Kaue Feitosa Dias de Sousa

• Cairns, Jill E; Fisher, Monica; Pinto, Francisco; Sousa, Kauê de; Etten, Jacob van & Zaman-Allah, Mainassara [Show all 9 contributors for this article] (2026). Advancing inclusive on-farm testing approaches to facilitate maize breakthrough product development in sub-Saharan Africa. Journal of Experimental Botany. ISSN 0022-0957. doi: 10.1093/jxb/erag431. Full text in Research Archive Show summary

  Abstract Developing breakthrough products that deliver at least 25% improvements in productivity in farmers’ fields requires that breeding pipelines more closely align with farmers’ and end-user needs and the target population of environments (TPEs). In the case of maize, climate change is accelerating climatic shifts within the TPE, potentially limiting future realised genetic gain. On-farm breeding approaches can play a valuable role in supporting breeding programs transitioning towards breakthrough products. Increased sampling of the TPE by moving selection into farmers’ fields can overcome the challenges of climatic changes within the TPE and extensive farmer diversity, whilst providing information to refine managed environment trials designed to sample the TPE. This review highlights advances in inclusive host farmer sampling, sparse testing strategies and phenotyping to facilitate scaling of on-farm testing within breeding pipelines.

• Jørgensen, Marit; Borchsenius, Ragnhild; Elverland, Ellen; Gillund, Frøydis; Muradagha, Khaled & Sousa, Kauê de [Show all 7 contributors for this article] (2026). Improving forage production in Norway: Participatory evaluation of climate-adapted seed mixtures. Grassland Science in Europe. 31, p. 516–518. Full text in Research Archive
• Dorado-Betancourt, Hugo; Eeuwijk, Fred van; Etten, Jacob van; Ramirez-Villegas, Julian; Sousa, Kauê de & Daudi, Happy [Show all 9 contributors for this article] (2026). Estimating on-farm genotypic performance and variability using ranking data. Theoretical and Applied Genetics. ISSN 0040-5752. 139. doi: 10.1007/s00122-026-05319-1. Full text in Research Archive Show summary

  Our scalable two-step method estimates genotypic performance and genetic parameters from ranking data, producing reliable results comparable to quantitative analyses, enabling the integration of ranking data into breeding pipelines. Abstract Plant breeding research has chiefly relied on on-station experiments to evaluate varietal performance. Nevertheless, these trials often fail to represent on-farm growing conditions and farmers’ preferences, potentially leading to poorly defined breeding targets. Recent work has demonstrated the potential of using on-farm verification trials combined with ranking data to support farmers in evaluating varieties while providing information that is representative of farmers’ needs. Despite this potential, scalable methods for quantifying genetic differences and assessing the strength of the genetic signal in such trials remain limited. Here, we present a two-step procedure for analyzing trials based on ranking data, allowing the estimation of genetic parameters. The approach follows a common strategy in quantitative genetics, in which parameters are estimated from tables of genotypic means and their variances. In our framework, these estimates are obtained from Thurstonian and/or Plackett-Luce models, which treat rankings as observations of an underlying continuous trait associated with genotypic performance. Using simulated data, we showed that genotypic mean estimates derived from ranking analyses are linearly related to those obtained from quantitative trait analyses and that their variances adequately capture estimation uncertainty. We further demonstrated that incorporating these estimates and their variances into a second-step mixed-effects model yields accurate estimates of variance components. Analyses of groundnut, maize, and sweetpotato datasets confirmed the applicability of the approach and showed that ranking data can provide reliable estimates of genetic parameters. We argue that this framework can be scaled to obtain genotypic performance estimates from multi-trial on-farm data.

• Daudi, Happy; Bujiku, Anthony Malehiwa; Oteng‐Frimpong, Richard; Mwololo, James; Ojiewo, Chris O. & Rathore, Abhishek [Show all 11 contributors for this article] (2026). Analysis of Genotype‐by‐Environment Interaction, Farmers' Preferences, and Gender Response in Groundnut Breeding in Tanzania Using Triadic Comparison of Technologies. Food and Energy Security. 15(2). doi: 10.1002/fes3.70228. Full text in Research Archive Show summary

  High kernel yield and farmer‐ and market‐preferred traits are overriding considerations for groundnut ( Arachis hypogaea L.) breeding, production and adoption. However, yield expression and cultivar selection responses in groundnuts are influenced by genotype‐by‐environment interactions (GEI) and management conditions. Therefore, it is essential to evaluate GEI to identify high‐yielding and stable groundnut genotypes preferred by farmers and markets for breeding or variety recommendations. The objectives of this study were to assess the GEI and farmers' preference traits in groundnut to facilitate the selection of superior genotypes for release and guide breeding with specific or broad adaptation while integrating farmers' and gender perceived traits. The study was conducted across 18 environments representing agroecological zones and potential groundnut production areas in Tanzania. Sixteen genotypes, including two commercial checks, were evaluated in selected locations using a randomized complete block design. Furthermore, on‐farm decentralized trials were conducted across 42 locations following the tricot approach. Significant ( p  < 0.05) variations were detected among the tested genotypes (G), environments (E), and GEI effects on kernel yield. Genotype ICGV‐SM 05534 had a relatively highest kernel yield of 927.232 kg ha −1 . The GGE biplot identified ICGV‐SM 16645 and ICGV‐SM 10014 as the most stable genotypes across locations, with mean kernel yields of 936.39 and 877.67 kg ha −1 , respectively. The triadic comparison of technologies (TRICOT) analysis identified gender differences in trait preferences among groundnut growers. Early maturity, ease of harvesting and shelling were the most preferred traits by female farmers, and haulm yield by males. Tan color and small‐medium kernel seed size were identified as the top traits selected by farmers' overall varietal preferences. Additionally, early maturity is an important trait to consider in the market segment. Farmers' preference traits are crucial during the initial stage of designing the target product profile to increase the adoption of the deployed groundnut variety. The selected genotypes, test environments, and farmer‐preferred traits are vital for breeding pipelines, targeted variety release, and production for different target population environments (TPEs) in Tanzania.

• Selby, Peter; Abbeloos, Rafael; Adam-Blondon, Anne-Francoise; Agosto-Pérez, Francisco J; Alaux, Michael & Alic, Isabelle [Show all 77 contributors for this article] (2025). BrAPI v2: real-world applications for data integration and collaboration in the breeding and genetics community. Database: The Journal of Biological Databases and Curation. 2025. doi: 10.1093/database/baaf048. Full text in Research Archive Show summary

  Population growth and the impacts of climate change are placing increasing pressure on global agriculture and breeding programmes. Recent advancements in phenotyping techniques, genotyping technologies, and predictive modelling are accelerating genetic gains in breeding programmes, helping researchers and breeders develop improved crops more efficiently. However, these advancements have also led to an overwhelming torrent of fragmented data, creating significant challenges in data integration and management. To address this issue, the Breeding Application Programming Interface (BrAPI) project was established as a standardized data model for breeding data. BrAPI is an international, community-driven effort that facilitates interoperability among databases and tools, improving the sharing and interpretation of breeding-related data. This open-source standard is software-agnostic and can be used by anyone interested in breeding, phenotyping, germplasm, genotyping, and agronomy data management. This manuscript provides an overview of the BrAPI project, highlighting the significant progress made in the development of the data standard and the expansion of its community. It also presents a showcase of the wide variety of BrAPI-compatible tools that have been built to enhance breeding and research activities, demonstrating how the project is advancing agricultural innovation and data management practices.

• Kang, Geon; Sousa, Kaue de; Manners, Rhys; Etten, Jacob van; Backes, Gunter & Rukundo, Placide [Show all 11 contributors for this article] (2025). Integrating environmental, socio-economic, and biological data in a farmer-led potato trial for enhanced varietal assessment in Rwanda. Experimental Agriculture. ISSN 0014-4797. 61. doi: 10.1017/S0014479725100100. Full text in Research Archive Show summary

  Potato (Solanum tuberosum L.) is crucial for food security in Rwanda, but its production growth has slowed. Improved potato varieties are urgently needed for Rwanda potato farmers. Crop breeding can effectively support smallholder farmers when it aligns with their environmental conditions and preferences. Additionally, integrating citizen science into variety development can enhance variety adoption and suitability for smallholder farmers. We assessed the insights from a crop trial following a triadic comparison of technology options (tricot) approach, linking the results with environmental, socio-economic, and on-station trial data. Under a tricot trial, 460 farmers tested eleven potato varieties, randomly allocated in incomplete blocks of three, allowing each farmer to test and compare three varieties. Biological data, reflecting breeding and variety genotypic values, were generated from multi-environmental tests conducted during 2018–2019 to evaluate the adaptability of new varieties. This research revealed that Rwandan farmers preferred the pre-1990 varieties (Cruza and Kirundo), while Gisubizo and Kazeneza, post-2018 varieties, were also considered competitive. Farmers’ preferences were influenced by diverse environmental and socio-economic conditions, with taste being crucial for home consumption and yield prioritized for market sales. Additionally, seasonal temperatures influenced the yield performance ranking of potato varieties across regions, while economic considerations and gender dynamics shaped different patterns of variety preferences. Despite challenges in aligning on-station and on-farm data, our integrated approach provides actionable insights for breeding programmes to develop potato varieties that better align with farmers’ needs, as well as environmental and socio-economic conditions. This innovative method can enhance breeding efficiency, variety adoption, and potato productivity, contributing to food security and agricultural sustainability.

• Voss, Rachel; Sousa, Kaue de; N’Danikou, Sognigbé; Shango, Abdul; Aglinglo, Lys Amavi & Laporte, Marie-Angélique [Show all 22 contributors for this article] (2025). Citizen science informs demand-driven breeding of opportunity crops. Plants, People, Planet. 7(6), p. 1700–1713. doi: 10.1002/ppp3.70035. Full text in Research Archive Show summary

  Societal Impact Statement Amid global challenges of food insecurity, poor nutrition, and climate change, neglected crops like amaranth are gaining renewed attention. We studied farmers' preferences for amaranth varieties across diverse geographical contexts to guide targeted breeding. Our results revealed significant variation in farmer preferences, emphasizing the need for context-specific breeding strategies. These findings can support the development of improved amaranth varieties that meet local needs, expand economic opportunities—especially for women—promote healthier diets, and boost biodiversity. This work also offers a model for participatory research on opportunity crops, informing inclusive agricultural policies and sustainable development strategies across Africa and beyond. Summary Opportunity crops, also known as neglected and underutilized species (NUS), offer benefits to diversify food systems with nutritious and climate-resilient foods. A major limitation to incorporating these crops in farming systems is the lack of improved varieties, which impedes farmers from accessing quality planting materials of these crops. The study explored how citizen science methods can support demand-driven breeding and seed production of NUS using leafy amaranth – a nutritious and hardy vegetable - as a case study. The study identified farmer preferences and market segments, with particular attention to gender and social differentiation. We used the tricot approach to conduct participatory on-farm trials of 14 varieties with 2,063 farmers from Benin, Mali, and Tanzania. We then analyzed farmer traits and varietal preferences in aggregate and among segments of farmers, using cluster analysis. Farmers' overall preferences for amaranth varieties were driven principally by plant survival, yield, leaf size, taste, and marketability. Distinct farmer segments (older women generalists, young women specialists, older men generalists, and young men specialists) preferred different varieties depending on gender and business orientation. The identified farmer segments, along with their unique variety preferences, provide valuable information for breeders and seed enterprises, and support demand-driven amaranth breeding and seed system development. The methods used and lessons learned from our citizen science exercise can be applied to enhance breeding and seed supply of other opportunity crops that are underutilized in Africa and elsewhere.

• Nabateregga, Mabel; Dorado, Hugo; Solberg, Svein Øivind; Etten, Jacob van; Heerwaarden, Joost van & Gregory, Theresia [Show all 7 contributors for this article] (2025). Accuracy of farmer-generated yield estimations of common bean in decentralised on-farm trials in sub–Saharan Africa. European Journal of Agronomy. ISSN 1161-0301. 170. doi: 10.1016/j.eja.2025.127730. Full text in Research Archive Show summary

  Improving agricultural productivity and resilience is essential to meet future food needs in sub-Saharan Africa under changing climate conditions. Achieving this will necessitate the development of high-yielding locally adapted crop varieties to mitigate the impacts of climate change. Despite advancements in crop improvement, varietal turnover in smallholder farms remains notably low. Continuous turnover of locally adapted varieties is essential, necessitating active dissemination of new varieties and withdrawal of obsolete ones across diverse target populations using participatory breeding approaches. A decentralised experimental approach, known as tricot, supported by citizen science, has proven effective in accelerating genotype selection while promoting inclusivity and diversity. However, the methodology has strongly relied on farmer-generated rankings, which provide relative performance insights but fall short in informing breeders with absolute yield data, limiting the ability to measure genetic gain or assess economic returns on breeding investments. To address this gap, we validated the accuracy of farmer-generated yield data for common bean (Phaseolus vulgaris L.), by comparing it with technician-generated volumes and researcher-generated absolute yield data. Results revealed strong correlations between farmer and technician volumes (r = 0.96, p < 0.001). The mean difference in farmer-technician log-yield was close to zero, indicating significant agreement. We further developed a predictive model to estimate absolute yields using farmer showing minimal influence from intrinsic and extrinsic factors. Our findings demonstrate that farmer-generated yield data can reliably inform breeding decisions and support the accelerated turnover of improved varieties. Integrating such data into breeding programs offers a cost-effective and scalable pathway to enhance agricultural productivity and sustainability across smallholder systems in sub-Saharan Africa.

• Sharma, Kalpana; Atieno, Elly; Mugo, James; Sousa, Kaue de; Etten, Jacob van & Nyawade, Shadrack (2025). Understanding Farmer Preferences through Citizen Science: Insights on Potato Varieties in Nigeria. Journal of Agriculture and Food Research. 23. doi: 10.1016/j.jafr.2025.102135. Full text in Research Archive Show summary

  Conventional top-down potato breeding often overlooks farmer input, leading to varieties that may not be suited to local conditions, limiting their adoption and impact on smallholder farming. To address this gap, this study evaluated whether a participatory, digitally enabled approach to variety selection better reflects farmer needs and improves uptake. This study employed the tricot (Triadic Comparisons of Technology Options) approach, a participatory framework, combined with digital tools for real-time data collection and decision support. Farmers from seven Local Government Areas (LGAs) in Plateau State, Nigeria (Barikin Ladi, Bassa, Bokkos, Jos North, Jos South, Mangu, and Pankshin), evaluated anonymized potato genotypes alongside the check variety Marabel. Trial design and genotype allocation were managed through ClimMob, a cloud-based platform (https://climmob.net), enabling live streaming and real-time tracking. Data were collected via a mobile app and Open Data Kit (ODK). Assessments occurred at three crop stages: vegetative (germination, disease resistance, drought tolerance), harvest (yield, tuber appearance, marketability), and post-harvest (cooking quality, storability). Farmer preferences were analyzed using the Plackett-Luce model, a probabilistic model that estimates the relative ‘worth’ (also referred to as log-worth) of each genotype based on observed rankings across multiple comparisons. CIP clones CIP392797.22 and CIP393371.157 emerged as top-ranked, with log-worth values of 0.620 and 0.309, respectively, indicating stronger preference relative to the check. In contrast, CIP398208.29 and CIP398190.200 were least preferred (–0.085 and –0.465). Socioeconomic factors influenced selection: market-oriented farmers prioritized commercial traits, while subsistence farmers emphasized resilience. This study highlights the value of participatory, data-driven breeding that integrates local knowledge to enhance adoption, resilience, and food security.

• Donovan, Jason; Rutsaert, Pieter; Mawia, Harriet; Sousa, Kaue de & Etten, Jacob van (2025). Farmers’ preferences for the next generation of maize hybrids: application of product concept testing in Kenya and Uganda. Experimental Agriculture. ISSN 0014-4797. 61. doi: 10.1017/S001447972500002X. Full text in Research Archive Show summary

  Step-change innovation in seed product design by public sector crop breeding has led to major contributions to global food security. The literature, however, provides few insights on how to identify forward-looking innovation opportunities. Inspired by discussions in the product innovation literature, this article describes our application of product concept testing in the context of hybrid maize in Uganda and Kenya. We identified the following eight maize seed product concepts based on interactions with seed companies, crop breeders, and farmers: ‘Resilience’, ‘Drought escape’, ‘Food and fodder’, ‘Home use’, ‘Green maize’, ‘Livestock feed’, ‘Intercropping’, and ‘Family nutrition’. These were described and presented to 2400 farmers using videos, where each farmer saw three concept-presentation videos. Farmers were most likely to have selected the resilience (Kenya and Uganda), drought escape (Uganda), and intercropping (Kenya) concepts. Farmers showed mixed interest in other concepts, such as home use and food and fodder, suggesting that investments in product production and promotion would be required in addition to investments in breeding. These results provide new entry points for conversations among transdisciplinary teams at regional and national levels on the current and future opportunities for crop breeding to respond to farmers’ requirements for new seed products.

• Sousa, Kaue de; Etten, Jacob van; Manners, Rhys; Abidin, Erna; Abdulmalik, Rekiya O. & Abolore, Bello [Show all 81 contributors for this article] (2024). The tricot approach: an agile framework for decentralized on-farm testing supported by citizen science. A retrospective. Agronomy for Sustainable Development. ISSN 1774-0746. 44. doi: 10.1007/s13593-023-00937-1. Full text in Research Archive Show summary

  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 tri

• Nanyonjo, Ann Ritah; Angudubo, Stephen; Iragaba, Paula; Brown, David; Nuwamanya, Ephraim & Esuma, Williams [Show all 15 contributors for this article] (2024). On-farm evaluation of cassava clones using the triadic comparison of technology options approach. Crop Science. ISSN 0011-183X. 64(5), p. 2679–2697. doi: 10.1002/csc2.21293. Full text in Research Archive Show summary

  The triadic comparison of technology options (tricot) approach to participatory varietal selection has been demonstrated to scale out the on-farm testing of elite candidate crop varieties. In this study, we evaluated elite clones of cassava (Manihot esculenta Crantz) using the tricot approach. We sought to (1) synthesize on-farm trial data from two cycles evaluating different sets of elite cassava clones; (2) assess the agronomic performance of elite cassava clones considering sociodemographic and climatic factors; and (3) assess the performance of elite cassava clones for both agronomic and food quality traits. The study involved 10 districts in Uganda, two cycles/seasons of evaluation, 20 elite cassava clones, one check variety, and 294 men and 320 women farmers. Our results indicate that the agronomic performance of elite cassava clones was influenced more by geographic than sociodemographic factors. Our analysis identified the number of days with rainfall higher than 20 mm as the most influencing climatic factor over agronomic performance. Further, the study identified superior elite cassava clones UG110164, UGC14170, and UG120193 as promising candidate varieties for release, targeting food products. Overall, our study emphasizes the important contribution of end-users to crop improvement and provides insights into use of tricot on-farm testing methodology to evaluate elite cassava clones during cassava variety development in Uganda, which can be used to support decision making for variety release.

• Occelli, Martina; Sellare, Jorge; Sousa, Kaue de; Dell’Acqua, Matteo; Mercado, Leida & Paredes, Saul [Show all 9 contributors for this article] (2024). Group-based and citizen science on-farm variety selection approaches for bean growers in Central America. Agricultural Economics. ISSN 0169-5150. 55(2), p. 270–295. doi: 10.1111/agec.12819. Full text in Research Archive Show summary

  Participatory approaches for crop variety testing can help breeding teams to incorporate traditional knowledge and consider site-specific sociocultural complexities. However, traditional participatory approaches have drawbacks and are seldom streamlined or scaled. Decentralized on-farm testing supported by citizen science addresses some of these challenges. In this study, we compare a citizen science on-farm testing approach — triadic comparisons of technology options (tricot-PVS) — with the benchmark state-of-the-art group-based participatory variety testing approach (group-PVS) over a set of socioeconomic outcomes. We focus on on-farm testing of common bean (Phaseolus vulgaris L.) in the Trifinio area of Central America. We measure the impact of these two approaches on bean growers in terms of on-farm diversification and food security. We use data from 1978 smallholder farmers from 140 villages, which were randomly assigned to tricot-PVS, group-PVS or control. Utilizing a difference-in-difference model with inverse probability weighting and an instrumental variable approach, we observe that farmers involved in group-PVS, and tricot-PVS had comparable levels of on-farm varietal diversification with respect to control farmers. Nonetheless, group-PVS appears to be significantly more effective in boosting household food security, which can be attributed to improved agronomic management of the crops. This study contributes to the next generation of innovations in exploring trait preferences to produce more inclusive, demand-driven varietal design that democratize participatory varietal selection programs.

• Sousa, Kaue de; Brown, David; Steinke, Jonathan & Etten, Jacob van (2023). gosset: An R package for analysis and synthesis of ranking data in agricultural experimentation. SoftwareX. 22. doi: 10.1016/j.softx.2023.101402. Full text in Research Archive Show summary

  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.

• Quiros, Carlos F.; Sousa, Kaue de; Steinke, Jonathan; Madriz, Brandon; Laporte, Marie-Angelique & Arnaud, Elizabeth [Show all 10 contributors for this article] (2023). ClimMob: Software to support experimental citizen science in agriculture. Computers and Electronics in Agriculture. ISSN 0168-1699. 217. doi: 10.1016/j.compag.2023.108539. Full text in Research Archive Show summary

  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.

• Alamu, Oladeji Emmanuel; Teeken, Béla; Ayetigbo, Olawatoyin; Adesokan, Michael; Kayondo, Ismail & Chijioke, Ugo [Show all 17 contributors for this article] (2023). Establishing the linkage between Eba's instrumental and sensory descriptive profiles and their correlation with consumer preferences: implications for cassava breeding. Journal of the Science of Food and Agriculture. ISSN 0022-5142. 104(8). doi: 10.1002/jsfa.12518. Full text in Research Archive Show summary

  Background Gari and Eba (cassava semolina) is mainly consumed in Nigeria and other West African countries. Defining the food product profile (biophysical, sensory, and textural qualities) that drives its acceptability, and integrating the component traits into breeding programs, are critical for the better adoption of new genotypes. This study aimed to define the Gari and Eba critical quality traits, define medium and high throughput instrumental methods for use by breeders, measure their respective heritabilities, and link the traits with consumer preference. Results A total of 80 cassava genotypes and varieties (3 different sets) from the International Institute of Tropical Agriculture (IITA) research farm were used for the study. Participatory processing and consumer testing data on different types of Gari and Eba products were integrated to determine the prioritization of the preferred traits by processors and consumers. The color, sensory, and instrumental textural properties of Gari and Eba were determined using standard analytical methods, and standard operating protocols (SOPs) developed by the RTBfoods project (Breeding Roots, Tubers, and Banana products for end-user preferences: https://rtbfoods.cirad.fr). There were significant (p

• Brown, David; Bruin, Sytze de; Sousa, Kaue de; Abadie, Catherine; Carpentier, Sebastien & Machida, Lewis [Show all 7 contributors for this article] (2023). Rank-based data synthesis of heterogeneous trials to identify the effects of climatic factors on the reaction of Musa genotypes to black leaf streak disease. Agronomy Journal. ISSN 0002-1962. doi: 10.1002/agj2.21436. Full text in Research Archive Show summary

  Synthesis of crop trial data can generate insights that are not available from the analysis of individual studies, but such synthesis is often constrained by the heterogeneity of data among studies. Rank-based data synthesis provides the flexibility to combine data of heterogeneous types and from different sources. We demonstrate the application of rank-based data synthesis of heterogeneous trial data to assess the effect of climatic factors on the reaction of several Musa genotypes to black leaf streak disease (BLSD; caused by Pseudocercospora fijiensis [sexual morph: Mycosphaerella fijiensis]). We aggregated data from the main public repositories of Musa trial data. We applied model-based recursive partitioning with the Plackett-Luce model, using climatic data as covariates. The model identified the maximum length of the dry spell as the main variable influencing differences in genotypic response to BLSD, dividing the aggregated trial dataset into humid and dry environments. We found differences in the reaction of genotypes to BLSD between these environments. In humid environments, NARITA 8 was found to be the most resistant genotype, while in dry environments FHIA-01 was the best performing improved genotype. We also assessed reliability, which is the probability of outperforming the reference genotype (Calcutta 4). In humid environments NARITA 2, NARITA 8 and FHIA-01 had the highest reliability, while in dry environments only the landrace Saba surpassed 50% reliability. The information generated by our data synthesis approach supports selecting Musa genotypes for further evaluations at new locations.

• Olaosebikan, Olamide; Bello, Abolore; Sousa, Kaue de; Ndjouenkeu, Robert; Adesokan, Michael & Alamu, Emmanuel [Show all 12 contributors for this article] (2023). Drivers of consumer acceptability of cassava gari-eba food products across cultural and environmental settings using the triadic comparison of technologies approach (tricot). Journal of the Science of Food and Agriculture. ISSN 0022-5142. p. 1–12. doi: 10.1002/jsfa.12867. Full text in Research Archive Show summary

  Nigeria and Cameroon are multi-ethnic countries with diverse preferences for food characteristics. This study aimed to inform cassava breeders on consumer-prioritized eba quality traits. Consumer testing was carried out using the triadic comparison of technologies (tricot). Diverse consumers in villages, towns and cities evaluated the overall acceptability of eba made from different cassava genotypes. Data from both countries were combined and linked to laboratory analyses of eba and the gari used to make it. Results: There is a strong preference for eba with higher cohesiveness and eba from gari with higher brightness and especially in Cameroon, with lower redness and yellowness. Relatively higher eba hardness and springiness values are preferred in the Nigerian locations, while lower values are preferred in Cameroon. Trends for solubility and swelling power of the gari differ between the two countries. This study also reveals that the older improved cassava genotype TMS30572 is a benchmark genotype with superior eba characteristics across different regions in Nigeria, while the recently released variety Game changer performs very well in Cameroon. In both locations, the recently released genotypes Obansanjo-2 and improved variety TM14F1278P0003 have good stability and overall acceptability for eba characteristics. Conclusion: The wide acceptance of a single genotype across diverse geographical and cultural conditions in Nigeria, and three acceptable new improved varieties in both locations, indicates that consumers' preferences are surprisingly homogeneous for eba. This would enhance breeding efforts to develop varieties with wider acceptability and expand potential target areas for released varieties.

• Gesesse, Cherinet Alem; Nigir, Bogale; Sousa, Kauê de; Gianfranceschi, Luca; Gallo, Guido Roberto & Poland, Jesse [Show all 11 contributors for this article] (2023). Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 120(14), p. 1–10. doi: 10.1073/pnas.2205774119. Full text in Research Archive Show summary

  Smallholder farming systems support the livelihoods of estimated two billion people on the planet. They are often characterized by challenging environments critically exposed to the climate crisis, with limited access to inputs including improved seed technology. To achieve the sustainable intesification of smallholder farming systems, crop breeding needs to tailor varietal development to local farmer needs. Here, we devise a method to integrate wheat genomics with participatory varietal selection that allows to capture farmers’ traditional knowledge in a fully quantitative framework and inform breeding decisions. Our work demonstrates that cultural and natural agrobiodiversity can be leveraged together to increase the effectiveness of genomics-driven breeding toward varietal development for smallholder farming systems.

• Etten, Jacob van; Sousa, Kaue de; Cairns, Jill E.; Dell'Acqua, Metteo; Fadda, Carlo & Guerena, David [Show all 16 contributors for this article] (2023). Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 120(14). doi: 10.1073/pnas.2205771120. Full text in Research Archive Show summary

  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.

• Ariza-Salamanca, Antonio Jesús; Navarro-Cerrillo, Rafael M.; Quero-Pérez, José L.; Gallardo-Armas, Belinda; Crozier, Jayne & Stirling, Clare [Show all 8 contributors for this article] (2023). Vulnerability of cocoa-based agroforestry systems to climate change in West Africa. Scientific Reports. 13(1). doi: 10.1038/s41598-023-37180-3. Full text in Research Archive Show summary

  Previous research indicates that some important cocoa cultivated areas in West Africa will become unsuitable for growing cocoa in the next decades. However, it is not clear if this change will be mirrored by the shade tree species that could be used in cocoa-based agroforestry systems (C-AFS). We characterized current and future patterns of habitat suitability for 38 tree species (including cocoa), using a consensus method for species distribution modelling considering for the first time climatic and soil variables. The models projected an increase of up to 6% of the potential suitable area for cocoa by 2060 compared to its current suitable area in West Africa. Furthermore, the suitable area was highly reduced (14.5%) once considering only available land-use not contributing to deforestation. Regarding shade trees, 50% of the 37 shade tree species modelled will experience a decrease in geographic rate extent by 2040 in West Africa, and 60% by 2060. Hotspots of shade tree species richness overlap the current core cocoa production areas in Ghana and Côte d’Ivoire, suggesting a potential mismatch for the outer areas in West Africa. Our results highlight the importance of transforming cocoa-based agroforestry systems by changing shade tree species composition to adapt this production systems for future climate conditions.

• Sousa, Kaue de; Etten, Jacob van; Neby, Magne & Solberg, Svein Øivind (2023). Climate variability indices for ecological and crop models in R: the climatrends package. Journal of Open Source Software (JOSS). 8(85), p. 1–13. doi: 10.21105/joss.04405. Full text in Research Archive Show summary

  Abiotic factors play an important role in most ecological and crop systems that depend on certain levels of temperature, light and precipitation to initiate important physiological events (Schulze et al., 2019). Understanding how these factors drive the physiological processes is a key approach to provide recommendations for adaptation and biodiversity conservation in applied ecology studies. The package climatrends aims to provide the methods in R (R Core Team, 2020) to compute precipitation and temperature indices that serve as input for climate and crop models (Kehel et al., 2016; van Etten et al., 2019), trends in climate change (Aguilar et al., 2005; de Sousa et al., 2018) and applied ecology (Liu & El-Kassaby, 2018; Prentice et al., 1992).

• Brown, David; Sousa, Kaue de & Etten, Jacob van (2022). ag5Tools: An R package for downloading and extracting agrometeorological data from the AgERA5 database. SoftwareX. 21. doi: 10.1016/j.softx.2022.101267. Full text in Research Archive Show summary

  Agrometeorological data is important in agricultural research, especially in agronomy and crop science, for investigating genotype by environment interactions. The AgERA5 dataset from the Copernicus Climate Data Store provides free and public access to global gridded daily agrometeorological data, from 1979 to present, with ready to use variables tailored for agricultural and agro-ecological studies. We developed the R package ag5Tools, which provides a simplified interface for downloading and extracting AgERA5 data. The package facilitates extracting time-series data for sets of geographic points in a format that can be conveniently used in statistical models applied in agricultural research. The use of the package is demonstrated with a synthetic dataset of multi-location trials in Arusha, Tanzania.

• Brown, David; Bruin, Sytze de; Sousa, Kaue de; Aguilar, Amilcar; Barrios, Mirna & Gomez, Marvin [Show all 18 contributors for this article] (2022). Rank-based data synthesis of common bean on-farm trials across four Central American countries. Crop Science. ISSN 0011-183X. doi: 10.1002/csc2.20817. Full text in Research Archive Show summary

  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.

• Woldeyohannes, Aemiro Bezabih; Iohannes, Sessen Daniel; Miculan, Mara; Caproni, Leonardo; Ahmed, Jemal Seid & Sousa, Kaue de [Show all 10 contributors for this article] (2022). Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates. eLIFE. 11. doi: 10.7554/eLife.80009. Full text in Research Archive Show summary

  In smallholder farming systems, traditional farmer varieties of neglected and underuti- lized species (NUS) support the livelihoods of millions of growers and consumers. NUS combine cultural and agronomic value with local adaptation, and transdisciplinary methods are needed to fully evaluate their breeding potential. Here, we assembled and characterized the genetic diversity of a representative collection of 366 Ethiopian teff (Eragrostis tef) farmer varieties and breeding materials, describing their phylogenetic relation and local adaptation on the Ethiopian landscape. We phenotyped the collection for its agronomic performance, involving local farmers expert teff growers in a participatory variety evaluation. Our analyses revealed environmental patterns of teff genetic diversity and allowed us to identify ten genetic clusters associated with climate variation and with uneven spatial distribution. A genome wide association study (GWAS) was used to identify loci and candidate genes related to phenology, yield, local adaptation, and farmers’ appreciation. The estimated teff genomic offset under climate change scenarios highlighted an area around lake Tana where teff cropping may be most vulnerable to climate change. Our results show that transdis- ciplinary approaches may efficiently propel untapped NUS farmer varieties into modern breeding to foster more resilient and sustainable cropping systems.

• Moyo, Mukani; Ssali, Reuben; Namanda, Sam; Nakitto, Mariam; Dery, Eric K. & Akansake, Daniel [Show all 12 contributors for this article] (2021). Consumer Preference Testing of Boiled Sweetpotato Using Crowdsourced Citizen Science in Ghana and Uganda. Frontiers in Sustainable Food Systems. doi: 10.3389/fsufs.2021.620363. Full text in Research Archive Show summary

  Crowdsourced citizen science is an emerging approach in plant sciences. The triadic comparison of technologies (tricot) approach has been successfully utilized by demand-led breeding programmes to identify varieties for dissemination suited to specific geographic and climatic regions. An important feature of this approach is the independent way in which farmers individually evaluate the varieties on their own farms as “citizen scientists.” In this study, we adapted this approach to evaluate consumer preferences to boiled sweetpotato [Ipomoea batatas (L.) Lam] roots of 21 advanced breeding materials and varieties in Ghana and 6 released varieties in Uganda. We were specifically interested in evaluating if a more independent style of evaluation (home tasting) would produce results comparable to an approach that involves control over preparation (centralized tasting). We compiled data from 1,433 participants who individually contributed to a home tasting (de-centralized) and a centralized tasting trial in Ghana and Uganda, evaluating overall acceptability, and indicating the reasons for their preferences. Geographic factors showed important contribution to define consumers’ preference to boiled sweetpotato genotypes. Home and centralized tasting approaches gave similar rankings for overall acceptability, which was strongly correlated to taste. In both Ghana and Uganda, it was possible to robustly identify superior sweetpotato genotypes from consumers’ perspectives. Our results indicate that the tricot approach can be successfully applied to consumer preference studies

• Sousa, Kaue de; Etten, Jacob van; Poland, Jesse; Fadda, Carlo; Jannink, Jean-Luc & Kidane, Yosef Gebrehawaryat [Show all 11 contributors for this article] (2021). Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment. Communications Biology. p. 1–9. doi: 10.1038/s42003-021-02463-w. Full text in Research Archive Show summary

  Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments.

• Zuza, Emmanuel Junior; Maseyk, Kadmiel; Bhagwat, Shonil A.; Sousa, Kaue de; Emmott, Andrew & Rawes, William [Show all 7 contributors for this article] (2021). Climate suitability predictions for the cultivation of macadamia (Macadamia integrifolia) in Malawi using climate change scenarios. PLOS ONE. 16(9). doi: 10.1371/journal.pone.0257007. Full text in Research Archive Show summary

  Climate change is altering suitable areas of crop species worldwide, with cascading effects on people reliant upon those crop species as food sources and for income generation. Macadamia is one of Malawi’s most important and profitable crop species; however, climate change threatens its production. Thus, this study’s objective is to quantitatively examine the potential impacts of climate change on the climate suitability for macadamia in Malawi. We utilized an ensemble model approach to predict the current and future (2050s) suitability of macadamia under two Representative Concentration Pathways (RCPs). We achieved a good model fit in determining suitability classes for macadamia (AUC = 0.9). The climatic variables that strongly influence macadamia’s climatic suitability in Malawi are suggested to be the precipitation of the driest month (29.1%) and isothermality (17.3%). Under current climatic conditions, 57% (53,925 km2) of Malawi is climatically suitable for macadamia. Future projections suggest that climate change will decrease the suitable areas for macadamia by 18% (17,015 km2) and 21.6% (20,414 km2) based on RCP 4.5 and RCP 8.5, respectively, with the distribution of suitability shifting northwards in the 2050s. The southern and central regions of the country will suffer the greatest losses (≥ 8%), while the northern region will be the least impacted (4%). We conclude that our study provides critical evidence that climate change will reduce the suitable areas for macadamia production in Malawi, depending on climate drivers. Therefore area-specific adaptation strategies are required to build resilience among producers.

• Sousa, Kaue de & Solberg, Svein Øivind (2020). Conservation Gaps in Traditional Vegetables Native to Europe and Fennoscandia. Agriculture. 10(8). doi: 10.3390/agriculture10080340. Full text in Research Archive Show summary

  Vegetables are rich in vitamins and other micronutrients and are important crops for healthy diets and diversification of the food system, and many traditional (also termed underutilized or indigenous) species may play a role. The current study analyzed 35 vegetables with a European region of diversity with the effort to map the conservation status in Fennoscandia and beyond. We mapped georeferenced occurrences and current genebank holdings based on global databases and conducted conservation gaps analysis based on representativeness scores in situ and ex situ. Out of the 35 target species, 19 got at a high priority score for further conservation initiatives, while another 14 species got a medium priority score. We identified a pattern where traditional vegetables are poorly represented in genebank holdings. This corresponds well to a lack of attention in the scientific community measured in number of published papers. Considering the grand challenges ahead in terms of climate change, population growth and demand for sustainability, traditional vegetables deserve greater attention. Our contribution is to provide a basis for conservation priorities among the identified vegetables species native to Fennoscandia

• Sousa, Kaue de; Sparks, Adam H.; Ashmall, William; Etten, Jacob van & Solberg, Svein Øivind (2020). chirps: API Client for the CHIRPS Precipitation Data in R. Journal of Open Source Software (JOSS). 5(51), p. 2419–2419. doi: 10.21105/joss.02419. Full text in Research Archive Show summary

  The chirps package provides functionalities for reproducible analysis in R (R Core Team, 2020) using the CHIRPS (Funk et al., 2015) data. CHIRPS is daily precipitation data set developed by the Climate Hazards Group (Funk et al., 2015) for high resolution precipitation gridded data. Spanning 50◦ S to 50◦ N (and all longitudes) and ranging from 1981 to nearpresent (normally with a 45 day lag), CHIRPS incorporates 0.05 arc-degree resolution satellite imagery, and in-situ station data to create gridded precipitation time series for trend analysis and seasonal drought monitoring (Funk et al., 2015). Additionally, the package provides the API client for the IMERG (Huffman et al., 2014) and ESI (SERVIR Global, 2019a) data. The Integrated Multi-satelliE Retrievals for GPM (IMERG) data provides near-real time global observations of rainfall at 0.5 arc-degree resolution, which can be used to estimate total rainfall accumulation from storm systems and quantify the intensity of rainfall and flood impacts from tropical cyclones and other storm systems. IMERG is a daily precipitation dataset available from 2015 to near-present. The evaporative stress index (ESI) data describes temporal anomalies in evapotranspiration produced weekly at 0.25 arc-degree resolution for the entire globe (Anderson et al., 2011). The ESI data is based on satellite observations of land surface temperature, which are used to estimate water loss due to evapotranspiration (the sum of evaporation and plant transpiration from the Earth’s land and ocean surface to the atmosphere). The ESI data is available from 2001 to near-present. When using these data sets in publications please cite Funk et al. (2015) for CHIRPS, Huffman et al. (2014) for IMERG and SERVIR Global (2019a) for ESI.

• Etten, Jacob van; Sousa, Kaue de; Aguilar, Amilcar; Barrios, Mirna; Coto, Allan & Dell'Acqua, Matteo [Show all 24 contributors for this article] (2019). Crop variety management for climate adaptation supported by citizen science. Proceedings of the National Academy of Sciences of the United States of America (PNAS). ISSN 0027-8424. 116(10), p. 4194–4199. doi: 10.1073/pnas.1813720116. Full text in Research Archive Show summary

  Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgaris L.) in Nicaragua, durum wheat (Triticum durum Desf.) in Ethiopia, and bread wheat (Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

• Sousa, Kaue de; Zonneveld, Maarten van; Holmgren, Milena; Kindt, Roeland & Ordonez, Jenny C. (2019). The future of coffee and cocoa agroforestry in a warmer Mesoamerica. Scientific Reports. 9. doi: 10.1038/s41598-019-45491-7. Full text in Research Archive Show summary

  Climate change threatens coffee production and the livelihoods of thousands of families in Mesoamerica that depend on it. Replacing coffee with cocoa and integrating trees in combined agroforestry systems to ameliorate abiotic stress are among the proposed alternatives to overcome this challenge. These two alternatives do not consider the vulnerability of cocoa and tree species commonly used in agroforestry plantations to future climate conditions. We assessed the suitability of these alternatives by identifying the potential changes in the distribution of coffee, cocoa and the 100 most common agroforestry trees found in Mesoamerica. Here we show that cocoa could potentially become an alternative in most of coffee vulnerable areas. Agroforestry with currently preferred tree species is highly vulnerable to future climate change. Transforming agroforestry systems by changing tree species composition may be the best approach to adapt most of the coffee and cocoa production areas. Our results stress the urgency for land use planning considering climate change effects and to assess new combinations of agroforestry species in coffee and cocoa plantations in Mesoamerica.

• Sousa, Kaue de; Casanoves, Fernando; Sellare, Jorge; Ospina, Alejandra; Suchini, Jose Gabriel & Aguilar, Amilcar [Show all 7 contributors for this article] (2018). How climate awareness influences farmers’ adaptation decisions in Central America? Journal of Rural Studies. ISSN 0743-0167. 64, p. 11–19. doi: 10.1016/j.jrurstud.2018.09.018. Full text in Research Archive Show summary

  Central America is one of the regions with the highest vulnerability to climate change, with negative effects projected to affect its economy and food security. To address this issue, an integrative farm management approach such as Climate-Smart Agriculture can help reorient agricultural practices towards climate adaptation and food security. Past studies have shown that several factors can either hinder or encourage the adoptions of Climate-Smart practices, including subjective expectations and perceptions. Building on this literature, we analyze farmers' climate awareness and their perceptions regarding the change in climate patterns as well as their choices of farming practices to adapt to these changes. We show that reforestation was the preferred adaptation strategy among interviewed farmers and that educational profiles and the size of landholdings drive the adoption of this and other practices. Soil management and introduction of new crops are preferred by literate farms with large farmlands, whereas illiterate farmers with smaller farmland tend to move towards farm intensification with an increase in the utilization of external inputs. Our findings provide evidence to support the design of capacity development interventions targeting specific groups of farmers according to their main crop and education profile.

• Sousa, Kaue de; Detlefsen, Guillermo; Tobar, Diego; Filho, Elias de Melo Virginio & Casanoves, Fernando (2017). Population dynamic and management of Pinus oocarpa and Tabebuia rosea within silvopastoral systems in Central America. Agroforestry Systems. ISSN 0167-4366. 91(6), p. 1119–1127. doi: 10.1007/s10457-016-9988-x. Full text in Research Archive
• Sousa, Kaue de; Detlefsen, Guillermo; Filho, Elias de Melo Virginio; Tobar, Diego & Casanoves, Fernando (2016). Timber yield from smallholder agroforestry systems in Nicaragua and Honduras. Agroforestry Systems. ISSN 0167-4366. 90(2), p. 207–218. doi: 10.1007/s10457-015-9846-2. Full text in Research Archive

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• Etten, Jacob van; Other, authors & Sousa, Kaue de (2021). The tricot citizen science approach applied to on-farm variety evaluation: methodological progress and perspectives. CGIAR. 27 p. doi: 10.4160/23096586RTBWP20212. Full text in Research Archive Show summary

  Tricot (triadic comparisons of technologies) is a citizen science approach for testing technology options in their use environments, which is being applied to on-farm testing of crop varieties. Over the last years, important progress has been made on the tricot methodology of which an overview is given. Trial dimensions depend on several factors but tricot implies that plot size is as small as possible to include farmers with small plots (yet avoiding excessive interplot competition) while many locations are included to ensure representativeness of trials. Gender and socio-economic work is focused on better household characterization and recruitment strategies that move beyond sex-aggregation to address aspects of intersectionality. Ethics, privacy and traditional knowledge aspects will be addressed through expanding digital support in this direction. Genetic gain estimates need to be addressed by yield measurements, which can be generated by farmers themselves. There is conceptual clarity about the needs for documentation of trials and publishing data but this aspect requires further digital development. Much progress has been made on the ClimMob digital platform already, which is user friendly and supports trials in the main steps and includes open-source data analytics packages. Further improvements need to be made to ensure better integration with other tools. A next step will be the development of scaling strategies that involve business development. An important input into these strategies are economic studies, which are ongoing.

• Sousa, Kaue de; Zonneveld, Maarten van; Imbach, Pablo; Casanoves, Fernando; Kindt, Roeland & Ordonez, Jenny C. (2017). Suitability of Key Central American Agroforestry Species Under Future Climates: An Atlas. World Agroforestry Centre. ISBN 9789290594079. 257 p. Full text in Research Archive

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• Jørgensen, Marit; Borchsenius, Ragnhild; Elverland, Ellen; Gillund, Frøydis; Muradagha, Khaled & Sousa, Kauê de [Show all 7 contributors for this article] (2026). Improving forage production in Norway: Participatory evaluation of climate-adapted seed mixtures. Full text in Research Archive
• Elverland, Ellen; Gillund, Frøydis; Muradagha, Khaled; Sturite, Ievina; Borchsenius, Ragnhild & Sousa, Kaue de [Show all 8 contributors for this article] (2025). INNOFORAGE – Ny metode for testing av grovfôr. NIBIO POP. ISSN 2464-1170. 11(19). Full text in Research Archive Show summary

  Vi bor i et land med store variasjoner i klima og landskap, men nesten overalt dyrkes det grovfôr. Valg av plantemateriale må derfor tilpasses regionene de skal brukes i, og det er nødvendig med egne utprøvinger i ulike deler av landet. I dag gjennomføres slike praktiske forsøk på få steder, som oftest i større forsøksfelt, på forskningsstasjoner eller hos gårdbrukere. Dette kan gjøre testingen sårbar for feil og uforutsette hendelser. Derfor kan det være verdt å forsøke noe nytt.

• Mulatu, Kalkidan Ayele; Sousa, Kaue de; Ebrahim, Mohammed; Notenbaert, An; Abera, Wuletawu & Mwendia, Solomon [Show all 8 contributors for this article] (2024). Unlocking farmer-preferred multipurpose forage mixtures: a tricot approach in Ethiopia. Full text in Research Archive
• Nabateregga, Mabel; Solberg, Svein Øivind & Sousa, Kauê de (2026). Crop breeding for climate adaptation supported by crowd-sourced citizen science in sub-Saharan Africa. Universitet i Innlandet / University of Inland Norway. ISSN 9788283805901. Full text in Research Archive Show summary

  Klimaendringer har påvirket matproduksjonen i verden negativt, spesielt i områder i Afrika hvor produksjonssystemene er lite utviklet og uten muligheter for vanning. Til tross for at planteforedlingen har klart å få fram nye forbedra sorter, blir disse i liten grad tatt i bruk av de mange bønder med små gårder. Dette skyldes delvis at fokuset i mindre grad har vært rettet mot småbrukerens miljø, preferanser og behov, men heller mot avling og produktivitet under mer storskala og gunstige produksjonsforhold. For å imøtekomme disse utfordringene, og for at nye sorter raskere skal kunne tas i bruk, blir deltakende planteforedling i økende grad integrert i foredlingsprogrammene. Mitt doktorgradsarbeid setter søkelys på en ny og desentralisert tilnærming som går under betegnelsen «tricot» (kortform for sammenligning av tre og tre teknologier). Forskningen ble delt inn i fire sammenkobla deler og spenner over ulike vekster (hagebønne, kassava, mais, sorghum og peanøtt) og ulike geografiske områder (Tanzania, Uganda, Kenya og Nigeria). Resultatene viste hvordan deltakende planteforedling med støtte i medborgerforskning kan produsere pålitelige data som kan så brukes av planteforedlere i deres valg og prioriteringer. Valgene kan på sikt få betydning for matsikkerheten også under ugunstige klima- og produksjonsforhold. En innledende litteraturgjennomgang viste hvordan de vanligste metodene for å registrere avling ikke kommer uten komplikasjoner. Metodenes egnethet er kontekstspesifikke i forhold til produksjonssystem (artikkel 1). Gjennomgangen viste at bønder kan produsere troverdige avlingsdata, og ga innsikt i hvordan protokoller kan utføres for å sikre gode registreringer på gårdsnivå for valg av sorter. Basert på litteraturgjennomgangen ble det undersøkt hvor nøyaktig bønder kunne registrere avling ay hagebønne (Phaseolus vulgaris L.) og med feltarbeid i den nordlige delen av Tanzania (artikkel 2). Resultatene viste en sterk korrelasjon mellom avling registrert av bønder og avling registrert av forsøksteknikerne, og med minimal påvirkning fra indre og ytre faktorer. Dette viste at bønders registreringer er robuste. Resultater ble bekreftet i kassava (Manihot esculenta Crantz) med data samlet inn fra delstatene Osun og Benue i Nigeria (artikkel 3). Her ble det i tillegg også undersøkt en tilnærming med bruk av «ledende bønder» for å undersøke genotyper. En sammenligning av avlingsregistreringer gjort av «ledene bønder» og «ikke-ledende bønder» bekreftet at data levert av vanlige bønder er robuste, spesielt for å fange opp samspill mellom genotype og miljø (G x E). Et slikt aspekt er av stor betydning for foredlingsprogrammene, dette for å utvikle strategier for at sortsmateriale skal kunne være tilpasset ulikt miljø. Siste del av arbeidet undersøkte et nytt verktøy, med bruk av videobasert testing av ulike produktkonsept, og dette på et stort antall (10 100) bønder som dyrker mais, sorghum og peanøtter i Kenya, Tanzania og Uganda (artikkel 4). Studien identifiserte de mest prioriterte egenskaper og foredlingskonsept: tørkeresistens, motstandskraft mot skadegjørere, høytytende hybrider og samdyrking. Videre viste en prinsipal komponentanalyse at fire tydelige sosioøkonomiske markedssegmenter kunne identifiseres, og som kan gi pålitelig informasjon om valg av egenskaper for sorter i planteforedlingsprosessen. Samlet sett gir forskningen en strategisk oppskrift for en inkluderende, databasert planteforedling som kan imøtekomme de komplekse realiteter småbrukere befinner seg, og med dette bidra til en anvarlig planteforedling tilpasset de aktuelle utviklingslandene «i» Afrika.

• Rutsaert, Pieter; Donovan, Jason; Mawia, Harriet; Sousa, Kaue de & Etten, Jacob van (2022). Future market segments for hybrid maize in East Africa. CGIAR. Full text in Research Archive Show summary

  The current seed product market segmentation by the Consultative Group on International Agricultural Research (CGIAR) for maize in East Africa includes four segments, which differ by agro-ecological zone and maturity class. However, considering the lengthy period required to produce a variety, from initial design to commercial production, a critical question should be asked: what are future segments that should be considered in discussions on current breeding investments? Video-based product concept testing (VPCT) is a novel approach for gathering insights from farmers about their varietal preferences to inform future market segmentation. This brief explains the conceptual and methodological underpinnings of VPCT. We present an application of the tool in hybrid maize. Seven new product concepts (representing potential future market segments) were identified based on discussions with breeders, seed companies and farmers, which we labelled: home use, intercropping, drought avoidance, nutritious, feed (yellow), green maize and food and fodder. These future concepts, together with the resilient benchmark product concept (the current breeding target), were evaluated through triadic comparisons with 2400 farmers in Kenya and Uganda. In Uganda, the drought avoidance concept ranked high, while in Kenya the intercropping concept stood out. Concept testing provides a strong case for new investments to integrate agronomic practices and preferences of farmers into breeding, on-farm testing and seed systems. Future work will estimate the implications of increased availability (and uptake) of these future segments on the current segmentation.

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