Trait preferences and lentil varietal adoption in central Ethiopia: A multistakeholder approach

Agricultural technologies, including modern/improved crop varieties, are a critical measure for improving productivity, meeting food security needs, and bridging inequalities. This notwithstanding, adoption of some improved crop varieties in sub-Saharan Africa (SSA) tends to be low, with factors such as limited information, poor access to inputs, and risk averseness cited as reasons for low adoption. Few studies in SSA, and Ethiopia particularly, examine the influence of lentil trait preferences on adoption, and the ones that do only look at farmers' perspectives who are often treated as a homogenous group. This is despite the importance of lentils as a subsistence and growing market crop, and the fact that diverse factors may determine adoption among farmers. To address these knowledge gaps, this study used a mixed methods approach involving multiple stakeholders (n = 808) to understand gendered patterns in lentil varietal adoption and trait preferences, using an intersectional lens. The findings revealed low adoption rates for improved varieties for women and men alike due to poor disease resistance, and insufficient attention from the breeding programs to preferred processing and consumer traits, as well as the differentiated needs of farmers. Paying attention to these trait needs serves to inform gender-intentional breeding and improve the income generation potential of lentil varieties for diverse farmer groups. As such, we recommend sex-disaggregated data collection from socially differentiated groups and market representatives in order to inform breeding priorities along with the development of multiple varieties that suit different needs.

How ignoring market-informed crop varietal development fuels food price volatility

In conclusion, aligning crop development with market demands is not just a strategic move for economic stability; it is a requisite for building resilient, profitable, and sustainable agricultural systems. By doing so, the sector can provide stability for farmers and affordability for consumers and contribute to the socio-economic resilience of communities worldwide.

Establishing the linkage between eba's instrumental and sensory descriptive profiles and their correlation with consumer preferences: implications for cassava breeding

BACKGROUND

Gari and eba, forms of cassava semolina, are mainly consumed in Nigeria and other West African countries. This study aimed to define the critical quality traits of gari and eba, to measure their heritability, to define medium and high throughput instrumental methods for use by breeders, and to link the traits with consumer preferences. The definition of a food product's profiles, including its biophysical, sensory, and textural qualities, and the identification of the characteristics that determine its acceptability, are important if new genotypes are to be adopted successfully.

RESULTS

Eighty cassava genotypes and varieties (three 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 prioritize the traits preferred by processors and consumers. The color, sensory, and instrumental textural properties of these products 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 < 0.05) correlations between instrumental hardness and sensory hardness and between adhesiveness and sensory moldability. Principal component analysis showed broad discrimination amongst the cassava genotypes and the association of the genotypes concerning the color and textural properties.

CONCLUSIONS

The color properties of gari and eba, together with instrumental measures of hardness and cohesiveness, are important quantitative discriminants of cassava genotypes. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

A case of transdisciplinarity and collaborative decision making: the co-construction of Gendered Food Product Profiles

Crop breeding in sub-Saharan Africa has made considerable gains; however, postharvest and food-related preferences have been overlooked, in addition to how these preferences vary by gender, social difference and context. This context is changing as participatory approaches using intersectional gender and place-based methods are beginning to inform how breeding programmes make decisions. This article presents an innovative methodology to inclusively and democratically prioritise food quality traits of root, tuber and banana crops based on engagement with food systems actors and transdisciplinary collaboration. The outcome of the methodology is the Gendered Food Product Profile (GFPP) - a list of prioritised food quality characteristics - to support breeders to make more socially inclusive decisions on the methods for trait characterisation to select genotypes closer to the needs of food system actors. This article reviews application of the methodology in 14 GFPPs, presents illustrative case studies and lessons learned. Key lessons are that the transdisciplinary structure and the key role of social scientists helped avoid reductionism, supported co-learning, and the creation of GFPPs that represented the diverse interests of food system actors, particularly women, in situ. The method partially addressed power dynamics in multidisciplinary decision making; however, effectiveness was dependent on equitable team relations and supportive institutions committed to valuing plural forms of knowledge. Actions to address power asymmetries that privilege particular types of knowledge and voices in decision making are crucial in techno-science projects, along with opportunities for co-learning and long-term collaboration and a transdisciplinary structure at higher level. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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.

Gender, rainfall endowment, and farmers' heterogeneity in wheat trait preferences in Ethiopia

Wheat is a vital cereal crop for smallholders in Ethiopia. Despite over fifty years of research on wheat varietal development, consideration of gendered trait preferences in developing target product profiles for wheat breeding is limited. To address this gap, our study used sex-disaggregated survey data and historical rainfall trends from the major wheat-growing regions in Ethiopia. The findings indicated heterogeneity in trait preferences based on gender and rainfall endowment. Men respondents tended to prefer wheat traits with high straw yield and disease-resistance potential, while women showed a greater appreciation for wheat traits related to good taste and cooking quality. Farmers in high rainfall areas seemed to prioritize high straw yield and disease resistance traits, while those in low rainfall areas valued good adaptation traits more highly. Most of the correlation coefficients among the preferred traits were positive, indicating that farmers seek wheat varieties with traits that serve multiple purposes. Understanding men's and women's preferences and incorporating them in breeding and seed systems could contribute to the development of more targeted and effective wheat varieties that meet the diverse needs of men and women farmers in Ethiopia.

Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers' traditional knowledge

In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers' appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker-trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers' traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation.