Evaluating rural household well-being and empowerment among women and young farmers in Senegal.

This article provides a description of baseline survey data that was collected in Senegal in the regions of Sedhiou and Tambacounda in 2020, respectively, and as part of an agricultural development project aimed at improving the well-being and resilience of farming households. The survey was implemented using a structured questionnaire administered among 1503 households, 70% of whom are women and 30% are young people, in the two regions. This paper contains data that can helps in understanding the socioeconomic well-being and resilience of smallholder farming households, especially among women and youth. This data helps to associate information on: (i) the socioeconomic project area variables, (ii) the extent of use of irrigated and climate change-adapted crops; (iii) the level of soil and water resource management in the study regions; and (iv) the food security and dietary diversity with the well-being and empowerment of women and young smallholder farming households. In addition, the dataset can be used as a baseline or reference point to track the economic empowerment and climate resilience building achieved in the study regions.

A scalable approach to improve CSA targeting practices among smallholder farmers.

With climate change, population growth, and land degradation exerting mounting pressures on agricultural systems in developing countries, climate-smart agriculture (CSA) strategies have been prioritized as a means to strengthen smallholder farmers' resilience. However, precise targeting methodologies remain a challenge. This study employs a comprehensive approach, integrating Socio-economic, and Biophysical (SEBP), and the Five Capitals Model analyses encompassing human, social, physical, natural, and financial capital. The study employs factor analysis for mixed data (FAMD), cluster analysis using partitioning around the medoids (PAM) and univariate and bivariate techniques to identify and classify distinct typologies of smallholder farming systems in Senegal's Tambacounda and Sedhiou regions in 2020. A probit regression model gauges CSA adoption probability, to better focus CSA efforts. Results underscore the pivotal role of SEBP factors in shaping distinct farmer typologies, enabling precise CSA targeting. Geographical distribution patterns of these typologies reveal non-random clustering, particularly in specific regions. Four farmer typologies emerge: Cluster 1 (Sedhiou, low-income, high climate challenges), Cluster 2 (Sedhiou and Tambacounda, low-to middle-income, moderate climatic challenges), Cluster 3 (Tambacounda, high income, favorable climate), and Cluster 4 (Tambacounda, low income, severe climate challenges). Technology mismatches emerge between farmers' SEBP profiles and capital assets, prompting the identification of relevant technologies for soil fertility restoration and increased output. These findings highlight the importance of implementing CSAs in accordance with specific requirements, such as enhancing soil fertility, yield, and nutritional quality. A contextual understanding of local agricultural dynamics is likewise necessary for optimizing intervention strategies, according to the study.

Survey-based data on food security, nutrition and agricultural production shocks among rural farming households in northern Uganda.

Climate change, degradation of natural resources, conflict or civil war, diseases and poverty are among the key threats that impact agriculture, human nutrition, food security and food safety among rural households in developing countries. Sustainability of food systems and livelihoods will thus crucially depend on not only the ability to accommodate or recover from these threats but also to tap into opportunities for strengthening long-term capabilities. One approach to enhancing resilience to enhance food security and nutrition is building an evidence base to better understand the various types of smallholders, threats to agriculture production and the associated risks to food security and nutrition and household food preferences. Unfortunately, such data in many African countries is still unavailable or has not been shared publicly. In this paper, we describe data that were collected in Nwoya district, Northern Uganda in December 2017. These data can be used to assess the relationship between resilience of farm households to climatic risks and their food and nutrition security.

GeoFarmer: A monitoring and feedback system for agricultural development projects.

Farmers can manage their crops and farms better if they can communicate their experiences, both positive and negative, with each other and with experts. Digital agriculture using internet communication technology (ICT) may facilitate the sharing of experiences between farmers themselves and with experts and others interested in agriculture. ICT approaches in agriculture are, however, still out of the reach of many farmers. The reasons are lack of connectivity, missing capacity building and poor usability of ICT applications. We decided to tackle this problem through cost-effective, easy to use ICT approaches, based on infrastructure and services currently available to small-scale producers in developing areas. Working through a participatory design approach, we developed and tested a novel technology. GeoFarmer provides near real-time, two-way data flows that support processes of co-innovation in agricultural development projects. It can be used as a cost-effective ICT-based platform to monitor agricultural production systems with interactive feedback between the users, within pre-defined geographical domains. We tested GeoFarmer in four geographic domains associated with ongoing agricultural development projects in East and West Africa and Latin America. We demonstrate that GeoFarmer is a cost-effective means of providing and sharing opportune indicators of on-farm performance. It is a potentially useful tool that farmers and agricultural practitioners can use to manage their crops and farms better, reduce risk, increase productivity and improve their livelihoods.

Survey data of intra-household decision making and smallholder agricultural production in Northern Uganda and Southern Tanzania.

This article provides a description of intra-household survey data that were collected in Uganda and Tanzania in 2014 and 2015, respectively. The surveys were implemented using a structured questionnaire administered among 585 households in Uganda and 608 in Tanzania. Information on decision making processes in agricultural production was collected from the principal adult male and female decision-makers in each household. The survey consisted of two parts. Firstly, the decision-makers, both male and female of each household were jointly interviewed. Secondly, individual interviews were carried out, questioning the decision-makers separately. The datasets include both household and individual level data containing numeric, categorical and string variables. The datasets have been shared publicly on the Harvard dataverse.