ABSTRACT
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.
ABSTRACT
Anthracnose caused by Colletotrichum lindemuthianum is the major common bean disease worldwide causing complete yield loss under favourable disease conditions. This study aimed to determine phenotypic traits associated with anthracnose resistance for future use in breeding programmes. Twenty-two common bean varieties (CBVs) were selected basing on susceptibility to anthracnose, advanced breeding lines, improved variety resembling advanced breeding lines and the farmer variety widely grown in Tanzania. Selected varieties were planted in anthracnose hotspot fields and the same CBVs were planted in a screen house to validate resistance to anthracnose. Anthracnose infection score, leaf length, leaf width, length of fifth internode, length of petiole, plant vigour, canopy height and canopy width were recorded. Data on number of plants emerging; days to flowering; days to maturity; plant stands at harvest; and grain yield were also collected and analysed using R software. Phenotypic traits evaluated differed significantly among genotypes, environment and genotype by environment interaction. Seventy-five percent of phenotypic traits evaluated were positively correlated to anthracnose resistance. Highly-strong correlations to anthracnose were observed on number of days to maturity, plant stands at harvest, plant vigour and grain yield. Leaf length, leaf width, length of fifth internode, length of petiole and number of stands emerging were strongly correlated to anthracnose resistance. Additive main effects and multiplicative interaction analysis (AMMI) revealed highest contribution of environment on anthracnose infection-58.9% and grain yield -84.9% compared to genotype effects on anthracnose infection -32.7% and grain yield-15.7%. Based on these results, four traits - plant vigour, number of days to maturity, number of plant stands at harvest and grain yield - are recommended for selecting anthracnose-resistant varieties. NUA 48, NUA 64 and RWR 2154 were superior varieties, resistant to anthracnose and high yielding, while Sweet Violet and VTT 923-23-10 were most stable varieties across environments. Further on-farm research is suggested to assess their performance and identify traits preferred by farmers.