Unlocking Barriers to Adoption and Scaling of Climate ... › 2019 › abstracts › posters ›...
1
Unlocking Barriers to Adoption and Scaling of Climate Smart Cocoa Practices in Ghana 1 International Institute of Tropical Agriculture (IITA), Ghana 2 University of Ghana (UoG), Legon 3 Opus Insights, Uganda Mustapha Alasan Dalaa 1 , Rich Kofi Kofituo 1 , Alvin Amoah 2 , Laurence Jassogne 3 Richard Asare 1 www.iita.org I www.cgiar.org Introduction Farmer typology has become a common method of segmenting farmers into groups to assist in developing targeted farm extension programs (Schwar et al. 2009). It takes into account the social values of farmers and their approach to farming, together with the structural and demographic variables of traditional market segmentation. This ensures that farmer’s specific training needs are addressed as individual farmers with different personal characteristics and resources may have different training needs at different times. Objective Identify farmer typologies across the different cocoa climate impact zones of Ghana and how this affect adoption of Site Specific climate- smart cocoa CSC recommendations. Context Cocoa output has been negatively affected by extreme rise in temperatures and sharp decline in rainfall over the years and this may worsen in the future. The introduction of site specific climate-smart cocoa (CSC) practices (Minimum, Bronze, Silver and Gold) which is tailored to individual resource endowments of farmers can reduce the impact of climate change on cocoa production with positive effects for optimum output. Materials and Methods Semi-structured questionnaire was administered to 270 cocoa farming household on socio-economic characteristics and intensity of CSC implementation across the climate zones. Using the R software statistical package, a principal component analysis (PCA) was carried out. Focus group discussion‘ was used to generate farmers constraints. Pair wise ranking was also used to prioritize. Fig. 1: Cocoa Climate Impact Zones of Ghana Source: Bunn et al (2015) Fig. 2: Focus group discussion with cocoa farmers to identify constrains to CSC adoption Results and Discussion Preliminary results show varying intensity of implementation of CSC practices which determines the efficiency of the clusters. • The first cluster of cocoa farmers is characterized as the least efficient in production in terms of Cocoa productivity (248 kg/ha) and Cocoa income (USD 981 per annum) • Second cluster of farmers are the most efficient with the highest cocoa income (USD 3000 per annum) and Cocoa productivity (583 kg/ha). • Third Cluster represent farmers with the most resources in terms of land under cocoa (3.7 ha) and hired out labor (≃4 people from the household) and also not efficient with cocoa productivity of (301 kg/ha) In all clusters, access to hybrid seedlings, financial challenges and extension service delivery were identified as challenges hindering adoption of CSC recommendation. Conclusion The efficiency of cocoa farmers is influenced by the level and intensity of implementing CSC practices. It is recommended that farmer typologies aligned with CSC recommendations in the climate impact zones should be taken into consideration for effective adoption. A farmer segmentation tool (FST App) is being developed and will be available on App Stores to enhance the adoption of CSC practices amongst different types of cocoa farmers. Reference Schwarz, I., McRae-Williams, P. and Park, D. (2009). Identifying and Utilizing a Farmer Typology for Targeted Practice Change Programmes: A Case Study of Changing Water Supply in the Wimmera Mallee. Extension Farming Systems Journal. Vol. 5, No. 1 – Research Forum. Peterson, C. A. (2014). Local-level appraisal of benefits and barriers affecting adoption of climate-smart agricultural practices: Ghana. Technical report for the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). Fig. 3: Distribution of cocoa farmer typologies in Ghana Fig. 4: MAPPING FARMER TYPOLOGIES &CSA PACKAGES Acknowledgements This study has made possible with the support of CCAFS and number of partners including BMZ, giZ ,USAID and the Climate Smart Cocoa consortium in Ghana.
Transcript of Unlocking Barriers to Adoption and Scaling of Climate ... › 2019 › abstracts › posters ›...
Unlocking Barriers to Adoption and Scaling of Climate Smart Cocoa Practices in Ghana
1 International Institute of Tropical Agriculture (IITA), Ghana 2University of Ghana (UoG), Legon 3Opus Insights, Uganda
Mustapha Alasan Dalaa1, Rich Kofi Kofituo1, Alvin Amoah2, Laurence Jassogne3Richard Asare1
www.iita.org I www.cgiar.org
IntroductionFarmer typology has become a common method of segmenting farmersinto groups to assist in developing targeted farm extension programs(Schwar et al. 2009). It takes into account the social values of farmersand their approach to farming, together with the structural anddemographic variables of traditional market segmentation. Thisensures that farmer’s specific training needs are addressed asindividual farmers with different personal characteristics andresources may have different training needs at different times.
ObjectiveIdentify farmer typologies across the different cocoa climate impactzones of Ghana and how this affect adoption of Site Specific climate-smart cocoa CSC recommendations.
ContextCocoa output has been negatively affected by extreme rise intemperatures and sharp decline in rainfall over the years and this mayworsen in the future. The introduction of site specific climate-smartcocoa (CSC) practices (Minimum, Bronze, Silver and Gold) which istailored to individual resource endowments of farmers can reduce theimpact of climate change on cocoa production with positive effects foroptimum output.
Materials and MethodsSemi-structured questionnaire was administered to 270 cocoafarming household on socio-economic characteristics and intensityof CSC implementation across the climate zones. Using the Rsoftware statistical package, a principal component analysis (PCA)was carried out. Focus group discussion‘ was used to generatefarmers constraints. Pair wise ranking was also used to prioritize.
Fig. 1: Cocoa Climate Impact Zones of Ghana Source: Bunn et al (2015)
Fig. 2: Focus group discussion with cocoa farmers to identify constrains to
CSC adoption
Results and DiscussionPreliminary results show varying intensity of implementation ofCSC practices which determines the efficiency of the clusters.• The first cluster of cocoa farmers is characterized as the least
efficient in production in terms of Cocoa productivity (248 kg/ha)and Cocoa income (USD 981 per annum)
• Second cluster of farmers are the most efficient with the highestcocoa income (USD 3000 per annum) and Cocoa productivity(583 kg/ha).
• Third Cluster represent farmers with the most resources interms of land under cocoa (3.7 ha) and hired out labor (≃4people from the household) and also not efficient with cocoaproductivity of (301 kg/ha)
In all clusters, access to hybrid seedlings, financial challenges andextension service delivery were identified as challenges hinderingadoption of CSC recommendation.
ConclusionThe efficiency of cocoa farmers is influenced by the level andintensity of implementing CSC practices.
It is recommended that farmer typologies aligned with CSCrecommendations in the climate impact zones should be takeninto consideration for effective adoption. A farmer segmentationtool (FST App) is being developed and will be available on AppStores to enhance the adoption of CSC practices amongstdifferent types of cocoa farmers.ReferenceSchwarz, I., McRae-Williams, P. and Park, D. (2009). Identifying and Utilizing a FarmerTypology for Targeted Practice Change Programmes: A Case Study of Changing WaterSupply in the Wimmera Mallee. Extension Farming Systems Journal. Vol. 5, No. 1 –Research Forum.
Peterson, C. A. (2014). Local-level appraisal of benefits and barriers affecting adoption ofclimate-smart agricultural practices: Ghana. Technical report for the CGIAR ResearchProgram on Climate Change, Agriculture and Food Security (CCAFS).
Fig. 3: Distribution of cocoa farmer typologies in Ghana
Fig. 4: MAPPING FARMER TYPOLOGIES &CSA PACKAGES
AcknowledgementsThis study has made possible with the support of CCAFS andnumber of partners including BMZ, giZ ,USAID and the ClimateSmart Cocoa consortium in Ghana.
