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Background: Agriculture is important for economic growth and development in many countries in Sub-Saharan Africa, including Tanzania. However, agricultural production and productivity remain relatively low, with significant yield gaps attributed to factors such as limited access to and low adoption of appropriate agricultural technologies, and climate-related risks resulting from climate variability and change. This paper explores the drivers of adoption of climate-smart agricultural (CSA) technologies and practices, taking into account the complementarity among agricultural technologies and heterogeneity of the farm households, using data from Lushoto in Tanzania. Methods: We use a Multivariate Probit analysis of cross-sectional data collected from 264 smallholder farmers in Lushoto—a climate hotspot in Tanzania—to understand the drivers of household decisions to adopt CSA technologies and practices. The technologies included diversification of multiple stress (drought, floods, pests, diseases)-tolerant crop varieties, use of fertilizers, and application of herbicides and pesticides. The Multivariate Probit model was preferred as it takes into account the inter-relationships of the technologies as well as heterogeneity of the smallholder farmers for more robust estimates. The independent variables used in the analysis included household socio-economic factors such as the relative importance of crop and livestock enterprises, household land size, social capital, access to agricultural credit and weather information, previous experience with fertilizer use and household characteristics (age, education and gender of household head, and household size). Results: About 63% of the households diversified their crop enterprises, shifting to improved resilient crops and crop varieties. Another 37% adopted fertilizers, while 38% applied pesticides and herbicides. Conditional on the unobservable heterogeneity effects, the results show that household adoption decisions on diversification of multiple stress-tolerant crops and crop varieties, fertilizer, and pesticides and herbicides are complementary. In addition, the results confirm existence of unobserved heterogeneity effects leading to varying impact of the explanatory variables on adoption decisions among farmers with similar observable characteristics. Conclusions: The findings indicate that any effective CSA technology adoption and diffusion strategies and policies should take into account the complementarity of the technologies and heterogeneity of the smallholder farmers. Therefore, inter-related technologies should be promoted as a package or bundled while taking into consideration household and farm-level constraints to adoption. [ABSTRACT FROM AUTHOR]

Abstract: Soil fertility depletion is considered one of the main biophysical limiting factors for increasing per capita food production for smallholder farmers in Sub-Saharan Africa. The adoption and diffusion of sustainable agricultural practices (SAPs), as a way to tackle this challenge, has become an important issue in the development policy agenda in the region. This paper examines the adoption decisions for SAPs, using recent primary data of multiple plot-level observations collected in 4 districts and 60 villages of rural Tanzania. The paper employs a multivariate probit technique to model simultaneous interdependent adoption decisions by farm households. The analysis reveals that rainfall, insects and disease shocks, government effectiveness in provision of extension services, tenure status of plot, social capital, plot location and size, and household assets, all influence farmer investment in SAPs. Policies that target SAPs and are aimed at organizing farmers into associations, improving land tenure security, and enhancing skills of civil servants can increase uptake of SAPs in smallholder systems. [Copyright &y& Elsevier]

This study analyzes the factors that influence the probability and extent of the adoption of mungbean production technologies in Tanzania, Kenya and Uganda, using multivariate probit and Poisson regression models. The results show that the probability and extent of the adoption of mungbean production technologies are influenced by gender of the household, household size, farm size, livestock size, household assets, access to extension services and access to credit. The study suggests that policy interventions that aimed at targeting women farmers, increasing household asset and information dissemination, such as field demonstrations and training programs, are crucial in enhancing technology adoption among smallholder farmers. [ABSTRACT FROM AUTHOR]