Sustainable intensification (SI) is promoted as a rural development paradigm for sub-Saharan Africa. Achieving SI requires smallholder farmers to have access to information that is context-specific, increases their decision-making capacities, and adapts to changing environments. Current extension services often struggle to address these needs. New mobile phone-based services can help. In order to enhance the public extension service in Tanzania, we created a digital service that addresses smallholder farmers' different information needs for implementing SI. Using a co-design methodology-User-Centered Designwe elicited feedback from farmers and extension agents in Tanzania to create a new digital information service, called Ushauri. This automated hotline gives farmers access to a set of prerecorded messages. Additionally, farmers can ask questions in a mailbox. Extension agents then listen to these questions through an online platform, where they record and send replies via automated push-calls. A test with 97 farmers in Tanzania showed that farmers actively engaged with the service to access agricultural advice. Extension agents were able to answer questions with reduced workload compared to conventional communication channels. This study illustrates how User-Centered Design can be used to develop information services for complex and resource-restricted smallholder farming contexts.

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the Rural Household Multiple Indicator Survey (RHoMIS) is a standardized farm household survey approach which collects information on 758 variables covering household demographics, farm area, crops grown and their production, livestock holdings and their production, agricultural product use and variables underlying standard socioeconomic and food security indicators such as the Probability of Poverty Index, the Household Food Insecurity access Scale, and household dietary diversity. these variables are used to quantify more than 40 different indicators on farm and household characteristics, welfare, productivity, and economic performance. Between 2015 and the beginning of 2018, the survey instrument was applied in 21 countries in Central America, sub-Saharan Africa and Asia. The data presented here include the raw survey response data, the indicator calculation code, and the resulting indicator values. These data can be used to quantify on-and off-farm pathways to food security, diverse diets, and changes in poverty for rural smallholder farm households.

Groundnut ( Arachis hypogaea L.) is a multi-purpose legume serving millions of farmers and their value chain actors globally. Use of old poor-performing cultivars contributes to low yields (< 1 t/ha) of groundnut in sub-Saharan Africa including Tanzania. The objectives of this study were to determine the extent of genetic variation among diverse groundnut collections using phenotypic traits and simple sequence repeat (SSR) markers to select distinct and complementary genotypes for breeding. One hundred and nineteen genotypes were evaluated under field conditions for agronomic traits and susceptibility to rust and leaf spot diseases. The study was conducted in two locations across two seasons. In addition, the 119 accessions were profiled with 13 selected SSR markers. Genotype and genotype by environment interaction effects were significant ( p < 0.05) for days to flowering (DTF), late leaf spot score at 85 and 100 days after planting, pod yield (PDY), kernel yield (KY), hundred seed weight (HSW) and shelling percentage (SP). Principal components analysis revealed that plant stand, KY, SP, NPP (number of pods per plant), late leaf spot and rust disease scores accounted for the largest proportion of the total variation (71.9%) among the tested genotypes. Genotypes ICGV-SM 08587 and ICGV-SM 16579 had the most stable yields across the test environments. Moderate genetic variation was recorded with mean polymorphic information content of 0.34 and gene diversity of 0.63 using the SSR markers. The majority (74%) of genotypes showed high membership coefficients to their respective sub-populations, while 26% were admixtures after structure analysis. Much of the variation (69%) was found within populations due to genotypic differences. The present study identified genotypes ICGV-SM 06737, ICGV-SM 16575, ICG 12725 and ICGV-SM 16608 to be used for development of mapping population, which will be useful for groundnut improvement. This study provided a baseline information on characterization and selection of a large sample of groundnut genotypes in Tanzania for effective breeding and systematic conservation. Electronic supplementary material The online version of this article (10.1007/s10722-020-01007-1) contains supplementary material, which is available to authorized users.