The dairy industry has great potential to improve living standards for the poor in Tanzania and more so for smallholder farmers who account for the largest share of milk consumed nationally.

This study examines women’s empowerment and its determinants for smallholder rice farming households in Kilombero, Tanzania. The Women Empowerment in Agriculture Index (WEAI) is adopted and for the study site, the overall WEAI was 0.54 with a 5 Domains Empowerment sub-index value of 0.50 and the Gender Parity sub-index of 0.86.

This study established the level of technical efficiency and its determinants among the informal and formal seed potato producers in the southwestern highlands agro - ecological zone of Uganda.

The study examines factors that influence the adoption of improved post-harvest storage technologies (IPHSTs) by smallholder maize farmers in Tanzania. The study employed a sample of 1620 observations from the National Panel Survey (NPS). Descriptive statistics indicated that 9 percent of the farmers experienced PHL and an average of 115 kilograms of maize per household is lost in various stages of post-harvest chain. Only 19 percent of farmers adopted IPHSTs.

The adoption of improved agricultural technologies is very low in Tanzania, which has led to both low crop productivity and low production. This paper therefore analyses the factors that influence the adoption of improved seeds, inorganic fertilisers and a package of technologies by smallholder maize farmers in Tanzania using the national panel survey (NPS) data collected in three waves: 2008/2009, 2010/2011 and 2012/2013, with a sample size of 1 551 maize-farming households used for analysis.

The adoption of improved agricultural technologies is very low in Tanzania, which has led to both low crop productivity and low production. This paper therefore analyses the factors that influence the adoption of improved seeds, inorganic fertilisers and a package of technologies by smallholder maize farmers in Tanzania using the national panel survey (NPS) data collected in three waves: 2008/2009, 2010/2011 and 2012/2013, with a sample size of 1 551 maize-farming households used for analysis.

This paper examines the determinants of adoption of improved agricultural technologies among smallholder maize farmers in Tanzania. Specifically, it reports the findings of a study that employed a sample size of 1,839 smallholder maize farming households that participated in three consecutive waves of 2008 - 2009, 2010 - 2011, and 2012 - 2013 of the National Panel Survey (NPS). Multinomial probit model was used to examine the factors that influence maize producers to adopt inorganic fertilisers, improved seeds, and herbicides.

Pervasive threats of climate change and land degradation have compounded the inherent low farm productivity problem in sub‐Saharan Africa. Though sustainable agricultural intensification practices have been shown to improve the resilience of farm production in the face of these emerging threats, they suffer low adoption rates typical of any technology adoption in these regions. Recent evidence points to an emergence of large traders in smallholder grain markets of countries in sub‐Saharan Africa.

Climate forecasting is a crucial tool for managing risks in climate-sensitive economic sectors like agriculture. Although rainfed subsistence farming dominates livelihoods in Africa, information on access, integration in farm decisions and impact of improved seasonal climate forecasting remains scanty. This paper addresses this gap using representative data of 653 households across three regions in North-Central Namibia.

Smallholder farmers form the vast majority of rice producers in Tanzania. Nonetheless, smallholder production is known to exhibit inefficiency in production. This study sought to analyze the determinants of technical efficiency of production of smallholder rice farmers in Tanzania using the stochastic frontier method while ensuring theoretical consistency through monotonicity and quasi concavity checks. Results show that empowerment of the woman, gender, primary occupation, group membership of household head and fertilizer use by the household affect technical efficiency of production.