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CONTEXT Digital innovations can enhance the participation of often-marginalized social groups – including women and resource-poor farmers in low- and middle-income countries – in sustainable, profitable food systems. But digital interventions can also reinforce existing inequities by further increasing the competitive advantage of user groups privileged with literacy, access to smartphones, or high investment capacity. To ensure that the digital transformation in the Global South leaves no one behind, therefore, deliberate efforts are needed to promote the inclusivity of emerging digital innovations. To date, however, there is a lack of practical guidelines and tools to critically assess, demonstrate, and enhance the inclusivity of digital food systems interventions. Too often, inclusivity remains a blurry concept and distant objective. In result, digital development researchers and practitioners have limited incentives for investing time and effort into safeguarding inclusivity.

Rigorous experiments show that nutrition-sensitive intervention programs can contribute to improved food and nutrition security (FNS) of rural households in low-and middle-income countries. Targeted individuals may, however, choose to engage with the intervention package at different intensities. It is yet unclear to what extent individual participation in more interventions influences FNS outcomes. Positive links would justify efforts by development stakeholders to diversify intervention packages and enable, encourage, or incentivize beneficiaries to participate in many different interventions. Using cross-sectional data from 2733 households across seven countries, we first estimate effects of a multi-sectoral intervention program using probit regressions, propensity score matching, and inverse probability weighted regression adjustment. Over the course of the three-year program, beneficiaries joined 8.3 interventions, on average. We find that targeted households were 6–9 percent more likely to be food secure, and targeted women and children were 15–17 percent more likely to consume a nutrient-adequate diet. Our estimates show that, across three indicators of FNS, each additional intervention increased the probability of achieving positive outcomes by about 1 percent. We conclude that investments in diversified intervention programs can be justified by stronger FNS benefits. Development stakeholders could enable strong individual participation by reducing transaction and opportunity costs of participation., Peer Reviewed

To derive insights from data, researchers working on agricultural experiments need appropriate data management and analysis tools. To ensure that workflows are reproducible and can be applied on a routine basis, programmatic tools are needed. Such tools are increasingly necessary for rank-based data, a type of data that is generated in on-farm experimentation and data synthesis exercises, among others. To address this need, we developed the R package gosset, which provides functionality for rank-based data and models. The gosset package facilitates data preparation, modeling and results presentation stages. It introduces novel functions not available in existing R packages for analyzing ranking data. This paper demonstrates the package functionality using the case study of a decentralized on-farm trial of common bean (Phaseolus vulgaris L.) varieties in Nicaragua.

Rural areas of Madagascar face a tense food and nutrition security situation. The country reports some of the highest rates of undernourishment and malnutrition worldwide. Evidence is scant, however, about how the rural people’s diets vary over the course of the agricultural year, and how different household types deal with fluctuating food availability. This lack of detailed understanding of the food and nutrition security situation across time and social strata currently limits development stakeholders’ ability to tailor interventions to local needs. Using randomly sampled survey data from Farafangana District in south-eastern Madagascar, this study analyzes rural households’ diets across three time points within one year (minor lean period, major lean period, main post-harvest period). In addition, anthropometric data on children aged 6–59 months were collected during the major lean period to determine levels of chronic and acute child malnutrition. Overall, food insecurity stood at high levels at all times, but with substantial variation across the year. Shortly before the main rice harvest, the prevalence of moderate and severe food insecurity was 78%, twice as high as shortly after harvest. With 57% of children stunted and a 17% prevalence of wasting, the observed levels of chronic and acute child malnutrition exceed levels reported previously. By studying what households eat and how they source it (own production vs. purchases), we found distinct patterns of food acquisition between the three periods. Diminishing food security is reflected by substituting rice by cassava, unripe jackfruit (minor lean period), and local tuber tavolo (major lean period), as well as by lower diversity of side dishes. Our results underline the need for long-term agricultural development strategies that contribute to greater household food self-sufficiency especially during the lean periods. But the alarming level of acute child malnutrition also calls for more immediate humanita, Peer Reviewed

This publication is with permission of the rights owner (Sage) freely accessible., This study investigates the impacts of the first wave of the COVID-19 pandemic on smallholder farmers and their coping strategies in three contrasting Low- and Middle-Income Countries. The case studies include Brazil (South region), Madagascar (Atsimo Atsinanana region), and Tanzania (Morogoro/Eastern Tanzania). These countries were chosen because i) the economies are strongly influenced by the agricultural sector; ii) their national food security is strongly affected by smallholder production, and, iii) they represent a set of contrasting government responses to COVID-19 including the denial of the pandemic. Data were collected through semi-structured household interviews in all three countries in rural areas. COVID-19 induced effects were found in all three countries, including in Brazil and Tanzania where both national governments initially neglected the existence of COVID-19 and introduced few containment measures only. Here, mobility and trade restrictions of other countries impact also on agricultural trade and production in countries in which governments took less action to COVID-19 and also people remained home and practiced social distancing even if no official government policy was issued. The findings in all three countries suggest that the COVID-19 crisis had negatively affected smallholders’ agricultural production, leading to a vicious cycle of low production, low incomes, and higher food insecurity. Results of this study raise the thorny issue of how best to balance containment of pandemic and future shocks against the well-being of the vulnerable rural population in lower- and middle-income countries; especially considering also the degree of global interconnected and the potential of polices to effect people beyond the national scale., German Leibniz Research Alliance 'Crises in a Globalized World', Peer Reviewed

Location-specific information is required to support decision making in crop variety management, especially under increasingly challenging climate conditions. Data synthesis can aggregate data from individual trials to produce information that supports decision making in plant breeding programs, extension services, and of farmers. Data from on-farm trials using the novel approach of triadic comparison of technologies (tricot) are increasingly available, from which more insights could be gained using a data synthesis approach. The objective of our study was to present the applicability of a rank-based data synthesis approach to several datasets from tricot trials to generate location-specific information supporting decision making in crop variety management. Our study focuses on tricot data from 14 trials of common bean (Phaseolus vulgaris L.) performed between 2015 and 2018 across four countries in Central America (Costa Rica, El Salvador, Honduras, and Nicaragua). The combined data of 17 common bean genotypes were rank aggregated and analyzed with the Plackett–Luce model. Model-based recursive partitioning was used to assess the influence of spatially explicit environmental covariates on the performance of common bean genotypes. Location-specific performance was predicted for the three main growing seasons in Central America. We demonstrate how the rank-based data synthesis methodology allows integrating tricot trial data from heterogenous sources to provide location-specific information to support decision making in crop variety management. Maps of genotype performance can support decision making in crop variety evaluation such as variety recommendations to farmers and variety release processes.

Background Severe food and nutrition insecurity persists in Madagascar. The Atsimo Atsinanana region is among the most affected areas due to elevated poverty rates and low levels of resilience to frequent shocks. Implementing food and nutrition security (FNS) interventions could help to improve this situation, but to be effective and sustainable, intervention packages must fit the local context. Objectives To identify locally suitable options, this study assessed the perceptions of local communities in rural Atsimo Atsinanana toward a range of FNS intervention options. Methods We held 12 gender-disaggregated workshops with 80 prospective beneficiaries of an FNS project, from inland and coastal parts of the region. Preferences were elicited for 14 potential FNS interventions. Next, through participatory ex ante impact assessment, participants ranked 8 impact criteria and individually estimated expected impacts of all intervention options on these criteria. Results Overall, participants preferred interventions targeting on-farm crop, vegetable, and livestock production. Income and food self-sufficiency were ranked as the highest intervention priorities. However, intervention preferences differed by gender and geographic location. Whereas preferences for interventions targeting dietary habits were weak across genders, women had relatively stronger preferences for these interventions than men. This shows that collecting gender-disaggregated preferences can enable more gender-sensitive choice of interventions. Preferences also reflected local livelihoods, as more market-oriented coastal sites showed stronger interest in income generation than more subsistence-oriented inland sites. The ex ante impact assessments highlight positive and negative expectations for most interventions, with increased labor burden being the most prominent negative impact overall. Conclusions The findings suggest that participatory, multidimensional impact assessments before project implementati, Peer Reviewed