Graduation model interventions seek to address multiple barriers constraining households’ exit from poverty, however, few explicitly target unequal gender norms. Using a randomized control trial design, combined with three rounds of data, we investigate the impacts on gender equitable attitudes and behaviors of a graduation program that seeks to simultaneously “push” households out of poverty and improve unequal gender norms in Ethiopia.

ICTforAg is an annual convening where agricultural stakeholders and technology experts come together to share knowledge, find solutions, and form partnerships to address challenges in agri-food systems across low- and middle-income countries. The main goal of ICTforAg is to grow communities and catalyze meaningful conversations, insights, and collaborations, increase participation of participants from the developing world, promote knowledge sharing and learning, and inspire practitioners to develop inclusive and sustainable ICT solutions.

Improving plant performance in salinity-prone conditions is a significant challenge in breeding programs. Genomic selection is currently integrated into many plant breeding programs as a tool for increasing selection intensity and precision for complex traits and for reducing breeding cycle length. A rice reference panel (RP) of 241 Oryza sativa L. japonica accessions genotyped with 20,255 SNPs grown in control and mild salinity stress conditions was evaluated at the vegetative stage for eight morphological traits and ion mass fractions (Na and K).

Field experiments were conducted in two different agroecological locations of Ibadan and Ikenne in Nigeria from August through December during the 2019 and 2020 cropping seasons. The studies were set up to reduce reliance on inorganic nitrogen fertilizer and to embrace the use of nitrogen-fixing bacteria to improve legume production to increase farmers' output and profitability. Ten accessions of the Bambara groundnut (BGN) were used in the trials. Seeds of each BGN accession were coated with each of the following Bradyrhizobium japonicum strains (B.

The cassava whitefly Bemisia tabaci causes damage in cassava through the feeding and vectoring of plant viruses that cause cassava mosaic and cassava brown streak diseases. This study sought to explore the efficacy of cutting dipping in flupyradifurone for whitefly control and the impact of the mode of application on whitefly parasitism under farmer field conditions. The insecticide treatment significantly reduced adult whiteflies by 41%, nymphs by 64%, and cassava mosaic disease (CMD) incidence by 16% and increased root yield by 49%. The whitefly parasitism rate by Encarsia spp.

Climate change is resulting in increased frequency of extreme weather events, especially in low- and middle-income countries (LMICs) already characterized by highly vulnerable malnourished populations. Unsurprisingly, there are many empirical studies of the linkages between extreme weather events and undernutrition, especially stunting and wasting in early childhood, and several existing reviews of this literature.

The quest to transform and hasten the role of smallholder farms in agricultural development and food security through farmer firm linkages has dominated development interventions in low-income countries for several decades. This has mostly been pursued through single- or multi-contract schemes implemented in isolation. Several studies have analyzed the efects of these schemes on smallholder farms with mixed results. A new paradigm is to use Agricultural Public Private Partnership (Ag-PPP) to achieve wider and sustainable impacts.

Climate change-induced heat stress combines two challenges: high day- and nighttime temperatures, and physiological water deficit due to demand-side drought caused by increase in vapor-pressure deficit. It is one of the major factors in low productivity of maize in rainfed stress-prone environments in South Asia, affecting a large population of smallholder farmers who depend on maize for their sustenance and livelihoods.

Banana Xanthomonas wilt (BXW) is a destructive disease caused by Xanthomonas vasicola pv. musacearum (Xvm) bacterium that indiscriminately infects all banana varieties grown in East and Central Africa (ECA). In this region, BXW was first reported in 2001 in Uganda and was projected to eliminate >90% of Uganda’s bananas worth US$4 billion if not controlled in less than 10 years. Lack of basic information led to application of control approaches that were based on similarity of BXW symptoms to those of Moko disease of bananas.

Context
Collection and analysis of large volumes of on-farm production data are widely seen as key to understanding yield variability among farmers and improving resource-use efficiency.
Objective
The aim of this study was to assess the performance of statistical and machine learning methods to explain and predict crop yield across thousands of farmers’ fields in contrasting farming systems worldwide.
Methods