovery of some discrepancies.
t
41
_.
.
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Recently ISRA has stated its intention to reorient its research strategy in the
region by building upon the achievements of the FSR team. The main features of
this strategy are the regionatizationof the research system with more responsibility
being given to the region in defining and managing its research program, and a
more clientele-oriented research strategy involving farmers, extensionists, local
farmer organizationsand policy-makers in the formulation, the implementation and
the evaluation of the research program. Existing local organizations which are
understood and accepted by village people offer one of the best possibilities for
building long term capacity for evatuation and transfer of technology.
The strategy is to break ISRA’s monopoly of agriculturaf research in Senegal,
and to split the activities and the resources for agricultural research among the
different partners working in this sector in Senegal. This way, they will diversify and
emphasize quality, resulting in a new research system that inctudes both industrial
and food crops. There is a need to follow national and international market trends
and provide this informationto the producers. The emphasis is to keep the research
in line with the market needs. Each partner wilt emphasize its comparative
advantages in the field of agricultural research. ISRA’s strength is in regional
multidisciplinary teams. They do not have the resources to continue doing basic
and strategic research, SOthey Will emphasize apptied and adaptive research.
Other organizationsWilldo some of the activities that fSRA used to do, and together
this wift make up the national agricuftural system. This witl inctude NGUs, the
extension service, and universities.
1
42
-.^
2.8 AgrlculturalExtensfon
Agricultural extension in Senegal dates back to the 1940’s at which time all
extension activities were the soie responsibility of the Ministry of Rural
Development, Currently this responsibility is divided among two ministries: Rural
Development and Animal Resources. Four Regional Development Agencies (RDA)
are located in the country, namely in the northern part, the Groundnut Basin, in
Lower Casamance, and in the east. RDAs are dependent upon donor financing,
which in recent years has become increasingfy scarce, leading to irregutar and
inconsistent extension activities. RDAs, until the New Agricutturaf Policy (NPA)
were responsible for a wide range of services in the agricultural sector, including
input and credit supply, technical assistance, extension and marketing, After the
NPA, as GOS policies started removing input subsidies and began privatizing many
of the RDAs’ activities, the unsustainability of the RDAs, dependent on externat
financing, became apparent.
in Casamance, SOMIVAC (Societe Regionale de Mise en Valeur Agricole
de la Casamance) was responsible for rural development until 1990. PIDAC (a
product of USAID financing), the extension agency of SOMIVAC, had emphasired
such themes as direct seeding of rice and the planting of maize as a field rather
than a garden trop to increase the avaifability of cereals for farmers. Other major
themes being extended by PIDAC in 1982 included flat plowing of upiand crops in
contrast with the traditional method of ridging and the use of animal traction.
In 1990, SOMIVAC, was dissolved and its regional responsibilities were
t
43
-
.
taken over by DERBAC, a project financed by the African Development Bank.
DERBAC includes the Ziguinchor region. With a &rong linkage with ISRA thrrough
a joint research-development project, DERBAC is in charge of the diffusion of
technologies and provides credit to farmers organized in GlEs through CNCAS.
Since 1987, the Wortd Bank has been working with the GOS to design and
implement a program that Will revitalize and reanimate the government extension
services. The pilot project was followed by the PNVA which began jmpiementation
in 1990. The ‘training and visit’ (T&V) extension methodology was chosen for use
in Senegal. In the T&V extension methodology, constraints to agricultural
production are diagnosed by researchers with input from farmers and extension
agents, and extension agents are trained in the appropriate techniques by subjeotmatter specialists. Jhe appropriate techniques are proposed for testing on small
plots by farmers. Extension agents visit farmers on a reguiar schedule through the
cropping season. Monitoring of the T&V system is focussed on adoption rates of
technologies on test plots fhe first year and on finding out whether farmers continue
using these technologies on a larger scale in subsequent years. The main tasks
ahead for this project are ver-ydifficult ones: revitalizing a lifeless public extension
service; improving technical and communication skills of extension agents;
improving communicationamong different technology transfer agents and farmers;
formalizing
research-extension linkages; and strengthening
organizations by direct training of their leaders.
of
producztx
2.9 Adoption of Improved TechncMgy In Lower Casamance
The diffusion of t~~no~ogy through the extension program focusses on one
major theme, the intensification of the cropping system. This includes the use of
improved varieties, the use of chemical and organic fertifizer, and weed controf.
Monitoring of the extension program is mainly concerned with the rates of
application of the different components of the theme on a trop by trop basis. Data
cotlected from 1991 to 1994 by DERBAC from systematic annual censuses are
used to assess the spread of the technologies and their components in the region
(CIMMYT, 1993). The data were coilected on a random sample of 256 farms in 46
villages. The plot was used as the unit of observation and the survey covered 1,304
plots.
Table 2.9 shows the results for groundnut, maize and millet. The use of
improved seeds is well established for groundnut and maize. The high level of use
of improved seeds in groundnut production cari be attributed to different factors
such as farmer’s preference for groundnut cultivation, and the only cash trop with
a well organized marketing system involving provision of seed on a credit basis.
The seed production has been largely privatized in that producer groups (GfE)
finanqed by loans from CNCAS produce most of the seed meant to be sold to
farmers. Two main improved groundnut varieties (28-206 and 69-l 01) and one local
(Bourkousse) are used in the area. The introduction and the use of the improved
maize variety ZMI 0 was boosted after the PIDAC maize intensification program in
1982. Farmers were given free inputs in order to convince them that maize
t
45
production could piay the same role as groundnut in providing cash income to
farmers. The same philosophy was followed by DERBAC with the difference that
to have access to improved inputs, farmers had to be osganized in GIEs. The low
tevel of use of improved seeds in millet is mainfy explained by the lack of improved
varieties adapted to the Lower Casamance. Most of the varieties tested were fout-rd
to be sensitive to blasts and insects.
Few farmers used fertilizer during the period 1991-7994. The difficulty of
obtaining eredit and the lack of cash prevented many farmers from using fertilizer.
This situation does not favor the deveiopment of maize production. The extension
of maize cultivation as a field trop requires the use of fertilizer since upland soifs
are poor in terms of soi1nutrients and maize is a very demanding trop in terms of
nutrients. The use of organic fertilizer (a mixture of animal manure and sand to
which is added organic matter which has been burned) is limited by the availability
of animais.
Table 2.9: Rates of Adoption (% of fat-mers) of Three Major Technical Components
for Groundnut (P), Maize (M) and Millet (Mi) in Casamance (1991-1994).
1
1991
I
2993
1392
Mi
P
M
Mi
Source : DERBAC, 1995.
li
46
P
fhe rates of adoption of improved rice varieties (TabJe2.10) vary across the
toposequence. They are higher for phreatic rice (2!596on average) and aquatic rioe
(26%) than for rainfed rioe (7%). The drought has led farmers to abandon this type
of rice cultivation which is known to farmers as Pam-Pam rice grown on recentfy
cleared lands. Few improved rice varieties are available. RAT-144 has been
recommended for a long time but recent studies have found that this variety is
sensitiveto btast. It is possible that with improvement in the rainfall profile, rainfed
rice Will gain in importance. Thus there is need for screening and multilocational
testing of more varieties.
Farmers do not use chemical fertilizer on their rice fields for different
reasons. These include:
(1)
Lack of credit and cash to purchase fertilizer.
(2)
They strongly believe that chemioalfertilizers destroy the aquatic animal Iife
specially fish, an important source of income.
(3)
The low-lying inland valleys are better watered and sufficiently upstream,
and have a higher level of organic matter coming from the river.
Instead of chemioal fertilizer, more farmers are using organic fertilizer in
their rice fields. Few research programs have paid attention to the use of organic
matter in their varietal screening research process.
47
-
Table 2.10: Rates of Adoption (% of farmers) of Three Major Technical Components
for Rainfed kice (RR), Phreatii Rice.(PR) &d Aquatic Rice (AR).
f
I
1
Source: DERBAC, 1995.
48
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Chapter 3
Framework for Technoiogy Adoption Analysis
The objective of this chapter is to review the literature about the concepts
and measurementof technology adoption, and to specify approaches for achieving
the study objectives,
3.1 Definitions
The abundant literature on theoretical models relating adoption of new
technologies to key socioeconomic and physical parameters, and the empirical
studies that focus on the relationship of key variables to adoption behavior have
been surveyed. There is considerable literature on adoption in Low Income
Countries (LICs) because of the conventionalwisdom that new technology gives an
opportunity to increase production and income.
Rogers (1962) defines adoption as “mental process an individual passes
from first hearing about an innovation to final adoption”. Henry (1987) defines
adoption as “acceptance over time of some specific item -- an idea or practice -- by
an individual, or other adopting unit, linked to (1) specific channefs of
communication,(2) a social structure and ( 3) a given system of values or culture”.
Here time is implicitin the definition of an adopter. It excludes a farmer who is in the
1
49
tria1 stage. In that sense we distjnguish between individual adoption which is the
adoption at the farm level from aggregate adoljtion which is measured by the
aggregate level of use of the technoiogy within a given geographic area or given
population.
For divisible technology such as high yielding varieties, and other variable inputs,
the levei of adoption at the farm level is given by the amount or share of farm area
utiiizing the technology. The same measure cari apply at the aggregate level. For
non-divisibleinnovations at the farm level the adoption is necessarily dichotomous
(use\non use) and at the aggregate level the measure is continuous (percentage
of farmers using). Folfowing Gershon, (1985) we have the following types of studies
on adoption.
3.2 Models of the Adoption of Individuai Farms
Static analysis relates the degree of adoption to factors affecting it. The
problem is characterized as one where the farmer has to choose between two
technologies: the new and the traditional.
Wiebert(1974) used a stochastic production function to examine the effects
of uncertainty. lie shows that adoption increases when information through
extension increases. Using a mode1that does not follow the Bayesian approach he
showed that due ta learning and experience, the probability distribution of the
parameters of the innovation as perceived by farmers Will shift overtime and be
redistributed and this Will induce farmers to adopt. Kistev and Shchori-Bachrash
?
50
., .- -
-
_ .- - _,
(1973) argued that the production function associated with the technology has an
efficiency faotor positively (the cumulative output) related to the level of knowledge.
The efficiency factor increases over time and raises the level of knowledge about
the technology which becomes more attractive to an increasing number of farmers.
Feder(l980), in his study, assuming a constant return to scale production function,
found that fertilizer used per acre is independent of risk aversion, uncertainty, and
farm size when there is no credit oonstraint. Risk affects only land allocation
between orops. His result is highiy dependent on the form of the production function
used. Traditionally, the impact of inputs on risk has been handled through
experimental data, or continuous response functions A reasonable production
funotion should includetwo oomponents: one that specifies the effects of inputs on
the mean output, and another which specifies the effects of inputs on the variante
of output. Just and Zilberman (1983) have extended these considerations to all
inputs. They have shown that if the correlation of output under old and new
technologies is low or negative and if the improved technology is more risky than
the traditional, then larger farms Willdevote more land but less proportion of land
to the new technology than will smail farms.
Using these models some hypotheses regarding the dynamic properties of
the adoption prooass are developed by different authors:
(1)
Adoption increases over time specially when it is a one-component
innovation and farmers use a stepwise approach to adoption (Byertee,
1988).
\
51
(2)
Fafmers improve their beliefs on the basis of observed performance and
then increase the share of land allocated’tu the new technology (O’Mara,
1971). This improvement is based on actual profits derived by other farmers
(Lindner, 1979).
3.3 Models of Aggregate Adoption
These modefs attempt to explain the S-shaped adoption patterns(Griliches
1957, Rogers 1969, Mansfield 1961). Parameters associated with these functions
are determined by factors characterizing the distribution of risk aversion, wealth,
economic factors pertaining to the technology, and the environment. Griliches
(1957) did a study of the adoption of hybrid corn in thirty-one states of the USA. He
compared the rates of adoption, long-run equilibrium tevels of adoption and the
dates of availability of hybrid corn (dates on whiçh hybrid corn made up 10 percent
of total maize production) for the thirty-one states. Griliches fitted a logistic function
to his data. The S-shaped function is asymptotic to zero and symmetric around the
point of inflection. He found that interstate variation in the rate of adoption and the
long run equilibrium were explained by demand factors. Differences in the rate of
adoption were interpreted as differences in the rate of adjustment of demand to a
new equilibrium level. After alt necessary inputs were made available, the rate of
adoption is given by the rate at which farmers moved from one equitibrium to
another.
The diffusion process described by those models contain four components
*
52
(Mahagan and Peterson, 1986):
(1)
The innovation is the new product being diffused;
(2)
A social system (individuals, agencies, organizations and their
adopting
strategies). The transmission of the information Will depend on how
heterogeneous and cohesive is a group of adopters;
(3)
The channels of communication;
(4)
The time, period over which individuats adopt an innovation.
The static diffusion mode1assumes that: (1) the adoption decision is binary,
an individual adopts or does not adopt; (2) there is a fixed and finite ceifing of
adoption; (3) The coefficient of diffusion is fixed overtime; (4) the innovation is not
modified once introducedand its diffusion is independentfrom the diffusion of other
innovations; (5) one adoption is permitted per adopting unit; (6) the boundaries of
the social system stay constant over time. The static diffusion mode1assumes that
the maximum rate of adoption ocours when 50 percent of the poputation has
adopted the innovation. This assumption has been made by Metcatfe (1986) and
by Knudson (1991) who showed that the dynamic diffusion mode1provides not only
a better fit to the data but also better insight into the economic determinants of
adoption. The dynamic diffusion models relax the above assumptions to altow more
flexibility.
Rogers (1957) assumed that farmers with respect to adoption are divided
into threé groups: earfy adopters, foliowers and laggards.
tr
53
---
3.4 Empiricaf Studies of Adoption
Theoretioal madefs suggest many important hypothesizes relating adoption
of new technologies to key economic and physical parameters. Parallel to that
development many empirical studies have evofved to analyze observed adoption
patterns by focussing on the relationship of key variables to adoption behavior.
These variables are:
(1) Farrn sire: Its impact depends on the type of technology and factors such as
fixed costs, risk preferences, human capital, credit constraints, and lahor
requirements. Weil (1970) suggested that large fïxed costs reduce the tendency for
smail farmers to adopt (animal traction in Africa). This negative relationship may be
caused by credit oonstraints. This is consistent with Just’s findings (1983). Feder
(1981) found that there is a relationship between uncertainty and holding size.
Larger farms start on a smali plot and over time increase the share of land aliocated
to the new technology, while small farms lag behind and adopt when larger farms
have already enjoyed several seasons of higher returns. In order to speed up
adoption the fixed costs must be attacked directly and indirectty by providing loans
to small farmers, improving the distribution system, and improving the information
system by improving extension services. A positive relationship between farm sire
and the adoption of high yielding varieties (HYV) has been found by Parthasarally
and Prasad (1978) in lndia, although Hayami, cited by Barker and Herdt (19781, has
found a negative relationship, Nevertheless the majority of evidence indioates that
the adoption of HYV is positively related to farm size. If fixed costs are considered
t
54
._
.__.
-
..__
-~
__-.
w--
to be associated with the HYV (fearning, locating and developing markets) they
tend to discourage adoption by small farmers.’ Ruttan (1977), Muthia (1971),
Schluter (1971), Sharma (1973) have found that small farmers over time catch up
with iarger farmers and that the intensity of HYV adoption on small farms exceeds
that of larger farms. The conclusion for the use of modern inputs (fertilizer,
pesticides) in their relation to farm size is not clear.
(2) Risk and uncertainty: Hiebert (1974) showed that when making decisions
farmers really don’t know everything about the teçhnology. They are making
decisions under uncertainty and it is when the process is taking place that they cari
accumulate information that allows them not to make wrong decisions. He showed
that the risk preferring farmer Will use more land and more fertilizer in modern
production than the risk neutral, while the risk averting producer Will use less land
and tess fertilizer than the risk neutral. He also showed that learning which
increases with the level of skills for decoding information, increases the rate of
adoption. Risk is often difficult to measure. An approach used by Q’Mara (1980)
and Binswanger (1980) was to ascertain farmer’s perceptions through direct
interviews, using sets of subjective yield distributions associated with HYV. They
showed that farmers’ perceptions were related ta adoption and were modified over
time when additional information was available.
tearning and info~ation accumulationplay an important role in the farmer’s
decision to adopt a new technology. Feder and CYMara used a mode1 of the
decision process in which uncertainty about an innovation depends on the
1
55
cumulativearea allocated to that innovation. It represents experience and with the
a~umulation of experience, uncertainty declines and the innovation is adopted by
more producers. Herath (1982) showed that land allocation between HYV and the
local variety cari be explained not only by expected outputs and costs of the
technology but also by the individualattitudes toward risk. Biswanger (1980) four-rd
that differences in investment behavior observed among farrners facing similar
technologiesand risks cannot be explainedprimarily by differences in their attitudes
toward risk but would have to be explained by differences in their constraint sets
such as access to credit, marketing and extension. Policy support to these farmers
could remove these constraints.
Mearth et al (I 982) compared the expected profit maximization model, and
the singfe and muiti attribute models in predicting trop variety selection by rice
farmers in Sri-Lanka. They found that the single attribute mode1performed better
than the mult~-a~ributemode1and that risk attitudes were important in the decision
process.
(3) Human capital: The rote of human capital is welf integrated with theory. Schultz
(1964, 1981) showed that changes in the technological environment increase the
value of farmer’s ability to perceive, interpret and respond to new events. Many
studies have found a positive relationship between education and the adoption
of
technology, for example, Chaduri (1968), Evenson (1974), Gerhart (1975), Ram
(1976), Sidhu (1976), Petzel(1976), Hu@man(1977), Villaume (19771, Rosenz,&g
(1978), Jamison and lau (1982), and Justin Yifu (1991).
li
56
--.
-.-....
.
-
-
.--.--.----.
-.-.-...
_-
.
.
_
._
---
..
1
*
:
Years of experience in farming often have been used in adoption studies but there
is no clear tut explanation in the relationshipwith the rate of adoption, In fact years
of experience may or may not be positively correlated with the use of the new
varieties, since experience may be associated with the inertia of traditional
practices and high level of risk aversion. On the other hand, experience may be
associated with knowledge accumulated and enable quicker and more accurate
decoding of information;
(4) Labor availability: Labor availability affects farmers’ decisions about adoption.
HYV generally requires more labor inputs (more weeding) SOlabor shortage may
inhibit adoption. It may afso increase the seasona! demand for labor. Hicks and
Johnson (1974), Harriss (19721,Helleiner (1973 and Norman (1969) showed that
in African farming system the main constraint may be a labor scarcity during peak
season activities.
(5) Cmdit constraint: Many studies have found that differentiat aocess to credit cari
expfain differences in the observed rates of adoption. This seems to be more Iikety
in the case of indivisible types of technology. Lowdermilk (1972), Lipton (19761,
Bhatla (1979), Van der Veen (1977) showed that the la& of credit atone does net
inhibit adoption of scale neutral innovations. In many studies farmers reported the
lack of credit for not using a specific technology (Bhalta, 1979; Frankel 1971; Wills
1972; Khan 1975). Gerhart (1975), Rochin and Witt (1975), Perrin (1976) showed
that off-farm incomes oan increase adoption. Glay (1975) showed that in areas
where adoption of divisible innovation (such as HYVs) depends on (or is greatly
\
57
-
_
_
_
-.
^
enhanced by) complementary indivisible investment (such as tube wells), lack of
credit cari impede the uptake of the divisible innovation by smaller farmers.. The
avaiîability of the HW, which is related to the existence of a reliable distribution
system, influences adoption
3.5 The Approach Used in the Study
Most studies have assumed that the innovation was right and Me
consideration has been devoted the characteristics of the innovation and their role
in the adoption process. Salem (1979) showed that the adoption of high-yielding
wheat varieties in Tunisia is conditioned by the extent of the technologicai traits and
palatability differences with the local variety. Byerlee (1986) used two measures
(i.e., profïtability and riskiness) to show that the pattern of adoption of a component
of technology is a function of characteristics such as profitability, riskiness,
divisibility, complexity and availability. Byerlee (1993) used a mode1that assumes
that the profïtability of varietal technologies is ver-ylocation specific and when they
are evaluated in a joint product framework their ranking Willdiffer from the one when
only grain yield is considered. He showed that with input levels fixed in the short
run, varietal adoption depends on relative prices of grain and straw and on input
use. The jointproduct characteristics may explain lagging HW adoption in a wide
variety of settings since grain-straw price ratio on the order of two or less is not
uncommon. The ‘adopter perception’ paradigm suggests that the perceived
attributes of innovations condition adoption behavior (Lynne et al, 1988). Limited
‘t
58
quantitative studies have consideredfarmers’ perceptions in the context of adoption
decisions.
8y ignoring the technofogy specific factors and how farmers evaluate the
appropriateness of the technologies, the literature on adoption has omitted major
sets of critical factors determining adoption behavior. Farmers’ perceptions of the
qualitative traits embedded in new agricultural technologies are particularly
important for modern trop varieties. In making decisions farmers for-m subjective
evaluations of the characteristics of modern varieties by comparing them with the
existing local varieties. Rather than socioeconomic factors explaining the lack of
adoption of new technologies, rejection of those technologies by farmers may be
a rational choice based upon their perceptions of the inappropriateness of the
innovation. Therefore models of adoption behavior should incorporate these
endogenous farmer evaluations.
Few studies have considered the socio-cultural aspects of adoption. In light
of the important role agriculture must play in the development of the economies of
LlCs, attempts have been made to enhance the level of productivity of this sector
(by transforming its production technology) with the introduction of new agricultural
technology to the farmers. However, in a number of cases the modern technologies
have been rejected by the farmers notwithstanding the high levels of potential
profitability. For example, farmers in Southern Senegal, rejected the use of
chemical fertilizers in their rice fields. This raises the problem of compatibility
between the innovation and the adopting system viewed from the standpoint of the
\
59
consequences of accepting and using the innovation, Following this notion, a newly
introduced technofogy that is highfy profitable but functionally incompatible may not
be adopted. Conversely, the greater the compatibilityof a given technalogy with the
culture of a society the more likely it Willbe adopted and the more rapid Will be the
rate of adoption of that technology. Economists are wont to think that if a new
agriculturai technology is introduced which is more efficient and hence more
profitable than the traditional technology, then farmers would immediatefy
appropriate the new. Schultz(1964) stated that economic factors are strong enough
to warrant the disregard of cultural factors. This conciusion has only limited
applicability and was based on a neglect of the fiterature on adoption by rural
sociologists. Socio-culturalfactors are often difficult to put in models. Nonetheless,
we need to recognize that economic considerations cari be good predictors of the
rate of adoption of a new technology only in the absence of cultural barriers. Wence
profitability may not be a strong explanatory variable when culture presents a
barrier to the adoption of new technology.
A number of characteristics have been suggested which would facilitate
appreciation of the economic and non-economicadvantages of the new technology.
Barnett (1973) distinguishedbetween material and nonmaterial advantages of new
technologies. Material advantages oan be more easily demonstrated and
communicated. Rogers (1971) has suggested relative advantages, trialability, and
observability, as characteristics of new technology which make for rapid spread.
Trialability of a new practice and observability stimulated interaction between
\
* 60
farmers. if farmers are interested in improving their economic situation, triatability,
observabitity, and interaction are important means by which they cari familiarize
themselves with a new technology. Past studies demonstrated that the more
observable the results of an innovation are the more likely Will the farmers adopt.
It follows from the above discussionthat more attention must be given to the
characteristics of the technology in the adoption literature. This will be a major
consideration in this study.The technoiogy Will be first evaluated using different
performance criteria and in a second step the role of those criteria in the adoption
process Will be addressed. Thus the study, in addition to the classical sets of
factors inctuded in the adoption literature, also includes farmers’ perceptions of the
qualitative traits embodied in the new technology.
3.57 The YieldGap befween On-Station and On-Farm Conditions
-.
Yield Gap analysis is a research methodology that emerged on a formal
basis in the 1970s. Developed by the Mernational Rice Research Institute (IRRI),
it was extensively used to measure and analyze the determinants of yield gaps in
farmers’ fields in Southeast Asia whefe high yielding varieties have been adopted,
The total Yield Gap is conceptually divided into two parts. Yield Gap I
represents the difference between experiment station yield and potential on-farm
yield. Yield Gap 1, exists mainly because of environmentai differences between
experiment stations and the average rice farm. The technology that gives high
yields on experiment stations may not give as high yields in the less favorable
environments that exist in a large part of the rice growing area of SouthernSenegal.
‘z
61
There may also be components of experiment station technofogy that are not
transferable to a farmer’s field. Yield Gap II is the difference between potential and
actual yield at the farm level . By definition, this gap exists because farmers use
inputs or practices that result in lower yields than those possible on their farms.
Yield Gap 11cari be broken into two components:
(1)
One area identifies what biological or physical inputs or cultural practices
account for the gap. Experiments in farmers’ fietds are essential to obtain
this information.
(2)
The other area identifies why farmers are not using the inputs or cuitural
practices that would result in higher yields. Economie analysis of the
experiment and farm surveys provide the main research inputs for this area.
The presence of the Yield Gap cari be interpreted in either of two ways: fit&,
as representing a potential production increment abwe fat-mers’ yield levels, or
second, as an indicator of more fundamental problems with the varieties
themseives, in particular their poor adaptation to farmers’ environmental or
\
management constraints. If the principal factors causing the yield-gap cari be
economicallyresolved at the farm level, greater weight should be given to the first
interpcetationand steps to resolve these factors might be considered as necessary
compkementsfor the extension of the new varieties. However, if these factors are
not economic to resolve, then the second interpretationbecomes more relevant and
it becornes necessary to reconsider the research objedives and methods which are
prodqcing poorly adapted varieties.
i.
62
Since the main focus is on Yield Gap II, it is essentially based on on-farm
testing after the fact. This Will allow us to anaiyze why on-farm yields do not
measure up to potential yields following the adoption of high yielding varieties.
Improved understandingof constraints Will enable research and extension workers
to help farmers make better choices among the production techniques currently
availabl,eto them, given their present resources. The general objective is to identify
the factors that explain the difference between actual and potential rice yields in
selected environments.
The contribution of test factors (variety, fertilizer, pest controt) to the Yield
Gap is determined from a factorial triai following a modified version of the design
developed by De Oatta (1978). In this setting the test factors are kept at the
farmer’s level: level l= local variety, no fertilizer and no pest control; and the
recommended level, level 2 = improved variety, 150kglha of fertilizer and pest
control. Factor levelsfor each treatment are shown in Table 3.1 for the case of the
three test factors.
Table 3.1 : Treatments Included in the Factorial Experiment.
Treatment
Factorial
1
2
3
4
5
8
7
8
Variety
Fertilizer
Pest Control
1
1
2
1
2
1
2
2
1
1
1
2
1
2
2
2
t
63
AIl other factors
1
1
1
1
1
1
1
1
--.
Based on the treatment description in Table 3.1 and using Yi to represent the yietd
of treatment i, the formula is:
Yield Gap = Vs - Y,
Contribution of varie#y =
Y2+Y5+Y@-*
4
YpY3+Y4+Y,
-
4
(3.3)
Cm~ibution of pi
contml =
Y4’Y6’Y,‘YS - Y1+Y2+Y3+Ys
(3.4
4
4
The design by maintaining ail other factors constant does not make it
possible to assess the contribution of farmers’ practices in rice production.
Productionfunction estimationWillenabte us to identify the major yield components
at the farm level. That is:
Yield = F( XJ
Where F represents a functional form and J$ rapresents
different farmers’ cuttivation practices.
The major problem is selecting the right functional form. TO overcome this
prob1e.mwe Will use the Box-Cox technique. It is an empirical technique that cari
give guidance on the appropriate functional form that best fits the data (Spitzer,
1982). The Box-Cox technique proceeds by a transformation of the variables, thus
‘t
64
..-..
.:-.I.---
.
..---......-
--~.-__
_-_
--.--
--.i_-
-
.
,,
-.-..
_
._
_.._
_._
.-
.-_,-
the madel cari be written:
With the Box-Cox procedure, we are able to test wether A = 0, % or 1 so that
inferences cari be made with regard to the optimal functional form.
3.52 A~~pfabi/ify Analysis
The description of the physical environment and farming systems of the
Casamance region in Chapter 2 stressed the variability of the environment.
Variabiiity is manifested most clearly in wide intra-annual and interspatial variation
in both the amounts and distribution of rainfall as well as in considerabte microvariability in soif quality. The quality of management also varies considerably
across farmers as a function of differences in resource endowments, inter-persona1
ability as well as due to stochastic events over which farmers have little control.
Because of farmers’ risk aversion, the probability of wide adoption of a new variety
witl be greater, ceteris paribus, to the extent that the variety shows stable yield
superiority over a range of physical and management environments.
Adaptability(i.e., fonnerly calledmodified stabitity) analysis techniques have
been devetoped to compare the performance of cultivars across such variable
environments. A commonly used technique which cari be applied to data drawn
from a large number of test sites is to regress the yiefd of each variety at eaoh site
against the mean yield of all varieties at each site (Weil and Quoi, $974)
(Hitdebrand, 1983; Hildebrand et al, 1996). The mean yield then represents a type
I
65
of environmental index. A site where yields are low, due either to management or
to physicat site characteristics, is considered a polir environment, and vice versa.
With this definition environment is measured as a continuous proxy variable across
the range of average yields.
We Willfit the following regression model:
(3.6)
where Y, = yields for the improved variety i and the local variety k at location j,
Zj - the average yield of all varieties at location j, and
Xi = a dummy variable that takes the value 1 for the improved variety and 0
otherwise.
We fit the regression for each pair of improved and local varieties examined while
automaticafly obtaining test statistics for the change in intercept (b2) and the change
in slope (b3)for the improved variety as compared to the local. Secause we assume
that the factors which define a good” or “bad” environment Willprobably be different
at different levels of fertility, we Will run the model, using data with zero fertilizer,
and secondly using data with different levels of fertilizer.
Using, the estimated regression coefficients we will categorize and group the
improved varieties according to four standard stability types: the first type (type A)
represents those varieties which are superior to locals across ail environments (b2
and b8are positive); the second type (type B) represents cases where the improved
variety is superior to locals over a range of poor environments but is inferior over
1
66
a range of better environment (b, is positive but b, is negative); the third type (type
C) represents the case where the improved Varie$ is inferior in poor environments
but superior in better environmentsfb, is negative but b, is positive); the fourth type
(type
D) represents the case where the improved variety is inferior over all
environments (b2 and b3 are both negative).
3.5.3 Response fo Improved Management
By contrasting the low-input environment within which local varieties have
been setected for generations by farmers with the high-input management under
which improved varieties are screened it would be expected that the most
management responsive cultivars would constitute the bulk of most modern
breeding lines. Hîgh management responsiveness may in fact comprise an explicit
breeding objective geared to achieve maximum production gains.
Several questions, however, arise in this context. First, are improved
varieties in fact more responsive to modern inputs when cultivated under farmers’
management that is, are their response curves steeper than locals over an
economic range of input levels when facing on-farm stresses? Second, do the
response curves cross, such that the ordering of varieties with respect to yietd
changes significantly between low and high input levels (Le.# the so-catted
crossover effect)? TO address these questions we Willfit the following regression
modela:
Y = bO+ blX + b2Xls5+ b,D, + b,D,X + b,D,X’.5 + e
where Y = yietd measured in kg/ha
\
67
(3.7)
X = fertilizer application measured in kglha
CI,= 1 for improved variety and 0 for local variety
e is a random variable N (0, 1)
We use a three-halves to mode1input response since it allows nested tests of
hypotheses concerning the evolution of varietal technologies (Traxler, 1993).
Studies have compared the performance of linear response and plateau models
and differential functional forms. Neither approach has estabiished a ciear
dominante over the other on theoretical or empirical grounds (Swanson, 1963;
Tronstad and Taylor, 1989).
We test two hypotheses; (1) that nitrogen response is equal for the improved
varieties as for the local varieties (b4 = b, = 0) and (2) that output without nitrogen
is the same for improved and local varieties (b, = 0 ).
3.5.4 Farmers’ Quantitative Assessment of Rice Varieties
Rioe varieties may best be described in terms of their characteristics (cycle,
yield) and often by the presence or absence of one or more characteristics. For
some characteristics (taste, cooking quality), it is often possible to define how
important they are to farmers. For others such as yield, it is possible to measure the
characteristic on a cardinal scaie.
This section focuses on the problems associated with the measurement of
the quafity of varieties available to farmers. The major concem is the development
of an index to measure the extent to which the varieties provided by research and
extension services meet the expectationsof farmers. The starting point for the study
i
68
is to elicit, by sample survey, ordinal data on farmers’ perceptions for the
characteristics of the varieties and on their perception of the quality of the
characteristics embodiedin the varieties. We Willuse in eliciting those attributes the
empirical approach developed by Reeds, Blinks and Ennew (1991). This approach
uses a relatively simple index that provide an indication of how well certain variety
characteristics meet farmers’ preferences. Implementation involves application of
a quasi-arbitrary ordinal weights in which farmers rank the importance of each
attribute and how well these specific attributes are being embodied in different
varieties. Reed et al show that by choosing weights meeting certain conditions, the
proposed indices are robust and when oalculated under different sets of weights,
these indices are highly correlated. Each farmer Willjudge each attribute along two
scales. First, what is the importance of the attribute to them (very important,
important, not SOimportant). Second, how do they judge the quality of the attribute
being supplied by the improved and local varieties (very good, good, poor). Thus
for N farmers, each ranking the characteristics according to their importance and
quality of supply, the response matrix is the folfowing:
Table 3.2: The Response Mattix
Each antry in the matriX, ni/, represents the number of farmers who fankecj the
particuiar attribute based on their perception. of its importance, j, and their
satisfaction with the quality provided, i. The bottom row entries, qt are the total
number of farmers who ranked the characteristic according to its importance. The
far right column entries, r,, are the total number of farmers who ranked the
charaGteristicas beingembodied at a certain level of satisfaction, Given the above,
it must hold that:
The weighting matrix is presented in Table 3.3.
Table 3.3: The Weighting Matrix.
The far right column in the table indicatesthe row weights, si. These are the weights
assigned to the farmers’ perception of how welf a specific attribute is bsing
embodied in a given variety. The bottom fow shows the demand weights, 4,
assigned to the farmers’ perception of how important is the specific attribute. Each
cell in the matrix is derived as:
Wd= SAa
(3.9)
70
Reed et al, recommended that certain restrictions be imposed on the weights, so
the folfowing inequalities hold:
W$j > Wti > Wq fOf
all j
(3.10)
The above inequality implies that regardless of how important a characteristic is,
the better the characteristic is being present in the variety as perceived by the
farmer, the higher the weight is,
Wir > W, > W, >
0 for all i
(3.11)
which is rated good or better.
Inequality Equation 3.11 states that, whenever a characteristic embodied in a
variety is rated as good or better, the weight ought to be positive and increase in
value as its levet of importance increases,
wit < w, < w, < 0
For all I
(3.12)
which is rated poor.
Inequslity Equation 3.12 implies that weights for characteristics rated as poor
should be negative and decreasing as their importance rises.
The above inequalitiesimply the following restrictionswhen constructing the supply
and demand weight:
s, > s, > 0 > 5-j
and
d, > dz > d, > 0
(3.13)
(3.14)
All demand weights, di are positive, while the supply weight for a characteristic
ranked as poor is negative. The above weighting scheme assures that the highest
(lowest) weights Will be given to those characteristics considered very important
and embodied very well (poor).
Given the response matrix ahd the weighting matrix, we Will calculate three
indexes.
First is the attainment index, W, given by:
(3.15)
The attainment index provides us with a measure of how well farmers’ perceptions
of the importance of the characteristic matches farmers’ perceptions of how well it
is being supplied in the variety. The maximum value carried by W is one, and it
implies a Perfect match. Al1farmers rank the particular attribute as very important
and all farmers rank the quatity supplied of it by the variety as very good. The
minimum vatue of the index depends on the supply weights, si, çhosen, and is
calcula%edto be (sJs,) < 0.
The second index that witl be used is the suppty index, S:
s=‘- ;y+,
S,N
(3.16)
i=l
This index is a measure of the perception of farmers on how well a characteristic
is being embodied in the variety. A maximumvalue of one indicates that atl farmers
perceive the characteristic supplied as being of ver-y good quality. The minimum
\
72
value of the index is (~JE+)< 0, and depends on the weights ohosen. The minimum
value Will be attained if all farmers perceive the Quaiity of the oharacteristic being
supplied as poor.
The third index to be used is the demand index, D:
--.L..Edr.
(3.17)
D - d,N i=l J J
The demand index is a measure of how important the farmers perceive a particular
characteristic to be. A value of one indicates that ail farmers perceive the
charaderistic to be very important. fhe minimum value of the index is (ddd,) > 0,
and is attained when all farmers perceive the characteristic to be of little
importance.
3.55 Theory of farmer Choi~e Behavior
The study focuses mainly on the adoption of improved rioe varieties,
oonsideredas an innovation which is divisible and neutral to soate. fts adoption is
analyzed as a one-component innovation. The diffusion of a high yielding varie&
is usually associated with the adoption of other improved inputs such as fertilizer.
In Casamance, farmers do net use fertilizer on their rioe ftelds. The Fow-lyinginland
valleys are better watered and sufficiently upstream, and have a higher level of
organic matter coming from the river.
The decision of a farmer to use improved rice varieties is oomplex and cari
be modeled as consisting of two mutually exclusive processes. First the decision
?
73
to adopt the varieties is made, while in the second step, the level or intensity of the
use
of the varieties is decided. Thus the theoretioal stochastic decision mode1for
the adoption behavior of rice farmer is represented, as:
Y = &B + Ui if (I’=XBi+ Ui )
=Oif
I’cT
>
T
(3.18)
i=l,2...N
where 1’is an unobserved latent variable;
Ui
is random error term that is distributed
normafly with mean zero and unit variante; & is a vector of explanatory variables
explaining adoption decisions Y. Equation (3.18) indicates that there is an
unobservable threshold level 7, and any level of the unobserved latent variable 1’
below T Will not lead to an adoption choice and Y takes on the value of 0. For 1’
above the threshold level. Equation (3.18) implies that two simultaneous choioes
are made: the decision to adopt, and the intensity of adoption. The dependent
variable Y is then a continuous function of the explanatory variables.
In the decision making of farmers on the new rice varieties it is assumed that
they seek to maximize utility derivable from any given variety of rice. The farmer
views the rioe variety as a complex embodiment of several characteristics that are
important in adoption decisions. The observed adoption choice is the end result of
an complex set of inter-varietal preference comparisons made by farmers. Let the
utility derived from an improvedrice variety be given by U(m) and the utility derived
from local variety by U(l). We define the ith farmer’s perceptions of the varietal
specific characteristics of the improved and local varieties as Pr,,, and ip
respectively. The farm and farmer specific factors conditioning adoption behavior
\
74
for the improved and local varieties are denoted by D,, and D, respectivefy.
J”hen
the utility function is represented as:
U(P; 0) where P=(Pi,; PJ, i = 1,Z...N; and D=( Di,; D,,), i = 1,2...N.
These utility relations are represented in Equations (3.19) and (3.20) as functions
of the farm and farmer specific factors affecting choice behavior and the varietal
specific traits as perceived by farmers.
Umi= G(Pi, ; Di,) + e,,,i
(3.19)
Uli = L( Pi,; DiI) + e,i
(3.20)
Where G(.) and L(.) are assumed to be monotonietransformations of the arguments
satisfying G’(.)>O, L’(.)> 0, and G”(.)< 0, L”()e 0. By monotonie transformation,
U’( G)z 0 and U’(L) > 0 respectively (Varian, 1992).
When the inter-varietal preference comparisons are such that Umi-Uil>0 or (G(P,
; DJ - L(P, ; Di/) + e’,) > 0 where e’,=( e,i , e,J the unobserved latent variable I’ will
be greater than T and the adoption and the intensity choices are made. Under this
situation farmers’ preferences are such that they prefer the attributes of the
improved variety to those of the local variety. Otherwise the farmer Will prefer the
local variety to the improved variety and no adoption or intensity of use decision is
observed for the improved variety. Therefore, the adoption choice mode1for the
farmer is a step function of the non-observed implicit inter-varietal preference
comparisons. We hypothesize that in the adoption decision making, implying that
farmers perception of the better performance of the improved varieties (with regard
to a number of varietal specific attributes) are positively related to the adoption
\
75
decision and use intensities of the improved rice varieties.
The methodology that Willbe used in the anafysis is Tobit (Tobin, 1958), a
method that is appropriate for studyingdecisions in cases where the en-or terms are
truncated or censored (McDonald and Moffitt, 1980). The approach has been
extensively used in the analysis of choice behavior(Akinola and Young, 1985;
Shakiya and Flinn, 1985; Shishkoand Rostker, 1976; Rosen, 1976; Kinsey, 1981).
The advantage of the Tobit mode1over the dichotomous choice models such as
Probit (Finney, 1971) and Logit (Aldrich and Neison, 1984) is that it allows the
~exjbilityof determiningnot onty the probability of adoption but also the intensity of
adoption once the adoption decision has been made.
Thus two types of effect shouid be discussed for each independent variable in a
Tobit model:
(1)
The effect on the values of the dependent variable for cases with nonlimit
(nonzero for those who adopt) value on the dependent variable;
(2)
The effect on the probability of having a nonlimit value for cases with the
Emit value (zero for those who do not adopt) on the dependent variable.
A common mistake made when interpreting Tobit coefficients is to treat them as
effects of the independentvariable for cases that are above the limit. TO avoid this
major drawback, the Tobit coefficientsWillbe decomposed following McDonatd and
Moffitt (1980). According to their formulation the mode1for predicting the valueof
y is:
(3.21)
if X8+e>O,theny=XB+e
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76
if XB+e&I,theny=O
(3.22)
Then the formula for the expected value of y for ail cases is:
Ey = XB x F(z) + sigma x f(z),
(3.23)
F(z) is the cumulative normal distribution function associated with the proportion of
cases above the limit, f(z) is the unit normai density, z is the z-score for an area
under the normal curve and sigma is the standard deviation of the errer term.
In order to find the effect of an independentvariable on the expected value of y, we
need to compute the partial derivative dEy@& and the formula is:
(3.24)
Ey* is the expected value for those who adopt the technology. dEy*@& is the
change in the expected value of y for cases of adoption. aF(z>l~?&is the change in
the cumulative probabilityof adoption associated with a given independent variable.
The tvvoterms in Equation 3.24 identify the two desired effects in a Tobit mode1for
those who adopt and those who do not adopt. McOonald and Moffitt (1980), and
Maddala (1983) provided formulas for calculating these two terms:
For farmers who adopt:
(3.25)
For farmers who do not adopt:
%
(3.26)
where Biis the Tobit coefficient for a particular independent variable. Wjth z, f(z),
F(z) and the Tobit coefficients, the change in the expected value of the dependent
variable when adoption takes place cari be computed from Equation 3.25.
Chapter 4
The Data and Variable Definition Procedures
The purpose of this chapter is to describe the data, survey methodology,
sampling procedures, characteristics of sample farmers, and specification of
variables for data analysis.
4.1
Sqcondary Data Sources
The study is iargely micro-economic in terms of data collection since it
concentrates on gathering information about farmers’ improved variety utilization,
their perceptions about improved varieties, and improved varieties design and
distribution poiicies. It utilizes both primary and secondary data to examine the
different issues.
Data on responses to improvedpractices under farmers’ conditions obtained
from the analysis of on-farm and on-station experiments conducted by ISRA in the
area during the period 1982436are used to assess the performance and profitability
of the new varieties. Data on the most promising materiais coming out of ISRA
prograims are used in the study.
From 1982 to 1986 the FSR program, using the agricultural zones in Figure
2.1, and described in Section 2.7.2.1, started off with the implementation of
indicative on-fat-mtrials based on the exploratory sunrey resufts. The surveys were
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79
designed to provide quantitative data about production practices and constraints
by trop and field operation. The data were collected in conjunction with the
information concerning farmers’ fesoufoe base on a sample of 235 farms. The data
were oolleoted on all plots cultivated by every househotd. The work at the plot level
simplified the collection of agronomie data and made it easier to conduct the
analysis at the househotd level by aggregating plot level information. A plot was
defined as a contiguous unit of land in the same trop or trop association.
On-fart trials during the fîrst year were designed to be indicative. Most tests
simply compared different local techniques or compared local with improved
practices under farmers’ conditions. They were generally conducted on small plots
(the variety tria1plots were 30 square meters) and ocoasionally on large sized plots
(the field size comparison plots were each 300-500 square meters) for
demonstration pur-poses.As indicative Mals, they were repticated only a few times
across farms. The varieties used had already been tested on the station and in
multilooationaf trials carried out by the Rice Program.
Experiments were r-unas a joint activity between researchers and farmers.
The FSR team provided the purchased inputs (seeds, fertilizer) while farmers
supplied labor at their own oonvenience.Flexibilitywas sought in the conduct of the
on-farm triats to permit the team to understand the rationale of farmers’ behavior.
The results for the rioe varietal trials conducted from 1982 to 1986 are used in the
anatysis.
During 1986, the ISRA rice program initiated a Wo year researoher-managed
\
80
on-farm experiment to measure the major determinants of the yield gap for rice. The
experiment was placed in four villages in thé study area. Data on farmers’
cuftivation practices taken from the FSR team agronomie surveys suggested that
three Management factors, which differ between the station and farmer, were
important: namely the type of variety used, the level of fertilizer used, and the
degree of protection against pests, These three factors were tested at the station
and thq farmers’ levels in a factorial design with three interna1replications. Different
varieties (a total of 10 varieties) and a local were tested for aquatic rice, phreatic
rice and rainfed rice. The fertilizer levels were: zero fertilizer and ISOkg/ha of
nitrogen, the recommended dose. Protection against pests involved a single dose
of the jecommended fungicide.
!Duringthe same period, and using the same research sites and the station
for refdrence purposes the program conducted a two year research-managed tria1
to stu4y the response to nitrogen of different rice varieties. lt used a split-plot
design with four levels of nitrogen (0, 50, 100 and 150 kgka) with three
replic@ions.
;During the 1982-86 period, rainfall was below the long term avetage rainfall
for thq Lower Casamance. The 1983 year was particularly dry and resulted in a
failure ;Ofmost of the rice trop. In çontrast, 1984 began well, encouraging farmers
to piant rice but a dry period in August negatively affected both uptand and Jowland
trop yjelds.
:The section above briefiy surveyed the sources of the data that were used
81
in the $Valuation of the performance of improved and local rice varieties. In order
to understand why a farmer may have opted for adoption or nonadoption, a survey
of the r&e farmers was undertaken. At this juncture, therefore, a brief review of the
survey, methodology Will be provided.
4.2 Pqlmary Data Çollectlon and Survey Methodofogy
The data were collected during the 1996 rainy season directly from the rice
producers, This timing was used in relation to the specific purpose of the study
which:included field observations. Thus, the optimal period for the survey was
during:the cropping season period. Randomly selected farmers were interviewed.
A suyey questionnaire was designed by the author. Prier tu the survey, the
questipnnaires were tested after which some modifications were made, based on
additional information from farmers. The field testing of the questionnaires was
done by three enumerators, SOthat they could participate in developing the final
version and have a good understandingof the questions. At the time of the survey,
the area was divided into five agricultural situations (zones). This zoning (see
Section 2.7.2.1) emphasized the identification of major production systems.
Previaus work (see Section 2.7.2) showed Jittle intrazone variability and rather
higher inter-zonevariability. Twenty villages were chosen according to the following
criter&:
(V
Two villages per zone where ISRA had conducted adaptive on-farm triais
and socioeconomic surveys since 1982.
1
82
“--“__
.-.
..~
.._
_.
-.-_-___
.
(2)
One village per zone where research and extension had worked in a joint
researchdevelopment program. In such a s&ting triais were designed by the
researcher and monitored by the extension services.
(3)
One village per zone where no such work was conducted.
The locations of the twenty villages (in italic) are given in Figure 4.1. A
stratifipd random sample of 400 farm households (20 farms per village) was
subsequently sefected for detailed data collection.
During a pre-survey of 2 months, farmers were formally interviewed on
differsnt aspects of their production systems. For the purpose of the survey the
household head was used as the unit of observation. Jhe survey was designed to:
(1)
Elicit the farmer’s characteristics such as age, sex, experience in farming,
contact with extension, wealth, access to credit.
(2)
Provide information about production practices and major constraints by
trop. The plot was used as the unit of observation thus atlowing for future
aggregation at the household fevel.
(3)
Obtain informationabout iabor avaitabitity, labor use, peak labor period, offfarm activities and different alternatives to sotve iabor problems at the farm
level, Jhe interview was conducted for each household member in order to
develop a rough tabor profite for each farm.
(4)
TO provide information about farm equipment and ownership.
As we were interested in the adoption of improved varieties, much tare was
exercised duringthe process of varietat identification. Because farmers tend to
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83
rename varieties according to their origin, and to prevent bisses from misidentification of varieties, the enumerators we& helped in this process by the
breeders’ technicians and the extension agents living in the area. Women were
especially targeted in this sutvey since in most cases they are the oniy rice growers
in the househoid. They were first informaiiy interviewed about the main
characferistics they expected in any type of rice variety. They were asked to iist and
rank the different characteristics. The main purpose of such a survey was to eiicit,
from the farmer’s point of view, the importanttraits of an acceptable rice variety and
thus d&ermine which attributes of varieties might be relevant. Those characteristics
were used iater to assess the performance of the improved varieties actuaiiy used
by fafmers.
The survey about the use of the improvedvarieties began in August after att
the rice fieids were pianted, This made the identification of the varieties easier and
farmers were more readiiy avaiiabie during that period. The survey tried to:
(1)
Elicit farmers’ knowiedge and experience with the variety. In this survey the
variety was the unit of observation. Farmers were asked about when they
first tried the variety, the source of the seed, the number of plots they
pianted the variety on, when they first used it, their perceptions about the
results and the factors to which they attribute the quality of the results.
(2)
:Provide information on farmers’ rice pradices for the current cropping
season. For each rice plot, information was obtained about the variety
pianted, the area, and the different cuitivation practices (type of ploughing,
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84
method of planting, type of fertilization).
Figure 4.1: Location Map of Sampte Area in Lower Casamance
Plot Si;remeasurement was done by enumerators and heiped by the farmer himself,
using tapes and compasses, This operation was time consuming due to the fact that
plots are often scattered in different areas of the village.
From the survey, farmers’ preference comparisons for several varietal traits
‘c
85
-
-_
_ . -.. . ----_
were obtained. Farmers compared their current local rice variety with the range of
improyed rice varieties being diffused and used’by them. They determined if the
modem varieties were better or inferior ta the local with respect to the varietal traits.
The fqrmers themselvesrated the different varieties according to several attributes.
Since the question of adoption did not corne up, the farmers should not have fett
obiiged to rationalize their adoption behavior. The field procedure involved asking
a farrrier to consider varieties familiar to them and then rate each variety on each
of the attributes. The primary concern was to determine whether perceived
differences in attributes of various varieties couid help to explain differences in the
rate a1which these varieties were adopted by farmers.
4.3 Rrce Variety Gategorles
A wide range of improved rice varieties have been tested by ISRA through
on-station trials, muftilocationaltriais and on-farm triais. Most of those varieties are
not msidered “released” since they did not go through the certification procedure
and thus are not part of any seed multiplication program (see Section 27.1).
Thus the study maximized variability in the area by including as many
varieties as possible in the research design. It concentrated on these varieties that
were released to farmers through the extension agency and for which a seed
multi~li~tion program exists. The research afso concentrated on those varieties for
which consistent data from on-station and on-farm trials exist. Those varieties are
well known by farmers in the area, The varieties are, for rainfed rice RAT 144,
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86
IRI 12, IRATIO, for phreatic rica DJl2519, IKP, TOX728, and for aquatic rice,
DJ68$?Dand ROCKS.
Lower Casamance is known for having a wide range of indigenous rice
varieties. As the result of the drought, most of the local varieties have virtually
disappeared. The most common local varieties now in the region are Ablaye Mano
and Barafita. They are used in the comparison with the improved varieties.
4.3 Variables Definition
In the dichotomous mode1the dependent variable is binary taking the value
1 when the farmer was cultivatingthe improved varieties and zero when helshe was
net. In determiningthe intensity of adoption the dependent variable (PERIMP) was
the percentage of total rice planted to improved rice varieties. Using the relative
measure maintained consistency with other studies, and allowed insight into the
competing behavior between the adoption of improved varieties instead of local
varieties.
There were two major categories of independent variables:
(1)
Variables representing farmers’ circumstances. Many empirical studies
have found those faotors highly correlated with the adoption of improved
technologies. But the size and sign of that relationship vary across
socioeoonomic environments. Table 4.1 shows the expected signs for the
different variables.
t
Table 4. ‘l: Expected Sign for the Relationship between Farm and Farmer
Characterîstics and the hdoption of Improved Rîce Varieties.
LABOR
APPREXP
ACCESS
INFORMATION
MEMBER
WEALTH
TRACTION
These independent variables were as foltows:
LABOR: Family size expressed in terms of the number of full time
agricuttural workers. In definingthis variable we take in account the effective
tîme of presence of the individual in the village, hîs tevel of effective
participation to the agricultural activity, and his age. Men and women
received the same weight. Sînce împroved varieties are often more labor
intensive (number of weeding), a positive relationship between family sîze
and the adoption of împroved rice varieties is expected.
SIZE: Farm sire expressed in hectares. There is no clear tut relatîonship
between adoption and farm sire.
AGE: Age of the farmer measured in number of years is expected to be
positively related to the adoption of improved technoiogy.
3
88
APPREXP:A variable that characterized the farmer’s initial impression with
a specific improved variety: ?= exoellent,‘2= fair, 3= poor. This variable is
hypothesized to be negatively related to adoption. Farmers that had a bad
experience with a technology Will be less willing to adopt.
ACCESS: A dummy variable that takes the value 1 if the farmer had access
to input credit and 0 other wise. Input credit is one form of credit farmers cari
access through the extension program. Also credit is linked with seed
availability. This variable is expected to be positivety related to adoption,
Many studies have reported the lack of credit as a reason for nonadoption.
INFORMATION: A measure of how knowledgeable a farmer is about
improved rice varieties. The number of improved rice varieties the farmer
has been cultivating was used as a proxy of hislher level of information. We
expect this variable to be positively related to adoption. The more farmers
were exposed to improved varieties, the more they learned about the
varieties and the more likely they were to adopt them.
MEMBER: Member of a village-level organization (GP). Measured as a
binary variable, whioh takes the value 1 if the farmer was an active member
and 0 other wise. The village-level organization is used by the extension
program. Farmers who are active members are more exposed to extension
activities. We expect this variable to be positively related to adoption.
WEALTH: A measure of how rich a fat-mer is perceived. TO elicit this variable
a small group of farmers was used to judge a given farmer. The concept
?t
89
included several attributes: the size of herd owned by the farmer, his off-farm
income, if he has children who have migrat’ed out of the village , the type of
housing, etc. The variable takes the value: 1= very rich, 2= rich, 3 = poor.
Wealth is expected to be positively related to adoption.
TRACTION: A dummy variable that takes 1 if the farmer used animat traction
and 0 otherwise. In Casamance few farmers use animal traction in rice fieids.
The expected sign of this variable on the adoption of improved rice varieties
is undetermined.
Variables representing farmers’ perceptions about rice varieties. The
numerous traits elicited from the pre-survey were grouped in a limited
number of categories to facilitate the survey. Using the initial listing of
characteristics from the pre-survey would be time-consuming for the
research and exhausting for farmers. Seven major characteristics were
identified and farmers used them to compare the local variety to the different
improved varieties. These variables are hypothesizedto be positivety related
to adoption (Table 4.2). The variables were:
CYCtE: A measure of the number of days between planting and harvest. ft
is measured as a binary variable: 1 if the farmer thought the improved variety
was superior to local in terms of shortness of growing cycle and 0 othewise.
RESISTANCE: Measured as a binary variable: 1 if the farmer thought the
improved variety was superior to the focal in terms of tolerance to major
stresses such drought, insect, and blasts, and 0 otherwise.
90
YIELD: Measured as a binary variable: 1 if the farmer thought the improved
variety was superior to the local in terms of yield, and 0 otherwise.
TILLER: Tillering capacity, measured as a binary variable: 1 if the farmer
thought the improved variety was superior to the local in terms of tillering
ability, and 0 otherwise.
HEIGHT: Measured as a binary variable: 1 if the farmer thought the
improved variety was supefior to the local in terms of plant height and 0
dherwise.
QUALITY: It captures the ease and the quality of cooking. Measured as a
binary variable: 1 if the farmer thought the improved variety is superior to the
local and zero otherwise.
TASTE: Measured as a binary variable: ‘l if the fat-mer thought the improved
variety was superior to the local in terms of taste, and 0 otherwise.
Table 4.2: Expected Sign for the Retationship between Technology Characteristics
and the Adoption of Improved Rice Varieties in Casamance
Expected sign
Variables
rlegative
CYCLE
RESISTANCE
YIELD
TILLER
HEIGHT
QUALITY
TASTE
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91
hdetermined
4.4 Main Socioecanomic Characteristics of Sanple Farms and Farmers
This section describes important socioecon~mic characteristics of this study
sample farms and their operators (Table 4.3).
Table4.3: DescriptiveStatisticson the VariablesUsedin the EmpiricatMode1
Yieid
Tillering ability
Cycle
Height
Resistame to stress
Cooking guality
Use of timal
traction
Access to credit
Age of household head
Family labor
Total fmm size (ha)
Area in rice prabuctian @a)
Wealth
Level of f&rnxxs’ information
Initial impression of mrieties
The age of farmers is ver-yhigh (on average 54) and the age pyramid in villages is
partiçularly skewed toward the very old and very Young. This is specially due to the
important out-migration of Young men and women for the cities, Studies (De Jong
et at, 1976) have shown the la& of eoonomicopportunities in rural Casamance and
the lack of suitabie lands caused by the different droughts were the main causes
of this migration. The same studies show that the migration has two effects: a
negative effect in terms of labor supply during the cropping season, and a positive
effect on family income since those migrants earn income and send money to the
family, which oan be used to hire labor during the peak periods. lt was also noted
that some of the migration is only temporary and happened during the slack period,
Women are the main component of the rural labor force in the area. On average in
the sample women contribute for 54% percent of the labor in agricultural
production. This net increase (Table 2.3 in Section 2.3) could be partially explained
by the increase in rice cultivation in 1995 and 1996 following the improvement in
the rainfall. They manage a very significantpart of agricuftural production, and they
are usually responsible for cereal production in the househotd. They predominate
in food processing and preparation, and spend time obtaining water and fire wood
required to make food and other agricultural(gathering fruits, vegetables, basketry)
products for home consumption and sale. A better understanding of this local
environment could help in designingtechnologies and institutional changes that are
likely to help women.
Farmers’ access to credit is a major concem in rural area with the New
ï
93
AgridtuFai
Pofioycentered on Statedisengagement and privatiration (sec Section
2.4).The drop in cash income, associated with the relative declins in peanut
production, has obvious implications for farm family welfare, because it seriously
restricts their ability to invest in technology which requires cash inputs. In the
sample, only 20.5 percent of the farmers had access to credit for the last two years.
This credit was obtained from the extension project (DERBAC).
The type of farm equipment used is also iinked to the credit availability (sec
Section 2.4). The predominance of hand cultivation is a major characteristic of
farming in the area. Sixty percent of farmers in the sample do not own and use
animal traction. The other 40% that use animal traction, are mainly located in the
northeast and the northwest. Animal traction is mainly used on uptand crops. In
recent years, some use of animal traction on rice fields has started with men
preparing rice fields with oxen and moldboard ploughs.
In terms of the use of improved rice varieties, 85 percent of farmers in the
sample have had experience with the cultivation of the improved cuitivars, The
median for this variable was found to be four years of experience. A total of 397
farmers did grow rice during the survey year and three fanners that did not grow
rice were facing different constraints such as sickness and consequent
unavailability of the women in charge of rice cultivation.
Farm sizes in terrns of area cultivated devoted to rice production vary across
zones, from OUF survey the mode for this variable being 0.46 heotares and the mean
0.77 hectares. Surveys from 1982 to 1985 showed than in the south, the average
1
94
total area of rice fields was about 0.66 hectares, 0.49 hectares in the northeast and
0.39 hectares in the northwest (see Table 2.3 in Section 2.3). Fifty five percent of
the farms in the sample have cultivated improved rice varieties. Table 4.4 shows the
distribution of farms in the sample with respect to improved variety use and rice
cultivation area.
The farmers’ contact with the extension services was assessed through
different variables. They show that 53.7 percent of farmers had no contact with the
extension services for the last two years (the mean for the number of visits was
0.54). Among those who had been in contact with the extension, only 24 percent
had been involved in demonstration trials or training programs. Also 65 percent of
those farmers had never received a visit from the extension agent. These figures
suggest that the performance of extension is very poor in the area. This is due to
many faotors such as poor training, poor supervision, and lack of incentives. The
1987 World Bank project was designed to reform and reanimate extension services
in the region.
Table 4.4: Distribution of Rice Area and Improved Variety Use in the Sample
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95
Farmers are organized in village groups catled ‘Groupement Villageois”
‘,
(GP). Those GPS are village-based groups organized by villagers for various
activities reiating to production and consumption. These groups are usually headed
by the village ohief or his appointee. About 75 percent of farmers in the sample are
organized into GPS.
The above characteristics of sample farmers and the descriptive statistics
(Table 4.3) indicate that this data represent a large diversity of conditions under
which farmers operate in the survey area.
96
-
. . - . .
_
_ .
- “ .
,
.
. . _ .
Chapter 5 ‘.
Measures of Rice Variety Performance
In this chapter different measures are used to evaluate the performance of
eiite rioe cultivars compared to local cultivars. Modets (3.1), (3.2), (3.31, (3.41, and
(3.5), given in Chapter 3 were used to estimate the Yield Gap and the contribution
of the different fatiors. Mode1(3.5) was solved by using Shazam software to get the
estimates. Models (3.6) and (3.7) were used to derive the types of stability, and the
response curves for the improved and local varieties. Equations (3.Q (3.9), (3. IO),
(3.111, (3.12), (3.13) and (3.14) were used to compute the supply and demand
weights for the derivation of the main indexesfollowing Equations (3. ‘l5), (3.16) and
(3.17).
5.1 The Station -to-Farmer Yield Gap
Data in Table 5.1 show that most of the varieties tested by ISRA since 1982
have experienced a yield loss of between 20 and 70 percent when transferred from
reseatoh station trials to farmers” management,with ali comparisons made at similar
levels of fertilization. In this oase the comparisons are made with zero fertitizer,
whioh is the common farmer’s practice in the area. The decline in yiefds between
on-station trials and farmers’ tests tended to be less for local varieties such as
Barafita and Abiaye Mano.
i
97
Table 5.1: Total Yield Gap in kg/ha for Rice Varieties Between Triais at Djibetor
Station and ISkA Farmers’ Tests in Cpsamance, 1982-86.
Since the focus was on Yietd Gap Il, the data from the two year researchermanaged on-farm experimentswere used to measure the major determinants of this
yield gap for rice. The factors are variety, fertilizer and pest control. These three
factors were tested for 4 improved varieties at two tevefs- the station and the
farmer’s level in a 23 factorial with three replications. Based on the treatment
description in Table 3.1, the Yield Gap and the contribution of the test factors were
computed (Table 5.2).
The three factors explained most of the yield variation in rice production in
the study area. This confirms results from the farming system constraint sutvey on
rice production in the area. The individual factor contribution to the Yield Gap II
differs from one faotor to another. On average the variety explained between 13 to
30 percent of yield variation, fer-Mirer explained between 61 to 78 percent of yield
variation, and pest control explained only between 2 percent to 5 percent of the
t,
98
yield variation,
Table 5.2: Yield Gap II and Contribution of each Pactor in kglha
L~
.- .-
Note:Thenumbersin parenthesesare the contributionof each factor in percentagetenns.
These results have important implications for the rice improvement
programs. The Yield Gap was found to be less for local than for improved varieties.
Since fertilizer is the major determinant of the yield gap, this reflects the fact that
local varieties are generally better adapted to zero fertilizer. Also it was noted
earlier that farmers are not willing to use chemioal fertilizer on their rice fields.
tnadequacies in the credit program, risk due to recurrent drought periods, and
concems about toxicity to fîsh, inhibit the adoption of fertilizer in the area. The ISFW
Rice Program has traditionally given priority to yield potential, that is
the
development of high yielding varieties under high management. This approach is
not compatiblewith the existing cultural factors, farmers’ resouroes, and institutions.
Critiques of ISRA’sresearch program which are of greatest relevance in this
context are that oommodity research programs unduly concentrate on plant
breeding and that food trop research oonoentrates exoessively on improved
Vari&es using only purchased inputs rather than on iow-cost technologies (the use
t
99
of organic matter as an alternative source of fertilizer) that would improve upon
existing traditionaf cultivation techniques, The development of FSR was designed
to significantly reduce those problems. FSR in fact has greatly improved the
definition of research problems and improved knowledge of where technologies
may be applicable. Nevertheless, some criticisms are stiil relevant. Crop-commodity
and FSR programs are not sufficiently ooordinated, resulting in trop-commodity
research that does not address farm-level constraints identified by FSR.
An important issue identified by FSR that could decrease the Yield Gap is
the use of organic matter, a traditional means of fertilizing the rice fields. Animais
are corrailed in specific areas and the manure colieeted and transported to the
paddies, In the south, women still bring organic fertilizer (manure and ashes) to the
aquatic rioa fields just before the rainy season. About a third of the better fields (20
percent of the total area) are fertilized in this manner each year (FSR, 1985). In
contrast to the wide use of organic matter at the farm level, this issue has not been
yet incorporated in commodity program research as an alternative to chemical
fertiliration.
The second determinant in terms of its potential contribution is the use of
improved rice varieties. Farmers oan increase rice production by an average of 500
kg to 1100 kg per hectare by just using an improved variety instead of their local
variety. That increase is very important for subsistence farmers,
Pest control has Littlecontribution to the yield gap. This is essentialiy due to
the low pressure of pest infestation in rice cultivation in the region. Recent studies
‘i
100
(ISRA, 1994) show a levsl of infestation between 2 percent and 8 percent of rice
plants. The estimates of such levels of infestationl’need ta be treated with caution
as rigorous yield loss assessments are not generally available.
5.7.1 Farmers’ Practices and Rice Yield
Plot level data collected in 1984 by the FSR team (see Section 4.1) were
used to estimate the production function. For this purpose the Box-Cox approach
was used to regress the yield on a set of explanatory variables. Table 5.3 shows
these variables and the expected sign of their impact on rice yield.
Table 5.3: Expected Sign of the Relationship between Farmers’ Practices and the
Yield of Rice Varieties.
(1)
PIANTING
4
VARIETY
*
SUBM
4
Growing period (GROW): The number of days between planting and harvest
is used as a measure of the impact of the length of the growing period on
yield. This variable is expected to ba positkely related to yield It is related
to the maturity of the variety.
(2)
Type of monitoring (MONIT): A dummy variable indioatingwhether or not the
plot was monitored by an extension agent. It has the value 1 if yes and 0
otherwise. The variable is expected to be positively related to yield,
conforming to the idea that extension positively affects yietd.
(3)
Basic fertilization (FERBASE): A dummy variable for basa1 fertilizer
application after land preparation. It has a value of 1 if the plot has received
fertilizer and 0 otherwise. The use of fertilizer is expected to be positively
related to yield.
(4)
Top dressed fertilization (FERTCOUV): A dummy variable for urea top
dressed application with the value 1 if apptied and 0 otherwise. Nitrogen
application (urea) is expected to increase yield.
(5)
The period of weeding (WEEDING): Number of days between planting and
the first weeding. Timeliness in weeding is expected to have a positive effect
on yield. Thus this variable is expected to be negatively related to yield.
(6)
The presence of iron toxicity (IRONPROB): A dummy variable for iron toxicity
with a value 1 if the problem exists and 0 otherwise. fron toxicity is expected
to affect negatively yield.
(7)
Herbicide application (HERB): A dummy variable with value 1 if the plot has
received herbicide treatment and 0 otherwise. Herbicide application
t
102
._--
.-.-.
-...
-
-
--
----.---
-1.-
-.-----.
--._-___
,.
0.
. .
deçreases the number of manual weedings and saves farm labor. lt is
expected to have a positive impact on yield since weed control is
hypothesized to be better.
(8)
The type of land preparation (PREPAR): A dummy variable for the type of
land preparation with value 1 for flat plowing and 0 for ridge plowing. Fiat
plowing facilitates the use of mechanical weeding while ridge plowing helps
better control weeds. The expected sign of this variable is undetermined.
(9)
The method of planting (PLANTING): A dummy variable for the method of
planting with value 1 for row planting and 0 for broadoasting. Since row
planting makes weeding easier, the variable is expected to be positively
related to yield.
VO)
The type of variety (VARIETY): A dummy variable that takes the value 1 for
improved variety and 0 for locaf variety. The type of variety is expected to be
positively related to yield.
UV
The number of weeks of flooding (SUBM): Number of weeks of flooding in
the rice fields as a measure of the quality of the rainy season. In rice
production the length of the flooding period is very important and is expected
to be positively related to yield.
With the Box-Cox regression, the linear mode1(A = 1) is rejected while the
double log model(h= 0) is not rejected. For a test of the double log mode1the test
statistic is:
ZfL(h) - L(A = O)]
‘t
103
--_
This cari be compared with a Chi-square distribution with one degree of
freedom(x2C,,).From the output the test static is ÿomputed as:
2f-1751.39+1753.71)= 4.64
Therefore, the double log mode1was estimated and the regression results
are shown in Table 5.4. Variables GROW, FERBASE, FERTCOUV, IRONPROB,
PREPAR, and SUBM are significant at the 1% level.
The results suggest that yield increases with the length of the growing period
(GRCIW). Varieties that are able to achieve their compiete maturation period, have
higher yield. This shows the importance of vafieties with a cycle adapted to the
existing rainfall pattern, and the importance of timeliness in planting. Planting
begins in the higher fïelds with short cycle fice varieties, and then progresses ta the
lower fields where longer cycle varieties are planted. Fields situated in the stream
bed are an exception. They must be planted early to avoid submergence of the
seedlingswhen the heavy rains begin. The upper rice fields, which are planted with
early season varieties, are often ready for harvest a fulf month before the rice fields
planted on the lowest fields. Planting depends on two major factors: the beginning
of the rainy season and the availability of the family tabor which in turn is highly
correlated to the type of social organization of labor. The advantage of division of
labor is that it makes it possible for all active family workefs to prepare the land and
get the season off to a good star-t in May-June. This reinforces the need for short
2
104
cycle varieties to be taken into acoount by rice breeders.
Table 5.4: Double Log Results of Yield Determinants
CONSTANT
GROW
MONIT
FERBASE
FERTCOUV
WEEDING
IRONPROB
tiERB
PREPAR
PLANTING
VARIETY
SUBM
U = 266
Me: parentheses. One asterisk denotes significance at the 10 percent level.
Two asterisks denote significance at the 5 percent level. Three asterisks
denote significance at the 1 percent level.
Yieid is positively related to the application of both basa1 fertilizer
(FERBASE) and urea (FERTCOUV). Posner et al(1991) shows that in 1984 and
1985, in the transitional rice growing areas (phreatic rice), there has been an
increase in yield from 2.5 kg/ha of paddy for every kifo of basa1fertifizer (8-18-27)
and 3.5 kg/ha of paddy for each kilo of urea. For rice fields on lighter soils which
are more acid and often have less availabie water, the response to fertilizer is less
t
uniform due to the presence of many constraints (iron toxicity, drought stress and
a lack of trace elements such as zinc).
Yield is negativelyrelated to iron toxicity (IRONPROB). Sylla (1994) showed
that with a pronounced dry season and a decrease of the annual rainfall over the
last 20 years, salinity levels are high in the top soil. In Young acid sulfate soils rich
in colloidal iron, the concentration of Fe” produced after flooding is likely to be
high. Therefore bronzing or iron toxicity is common in such soils. The cumulative
effect of acidification as well as of salinization and the subsequent acid leaching
with saline water has affected the soils. In 1984 this problem was apparent in 9
percent of the aquatic rice fields (ISRA, 1985). lt is in areas where iron toxicity and
sait intrusion are problems that the greatest research challenges occur. Sylla
(1994) showed that the rice variety ROCK5 seems to have the most stable yield in
soils with iron toxicity problems. This implies that location-specific trials are needed
to determine which variety is best for farmers.
Flat tillage (PREPAR) increases yield. Posner (1991) showed that fields
prepared by the ridge method did not yield significantly more than those that were
flat plowed. lt is logical that in aquatic rice fields, if flooding is adequate, the two
methods of preparing the fields would result in similar yields. In the nappe zone on
the other hand, flat tillage appears to produce somewhat better results (Posner et
al, 1991). Other studies (Dobos, 1991) have shown that ridge plowing is more
efftcient in controlling weeds and salt intrusion.
Rainfall (SUBM) is obviously an important determinant of rice yield in rainfed
‘t
106
agriculture. Gersovitz (1987) showed that in Senegal,rainfall in the growing season
cannot be predicted from weather earlier in th6 year. He also showed that rice
yields are relatively more sensitive to changes in rainfall at low levels of rainfall.
This points out the need for more drought tolerant varieties. In rice production this
seems to be difficult. The potential solution is a combination of short cycle varieties
and an early planting date. Using linear regression Posner (1991) showed that a
delay of one week in the date of plantingltransplanting resulted in yields lowered
by approximately 55kgIha.
Environmentalfactors such as the quality of the rainy season, the presence
of soil-relatedconstraints and farmers’ practices explained most of the variation in
rice yield. Thus because of the variability of the environment and farmers’ risk
aversion, varieties that show stable yield superiorityover different environments are
more tikely to have wider adoption rate. The next section addresses the issue by
comparing the yield of rice varieties across such variable environments.
5.2 A~aptability
of Rice Varfeties
Figure 5.1 shows the plotting of the observations for the different varieties
(unfertilized) against the environmental index. The results for the unfertilized and
fertilized plots are summarized in Tables 5.5, 5.6 respectively.
Examining the zero fertilizer case first, the results of the stability analysis
highlight several points. We observed three cases of stability: 2 cases where the
improved variety is superior to the local across all environments (type A stabifity),
3
107
II
Figure
1500
5.1: Y&kb
of wiet&s
FbtWdOnEl
2000
2500
Envlronm+ntxl
Figure
1000
1500
3voo
lnd+x @l) h k#ha
5.2: %biMy
2ooo
Type
C
3wo
2500
3540
-h6xhkm
Figue
5.3 : Stabif&
Type
A
1100
._
._
. . “..-I--r-.-
-.---.
-l---lrlsr-‘hil.-
v-v-.
.
‘>
‘-’
-----
,v.---
..--.
“,
_,
_
*
i:
/<.)’
*.
-,,.
;.
I_
i .
,-;
,.>,
..,~..,
_-
-
5 cases where the improved variety is supsrior only in better environments (type C
stability). The varieties that show a stable behavior across all environments are
those that are for rainfed rice plots. This type of rice is less commun in the area.
Farmers used to cultivate this type of rioe on newly cleared lands by cutting the
forest. After three years, farmers were confronted with fertility and weed problems,
and thus moved to another plot. This practioe is no longer possible beoause of the
lack of land and forest in many villages. For the phreatic rice, all varieties exhibit
a C type of stability (Figure 5.2). Those varieties do not perform better than the
local in poor environments. This could explain one aspect of the possible
nonadoption of those varieties in some oases.
Theresultsfrom the 100 nitrogen fertilizer experiments show a similar trend.
Most of the varieties exhibit a type C stability. None of them are superior to the local
across all environments. The variety that shows a B type stability (i.e., perform
poorer under better environments) is the most susceptible to a particular type of
blast (pyriculariose).
One faotor that defines a “better environment” in trop production is the use
of fertilizer. in the quest for higher yield potential, breeders have given high priority
to the response of varieties to fertilizer, especially nitrogen, in the sereening
prooess. The main issue addressed in the next section is whether or not improved
varieties response to nitrogen differs when oultivated under farmers’ management.
Table 5.5: Stabilîty Analysîs for Improved Rîce Varîetîes at Zero Fertîlîrer.
Improved
vwiety
Type of
rice fieid
Mercept&)
Slope (bd
DJl2519
Phreatic
+-
IKP
Phreatic
+-
TOX-728
Phreatic
OJ684D
Aquatic
IRA-r1 33
Phreatic
IRI12
Rainfed
.n
-
++
+’
l
+
+
Stabitity
type
c
c
c
c
c
A
A
Average
Wd (kgtha)
3066
98
2717
97
3010
94
1800
68
2781
55
2280
75
+
Rainfed
FIAT10
2428
75
lote: One a erisk denotes signifïcance
at the 10 percent levt ?l. Two asterisks
enote
significance at the 5 percent level. Three asterisks denote signifrcance at the 1 percent levet.
+”
Table 5.6 Stabîlîty Analysis for Improved Rîce Varîetîes at IOON Fertîlîzer Level
Impraved
variety
Type of
rice field
Slow @J
StabMy
type
Average
yield(kgIha)
DJi2519
Phreatic
+
c
4973
IKP
Phreatic
+
c
4682
TOX-728
Phreatic
+
C
5014
FIAT1 33
Phreatic
+
c
4333
IRI 12
Rainfed
-
+
C
3331
MT10
Rainfed
+
B
3424
5.3 Response to Ferttllzer and the Issue of Response Curve
A J-test was performed to test for the correct specîfication of the response
functîon. tt was carrîed out on the quadratic functional form and the three-halves
functîonal form. TO do so, both equatîonswere run and the predîcted values for the
response were kept in both cases (Le., gamma1 and gamma2 respectivety). The
t
110
models were then estimated again, this time including the predictions of the other
mode1 (Le., the quadratic mode1 was re-estikated for a second time but with
gamma2 included as an independent variable; the same procedure was repeated
for the three-halves model).
If the parameter estimate for gamma1 is significantly different from zero, then
the considered mode1is not the correct specification. Gamma2’ s coefficient was
2.6849 with a t-statistic of 1.8882. The critical value is 1.96, thus gamma2 is not
statistically significant from zero, implying that the quadratic formulation was
correc=tlyspecified.
The same test was performed for the three-halves model, using the predicted
values from the quadratic. The gammal’ s coefficient was -1.714 and the t-statistic
was -1 .178. Thus the three-halves was correctly specified. Neither of the two
models were rejected. This corroborates Swanson (? 963), Tronstad and Tayior’s
findings (1989). Thus the three-halves mode1was used to estimate the response
curves. For the test of equal response to fertilizer, the mode1was estimated using
all the observations for ait the varieties, and for the test of equal response at zero
levei of fertilizer, the mode1was fitted for each pair of improved and local varieties.
The results for all the varieties are shown in Table 5.7.
The assumption of equal response to fertilizer for improved varieties and
local varieties was rejected. The F-statistic with (2, 354) degrees of freedom was
10.40 which is greater than the critical value from the F-table (3.00). Thus with
respect to fertilizer, improved varieties and local varieties under famers”
3
111
circumstances have different response curves.
.
Table 5.7: Estimates of Response Funot ans for Rice Varieties
I DJ12519
I IKP
f TOX728
DJ684D
RAT112
RAT10
14409
32.53
18.53
18.52
16.95
147.51
(0.69)
Note: T-statisticsare in parentheses.
The assumption of equal response at zero level of fertilizer was rejected for
two varieties DJ12519 and TOX-728 but was not rejected for W,
IRATIO,
IRATl44, DJ684D, and IRAT112 (Table 5.8).
The resufts demonstrated that under the stress conditions and low yields
encountered at the fann level, response ourse oross-over did indeed occur for many
of the varieties tested. Of the 7 vafieties examined, cross-over was identified in 5
cases. Most of the cases correspond to a type C stability.
1
112
Table 5.8: Results of Hypothesis Testing for Response Curve
-V-
Nul1 hypothesis
Equal response to N
Parameter restriction
Test statistic
b, = b, = 0
F = 10.40’
DJ12519
b, = 0
t = 10.40’
IfWT112
b, = 0
t = -0.462
14409
b, = 0
t = O.332
RAT 10
b, = 0
t =-0.3g2
TOX728
b3 = 0
t = 7.83’
D J684D
b,= 0
t = 0.6g2
IKP
b, = 0
Reject Hoat 5% significance
t = -o.532
Equal response at N = 0
2 Failto reject H, at 5% signikance level.
The results also suggest that the ordering of a set of varieties according to
yield is not necessarily identical at high and low management levels. The two local
varieties used in the study, Abtaye Mano and Barafita, are competitive in terms of
their yields and are especially vigorous at emergence (Posner, 1991). Recent
studies (Mbodj, 1986) show that at a high level of nitrogen, some rice varieties
become more sensitive to a particular blast (pyriculariose) and the yield ioss cari
in some cases be ver-y important. For example, IRATl44 cari experience a 100
percent yield loss. This is a very serious problem, since one of the main advantages
attributed to improved rice varieties was their tolerance to rice blast and resistance
to bdging. The main conclusionis the need for more moderate rates of fertilizer for
most of the varieties plus adequate land preparation that improve soil moisture
availability.
t
113
--
Few varieties (If?172, RATIO) exhibit type A stability, the most desirable
type of stability. This suggests that recommending?hese varieties to farmers facing
different circumstances cari be very hazardous. TO more finely tune technical
recommendationsbeing proposed ta specific types of farmers more work needs to
be done. The adaptability analysis carried out in this study could result in multiple
recommendations appropriate for specific groups of farmers in different
environments. But the lack of data to characterize these environments is a serious
shortcoming to fulfiiling such an objective.
5.4 Farmers’ Evaluation of Rice Varieties
5.4. f Farmers’ Perceptions About Rice Variefies
TO date, there are officially more than 400 varieties in ISRA’s
agronomiclmorphological inventory. Many of those varieties have been tested for
their resistance to different stresses especially rice blast. Some of those varieties
have been released to farrners through the extension service and onfarm research
trials.
The varieties widely used in the sample are shown in Table 5.9. ROCKS was
the most widely used improved variety, followed by DJ12519, IKP, and DJ684D.
Farmers’ experience with the different varieties is also shown in Table 5.9.
IKP was the oldest improved variety used by farmers. This variety was introduoed
by the Chinese Agrkultural Mission in the region in the ?97U’s.The other varieties
were introduced at about the same period.
t
114
- -- .--. -
.--.I---
-___-._
Table 5.9: Adoption Level and Experience with Improved Varieties in
DJ684D
DJl2519
For those farmers that were using the varieties, the most important s( me
of information was other farmers, whiie either extension and research were the
secondary sources (Table 5.10).
Table 5.10: Sources of Farmers’ Information (Percent of Farmers) in Casamance
1 Extension
I
Research
ROCK5
29
23
DJ684D
21
34
DJ12519
24
18
IKP
37
0.i
The first time they used the varieties‘1 farmers tried them on a very limited
scale. Most of them cultivated the variety on only one plot. This behavior is
consistent with the findings in the adoption literature about risk attitude, land use,
and technology adoption.
About 38 percent of farmers tried the technology because they had seen the
resufts obtained by another farmer, 23 percent were convinced by the extension
agent with whom they were in contact, and 20 percent tried it because they wanted
to evaluate the extension agent daim. Another 14 percent tried the variety, because
*
115
they did not have enough seed, and had the opportunity to receive free seeds.
Finally 6 percent tried it beoause they had earlier visited a demonstration triai.
The following desirablecharacteristics conceming rice varieties were elicited
from a random sample of 400 farmers in the 1996 survey:
(1)
The increasing pfevalence of rainfall deficits leading farmers to begin
changing their appfoach to farming. In the case of rice, farmers bave opted
for short cycle varieties (CYCLE) and have begun adopting direct seeding.
This trend is being reinforced by the local extension service through the
promotion of short cycle rice varieties. Farmers are continually looking for
early maturing varieties adapted to the current shorter rainy season.
(21 The desire for increased resistance (RESISTANCE) to different stresses
such as blast, insects, and a short drought period. In a very hostile
environment it is important to consider those vafieties that cari at least
tolefate a minimum level of stress.
(3)
A height of the variety (HEIGHT) that is consistent with the local way of
harvesting. This is done manually by women using a knife. Short varieties
bave been found to be less attractive to women since they have to bend in
order to harvest them. They also pfoduce less biomass especially straw, an
important source of feed for cattle in areas with less access to upland crops.
(4)
Tillering capacity which (TILLERING) is strongly related to fish damage, a
problemto Youngrice seedlingsin aquatic nœ ecologies. Varieties with high
tillering
capacitystill give good yields despite fish damage, due to the growth
1
116
of new tillers.
(5)
Yield of the variety (YIELD) becoming moré and more important to farmers
in the region following persistent drought patterns. In most parts of the
region, rice is the main staple food and any yield increments cari have a
substantial impact on the survival of the household.
(6)
The ease of cooking (QUALITY) being important to farmers because rice is
grown mainfy for subsistence. Rice is still not a commercialized trop in the
study area and most of the harvested rice is consumed at home. Women
have to travel several miles away from home in search of firewood for food
preparation. Rice varieties that require a long time to cook (a trait directly
iinked to the percentage of amylose content in the rice grain) are not
preferred by farmers due to the need to conserve the limited firewood
available per household.
(7)
3
Farmers have preference for the taste (TASTE) of their local varieties. They
are more likely to judge the local varieties as better in terms of taste. A
fundamental aspect of Senegalese consumer behavior is a strongly marked
preference for any rice variety with the following traits: high volume after
cooking, low oil absorption, and better taste. This strong preference has left
little room for the other grains to gain wider acceptance by consumers. The
Senegaleseconsumer is very choosy about the type of rice he/she eats and
he/she is willing to pay a premium for the variety helshe likes rather than
consume another type of grain.
‘I
117
The seven rice technology specific traits were tested using the master
sample aocording to the keys shown in Appendix A. Table 5.11 shows the resutts.
Table 5.11: Farmers’ Ranking of Varietal Characteristics (Percent of Farmers)
Notimportant
1
0.5
12
0.25
0
6
11
Total
100
100
100
100
100
100
100
Ninety nine percent of farmers found that yield is a very important
characteristic for a rice variety. It is very important to understand the idea behind
the farmer’s concept of yield. In fact farmers often mean production and this
became obvious during the whole survey when farmers tatked about the number of
baskets of rice they could get from a specific rice plot.
Most trop improvement programs especiallythe Rice Program, have defined
several objectives but priorii has traditionally been given to yield potential, that is,
the development of high yielding cultivars under high management. However, the
high yielding variety package approach requires increased plant density and high
ievels of chemical fertilizers to ensure exploitation of production potential. Since
there is no land pressure in some areas, there is less economic incentive to
intensify land use at the expense of traditional risk reducing land extensive
strategies. Almost 97 percent of farmers found that tillering ability is a very
important characteristic. There is a direct relationship between tillering ability and
yield. Resistance to the most common pests and other environmental stresses is
reported to be a very important trait. Greater drought resistance and improved
seedling vigor are equalfy important. Oniy 54 percent of farmers found that height
is a very important trait.
5.4.2 Quantifative Assessment of Rice Vafiety Performance
Since the number of observations for each characteristic and each variety
listed in the survey differed and in some instances were low, we report the
calculated indices for only those varieties for which we obtained 100 or more
observations (Appendix B). We report these in order to provide a comparison with
the indices for the local variety.
There is one major drawback to the methodology for evaluating farmers’
perceptions of the quality of improved and local rice varieties. There are no unique
weights for calculating the indices. The contribution of Reed et al (1991) is that they
have developed a set of conditionswhich, if met, assure that the indices are robust.
Using Equations (3.13) and (3.14) four sets of weights were computed [Le., SA(3,1,2),dA(~,2,~f;SB(2,~,-~),d~(~,3,~);SC(3,~,-~],~(3,2,1);SD(l,O,-1),dD(5,
2, l)] and used to calculate the indices. TO verify the robustness of the procedure
with the sample these indices were computed for all the varieties and
characteristics. The results were found to be consistent across ail four weighting
schemes fur all the characteristics tested. Table 5.12 gives the ranges of the
indices for each set of demand and supply weights.
i
119
Table 5.12: Ranges of Indices for the Sets of Weights
Attainment index
Supply
. . _ index
Demand index
Max
Mi
Max
Mi
Max
0.97
0.15
0.99
0.71
1 .oo
B
0.35
0.97
0.21
0.98
0.74
1 .oo
C
0.20
0.97
0.18
0.94
0.78
1 .oo
Il
-0.03
0.96
-0.02
0.98
0.88
1 .oo
The results with set A are represented because both the supply and attainment
indices have a wider range from 0.14 to 0.99 and a midpoint of 0.55, and the
demand index has a range from 0.71 to 1.0 with a midpoint of 0.85.
TO ensure that the results in this study are indeed robust with thé respect to
the set of weights chosen, following Reed et al (1991) the resutts were tested. The
attainment index was computed for each possible combination of supply and
demand weights for all characteristics for the varieties. Given that there are four
sets of supply weights and four sets of demand weights, there are 16 different
combinations of weights. Then the Pearson correlation coefficients and the
Spearman coefficients were computedfor each set of caiwlated attainment indices.
Tables 5.13, 5.14 report these results. The Spearman correlation coeffkients
measure the consistency in ordering the scores, while the Pearson cor-relation
coefficients measure the linear relationship between the different scores. The
results show strong support for the robustness of the results. tt reinforces the
results obtained by Reed et al(l991). The high correlation gives more confidence
in the results.
%
120
Table 5.13: Pearson Correlation Coefficients for Attainment Indexes
WI
Iwon
M
089613
IcmJ
w3
Il 96685
O!s619
ION0
W4
089410
0!?%9*
099175
Icalo
FS
0994%
092288
09x8?
0.91916
Icml
Wb
09%351
093318
094560
0.9217
0994%
I.Mxy)
w7
099251
omO3
092119
0.9Oc62
0.99716
099107
lwob
WI
099216
0929%
0937%
0.9281
099893
0.99393
0.99262
0.98714
0.98842
I.om
w9
r)P9434
093431
0941i7
093224
0.99314
0.99346
l.oom
WI0
0 PJ595
0 93049
093976
092691
0 99655
0.99034
0.99414
0.99527
099369
1 OC00
WI1
05Ç559
092316
093413
0.91747
0.99555
098921
0.99614
0.99244
0.99647
0.99919
WI?
0 99729
0939%
0 945%
0.94030
0.99437
0.98776
0.98634
0.99655
0.59816
0.99716
0.99339
Pxim
W13
2.98453
08333
0.84195
0x3037
0.9596P
0.94038
0.96029
0.95664
0.97118
o.Pmw
0.97076
0.96481
l.iml
0937%
o.%cm
I.mo
w14
098310
0x2451
0 836%
082334
0 95762
0.95344
0.96874
O%s40
0.9X07
0.96124
099965
1 OOM)
WIS
008036
081659
082994
081416
0 95412
0.93329
0.95893
0.94851
0.964S2
0.96532
0.%x29
0.95589
099itm
0.99940
1 ci-m
WI6
041529
083-l’
OX47?9
083888
096135
0.943œ
0.95927
0.95994
0.97)51
097119
097342
0.9685X
0.99916
0.99793
0.99516
WI
w
w3
w4
w5
W6
wl
WI
WP
WI0
WI1
WI3
WI2
WI4
w15
1 @X4
W16
Table 5.14: Spearman Correlation Coefficients for Attainment Indexes
WI
l.oûoo
wl
091744
w3
094221
0.99174
l.lmxJ
w4
0.90299
PS9174
0.97733
I.woQ
W5
099174
091x58
o.Pl982
0.9112s
I.om
W6
0.99174
0.%911
oFlsm
0.%093
099m
I.oam
0.9Pl74
039174
mloo
099174
1.m
w7
LMXXI
091’44
0.94221
o.RT&x
wx
099174
0.915311 o.pBe2
0.91125
mm
0.99587
WP
0.99794
0.936m
0 95872
0.921s7
0.98968
0.9119611 0.99794
0.98%8
uoov
WI0
0 9x94
o!?xm
0.9ml
0.921s7
o.Pl%x
oB968
6.9!m4
iMs%8
Moiw
WI1
OS9587
0.93189
0.9%66
0.91950
OS762
0.98762
0.995X7
OS762
OS9794
0.99794
l.ooco
0.98968
0.99794
099174
0.99174
09x%8
1.ovco
LWQO
bmal
WI2
@9896x
0.93395
0.94634
092982
0.99794
0.993x1
w13
0.m
O.IWS
0.92776
0.8X648
0.98142
0.98142
0.98968
0.98142
0.96161
098762
o.Px%x
0.97936
l.mo
w14
098142
0.x8235
0.91744
0.x5791
o.%sa
056698
osa142
O%s8
0979%
w7P?4i
0.98349
096@\
0395c7
WI5
v.97936
0.87616
0.91538
0.85965
0.964’78
WI6
0.99174
WI
0.92Tl4
Qn
09.5253
w3
0.91X#J3 0.98349
w4
w5
I.wLkl
0.%07x
o9m6
0.960%
0.977-M
091130
0.911142 o.mn
029174
0.99m
0.98142
0.99174
0.9x349
0.99381
0.993x1
0.99287
099937
0.99174
W6
Wl
W8
WP
121
WI0
WI1
WI2
o.suss5
WI3
WI4
mlOo
WI5
098762
t vlm
WI6
Table 5.15 shows the resutts for the attainment indices.
Table 5.15: Attainment Indices for the Main Six barieties
AMAN
Local
0.42
0.77
0.42
0.79
0.78
0.69
0.54
0.75
0.87
0.61
0.49
0.71
0.18
0.40
For the yield and tillering criterion, the attajnment indices show that all the
improved varieties were highly rated, Most improved varieties have good yield and
tillering ability according to farmers’ perceptions. Amano was poorly rated.
The attainment index scores for the height criterion indicate that apart from
ROCKS all the improved varieties are poorfy rated by farmers. The local variety and
Amano have higher attainment indices.
In terms of quatity, DJ684D, DJ12519 and the local have the highest
attainment indices. The other improved varieties are equafly rated by farmers.
For the cycle criterion IKP and Amano have the highest attainment indices.
The other improved varieties and the local are equatty rated. This explains why
fat-mersare fooking for varieties that are superior to their local in terms of growing
cycle.
In terms of the taste criterion only one improved variety (056840) is found
t
122
to have a higher attainment index than the local variety.
AIl the varieties are poorly rated with fespe& to their resistance ability. The
mean attainment index is about 0.34.
Tables 5.16, 5.17 show the results for the demand and supply indices.
Table 5.16: Demand indices for the Main Six Vari&es
ROCKS
DJ12519
DJ684D
IKP
I AMANO
Local
TILLERING
0.99
0.98
0.98
0.97
0.98
0.98
YIELD
1 .oo
0.99
0.98
0.99
0.99
0.99
HEIGHT
0.74
0.80
0.80
0.71
0.80
0.74
QUALITY
0.86
0.92
0.92
0.85
0.91
0.84
CYCLE
0.93
0.92
0.91
0.94
0.89
0.89
TASTE
0.80
0.90
0.87
0.75
0.82
0.77
RESISTANCE
0.92
0.94
0.93
0.95
0.93
0.91
Table 5.17: Supply indices for the Main Six Varieties
ROCK5
DJ12519
DJ684D
TILLERING
0.94
0.88
0.99
YIELD
0.93
0.89
0.99
HEIGHT
0.94
0.62
0.49
QUALITY
0.81
0.76
0.82
CYCLE
0.76
0.82
0.71
TASTE
0.84
0.62
0.90
RESISTANCE
0.44
0.34
0.49
For the yield criterion, the demand index scores indicate that this trait was
rated highest for ail varieties, refkting its importance in farmers’ expectation about
new rice varieties. The supply index for the same cfiterion indicates that DJ6840
i
123
is perceived as the best variety followed by ROCKS, DJi2519 and IKP. Amano is
the poorest variety.
Closely related to yield, the second highly demanded criterion is the tillerjng
ability of the varieties. When considering the supply index for the four
improved
varieties ROCKS, IKP, DJ684D and DJl2519 seem to be doing well. Amano and
the local variety are poorly rated.
The above results corroborate research estimates of the tillering capacity
given in terms of the number of panicles per square meter (Table 5.18 ).
For the resistance criterion the demand index indicates that the farmers are
very concerned about the ability for new varieties to toierate a minimum level of
stress’. The resistance to drought and soil-related constraints such as satinity and
acidity is a major issue in rice cultivation in the area. Likewise the supply index for
that criterion is very low for all varieties indicating a poor performance according to
farmers’ perceptions. This highlights one major drawback in the past breeding
approach in which the materials were sefected in a high management environment
with little consideration for the environment where they are going to be used, the
farmer’s field. This also points out new challenges facing breeders in the screening
of new materials. There is a need for varieties specifically adapted to the varying
agro-ecotogicalconditions across the region. For example, more adaptive research
and screening work with respect to salinity and iron toxicity, in collaboration with
‘Theinterpretation
excludes
theresistance
to pestsanddiseases
sinceearlierresultsindicatechat
yestsandfiseaseswerenota majorprobhn in thearea(secSecticm
5.1)
124
other institutes such as WARDA will be needed in the future.
For the cycie criterion the demand index is ;ery high which corroborates the
idea that rice farmers are continuouslyseeking for short cycle varieties because of
increasingshortness of the rainy season. The supply index for that criteria seems
to indicate that the farmers’ desire for short cycle varieties is being taken into
account by the ISRA rice breeders. Local varieties have on average a growing cycle
of 130 days compared to the improved varieties listed in Table 5.18.
The two criteria, cooking quality and taste show a similar trend for the
demand index and the supply index. They are important criteria and the different
varieties on average seem to be doing just fine. If in the future, because of surplus
production, farmers sel1 rice, rice cultivars of high grain quality Will become
increasingiy important as markets become liberalized.
Table 5.18: Cycle(days), Height(cm), and Tillering Capacityfpanln?) for the 5
Varieties.
Source: FSR (1986)
The height criterion supply index shows that besides ROCKS, Amano and
the local ali varieties are poorly ranked by farmers who are seeking for tall varieties
easy to harvest. This in fact is a gender issue because women are in charge of rice
harvesting. tt is also a very difficult task for breeders to deal with. tt seems that
there is a negative relationship between height and yield potential.
1
125
The results show that an emphasis on yield potential under an “idealistic”
high management environment that has chara&erized the lSRA R@ Program.
Support of this claim is found either explicitfy in statements of objectives,
or
implicitly in the management levels and screening procedures employed in the
program.
Compared with the most common local varieties, improved rice varieties
have lower yields at lower input levels, but are often more responsive to improved
inputs to the extent that cross-over effects frequently occur. DJ12519, ROCKS, and
DJ684D do well in better environments. The local varieties, Abtaye Mano and
Barafita, continue to be competitive and have certain traits which are valued by
farmers. The diierent indices computed show that farmers are demanding shorter
duration varieties, with good plant height and cooking quality. In an environment
where the use of fertilizer is very limited, local varieties may be more suited, if the
physical environment is improved to protect the rice fÎelds from the salinization. The
demand indices for height, resistance and cooking quality for most of the varieties
were greater than the supply indices. This shows that the farmers’ desire for tall
varieties,with a good resistance to soit-related constraints and a good cooking
quatity is net being taken into account by ISRA Rice Program. The desire for high
yielding
varieties is being taken into account by ISRA (demand and supply indices
are equal). How the different factors embodied in the varieties affect their adoption
by farmers is addressed in the next Chapter.
\
126
Chapter 6I
Determinants of Adoption: Empirical Resuits
and Implications
In this chapter different factors affecting the adoption of improved rice
varieties in Southem Senegalare discussed. The study explores the extent to which
these factors have general utility in accounting for differences in rates of adoption
of various improved rice varieties. We draw some implications for agricultural
research and development. Models (3,18), (3.19) and (3.20) given in Chapter 3
were solved by using Shazam software to get the different estimates. In order to
isolate the contributions of the two different groups of factors in conformity with the
major hypotheses three variations of the empirical mode1were estimated:
(1)
Using farm and farmer specific factors;
(2)
Using only the technofogy-specific factors;
(3)
Using the fart and farmer specific fadors, and the farmer perceptions of the
technology specific characteristics.
The Tobit technique uses all observations,both those who do not adopt and
those who adopt, to estimate a regression line. Thus Tobit was used to determine
bath changes in the probabilityand changes in the intensity of adoption. It uses an
iterative maximum likelihoodalgorithm to estimate the empirical models in order to
‘i
127
obtain asymptotically efficient parameter estimates. The Tobit estimates were
decomposed using Equations (3.25) and (3.26). ‘?he decomposition has important
substantive economic and policy implications. It cari help answer the following
question: “how Willthe credit-supply reduction induced by an increase in the down
payment required by the lending authority (CNCAS) be spread between marginal
decrease in the intensity of adoption and decreases in the probability of adopting
the technology?” Since the analyses involve variables measured in the same unit
(binary variables), standardizing may be irrelevant.
6.1 Farm, Farmer-Specific Factors and the Adoption of Improved Rke
Varieties
When farm and fanner-specific variableswere considered the results (Table
6.1) show that the variables representing farmers’ level of information about
improved rice varieties, farmers’ participation in village-level organization, and
access to credit were significant respectively at 0.01 and 0.05 signifioance levels.
However at the 0.10 significance levei, age and the farmers’ initial impression of
improved varieties were signifioant in explaining adoption decisions.
Age (AGE), a measure of farming experience, was positively related to
adoption, meaning that age may be associated with a quicker and more accurate
decoding of information. Farmers over time acquire the knowledge necessary to
adjust to their changing environment. Farmers, especially resource-poor farmers,
continuouslyexperiment, adapt and innovate. Ether studies (Bultena and Hoiberg,
1963) have found that age is negatively related to adoption. Younger farmers have
\
128
IliL.-
.-
- .
_
_” _ _.. “..” -
_-..
-
been found to be more knowledgeable about new practices and may be more
I)
willing to bear risk due to their longer planning horizons. In Lower Casamance, out
migration is a serious problem. Farming has become an occupation for women,
children and the old, while the young able-bodied men go in search of nonagricultural employments. We would expect that the older farmers, having
established themselves over the years, would encounter fewer difficulties getting
credit, a precondition to adoption according to different empirical studies.
Table 6.1: Estimated Results for Farmer Adoption Mode1Using Farm and Farmer
Specific Factors
.
ACCESS
MEMBER
INFORMATION
APPREXP
WEALTH
TRACTiON
INTERCEPT
0.4603
-1 .oQ74-
-2.3839
tote: one asterisk denotes significanceat the 10 percent level. Two asterisks deno e
significance at the 5 percentlevel.Threeastetisksdenotesignificanceat the ? percentlevel.
Credit(ACCESS) availabilitywassignifiintly relatedto the adoptionof high
yieldlng varieties. A common argument in a number of studies is that any
requirement of farmers to initially undertake investments impedes the speed with
1
229
which the small farmers adopt new technology. Accordingly, access to capital or
capital markets is a necessary condition for financing adoption of HYVs. Henc@,
differential access to credit has been frequently cited by farmers and extension
agents in Lower Casamance, as a factor affecting differential rates of adoption.
Several studies have reported that credit availability is a significant factor to
adoption, and may imped adoption of HYVs even when the fixed pecuniary costs
are relatively small. In his Indian study, Bhalla (1979) reported that a number of
different reasons were responsible for farmers failing to use fertilirer, although
unavailabilityof credit was the principal reason given by farmers for their failure in
this regard. tnadequate availabilityof credit may entail restrictions on input use (for
example, the credit constraint may limit the quantity of fertilizer (pet- hectare) and
thus discourage adoption). Many farmers may remove the input shortfall by other
means (using alternative inputs), especiallywhen the restricted quantity of the input
significantlyaffects the yield. For a long time in Senegal, the subsidization of credit
has been suggested as an appropriate policy measure to mitigate the ilf-effects of
a paucity of credit on technology adoption. Lipton (1976) argues that subsidization
of credit does not necessarily circumvent the problem for smaller farms since in
many casas the larger and more influential farms manage to get the bulk of SUC~
credit. Where a new variety is marginally profitable, the subsidies implied by
govemment credit programs could be expected to affect many farmers’ decisions.
But if the new technology is profitable, even at unsubsidized capital and input
prices, farmers could be expected to adopt the technology and to purchase the
t
130
inputs through the credit program if it in fact provided capital and inputs at
subsidized prices. In the latter case, one would se6 a high correlation between the
use of credit and adoption even though the credit program itself had Littleeffect on
the adoption decision. Thus some studies {Von Pischkle, 1978) bave even
questioned the validity of the argument that credit availability is a precondition for
adoption. The fact that a farmef may have failed to get credit frorn the lending
institution does not preclude the possibilityof other sources
of funds being available
to him. Hence, the farmer may indicate having difficulties getting credit but may yet
adopt. A major aspect in the availabilityof credit in the area is the fact that improved
seeds or certified seeds are only availablethrough those credit programs. They are
not sold on the market, meaning that farmefs outside the credit program wifl have
difficulties in finding the seeds. The privatization of the seed production sector has
not yet solved the problem. However in addition to the credit program organized by
the extension program, farmers have access to the improved rice varieties through
on-farm triaIs conducted by research and extension programs. In many cases,
farmers having difficulties getting credit may simply borrow inputs from another
farmer who has enough “contacts” to get a largef quantity of seeds than helshe
requires for his/her own use. Consequently the access to improved seeds is more
of an institutional problem than a fïnancial problem. In fact there are two major
problems retating to access to in?provedrice varieties: the dependence of the
farmers on the public or private sector for supply of seed evety cropping season,
and the lack or inadequacy of suitable infrastructure to produce, cetiify and
f
131
distribute improved rice seed’.
Membership (MEMBER) of a village-levei brganization was significant and
positively related to the adoptionof high yielding rice varieties. The GPS are used
by DERBAC in its extension effort. Ali heads of households are voluntary members
of the GP. Each household pays a retainer fee, used to caver the cost of group
business activities, and a sum provided as a security deposit. This sum is also used
to pay for delinquent debts. At the beginning of each agricultural season the leaders
and extension agents survey members to estimate their credit worthiness and input
requirements. All credit is provided in the form of inputs. Debt recuperation is
always a problem when farmers produce only food crops and few cash crops.
However, the villagers know the character of each member and are able to apply
social pressure on delinquents. In situations like this, the only recourse for debt
reimbursement is to make the entire village responsible for a loan. Thus,
participation in a GP2 is a necessary condition for access to credit in a setting
where the small farmer is the norm rather than the exception. Farmers who were
cooperative members and who were exposed to extension activities were more
likely to adopt modern varieties.
Differences in the cost of acquiring and processing information (Information)
‘Farmersaresupposedto keepplanting seedeachyearout of their harvest.The GOS basbeentrying
o encouragethis practiceby buildingstoragefacilities in rural areas.This policy hashad very little suuxss
“or two main reasons: the low ievel of harvestandthe lack of trust in a public seedstoragesystem.
2Themembershipis confmedto the householdheadandthis hasbeenviewedas a problem whenthe
~.:re.dit
is important for activitiesspecificto women.This is partly why DERBAC baspromotedthe
AevelopmEntof GIEs that haveaccessto crtxiit tbroughGNCAS. Women arewell engagedin theseCIES.
132
-.
._.-_
-.--.-.
~. _
‘,.
:
i’.
.~?
_‘,
.
‘.<a:
as measured by the exposure to more improved rica varieties through contacts with
extension and research, was significantand positively related to adoption. Learning
and information accumulation are hypothesized to play a major role in adoption.
The greater the farmer’s oommandof technioal knowfedge or the greater his access
to it, the greater is his familiarity with the technology, and therefore, the greater is
the probability of adoption. Farmers may have obtained the technical knowledge
of the HWs through interaction with extension agents, but also neighbors. in this
study, the main source of information for farmers is represented by other fat-mers
(see Section 54.1, Table 5.10). In the learning process, two main considerations
are important:
(1)
The regularity of rewards as an attribute to measure risk and uncertainty. ft
is the recognition that few varieties always perform better than the local.
(2)
The clarity of results would appear to be an important component of the
communication process, as perceived resutts of tentative adoption contribute
to commitment or rejection.
Farmers’ initial impressionof the technofogy (APPREXP)was significant and
negatively related to adoption. This means that farmers that had a bad initial
experience with the technology were less wilfing to adopt it. Economie pressures
couid be expected to be more important at lower levels of living because there is
more to iose by trying an innovation. Gafsi and Roe (1979} found that dumesticalfy
produoed HWs were more readily adopted by focal farmers than the relatively
unfamiliat imported varieties. Other studies used more sophistioated Bayesian
\
133
----
. .._._
‘-6
.
.*.
.
13
.,
1,
.
.’
,
.<
i
models for learning. Lindner (1990) elicited estimates of farmers’ subjective beliefs
about the mean and variante of wheat variety yields, to test propositions about
Bayesian learning. The results of his analysis neither confirm nor reject the
Bayesian approach as a mode1of how farmers revise subjective beliefs, but do
raise serious doubts about its realism.
The variables representingsize (LABOR, SIZE) were not significant but were
negatively related to adoption. Small fan-ns should be more willing to adopt
improved rice varieties in the area. In Casamance rice cultivation is more important
to small fan-nsthan large fan-ns.In the south (Oussouye) farms are small in size and
rice is the main and some times the only trop grown. Farmers have less access to
plateau lands and all investments are directed toward rice production. In the areas
(northwest, northeast) where farmers have access to more plateau lands, the
emphasis is put on dryland crops, especially groundnut. In these areas, rice is a
marginal trop compared to groundnut. Improvement in groundnut production, using
improved seeds, is more relevant for farmers. The main idea is that since there is
a well developed market for groundnut, income generated from the activity cari be
used to purchase rice, and thus make up for the deficit in rice production. However,
the relationship between fan-nsize and adoption may refiect a number of underlying
factors. The relationship may differ in different socio-cultural environments, and
hence the empirical observations may seem rather conflicting if the basic or
underlying factors are not considered directly. A negative relationship between
adoption of improved varieties (i.e., divisible technologies) and farm size is
\
134
supported
by many studies (Biswanger, 1980; Gafsi and Roe, 1979). Weil (1970)
suggested that a credit constraint may be the reason for the observed negative
relationship between farm size and lumpy technologies. Perrin (1978)
using
a
multivariate analysis showed that once credit and extension contacts are
considered, the residual effect of size was minor. After a oareful consideration of
extension and credit activities, he concluded that the orientation of those
programs
toward small farmers contributed substantially to the greater adoption rate among
small farmers. This negative relationship may be the result of risk and uncertainty.
Farmers with different family sizes may respond differently to the same expected
profit increment from adoption in the presence of risks. At this point the evidence
from most empirical studies do not support the hypothesis of a significant positive
relationship between farm sire and adoption.
The variable WEALTH, a measure of how rich a farmer is perceived, was not
significant in explaining the farmer’s decision to adopt improved rice varieties. Two
main reasons oan be listed: (1) the level of investment required by the adoption of
rice technology is limited to the purchase of seeds (a divisible technology); (2) few
farmers (1.7%) in the sample were perceived as rich and 98.3 Ot6were ranked poor.
The use of animal traction (TRACTION) was not significant in explaining
farmer’s adoption behavior. The use of animal traction in rice fiefds is very fimited
and has been only recently introduced by the FSR in some areas (see Section
2.7.2)
135
6.2 Technology-Speciflc
Factors and Adoption
In conformity with the hypotheses of the study, ail the varietal specific
variables were positively refated to the probability of adoption and the intensity of
use of the improved rjce varieties (Table 6.2). The four attributes, CYCLE,
RESISTANCE to stress, HEIGHT, and COOKING quality, were signifîoant and
positively related to adoption. In order to adjust to the new environment
characterized by the shortening of the cropping season, farmers are continuatly
Jooking for early maturing varieties. Farmers are, in their own way, engaged in a
constant screening program. A range of varieties are planted on ail types of rice
fields. Posner (1991) showed that, in the case of aquatic rioe, farmers usually
transplant long cycle varieties on good fresh water fields and shorter cycle varieties
on either Salt-affected
or drought prone fields. He also showed that higher yields
are associated with varieties that have cycles between 90-105 days.
Height (HEIGHT) is particularly important for rice growers and affect their
willingness to adopt the new varieties. Local varieties are usually tall and leafy, and
this facilitates harvesting.This task is carried out by women using a knife. Improved
varieties are usuatly shorter than local varieties and hence are more diffioult to
harvest. Improvement programmes have given priority to the development of
varieties with short stature. This element of the new teohnology has a negative
value since women have to bend in order to harvest the trop. Studies have shown
that it takes at least 40 person days to harvest one hectare. This technological
innovation has tended ta disadvantage women relative to men. Thus this type of
‘)
136
innovation may not have the social approval which is Iikely to be important in
determining adoption especially in societies .where modern technology in
agriculture is itself an innovation. The problem with tall local varieties is that when
fertilizer is applied at rates exceeding 40kg/ha, many of them tiller profusely, grow
exoessivelytall, lodge early, and yield less than they would with lower fertilizer rates
(IRRI, 1980). However in an environment where fertilizer application on rice fields
is the exception rather than the norm, this problem may be less relevant.
Table 6.2 Estimated Results for Farmer Adoption Mode1Using Technology-Specific
Variables
Parametef
I Normalized coeff.
Asymptotic stand. error
Asymptotic t-ratio
I
CYCLE
0.4492”
0.1537
2.9920
RESISTANCE
0.4125”
0.1892
2.1800
HEGHT
0.5227”
0.2312
2.4773
TILLER
0.1626
0.4520
0.3596
YIELD
0.3709
0.4565
0.8124
QUALITY
0.4776”
0.2915
1.6382
TASTE
0.1620
0.3266
0.4960
INTERCEPT
-0.0878
0.0728
-1.2072
The attribute resistance (REWTANCE)
to stress (disease and insect
resistance, drought resistance, and toleranee to problem soils) was significant and
positively related to adoption. Most of the varieties released are resistant to rice
btast. However, few varieties are adapted to areas where iron toxicity and salt
intrusion are problems for farmers. Research leading to varietal improvement for
adaptation or resistance to soil-related stresses, needs to be developed in the area.
\
137
Cooking quafity (QUALITY) was significant and positively related to adoption.
.
This attribute is specially important for these farmers because rice is grown mainly
for hame consumption. Cooking quality is determined by the physicochemical
properties of the starch. Farmers look for varieties that have some specific cooking
qualities: tenderness and stickiness of grains once cooked. The cherni&
characteristics, amylose content, gelatinization temperature (GT), gel consistency,
and fragrance, affect cookingand eating quality. Amylose content is the most
important chemical characteristic and determines the hardness of cooked rice.
Many traditional varieties have intermediate amylose and cook moist and tender,
while most improved varieties developed by the national rice improvement
programme have high amylose content and harden after cooling. Varieties with an
intermediate amylose content which are soft cooking should have broad acceptance
in the area. Gelatinization temperature determines the time required for cooking.
Rice with an intermediate gelatiniration temperature is expected to be preferred
over those with low GT, because most local varieties have intermediate GT. The
ease of cooking is important for farmers since it saves energy (ftre-wood is very
limited in rural areas) and time for female labor. Innovations perceived as means
of saving time for the family farm would be adopted relatively quickly. Relatively
expensive innovations would be adopted at a slower rate than the less expensive
in view of the many demands on scarce financial resources.
Yield (YIELO), and the related attribute tiliering ability, were positively related
to adoption but were not significant in explainingthe decision to adopt the improved
1
138
rice varieties. This seems to indicatethat yieid superiority of the elite cultivars is net
the main characteristic farmers are iooking for when deciding or rejecting a given
rice variety. This could also be interpreted as the beliefs of farmers that under their
“poor” production environments their local varieties stili perform better as far as
yield is concerned. Their main problem could be the lack of adaptabiiity to the
new
production environments characterized by less rainfall, salt intrusion and iron
toxicity. In most trop improvement programs, priority has been traditionally given
to yield potential. In their screening process rice breeders were more interested in
the yield component variables such as seedfing establishment, plant stand,
seedling vigor and number of panicles per plant. Thus yield has been the major
criterion used by breeders when ranking varieties. The findings suggest a major
difference between farmers and researchers’ subjective evaluation of a given
technology. This also means that in terms of research priorities, more emphasis
should be given to the improvement of other varietal characteristics. The actual
yield performance of improved varieties is acceptable.
Taste (TASTE) was not significant in explaining adoption behavior. Three
possible reasons for that finding are:
Farmers are very used to the taste of their local variety SOthey Will always
consider them better than any other variety;
Local varieties actually do taste better than improved varieties;
Farmers consider taste as a residual factor easy to overcome once the
cooking quatity is improved.
139
These results are consistentwith eariier findings of Section 5.4.2. For
the yield Met-ion, the mean demandand suppiyindicesfor improvedvarieties
were respectiveiy0.99 and 0.90, meaning that actuai improved rice varieties
meet farmers’ expectations. Thus yield is no longer a characteristic that
farmers are using to decide to adopt or not adopt. For the cycle criterion the
mean demand and suppiy indices were respectiveiy 0.92 and 0.80 meaning
that this characteristic is not perfectiy embodied in ail the improved varieties
reieasedto farmers.improvementin the quaiity of that characteristicwiil affect
the farmers’decision to adopt. The mean demand and suppiy indices for the
cooking quality characteristic were respectiveiy 0.89 and 0.77. This shows
there is scope for improvement in the quaiity trait in order to boost famers’
adoption. The resistance to stress has a mean demand and supply index of
respectiveiy 0.93 and 0.37. This indicates that, actuai rice varieties with
respect to the resistance criterion (drought, saiinity and iron toxicity) do not
meet farmers’expectations,there is room for improvement.This Willultimateiy
determinefutureadoptiondecisions.With respectto taste, the mean demand
and supply indiceswere respectiveiy0.83 and 0.78.Thus taste has the iowest
demand indexmeaningthat this characteristicis not the most important factor
in farmers’ adoption behavior.
140
6.3 Farm, and Farmer Specifk Factors, Te~hn~f~OyaSp~~tf~cVafiables
and Adoption
When bath farm, farm-specific, and technology -specific variables were
considered the results showed the same patterns with more emphasis on the
importance of the variables related to the characteristics of the technology: 4 factors
out of 8 were significant compared to 4 out of 9 for the fafmer specific factors (Table
6.3). The results are consistent with the major hypotheses of the study that both
socio-economicfactors and specific technology characteristics determine whether
a farmer Willor Will not adopt the new rice teohnology.
The objectives of the technology policy being implemented in the tower
Casamanoe are to foster diffusion and adoption of improved technologioal practices
for the expansion of rice production, in order to satisfy domestic needs, and to
enhance foreign exchange earnings through reduced rice imports. The findings of
this study show that the devefopment and diffusion of improved rice varieties are
linked, on the one hand, to the local research and development programme, and,
on the other hand to the iocai sooioeconomicor human (farmers, extension agents,
etc.) and to the physical environment. The potential effects of any change in the
different faotors on the intensity and probability of adoption of the new technology
could be a valuable input in the formulation of technology policy.
6.4 Quantitative Implications for Research and Devetopment Strategies
The Tobit mode1provides a rich framework for deoomposing the effects of
changes in the level of the explanatory variables. This decomposition of the Tobit
coefficients followîng equations (3.25) and (3.26) involves the computation of F(z),
3
141
an area under the normal curve. Finding the appropriate area in tables presenting
only half of the curve depends on F(z). F(z) ddned as the proportion of cases
above the timit (the proportion of fat-mers tbat have adopted) is 0.5575, which is
greater than 0.5, thus the desired area is 0.0575 (0.5575-0.5). After iocating the
area in the table, the ordinate f(z) (0.397) and the z-score (0.1) are computed. With
z, f(z), F(z) and the Tobit coefficients, the effects on the intensity and probability
of adoption for the statistically significant independent variables are computed.
Table 6.3: Estimated Results for Farmer Adoption Modei Using Farm and Farmer
Specific Factors and Technology-Specific Variables.
ACCESS
MEMBER
INFORMATION
APPREXP
WEALTH
TRACTION
RESISTANCE
QUALITY
t
142
Table 6.4 shows the decomposition results.
The results show that a unit increase in thé aocess to credit (ACCESS) for
farmers implies an expected change of only 0.113 in the intensity of adoption for
those farmers who have already adopted the rice vanities. The bracketed term in
Equation 3.25 is equal to 0.42 and represents the fraction of the total effeot of the
access to oredit for those farmers that have adopted. Put simply, 42 percent of the
total effect of increasing farmers’ aooess to credit is on increasing the intensity of
adoption, The obverse statement is that 58 percent (I-0.42) of the total effect of
access to oredit is associatedwith increasingthe probability of adoption for farmers
that have not yet adopted the rice varieties. Since z, f(z), F(z) remain the same for
our sample, the proportion of any independent variable’s effect for adopters is
always the same. The total elasticity value for the access to credit is 0.377,
meaningthat a 10% increase in the access to credit is expected to result in about
4% increase in the adoption and use intensities of the improved rice varieties. The
probability of adoption Will increase by 3% while the intensity will increase by 1%.
The elasticity estimate shows inelastic response to change in the acoess to credit.
However, a defeotive credit system has been viewed as an important cause of slow
progress in the adoption of high yielding varieties. The traditional credit system run
by government has failed due to poor managementand higher administrative costs.
New the credit system is private with more requirements often out of the reach of
pour farmers. The need for collateral and down payment limit small farmers’ access
to oredit. Since there is no private ownership of land, it oannot be used for credit.
‘F
143
Table 6.4: Tobit Total Effects for Changes in the Farmer-Characteristics and
Technology-Specific Characteristics ,
Parameter
Intensity of adoption
QUALITY
0.201
Probabili
1 0.462
of adoption
Total Elasticity
1 0.663
1
Senegalese policy-makers always argue that in order to speed up the adoption
process, institutional credit should be provided for long term credit needs while
essentiai inputs should be made available at subsidized rates. Different types of
subsidies such as reduction in input prices, reduction in interest rates, raising
output prices and credit subsidy have been used in the past. Stevens and Jabara
(1988) show that subsidized credit wiii cause an increase in the amount of credit
used but it has a negative impact. ft Willresult in a net transfer from consumer-sto
the agricultural borrowers. Often the wealthier more influential farmers obtain most
of the subsidized loans, hence the income transfer cari be from the poorer to the
more weafthy. Targeting programs to specifïc types of faf-mers cari be more effective
than subsidizing credit. In the corlfext of the Basse Casamanoe, the provision of
credit is tied to the supply of farm inputs and in terms of improved rice varieties, the
problem is more the avaitability of an adequate distribution system which ensures
a timely supply of improved seeds than provision of credit per se. In fad, besides
t
144
the credit suppîied by DERBAC, there are few input supplier-sthat have access to
seeds in order to ensure a regular supply to farmers. Private input
improved
ricx
suppliers,
because of high perceived risks, are still very reluctant to commit more
resources in the subsector. lncentivesthat would bring input suppliers in rural areas
Cou\dbe more effective than a formal credit program out of the reach of the majority
of producers.
Improving farmers’ level of information about improved rice varieties
(INFORMATION) is estimated to increase the total elasticity by 0.519. This means
that a 10% increase in that variable Will lead to a 5% increase in the intensity and
probability of adoption. The intensity of adoption wouJd increase by only 1% while
the probability of adoption wou/d increase by 4%. The response to the change in
the fevel of information is relatively more eîastic than the one for the change in the
access to credit. Thus improvinginformation seems to have greater potentiaf impact
on the decision to adopt than the acoess to credit. Few people (poiicy-makers,
researchers) mention information as an important factor to adoption in the
Casamance region, the major focus being more on the need for oredit than in
anything else. Technological information dissemination in the region has mainly
been perfonned by extension agencies with very Iittle involvement of research. As
trop researoh has expanded to include other crops, the emphasis for researchers
has been to produce improved varieties that performed welf on-station. Once
varieties have proven themselves on-station they are tested in multi~o~tionaï triais
under controlled conditions. ISRA has a network of PAPE!& (Point #Appui
145
pour
I’Experimentation Multilocale) or experimental test areas in different locations.
Experiments conducted at PAPEMs are essentially on-station research, reflecting
only variations in the physical environment (e.g., climate and soil). In the past, once
varieties performed well on-station and in the PAPEMs,breeder seed was produced
and turned over to the seed service for multiplication and distribution through the
extension program that used demonstration trials or adoption trials to validate the
performance of the varieties under farmers’ conditions. The tests often involved one
improved variety which is compared to the local variety. This type of design timited
the number of varieties with which farmers would be in contact. Another
shortcoming of the approach was the fact that farmers got involved in the screening
process only at the end. This weak linkage between research and extension in the
disseminationof information about improved technology is a major shortcoming in
improving agricultural production in Lower Casamance. In 1982, ISRA rectified
some of the shortcomings in research program priorities, execution and information
dissemination, with the institutionalization of the fanning system approach to
research. This new approach allowed more testing using on-farm triais and greater
interaction with farmers and extension agents. Farmers have the opportunity to
intervene earlier in the screening process by being exposed to more varieties. It
allows ISRA to produce extension recommendations that are ‘farmer-ready’,
meaning tested under farmer conditions and presented in a form that is readily
understandable and useable by extension agents. The information flow between
ISRA, the extension, and farmers is much improved because the new strategy
146
(conducting most of the steps involved in the screening of the technology at the
farm level) is closing the gap between farmers &d sources of information. This
ultimately Willshorten the cycle of technology generation and save scarce research
resources. In addition, recently researchers and extensionists have started seeking
out cooperating farmers or farmer groups with whom to test and evafuate improved
technologies. A growing number of farmer organizations are also appearing, giving
more opportunities to farmers, and encouraging feed-back from them through
extension to research and vice versa.
Fat-mers’ participation in a local organization (MEMBER) is expected to
increase the total elasticity by 0.60. This means that a 10% increase in that variable
Will fead to a 6% increase in the intensity and the probability of adoption. The
intensity of adoption Will increase by 1.8% while the probability of adoption Will
increase by 4.2%. Individual behavior is influenced through relationships the
individual has with others. The communication networks in which an individuat
participates have a substantial influence on an individual’s behavioral change.
Farmer adoption is therefore partly a function of the farmer’s network of
relationships with and between different village groups and organizations.
Village cooperativeorganizationshave historicallybeen part of West African
and Senegalesesocieties.Jolly (1987) reported that in West African societies there
were groups for Young, old, female, and male that conducted business on behalf
of these groups. These communal groups are sometimes referred to as
cooperatives. Development agencies have sought to organize production and
147
consumption activities along cooperative lines. Village groups have been organized
to conduct business relating to production and consumption. These groups are
informai types of cooperatives.They have emerged as a consequence of the faiture
of the Cooperative Movement. in the postindependence era, the GOS made the
cooperative movement an integral part of its development plan. The cooperative
movement was to become the basic unit for mixing the traditional African values of
solidaritywith modem democratic pfinciples. Critics of the Senegalese cooperative
movement indicatedthat it was difficult to attain rural development goals in Senegal
with a movement that was organized around principles alien to the peopte. The
movement’s organizational and cooperative principles were based on the French
Societe d’lnteret Collectif Agricole. Goals set by the movement were unrealistic and
did not reflect the needs of the peasantry. The functioning of the cooperative
movement was made difficult because of conflicts between the general Princip!es
of the international cooperative movement on which the Senegalese cooperative
movement was based and that of the rural community groups. Two specific
problems were:
(1)
Democratic control implies that each member has equal rights or is
adequately represented in decision making. However, in Senegalese
society, at the village level patriarchal headship is an important aspect that
varies across ethnie groups. In Lower Casamance, each village member
participates in village meetings and has input into decision making, but the
eiders, predominantly men, make the final decisions;
%
148
(2)
The principle of voluntary membership is constrained by the political culture
of traditional societies. In such societies, the political culture that values
hierarchical relationships is likely to grant less freedom to individuai
members. Patriarohalauthority is valued and an individual acts according to
the dictates of the chief and eiders.
Development efforts through local organizations have proven more
sucoessfulthan through cooperatives. In Southern Senegal, an attempt was made
in 1982 to work with local groups to increase agricultural production through making
credit more availableand through greater distribution of production inputs. A major
reason for the succoss of this type of organization is the fact that villagers prefer to
work through indigenous groups rather than through large organizations forced
upon them by the state. Those local organizations offer the best possibilities for
building long ter-mcapacity for diffusion and adoption of technology. In the last ten
years, farmers have increasingly taken matters into their own hands, organizing
their own associationswhich appear to have considerable potential. It Willtake time
for them to develop the capacity to undertake more complex functions. ISFWs
commitment to working with farmers’ organizations cari help in strengthening those
organizations through the training of its members.
The results in Table 6.4 show that the response to changes in the
technology-characteristic factors, is relatively more elastic than the response to
changes in the farmer-characteristic factors.
Research targeted at improving cycle (shortening the cycle of the varieties
*
149
to adapt to the new environment), (CYCLE) is estimated tu have an important effect
on adoption elasticity. The total elasticity is estimated to be 9.824 which is
decomposed into 0.20 for the elasticity of the expected use intensity and 0.40 for
the elasticity of the probability of adoption. A 10% increase in that variable witt tead
to a 2% increase in the intensity of adoption and a 4% increase in the probability
of adoption. Most of the impact will be in increasing the probability of adoption for
those farmers who have not yet adopted the varieties. Farmers are looking for
shorter cycle varieties. Breeding efforts for the last decade at ISRA focussed on
varieties with short growth cycles adapted to different ecological niches. For both
the phreatic rice zone and the aquatic zone net affected by sait intrusion, several
short cycle varieties are currently being tested for their adaptability to local
conditions. This trend is being supported by the local extension service (DERBAC)
through its program of promoting short cycle rice varieties. These shorter duration
varieties have very rapid growth rates and improved harvest index SOthey are
capable of producing high yields (tRRI, 1985).
Breeding efforts aimed at improving the resistance (RESISTANCE) of the
varieties to insects, blasts, drought and especially soil-related constraints such as
salinity and iron toxicity, are expected to affect the elasticity of adoption by 0.572.
A 10% increase in that variable will result in a about 6% increase in the overall
adoption of improved rice varieties. The increase is modest for the intensity of
adoption (2%). Most of the expected effect (4O/6)Will be in increasing the probability
of adoption. Varietal resistance to insects and blasts is essentiaf for yield stability.
*
150
Therefore, major resources have been allocated for incorporating genes for disease
and insect resistance. IRRI, for example, has developed improved lines that
possess resistance to many diseases and insects. The value of multiple resistance
to diseases and insects for yield stability is shown by the fact that the yields of a
susceptibie variety fluctuate greatly due to pressure of diseases and insects,
whereas the yields of varieties which have multiple resistance, show Iittle variation
from year ta year. Most of the varieties tested in lower Casamance are toierant to
rice blasts. Some varieties are susceptibleto a particular blast (Pyriculariose) when
cultivated under high fertilization level (Mbodj, 1991). The importance of drought
tolerance in varieties for upland and rainfed low conditions cannot be
overemphasized. Farmers are looking for varieties that tolerate a short period of
drought, and that show very good recovery from drought under both transplanted
and direct-seeded conditions. Tolerance to drought has not been sufficiently
emphasized as a breeding objective in the ISRA rice program. The new and major
challenge for rice breeding is to screen varieties that are toferant to salinity and iron
toxicity. It is in that area that the greatest amount of work remains to be done. Some
varieties introduced by WARDA such
as ROCKS, and WARl, WAR77 are
promising varieties for their toferance to salinity. The problem of iron toxicity is
difficult to tackle through varietal selection. Late rains and short periods of
desalinization impose constraints that make the use of improved varieties
impossible. The emphasis in those zones should be on improving the physical
environment through the construction of anti-salt dikes with gates which protect the
f
151
rice fiel& from salt intrusion and facilitate direct-seeding. Once the physical
environment is improved and reclaimed varietal issues cari be better addressed.
lmprovement in the height (HEIGHT) of the varieties is expeoted to have the
greatest impact on the adoption of improved rice varieties. The total elasticity is
expected to increase by 0.80 which is decemposed into 0.20 for the intensity of use
of the improved varieties and 0.60 for the probability of adoption. A iO%
improvement in that variable Willlead to a 2% increase in the intensity of adoption
and a 6% increase in the probability of adoption. Research efforts targeted solely
at improving the height Will benefit more farmers who are willing to adopt varieties
that are more convenient to harvest. However, for a long time, national rice
improvement programmes have developed varieties with short stature. Most of
those varieties have the semiidwarf, nitrogen-responsive plant type. The results
show that small farmers are more interested in varieties with tall stature.
Researchers view this problemin terms of trade-off between higher yield with short
varieties and iower yield with tall varieties less responsive to fertilizer. The findings
support the faot that rice farmers in Southem Senegalhave already made the tradeoff, by giving less importance to the higher yield strategy. There is increasing
interest in the utilization of the entire rioe biomass such as straw and hulls for
animal feed, and for fuel. However, varieties that cari produce higher biomass are
likely to have lower grain yield potential.Therefore, eamest efforts should be made
to breed rice varietieswith increasedbiomass for farmers in areas where rice straw
is the main animai feed. This straw is often left in the field and is partly consumed
1
152
by livestock and partly used as organic matter for the following oropping season,
ERA aocoptance of the farming system approach to researoh with a client-oriented
strategy couid help researchers better understand farmers’ effective demand for
rice technology. Ascertaining the biological and technical feasibility of alternative
rice varieties and their acceptability to different oategories of farmers bas to be
assessed. Social research is often necessafy to determine under which conditions
farmers are willing to accept the new varieties. consequently, ways to identify the
farmers’ agricultural decision criteria, which are related to rejeotion or acceptanoe
of newly designed varieties, have to be identified and tested.
Efforts to improve cooking quality (QUALITY) would increase the range of
good quality varieties (varieties with intermediate amylose content) available to
other fat-mers.This oharacteristic has the second highest impact on the probability
of adoption and use intensities. A 10% improvement in that variable wiil lead to a
2% increase in the intensity of adoption and a 4% inorease in the probabiiity of
adoption. Since rice production is mainly home consumed by the producers, the
lower rate of adoption of improved rice varieties should increase ooncerns for
improving rioe grain quality in the research program. The results show that the
observed producer preferences do not always correspond to measures of quality
used to screen material in breeding programs. Aocordingly one major question is
what are the retums to researohfor quality improvement. Many studies (Norton and
Davis, 1981) have estimated the returns to raising yields of agricultural
commodities. For example Evenson (1978) found that the returns to research for
153
improvements in rioe yields vary between 84% and 87O/6.Few estimates of the
returns to quality improvement exist in the Merature. Lawrian (1986) found in
Philippines, a rate of return to less amylose of 29%. The estimated returns to
research for improvementsin quality characteristics appear to be quite high, These
large returns to quality in poor countries are consistent with the finding that even
the very poor have higher income elasticities of demand for food quality than for
food quantity (Shah, 1983).
Therefore, in general, results indicate that wide spread adoption of improved
varieties would be better achieved through encouraging farmers who have not
adopted to adopt rather than increasingthe intensity of adoption by those who have
already adopted.
6.5 Future Directions in Rlce Breeding
The yield potentialof improved rice varieties was not significant in explaining
farmers adoption behavior. TO meet the challenge of developing improved rice
varieties for diverse ecological conditions, rice breeding objectives Will need to be
reformulated (Table 6.5)‘. In the past, improvement of yield potential, a most
important agronomie trait received the major attention in the early years. Soon
afterwards, the signifkance of disease and insect resistance for imparting yiefd
stability was recognized. Subsequently, development of early-maturing rice
‘The rankingin Table6.5 is derivedusingthe total elasticity in Table 6.4 andthe ISRA Rîce
Program’s,objectivesas standin Sections
2.4.1.
154
varieties possessing high yield and multiple resistance to diseases and insects was
undertaken to enable the rice farmers to increase their cropping intensity. Now
whiie breeding for high yield potential and stability, researchers need to emphasize
improved grain and cooking quaiity to meet the producers’ requirements. With the
shortening of the rainy season, and accordingly the start of breeding for poor and
unfavorable environments, tolerance to drought, and toxicities, (salinity, iron) need
also to be included as important breeding objectives.
Table 6.5: Prioritization of Breeding Objectives Among Researchers and Farmers
Note: 1 = first priotity,2 = second priority..etc
Research attempts to develop new technologies that are acceptable to
farmers, SOthey Will adopt them and, as a result, increase their standard of living.
Factors affecting technology acceptability are numerous induding:
(V
Environmentalfactors. They are a primary determinant of the acceptability
of a technotogy to farmers. This is because some technologies perform
successfuily in one environment, but not in others. In most instances,
1)
environmental factoss interact with specific characteristics of most
155
technologies SOthat they cranonly be successfully employed in certain
agro-
climatic situations, While technologies differ in term of the degree of
transferability fram one environment to another, few technologies are
environmentally neutral;
(2)
C&ure. Croups of people differ in terms of how they view the world, These
differences are reflected in a people’s tastes and preferences. In a situation
where most of the output is consumed by th8 househotd, culturaf
preferences will be strongest;
(3)
Farmers’ resources and goals. Although we often talk about ‘farmers’, as a
unifonngroup, we know that there are many different types of farmers. One
useful way to describe this variability is in terms of an individual’s access to
resources, credit and infomation. Resources available to farmers are
important in explainingthe acceptabilityof technology because these factors
affect farmers’ goals;
Institutions. These are the rules of behavior and structures society has
established for people to follow. Some are social (harvest sharing
arrangements) and others are formal (extension service, cooperatives);
Characteristics of the technology.
Existing explanations of the gap between farming recommendations at the
research institutes and what actually takes place on the farm are inadequate,
placing undue emphasis on the farmers’ sociodemographic characteristics and
communication variables. More important than the farmer’s sociodemographic
)r
156
characteristics are the characteristics of the technology itself and the inst~tutional
support provided for its diffusion. The compatibil~tyof the technology with existing
values, farming systems and resources, the relative advantage of the technotogy
over the one it supersedes, the provision of credit and an adequate distribution
system, the method of dissemination of the information about the technofogy, etc.,
are some of the factors which should be properly investigated to improve the
adoption of improved technology. Technological innovations provide no benefit to
society if they are not adopted by farmers.
Chapter 7 ,
Conclusions, implications and Suggestions for
Future Research
There is abundant literature on adoption of improved technologies in LI~S.
These studies suggest many hypotheses relating the adoption of new technology
to key economic and physical parameters. They have evolved to anatyze observed
adoption patterns by focussing on the relationship of variables such as farm size,
risk and uncertainty, human capital, rabor availability, and credit constraints to
adoption behavior. The majority of the evidence indicates that the adoption of
technology is positivelyrelated to fan-nsize. Leaming and information accumulation
play an important role in the farmers’ decision to adopt a new technology. With the
accumulationof experience,uncertainty declines and the innovation is adopted by
more producers. Many studies have found a positive relationship between
education, years of experience in farming, and the adoption of technoiogy.
Most of these studies have assumed that the innovation was right and have
devoted Little consideration to the characteristics of the innovation and their
potential rote in the adoption process. A number of characteristics (relative
advantage, trialability, observabitity), which would facilitate the appreciation of th8
different advantages of the new technology, have been suggested to explain the
*
158
adoption decision of small farmers. Past studies demonstrate that, ceteris paribus,
the more observable the results of an innovation, the more likely Will the farmers
adopt,
The study addressed the factors affeoting the adoption of improved
rice
varieties in Southern Senegal. It used a different approach by assuming that in
addition to socioeconomic faotors commonly used in the literature, farmers’
perceptions of the qualitative traits embodied in the new technologies are
partioularly important for improvedrice varieties. The rejection of these varieties by
farmers may be a rational choice based upon their perceptions of the
inappropriateness of the innovations.
In order to take into account similaritiesand differenoes among varieties, and
to generatize at best from the known determinants of adoption of a given variety,
the varieties were evaluated using different measures of performance. The yield
gap technique was used to measure and analyze the determinants of yields. It
helped identify the factors that explained the difference between actual and
potential rice yields in selected environments. The adaptability analysis technique,
regressing the yield of each variety against different environmental indices, was
used ta compare the performance of improved varieties with the local variety.
Response funotions were used to determine if improved varieties were more
responsive to modern inputs, and if the response curves of improved and local
varieties showed cross-over effeots. Different indices (demand, supply and
attainment) were used to measure the extent to which the varieties provided
159
through research and extension pfograms meet the expectations of farmers.
The decision of a farmef to use improved rioe varieties has been modeled
as consisting of two mutually exclusive processes. First, the farmer decides to
adopt, while in the second step, he/she decides the intensity of the use of the
varieties. Farmers were assumed to maximize utility derived from any given variety
of rice, viewed as a complex embodiment of several characteristios.
The Tobit framework, an approach extensivelyused in the analysis of choice
behavior, was used in the study, to determine both changes in the probability and
in the intensity of adoption.
7.1 Summary of Resufts
The results of the study may be sumImarizedas follows:
(1)
Improved rioe varieties experienced a yield Eossof between 20 and 70
percent when transferred from research station to farmers’ fields. Three
major factors explained most of the yield variation in rice production. On
average the variety expfained 13 to 30 percent of yield variation, fertilizer
explained 61 to 78 percent, and pest control only explained 2 to 3 percent.
tn addition to the thfee oontrotled factors, different farmers’ praotices were
found to be significant in explaining yield variation at the farm level:(?) the
growing period was positivelyrelated to yield. The level of maturation for the
different varieties is a function of the growing period and the planting date.
The latter depends on the beginningof the rainyseason, and the availabitity
a
160
of the family labor, which is corretated to the type of social organization of
labor; (2) iron toxicity, a new soit-related ckstfaint, was negatively reiated
to yield; (3) fields that were flat plowed experienced higher yields than ones
prepared by the ridge method; (4) rainfali was an important determinant of
rice yields in rainfed agriculture.
(2)
A comparison of the performance of cultivars across environments showed
that: (1) under no fertilizer, only two varieties Ri 12, RAT1 0, were superior
to the local variety across all environments. The varieties DJl2519, IKP,
TOX728, DJ684D, IfWT133, were superior to the focal oniy in better
environments;(2) under moderate fertilizer levels, most of the improved rice
varieties were inferior to the local variety in poor environments, but super&
in better environments. Thus most of the varieties did not perform better than
the local in poor environments. This lack of yield superiority over a wide
range of physical and management environments could be a constraint to
broad adoption of the improved rice varieties.
(3)
The assumptionof equal response to fertilizer for improved rice varieties and
local was rejected. Thus, under farmers’ circumstances, improved varieties
and local varieties have different response curves. WI-ien no fertilizer is
applied, improved varieties and
local varieties had different responses.
Under the conditions prevailing at the farm level (stress conditions, low
yields) response ame cross-over did indeed occur for many varieties, Thus
the ordering of improved varieties with respect to yield Will vary at high and
I
161
low management levels.
(4)
The main characteristios used by farmérs to discriminate among ria
varieties were:cycle, yield, tillering ability, resistance to pests, drought and
soit-related stresses, cooking quality and taste.
(5)
The demand indexfor yield criterion was on average 0.99, meaning that this
characteristic is highly valued by farmers in their choice of rice varieties.
Using the supply and attainment indices for that trait, the variety DJ684D
was perceived as the best variety followed by ROCKS, DJ12519, and IKP.
(6)
The tillering ability, highly correlated to the yield characteristic showed a
similar trend.
(7)
On average the demand index for the resistancecriterion was 0.93. Farmers
were very concerned about the ability of new varieties to tolerate a certain
level of stress. The supply index was on average 0.34 meaning that the
improved varieties poorly performed according to farmers’ perceptions.
(8)
The mean demand index for the cycle criterion was 0.91, which showed that
rice farmers are continuously seeking for short cycle varieties. The mean
supply and attainment indices for that criterion were respedively 0.80 and
0.75. On average the improved varieties studied performed well.
(9)
The mean demand index for the height quality was 0.76. The mean supply
and attainment indiceswere respectively0.66 and 0.53. Besides ROCK!S,all
improved varieties were poorly ranked by farmers.
WI
‘I
Cooking quality was highly valued by farmers tien
162
selecting improved rice
varieties. The mean demand index for that characteristic was 0.88. The
mean supply and attainment indices w&e respectively 0.75 and 0.67.
ROCK5 and DJ684D received the highest ranking.
(II )
The mean demand index for taste was 0.82. Among the improved varieties
ROCK5 and DJ684D had the highest supply and attainment indices. The
other varieties were poorly rated by farmers.
(12)
Farmer-specificvariables(information, farmers’ participation in village-level
organization, access to credit, age) and technolagy-specific factors (cycle,
resistance to stress, height, cooking quality) were significant in explaining
fat-mers’ adoption of improved rice varieties.
(13)
Farm size and family size did not influence whether or not the improved rice
varieties were adopted.
(14)
Yield, tillering ability, and taste of improved varieties were not signifioant in
explaining farmers’ adoption behavior, but were positively related to
adoption. Yield a very important biologioat characteristic to breeders, was
not a determinant in the farmers’ decision to adopt or rejed a given rice
variety.
(15)
Forty two percent of the total effect of increasing the level of the significant
variables was on increasing the intensity of adoption. FifQ eight percent of
the total effeot was associatedwith increasing the probability of adoption for
farmers that had not yet adopted.
(16)
The total elasticity value for the aecess to oredit was 0.377, meaning that a
v
163
10% increass in the farmers’ access to uedit would increase the probability
of adoption by 3% and the intensity of adoption by lob.
(17)
The effect of improving farmers’ level of informationon the total elasticity was
0.519. Thus a 10% increase in that variable would lead to a 4% increase in
the probability of adoption and a 1% increase in the intensity of use of the
new varieties. Improving fanners’ information about improved varieties
through research and extension programs was found to have more impact
on the adoption process than the common credit availability paradigm.
(18)
Farmers’ participation in village-level organization would increase the
probability of adoption by 4.2 percent and the intensity of adoption by 1.8
percent. Farmers” adoption was partly a function of relationship networks
within and between village groups and organizations.
(19)
Technology-characteristic factors were found to have more impact on the
farmers’ adoption behavior than the farm and farmer-specific factors.
(20)
Research targeted at shortening the cycle of the improved rice varieties
would affect the total elasticity by 0.624. It woufd increase the probability of
adoption by 4% and the intensity of adoption by 2%.
(21)
Improving varietal resistance to salinity and iron toxicity affected the total
elasticity by 0.572. The probability that farmers would adopt the varieties
increased by 4%.
(22)
impt-ovementin the stature of vaneties, especiatly their height, had the most
significant impact on the total elasticity of adoption. This would increase by
1
164
0.80. The probabilitythat other fanners would adopt the varieties increased
by 6%. This characteristic generafly neglected by breeders was highJy
vatued by rice farmers.
(23)
Cooking quality was found to be the second characteristic after height to
have the highest impact on both tha probability and intensity of adoption,
The probability would increase by 4.6% and the intensity of use by 2%.
The different results of the study may be another way of highlighting the
importance of farmer perceptions of technology specific characteristics in the
adoption of new technology. A more rigorous approaoh to evaluating the
determinants of adoption of new technologies should, in addition to the
conventional factors, inoorporate the farmers’ perceptions.
7.2 Policy Implications
Results of the study do cany important policy implications that could help
ISRA researchers better understand farmers’ effective demand for new
technologies. The purpose of these suggestions is to indicate the consequences
of different policy alternatives.
(1)
The bigger payoff to increasing the rate of adoption of improved rice
varieties occurs through getting more fat-mersto adopt rather than increasing
the intensity of adoption for those farmers who have already adopted. Thus
research and extension programsde%ignedto inorease the use of improved
varîeties should focus on convincingthose farmers who for different reasons
f
165
are still refuctant to adopt. From the study findings, there seem to be
grounds for a modification of the commofi belief that fesearch has already
led to the accumulation of an important reserve of rice varieties that only
need to be adopted by enoughfarmers for rice production to increase in the
area. There are still many different environments for which research has yet
to devise viable rice varieties.
(2)
Rice improvement programs traditionaliy have given priority to yield potential,
under high fertility conditions. This explained why the major determinant of
the yield gap was found to be fertilizer application. Since farmers are facing
many constraints in the use of chemical fertiliter (lack of cash, lack of credit,
and psychofogical constraints), food trop research must concentrate on
lower-cost technologies that coufd impfove upon existing traditional
cultivation techniques rather than on purchased inputs.
tncorporating the use of organic matter (manure, ashes) and a low input
approach in the screening process could enhance the development of
varieties with a higher probabilityof being adopted by farmers. Grop-specific
research programs could be more effective by addressing farm-level
constraints. Better coordination between trop research and FSR should
produce improvements in the research approach: closer interaction of trop
researchers with farmers, realistic diagnosis of problems, and the testing of
technology in farmers’ fields and by farmers themselves. Table 6.5 shows
that researchers and famters have different ways of ranking research
*
166
priorities. However, by conducting a considerableportion of the development
of new technologies in close collaboration&ith fat-mers, and by incorporating
farmers’ perceptions and judgements, the research process could be more
timely, thereby ensuring relevance to these specific circumtances.
(3)
Most of the improved rice varieties were superior to the local in better
environments, but did not perform well in poor environments. Our definition
of environment quality was tied to whether or not farmers used fertiliser. One
of the important cause of slow progress is the undue attention given to
developing technologies for favorable environments. The economic costs
associated with the creation and the maintenance of such highly controlled
environments are not sustainable in the long term. In order to better
determine the respective ecological niches of these varieties, it is important
that ISRA, in collaboration with the extension agency and farmers’
organizations, initiate multilocational trials of the most promising varieties.
The main objectivewould be to develop more specific recommendations that
are consistent with the diierent types of environments. TO be more effective,
this type of tria1should include systematic data collection on environmentaf
characteristics such as rainfalf, soil types and practices. In the past on-fat-m
researchers have paid lit% attention to the environmental factors. This
change in emphasis, and the current imperative to target specific
environmental conditions Will make on-farm research activities critically
important in the development of tachnologies, specifioally adapted to the
1
167
more variable environmental conditions,
(4)
We sec that only a very smatl fraction of farmers currently apply fertilizer to
rice production. T~USin the short-term varieties with the type C stability Will
be attractive only to that smali fraction of farmers. Continua1development of
such cultivars, without a simultaneousshift in the distribution of farmers with
respect to fertilizer use, Willmean that adoption rates Will remain low.
Wide adoption Willoccur in the short run only for these varieties superior to
the local at relatively low-fertifity levels, such as for varieties with A or 6 type
stability’. This cari be accomplished by giving greater weight to stability in
rice improvement programs through the development of cultivars with
increased resistance to the major yield-loss factors and that possess the
characteristics valued by rice farmers.
It is cfear that over the long-term major breakthroughs in rice
production cari only be realized through substantial improvements in the physicai
and management environment of the majority of small farmers. This could be
accomplished through the deveiopment of profitable farmer adapted methods of
improving soii fertility on a sustainabie basis. Thus in order to ensure broad
adoption pattems in the long term, reduce farm level risks associated with adopting
new rice varieties, the development of variefies with type 5 stability rather than just
type C is essential. Greater attention should be devoted to the development of
‘Obviously,it wcmldbedesimble
to develop
vari&e~with typeA stabilitybut il& maybemore
dif35cult
to5acumplish.
168
._----...
_, _
.
J.
alternative agriculturalsystems. Farmers shoutd hav8 more options to choose from,
according to their specific conditions. Offering options,and indicating th8 conditions
under which they work best (i,e., conditionaland targeting information) is becoming
more conventional (Norman et al, 1995). This approach is the recognition that the
limited-resource farm households live and work on farms characterized by a high
degre8 of both biophysical and socioeconomic diversity. This Will r8quire a new
screening and selection procedure. Farm level stresses which cause instability, and
response cross-over effects n88d to be identified and introduced in the research
process at an early stage of selection. In FSR terminology, this necessitates the
us8 of f8%?arCh/recOmm8ndatiOn
domains.
(5)
Information flow and farmers’ participation in a local organization were
significant in explaining the adoption of improved technologies. In order to
sp8ed up the adoption process, more emphasis should be put on the
information dissemînation pfocess, involving bath extension services and
village-level organizations. involving local organizations as partners in th8
identification, testing and diffusion of technologies îs a vatuabie alternative
in the context of the Lower Casamance. This Will help develop and test a
collaborative institutional partnership among key peopte and groups
(externat to th8 village and within the village) in the technology transfer
process. There are a growing number of local organizations in the rural
sector. Thus an importantstep to be considered is the analysis and selection
of the types of local organizations that possess the capacity for technology
transfer. These organizations have multiple objectives and particularly at the
onset are inclined to pursue social rither than production objectives,
Although most associations have had little direct contact with agriculturat
research or extension agencies, CADEF (Comite d’Action pour le
Development du Fogny) has demonstrated that farmers cari work directly
with agricultural researchers, defina priorities, collaborate in the research,
and diffuse results. These organizations have the potential to play important
roles in credit and extension. They will need assistance that focusses on
strengthening them rather exclusively on utilizing them as an instrument to
carry out assigned functions. lt is crucial to respect the essential
characteristics of these organizations which are based on local (internal)
initiative and resources. Implementing the proposed strategy Will require
more on-fart testing of new technologies than has usually been the case to
date. This could help tut the length of time of the technology development
/ testing cycle (time between the identification of the technology and its
appropriation by farmers), and conserve research resources for ISRA,
(6)
Credit availability was positively related to the adoption of improved rice
varieties. But ii was not SOcritical as other issues according to the Tobit
analysis. Agricuitural credit programs have been a large part of the efforts
aimed at agricuttural development. This was due to the feeling that loans are
a vital part of a package of technologies needed to stimulate change in
agricutture. Access to uwiit is dîîwlt
r4
170
in Senegal,and this is particularly truc
for agricultural production. The PIDAC experience using the GPS has shown
that local groups cari participate in a oooperative credit system scheme
without major disruption to the community social organizations. This mode1
and others operated in the areas by donors, must be evafuated in order to
corne up with a credit &-terne better adapted to specific groups of
producers, thereby enoouraging diversity in rural credit programs. It is
important to make seed available separately from conventional credit
system. This may in term diminishthe need for credit. However without basic
improvementsin agricultural research and basic infrastructure for marketing
and information dissemination, the impact of oredit programs in agricultural
development Will be sub-optimal. The development of relevant improved
technologies by research is only one component of agricultural development.
There are also needs for the development of relevant policies and support
systems. These play important roles in the suocessful implementation of
strategies directed at improving the productivity of smalt farmers.
7.3 Llmltations of this Study
The results of this study should be interpreted with caution bearing in mind
the following:
(1)
The farmers’ decision making prooess was modeled using a univariate
appfoach.
(2)
‘I
This study was concernedwith rice produotion,which is only one component
171
of the farmlng systems prevailing in the area. It was assumed that the other
components did not influence the fan-ne& decision to adopt or reject a
specific rice variety. This assumption may not be realistic.
(3j
This study is based on cross sectionai data, and are influenced by the
seasonal conditions prevailing in those years. Rainfall variations do affect
agronomie results. Acoordingly using data from different time periods (e.g.
yield gap analysis and adaptability analysis used data collected in 1982-66,
while the sutvey on farmers” perceptionswas conducted in 1996) may mean
the results should be treated with caution.
(4)
All subjective evaluations of the characteristics of the rice varieties are
relative to the sample only.
7.4 Needs for Further Research
The methodotogy developed in this study could be further extended and
used to analyze other issues of equai importance to JSRAand in the development
of improved technologies in rurat Casamanoe.
(1)
In this study quality characteristics of rice varieties were measured using
farmers’ subjective evaluations. An additional step woufd be to use
quantitative measures of these oharacteristics for each varie& and express
the rate of adoption as a function of the amount of each chareoteristic. Then
simulation models could be used to project the impact of potentiat
improvements in cycle, height, cooking quality (amytose content), and
*
172
‘:..’
resistance to different stresses, on adoption rates of new rice varieties in
Casamance. The simulationswouid be peformed by replacing mean values
of seiected independent variables with a range of values which represent
potentiaf outcomes of plant breeding feSearGh.The results of SU&
a study
would provide usefu! information concerning the opportunity costs in terms
of adoption rates, of the large number of research objedives facing rice
breeders. They face important trade-offs between the large and increasing
inventory of research objectives including yield levels and stability, end-use
quatity, and disease resistance.
(2)
The results of this study could be futther used to assess the impact of rice
research in Casamance. The main objective would be to conduct ex-ante
and ex-post evaluations of the benefits and costs of rice research in the
Southem Senegal.A partial equifibrium framework based on the concept of
eçonomic surplus coutd be used. Such analysis would provide more
accurate figures for the rates of retum to investment on the new varieties. in
addition to calcufating the rates of return, the study could also consider
distributional issues.
(3)
In this study we foeussed on a single technology and used a univariate
modeling approach. This was relevant since farmers did not use fertitizet
and therefore the adoption of impfoved rice varieties was a one componenttechnology. In order to use the methodology to study a wide range of
technologies devetoped by ISRA in the area, we need to take into account
some additional considsrations. in many circumstances, the poiitical, social
and technological ctimate ticed by farn&s, involves the increased use of
sustainabie production techniques in as many areas of agricuttural
production as possible. This is done by adopting a combination of new
technologies. Thus the adoption decision is an inherentiy multivariate one,
and attempting univariate modeling excludes useful economic information
contained in interdependent and simultaneous adoption decisions. Thus
treating the farmer’s adoption policy as a number of possible related
choices, rather than isolated dichotomous decisions should lead to a better
understanding of characteristics which are associated with the technology
adoption decision, and could improve the ability to forecast adoption of a
particular technology or technology bundle. Looking at rates of adoption and
the impact of changes resulting from the dissemination of improved
technologies cari help justify net only future funding for agricultural
development activities, but also hetp provide ideas on future research
priorities, and indications on adjustments that are necessary to facilitate
greater adoption.
(4)
The variability of yields cari lead to a major source of fluctuation in food
availabilityfor fat-mersand is therefore a primary production risk. Little study
has been focused upon agronomie research directed at the reduction of the
variabilityof yields. This could provide insight into the adoption process, and
mietoeconomiceffects of alternative cuttivars for rice producers in Southern
1
174
Senegal. Consideration of the desired Ievel of researoh and potential
adoption by farmers is useful in evaluating benefits of research projects. In
terms of agronomieresearch, several areas of economic importance cari be
addressed other than the investigation of new improved varieties strictly
aimed at increasing yield potential. While economic benefits have been
evaluated in relation to agronomie research such as breeding resistance,
consideration of risk could be included in the microeconomic analysis of
agronomie research. Such a study would not focus upon the macroeconomic
value of agronomie research but rather on the individual producer’s
response to new cultivars.
175
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Appendices.
Appendix A: Quantitative Assessment af tmprovod Rice Varieties in
Casamance
Name of improved Variety
Name of Local Variety
Position on Toposequence
Desired Characteristics
1 = vefy important
2 = important
3 = not SOimportant
Improved Variety
A = very good
B = good
C = poor
Local Variety
X = very good
Y = good
2 = poor
Please circle the most appropriate response. * if the response is “don’t know,”
“didn’t respond” or “doesn’t appfy,”leaveblank.
I Qua&
Characteristks
I Desired Characterktics
189
I Improved Variety
I Local Variety
I
Appendix B: Response Matrix for the Main Variaties
Bl: The response matrix for the variety IKP
Poor
1
0
0
1
Cofumn total
102
11
1
114
Poor
1
1
0
2
Column total
58
33
II
102
191
82: The response matrix for the variety Rock5
Poor
4
1
0
5
Coiumn total
147
26
0
173
Not SQimportant
Row total
Poor
31
13
Coiumn total
142
27
Tiltering
Very important
important
Not SOimportant Row total
Very Good
162
2
0
I 164
Good
15
0
0
I 15
Poor
0
0
0
I0
I2
0
I 179
l Column total
I 177
192
.
- .--
______-
I_--
,-_-_,
,,
----Y--‘-‘---
.
-,
_.
I,‘,..
,,
>
I
i
.i,
Poor
0
0
0
0
Column total
180
u
0
180
Poor
0
0
Column total
100
47
0
10
157
3
138
63: The response matrix for the variety DJI 2519
Column total
118
17
193
Column total
90
Paor
1
0
10
1
Column total
138
1
10
139
194
-
..-
--.
----_-,~-_/
:
.--.-L-_
.
,.,
“.W,
‘x~~.
,_
POOI-
1
1
0
2
Cotumn total
127
19
2
148
84: The response matrix for the variety DJ684D
Resistance
1 Important
ver) ( important
.
Very Good
27
Column total
1
I 61
195
1Not SOimportant I1 Row total I
0
128
Column total
72
196
B5: The response matrix for the variety Abtaye Mano
Poor
Column total
145
112
11
197
2
56
2
126
POOf
6
0
0
6
Column total
125
4
0
129
Column total
128
1
0
129
198
f36: The response matrix for the local variety
Poor
0
0
Cohmn total
209
131
Poor
2
0
Column total
381
13
0
46
386
2
10
394
199
-----
..-..m.
.-%T.
.‘”
I
P00r
0
0
0
0
Cotumn total
391
2
0
393
87: The response matrix for the variety Senicoly
200
---
._
__-.-
‘.
i.
Poor
3
5
0
8
Cofumn total
25
8
0
33
POOr
0
0
0
0
Column total
24
6
3
33
201
Important
Not SOimportant Row total
2
1
26
1
7
10
0
2
0
I