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Women's empowerment has been promoted by researchers and development practitioners as one of the most promising strategies to address widespread hunger and malnutrition. However, the relationship between women's empowerment and dietary diversity and child nutrition has rarely been studied among vulnerable populations or individuals at greater risk of poor physical and social health status. Moreover, the effects of different domains of women's empowerment on nutritional outcomes, including dietary diversity and child anthropometry, have rarely been examined, especially with panel data. Using two rounds of panel data from 1900 households and fixed effects regression models, we analyze the effect of women's empowerment on household dietary diversity score (HDDS) and child anthropometry among the particularly vulnerable tribal groups in Odisha, India. We also estimate the effects of various decision-making domains of women's empowerment on HDDS and child anthropometry to understand which empowerment domains matter for nutrition. Results show that women's empowerment is positively associated with HDDS (coef. 0.41 food groups; p < 0.1) and reduces the prevalence of underweight (coef. 39%; p < 0.05) and wasting (coef. 56%; p < 0.1) in children but has no effect on the prevalence of child stunting. Women's empowerment in agricultural input use; output sales; income; food purchases; and credit, group membership, and employment contribute to improved dietary diversity and child nutrition. We conclude that women's empowerment contributes to improved dietary diversity and child nutrition and is a promising strategy to improve farm household diets and child nutrition among vulnerable populations. Strengthening women's empowerment through the promotion of women's access to land and other agricultural inputs, market participation, access to information, capital, and credit is important., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ogutu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In Asia, cassava ( Manihot esculenta ) is cultivated by more than 8 million farmers, driving the rural economy of many countries. The International Center for Tropical Agriculture (CIAT), in partnership with national agricultural research institutes (NARIs), instigated breeding and agronomic research in Asia, 1983. The breeding program has successfully released high-yielding cultivars resulting in an average yield increase from 13.0 t ha -1 in 1996 to 21.3 t ha -1 in 2016, with significant economic benefits. Following the success in increasing yields, cassava breeding has turned its focus to higher-value traits, such as waxy cassava, to reach new market niches. More recently, building resistance to invasive pests and diseases has become a top priority due to the emergent threat of cassava mosaic disease (CMD). The agronomic research involves driving profitability with advanced technologies focusing on better agronomic management practices thereby maintaining sustainable production systems. Remote sensing technologies are being tested for trait discovery and large-scale field evaluation of cassava. In summary, cassava breeding in Asia is driven by a combination of food and market demand with technological innovations to increase the productivity. Further, exploration in the potential of data-driven agriculture is needed to empower researchers and producers for sustainable advancement., (Copyright © 2020 by JAPANESE SOCIETY OF BREEDING.)

It is widely recognized that increasing agricultural production to the levels needed to feed an expanding world population requires sharply increased public investment in research and development and widespread adoption of new technologies, but funding for national and international agricultural research has rather declined in recent years. In this situation, priority setting has become increasingly important for allocating scarce research resources among competing needs to achieve greater impacts. Using partial equilibrium economic surplus models and poverty impact simulations, this paper assesses cassava research priorities in Africa, Latin America and Caribbean, and Asia based on the potential economic and poverty reduction impacts of alternative research and technology options. The results showed that efficient planting material production and distribution systems and sustainable crop and soil fertility management practices have the greatest expected economic and poverty reduction impacts in the three regions. Lack of clean planting materials is a major constraint to adoption and it is envisaged that efficient production and distribution systems for planting material can accelerate technology adoption by farmers. Similarly, sustainable crop and soil fertility management practices play a key role in closing the observed yield gaps, especially in Africa. The paper discusses the results of the priority assessment for key cassava research options and concludes with the implications for cassava research priorities., Competing Interests: The authors have declared that no competing interests exist.

This article provides a description of an agricultural household survey data of rice growers collected in Ecuador between October 2014 and March 2015. The household survey was implemented using a structured questionnaire administered among 1028 households in the main rice production areas of Ecuador (i.e. Guayas, Los Rios, Manabi, and El Oro provinces). Information collected was provided by household heads (male or female) and included household and plot level data. The survey information includes household socio-demographic characteristics (e.g. age, education, gender, main economic activity, etc.), farm characteristics (e.g. farm land size, assets ownership, other crops planted, etc.), rice management practices (e.g. variety and input use, production costs, etc.), and rice production and utilization (e.g. yields, prices, sales, etc.). Additional socio-economic context variables were also recorded such as government subsidies to rice production, participation in rural organizations, and food security related questions. The dataset contains a total of 6288 variables among numeric, categorical and string variables. The dataset is shared publicly on the Harvard dataverse site and provide access to questionnaires, the complete data and a brief report.