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Soil degradation and low crop productivity negatively affect the food security of smallholder farmers in West Africa. Various agricultural techniques have been developed as components of food security interventions, but their effectiveness in addressing food insecurity in part depends upon farmers’ willingness to adopt these techniques. Likewise, adoption depends upon the effectiveness of these techniques in fulfilling farmers’ objectives. The institutional and biophysical environments mediate not only the effectiveness of the techniques, but also how farmers value a technique. This study examined the evidence for fertilizer microdosing as a form of agricultural intensification and the socio-economic conditions that influence its adoption among smallholder farmers. A census was conducted in one village in northwest Benin that had recently seen the introduction of fertilizer microdosing. Key household-level determinants of adoption identified in the literature—household resources, household demographics, and access to inputs— were included in the household surveys. Using partial budgeting analysis and yield data from demonstration plots, the relative profitability of fertilizer microdosing was calculated as a necessary condition of adoption. Drawing from farmers’ stories, the potential value of microdosing was contextualized within the larger social and institutional context. Based upon the village census, there was little adoption outside of the research project that introduced microdosing to the village. Households using microdosing (predominantly found within the research project) had, on average, higher socio-economic status, more cultivable land and larger labour forces. Profitability analysis indicated that microdosing was on average less profitable than the point-source application of the recommended dosage rate in Benin (the common alternative). However, farmers still expressed a desire to microdose, due to poorly functioning input markets, poor infrastructure, and lack of access to financial instruments, all of which limited the availability, access and utilization of inorganic fertilizer.

Farmers generally produce multiple crops while selectively adopting modern technologies to meet various needs. The main aim of this study is, therefore, to identify the range of socio-economic factors influencing the adoption of modern agricultural technology in multiple food crops and the corresponding impacts on productivity and food availability at the farm-level in South-eastern Nigeria. In this study, three major food crops (i.e., rice, yam and cassava) and two elements of modern technologies (i.e., HYV seeds and inorganic fertilizers) are considered. The hypotheses of the study are that inverse farm size – technology adoption, size – productivity, size- profitability and size – food availability relationships exist in Nigerian agriculture. The research is based on an in-depth farm-survey of 400 farmers from two states (251 from Ebonyi and 149 from Anambra states) of South-eastern Nigeria. Data has also been derived from surveys and interviews of ADP Program Managers and NGOs. A range of qualitative and quantitative methods including inferential statistics, bivariate probit model and regression analysis were used in order to achieve the specific objectives and test hypotheses. The results show that sample respondents are dominated by small scale farmers (81% of total) owning land less than 1 ha. The average farm size is small estimated at 1.27 ha. Farmers grow multiple crops instead of a single crop, i.e., 68% of the surveyed farmers grew at least two food crops. The level of modern technology adoption is low and mixed and farmers selectively adopt components of technologies as expected and use far less than recommended dose of fertilizers in crops. Only 29% of farmers adopted both HYV seeds and fertilizers as a package. The study clearly demonstrates that inverse farm size – technology adoption, farm size – productivity, and farm size – food availability relationships exist in agriculture in this region of Nigeria; but not inverse farm size – profitability. The bivariate probit model diagnostic reveals that the decision to adopt modern technologies are significantly correlated, implying that univariate analysis of such decisions are biased, thereby, justifying use of the bivariate approach. Overall, the most dominant determinants are the positive influence of farming experience and the negative influence of remoteness of extension services on modern technology adoption. The per capita per day level of mean food produced is 12322.74 calories from one ha of land and food available for consumption is 4693.34 calories which is higher than the daily requirement of 2000 calories. Yam is produced mainly for sale while cassava is produced for consumption. Regression analysis shows that farm size and share of cassava in the total crop portfolio significantly increases food availability. A host of constraints are affecting Nigerian agriculture, which includes lack of extension agents, credit facilities, farm inputs, irrigation, and value addition and corruption, lack of support for ADP staff and ineffective government policies. Policy implications include investment in extension credit services and other infrastructure (e.g., irrigation, ADP staff), training of small farmers in business skills, promotion of modern technology, as a package as well as special projects targeted for cassava (e.g., Cassava Plus project) in order to boost modern technology adoption in food crops, as well as improving productivity, profitability and food availability at the farm-level in Nigeria.

The dissertation consists of three studies that seek to identify school caterer and women farmer constraints that have hindered the buy-local policy mandate of the Ghana School Lunch program, and to explore gendered agricultural technology adoption and contract participation strategies that could facilitate the policy mandate. The first study documents the constraints that have minimized caterer purchases of school food items from local farmers. The study presents an overview of the Ghana School Lunch Program and the buy-local policy mandate issued to school caterers. Survey data and descriptive analysis are employed to document and discuss the constraints that prevent school caters from purchasing from local farmers as well as the constraints faced by smallholder women farmers in supplying to school caters. The study subsequently discusses school caterers’ compensating variation of a hypothetical policy that requires them to firstly provide recommended portions of vegetables and protein, and secondly include fruits in the lunch of the schoolchildren. The second study analyses the factors underlying the probability that women smallholder farmers - compared to male farmers - adopt less a) improved seeds, b) fertilizer, c) herbicides and d) pesticides. The study further examines the sensitivity of gender differences in technology adoption to crop choice, particularly maize and legume, as well as the possible heterogeneity of technology adoption differences within rural and peri-urban communities. The adoption of these improved technologies is modeled using multivariate probit regressions. A gender gap is observed among legume farmers for improved seed and pesticide adoption. Moreover, the findings indicate that female maize farmers who have input into all cash crop production decisions are more likely to adopt improved seeds and pesticides. Among legume farmers, the results indicate that female farmers who are educated and have access to credit are more likely to adopt fertilizer, while female legume farmers who have a say in what the use of income generated from cash crop farming are more likely to adopt pesticides. These results imply that policy-makers and development practitioners in sub-Saharan Africa should consider strategies to target and increase educational, financial and productive assets of female farmers in order to close the gender technology gap and increase multiple technology adoption. The third study examines the use of farm-to-school contracts as a means to provide access to credit for women farmers in rural and peri-urban areas and facilitate the buy-local policy mandate. In particular, the study examines the factors influencing male and female smallholder farmers’ minimum willingness to accept (WTA) farm-to-school-lunch contracts for maize and cowpea beans. The minimum WTA simultaneously measures the decision to participate as well as the minimum price at which the smallholder farmer accepts the contract. Using sex-disaggregated data from a field experiment, a Tobit model is applied to explain the underlying factors influencing male and female smallholder farmer’s minimum WTA for a set of hypothetical maize and cowpea beans contracts. The results for the pooled sample indicate that the delivery at harvest option increases farmers’ minimum willingness to accept both the maize and beans contracts. The study further examines heterogeneity in the minimum WTA among smallholder farmers. The results in the female specification indicate that, the advance pay option lowers the minimum WTA for maize contracts. Additionally, women farmers who own non-farm business, compared to a male with a non-farm business, have a lower minimum WTA for the maize and beans contracts. The results suggest that if the government considers contractual arrangements between school caterers and local farmers to facilitate the buy-local policy mandate, an advance pay option to women farmers may yield lower premiums for contracted food items.

This exploratory study assessed attitudes and perceptions of smallholder farmers towards agricultural technologies in Kakamega County, Kenya. Through a mixed-methods sequential design, the study evaluated the key variables predicting farmer adoption of agricultural innovations. While social sciences provide a clear human-driven pattern explaining the process of choices and behaviors regarding technology use, there is still little clarity on the influences of adoption decisions among smallholder farmers in rural Kenya. Using the diffusion of innovations theory, the study explored the attitudes and perceptions of smallholder farmers toward technology adoption in seven sub-counties of Kakamega County (Lurambi, Ikolomani, Shinyalu, Mumias East (Shianda), Malava Butere, and Khwisero). The study design utilized a quantitative survey of 245 smallholder heads of households, followed by focus group discussions to further probe attitudes, values and practices that could influence technology adoption. The survey questionnaire tested two hypotheses: (H1) socio-demographic characteristics are related to agricultural technology adoption; and, (H2) farmer access to extension services was related to agricultural technology adoption. A binary logistic regression model was used to quantitatively estimate socio-demographic variables presumed to influence the adoption of agricultural innovations. Subsequently, four informal focus group discussions of 28 discussants was conducted across representative sub-counties (Lurambi, Shianda, Malava and Ikolomani), to elicit an in-depth understanding of farmers’ perspectives on technology adoption. The focus group participants included farmers recruited from among survey participants. The qualitative research instrument sought to answer three questions, (RQ1) what are farmer attitudes and perceptions towards agricultural technologies; (RQ2) what socio-cultural values influence farmers’ choice of agricultural technologies; and, (RQ3) what sources do farmers use for obtaining information on agricultural technology? Quantitative results included a principal component analysis (PCA) in which 14 attitudes questions were reduced to five conceptual clusters. These clusters included: challenges in accessing modern agricultural technologies (explained 19.09% of the total variance); effectiveness of agricultural technologies (11.88%); enjoyment of agricultural technologies (10.02%); social influence in use of technology (9.47%); and experience with agricultural technologies (8.13%). A logistic regression model indicated that independently age (.07), education (.10), and off-farm income (.08) were significantly associated with adoption of technology at the 90% confidence level when controlling for all other variables in the model. However, agricultural extension (.42) was not a significant predictor of agricultural technology adoption in this model. Qualitative results provided rich insights which enhanced findings from the survey data. Key insights in the thematic analysis included: farmers’ ambivalence about agricultural technologies; lack of trust in agricultural agents; low levels of agricultural technology knowledge; extension services as the main source of information dissemination to farmers; predominance of gender in determining agricultural technology adoption; and gender inequity in agricultural decision-making. In conclusion, the study results suggested that a mixed-methods approach was valuable in probing the nuances of farmers’ perceptions of agricultural extension and technology adoption among smallholder farmers. The results supported the following recommendations: the agricultural extension efforts could be more effectively structured in order to support the dissemination of agricultural information; the issue of gender should be adequately addressed by engaging male and female in collaborative agricultural efforts to help break the barrier of gender inequity; and future research would benefit from disaggregating public and private extension services as a more robust method for determining their individual effects in the promotion of agricultural innovations among smallholder farmers.

<p>We followed up with about 2,000 smallholder households in Senegal, two years after these households participated in a randomized controlled trial (RCT) aimed at reducing levels of aflatoxins in smallholders’ stored maize. In the initial intervention, treated households were provided with training on proper post-harvest practices, low-cost moisture meters for testing if maize was sufficiently dry to store, plastic tarps for drying maize of the ground, and hermetic (airtight) storage bags to mitigate aflatoxin development in stored maize. Using cross-sectional follow up data on aflatoxins levels and drying and storage practices from 2019 along with baseline demographic data from 2016, we estimate both the longer-term intention-to-treat (ITT) effects and the treatment on the treated (TOT) effects that the four inputs provided on households’ aflatoxins levels in stored maize. The ITT analyses estimate the intervention’s average effect by treatment group, but this may underestimate the true impact for households who complied with recommended post-harvest practices and adopted the recommended technologies. The TOT analyses estimate the local average treatment effects (LATE) of the intervention, that is its impacts on those who were driven by the intervention to follow best practices or use a given technology. Since the decision to follow these practices or adopt a technology was not random, we instrumented the usage decision with the exogenous, random treatment group assignment to get an unbiased estimate. Outside of our main models, we conducted a heterogeneity analysis to test if households with different characteristics benefit differently from the intervention. We interacted each treatment assignment with various household characteristics, including the woman’s level of involvement in the intervention. Additionally, we estimate the cost-effectiveness of providing training and a tarp, according to WHO guidelines for public health interventions. </p>