ClimMob: Software to support experimental citizen science in agriculture.

Experimental citizen science offers new ways to organize on-farm testing of crop varieties and other agronomic options. Its implementation at scale requires software that streamlines the process of experimental design, data collection and analysis, so that different organizations can support trials. This article considers ClimMob software developed to facilitate implementing experimental citizen science in agriculture. We describe the software design process, including our initial design choices, the architecture and functionality of ClimMob, and the methodology used for incorporating user feedback. Initial design choices were guided by the need to shape a workflow that is feasible for farmers and relevant for farmers, breeders and other decision-makers. Workflow and software concepts were developed concurrently. The resulting approach supported by ClimMob is triadic comparisons of technology options (tricot), which allows farmers to make simple comparisons between crop varieties or other agricultural technologies tested on farms. The software was built using Component-Based Software Engineering (CBSE), to allow for a flexible, modular design of software that is easy to maintain. Source is open-source and built on existing components that generally have a broad user community, to ensure their continuity in the future. Key components include Open Data Kit, ODK Tools, PyUtilib Component Architecture. The design of experiments and data analysis is done through R packages, which are all available on CRAN. Constant user feedback and short communication lines between the development teams and users was crucial in the development process. Development will continue to further improve user experience, expand data collection methods and media channels, ensure integration with other systems, and to further improve the support for data-driven decision-making.

The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective.

Matching crop varieties to their target use context and user preferences is a challenge faced by many plant breeding programs serving smallholder agriculture. Numerous participatory approaches proposed by CGIAR and other research teams over the last four decades have attempted to capture farmers' priorities/preferences and crop variety field performance in representative growing environments through experimental trials with higher external validity. Yet none have overcome the challenges of scalability, data validity and reliability, and difficulties in capturing socio-economic and environmental heterogeneity. Building on the strengths of these attempts, we developed a new data-generation approach, called triadic comparison of technology options (tricot). Tricot is a decentralized experimental approach supported by crowdsourced citizen science. In this article, we review the development, validation, and evolution of the tricot approach, through our own research results and reviewing the literature in which tricot approaches have been successfully applied. The first results indicated that tricot-aggregated farmer-led assessments contained information with adequate validity and that reliability could be achieved with a large sample. Costs were lower than current participatory approaches. Scaling the tricot approach into a large on-farm testing network successfully registered specific climatic effects of crop variety performance in representative growing environments. Tricot's recent application in plant breeding networks in relation to decision-making has (i) advanced plant breeding lines recognizing socio-economic heterogeneity, and (ii) identified consumers' preferences and market demands, generating alternative breeding design priorities. We review lessons learned from tricot applications that have enabled a large scaling effort, which should lead to stronger decision-making in crop improvement and increased use of improved varieties in smallholder agriculture.

Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products.

This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.

Climate-Related Risk Modeling of Banana Xanthomonas Wilt Disease Incidence in the Cropland Area of Rwanda.

Banana Xanthomonas wilt (BXW) is a major threat to banana production in Rwanda, causing up to 100% yield loss. There are no biological or chemical control measures, and little is known about the potential direction and magnitude of its spread; hence, cultural control efforts are reactive rather than proactive. In this study, we assessed BXW risk under current and projected climates to guide early warning and control by applying the maximum entropy (Maxent) model on 1,022 georeferenced BXW datapoints and 20 environmental variables. We evaluated the significance of variables and mapped potential risk under current and future climates to assess spatial dynamics of the disease distribution. BXW occurrence was reliably predicted (mean validation AUC values ranging from 0.79 to 0.85). Precipitation of the coldest quarter, average maximum monthly temperature, annual precipitation, and elevation were the strongest predictors, which were responsible for 22.1, 13, 12.6, and 9.4% of the observed incidence variability, respectively, while mean temperature of the coldest quarter had the highest gain in isolation. Furthermore, the most susceptible regions (western, northern, and southern Rwanda) were characterized by elevation (1,350 to 2,000 m), annual precipitation (900 to 1,700 mm), and average temperature (14 to 20°C), among other variables, suggesting that a consistent, rainy, and warm climate is more favorable for BXW spread. Under the future climate, the risk was predicted to increase and spread to other regions. We conclude that climate change will likely exacerbate BXW-related losses of banana land area and yield under the influence of temperature and moisture. Our findings support evidence-based targeting of extension service delivery to farmers and national early warning for timely action.

Life cycle assessment of animal-based foods and plant-based protein-rich alternatives: an environmental perspective.

BACKGROUND: In the European Union proteins for food are largely animal based, consisting of meat and dairy products. Almost all soy but also a larger part of pulses and cereals consumed in the European Union are used for animal nutrition. While livestock is an important source of proteins, it also creates substantial environmental impacts. The food and feed system is closely linked to the planetary and health boundaries and a transformation to healthy diets will require substantial dietary shifts towards healthy foods, such as nuts, fruits, vegetables and legumes. RESULTS: Extrudated vegetable meat alternatives consisting of protein combined with amaranth or buckwheat flour and a vegetable milk alternative made from lentil proteins were shown to have the potential to generate significantly less environmental impact than their animal-based counterparts in most of the environmental indicators examined, taking into account both functional units (mass and protein content). The underlying field-to-fork life cycle assessment models include several variants for both plant and animal foods. The optimized plant-based foods show a clear potential for improvement in the environmental footprints. CONCLUSIONS: Development of higher processed and therefore higher performing products is crucial for appealing to potential user groups beyond dedicated vegetarians and vegans and ultimately achieving market expansion. The Protein2Food project showed that prototypes made from European-grown legumes and pseudocereals are a valuable source for high-quality protein foods, and despite being substantially processed they could help reduce the environmental impact of food consumption. © 2021 Society of Chemical Industry.

Life cycle assessment of animal-based foods and plant-based protein-rich alternatives: a socio-economic perspective.

BACKGROUND: Extensive research shows that replacing animal protein with plant-based protein in the diet would strongly alleviate the environmental impact of the food system. However, much less attention has been given to the socio-economic considerations of dietary transitions. This study analyses the socio-economic performance of innovative legume-based food prototypes, developed in the Protein2Food research project, and conventional animal-based products (chicken meat and dairy milk). We implement a social life cycle assessment (sLCA) to quantify and compare their potential socio-economic impacts along the entire life cycle. RESULTS: Findings from this analysis show that legume-based prototypes and their respective animal-based counterparts have, overall, a comparable socio-economic performance. Looking at the disaggregated life cycle stages, socio-economic hotspots (points of most negative impacts) were mainly identified at the production stage in legume-based products. Farm-level net margin and profitability are low when compared with their animal equivalents. However, at the processing stage, there are socio-economic gains for plant-based products regarding lower unemployment rates. Finally, at the consumption stage, there are mixed results. Plant-based products show worse protein affordability but better nutritional contents (lower saturated fat and cholesterol) than their animal counterparts. CONCLUSIONS: To improve socio-economic performance of legume-based foods, greater emphasis should be placed upon developing improved processing technologies and supply chains. This would broaden the supply of sustainable protein-rich food options and make these products more economically attractive. The research illustrates that policies should be targeted to the different stages of the food value chain to optimize the development of innovative plant-based foods. © 2021 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Characterizing cassava farmer typologies and their seed sourcing practices to explore opportunities for economically sustainable seed business models in Rwanda.

The overdependency on local cassava varieties and informal seed sources by farmers in Rwanda has contributed to the spread of cassava viral diseases. The use of improved planting materials made available through formal seed sources, that assure seed quality, is one way to prevent future disease outbreaks. In order to increase the availability of, and farmers access to, such materials there is increasing interest to develop seed business models. This study aims to understand seed sourcing practices of different farm typologies to inform the development of tailored seed business models. A total of 390 farmers were interviewed and the collected data was analyzed into clusters, resulting in seven farm typologies. Seed sourcing strategies, seed replacement dynamics and purchasing behavior of these typologies were explored via a seed tracing study. We find that more commercial oriented farmers have better access to formal seed sources. Nevertheless, the majority of farmers in all typologies accessed new varieties and quality cassava seed via informal channels. At both formal and informal sources, cash investments in seed were mainly made by the categories of better-off farmers, and were one-time investments to acquire a new variety. Based on farmers current seed sourcing practices, clarifications on the differences between farmers and their willingness-to-pay, the roles of seed degeneration, cost-benefit analysis, value propositions and profit formulas seem important requirements for the further development of viable cassava seed business models. We conclude that tailoring seed business models can have a high potential as it acknowledges differences among farmers, but that careful coordination is needed to ensure that one approach or intervention does not contrast with and/or undermine the others.

Evaluating Animal-Based Foods and Plant-Based Alternatives Using Multi-Criteria and SWOT Analyses.

Global diets have transitioned in recent decades with animal and processed products increasing. Promoting a reversal in these trends towards plant-based diets could reduce the environmental impacts of food systems and reduce the prevalence of non-communicable diseases and malnutrition. In Spain, a reference point for the Mediterranean diet (predominantly plant-source based), plant-based alternatives to traditional animal-based products are receiving increased attention. However, limited focus has been given to the opinions of stakeholder groups on the potential of these novel products. We evaluate the opinions of stakeholders within the Spanish agri-food sector, using multicriteria and SWOT analyses, on traditional and novel food products. Stakeholders involved in the supply chain of food products (producers, processors, and distributors) were critical of novel plant-based foods, highlighting problems with their taste, processing technology, and high prices. These results contrast with the perspectives of policymakers, researchers, environmental NGOs, and consumers who see novel products more positively - healthier, more sustainable, and highly profitable. These results illustrate the more traditional mindset seen in Spanish production systems, contrasting with the rapidly shifting tastes and demands of consumers and the potential legislative orientation of policymakers. This study calls for improved understanding and collaboration between stakeholders to better manage complex choices that affect the future of food systems during their needed transformation.