Hierarchical Bayesian Modeling for Flexible Experiments in Decentralized Participatory Plant Breeding

Abstract

Decentralized participatory plant breeding (PPB) is a method for creating new varieties adapted to agroecology based systems. Selection is decentralized in the target environments and relies on collaboration between farmers, Non Governmental Organizations (NGOs), and researchers. In the wheat PPB project studied, the decentralization was extensive as each farmer participating in the project performed the selection experiment on his farm. This led to unbalanced designs with few residual degrees of freedom available for the within‐farm comparison of means. We investigated a hierarchical Bayesian modeling of trials’ residual variances using information from a large network of environments (48 farm × year). We found that the hierarchical approach allowed for robust results leading to reliable mean comparisons on farms. For each variable studied, differences among breeding populations within farms were large enough to carry out selection. This was possible because the farms shared a common experimental design and the number of environments in the network was large. Our approach is useful for farmers who cannot set up replicated trials on their farm but wish to participate in the program. The only constraint being the replication of at least one control on each farm, farmers are free to choose the populations they wish to test. This allows for the evaluation and selection of a wide range of diversity over the network of farms. This approach could also be interesting in other types of decentralized unreplicated trials such as those encountered in genetic resources screening or in multiple environments breeding.

Agronomic Evaluation of Bread Wheat Varieties from Participatory Breeding: A Combination of Performance and Robustness

“…This is the case of the bread wheat PPB program that was studied here. In previous studies, we showed that on-farm evaluation and selection of populations can be organized through specific experimental devices that have been adapted to fit to a large number of small size trials with limited replication of entries within and among trials [6,7]. This is very flexible and convenient for the farmers, as only a small number of common controls are replicated within and among farms, and the rest of entries are populations chosen by each farmer on their farm.…”

“…Indeed, on-farm evaluation and selection of heterogeneous populations lead to methodological challenges in the set-up of adapted experimental designs and in the analyses of data, because each on-farm trial is often of small size, with a limited number of plots, and a low level of replication [6,7]. Several PPB programs have therefore developed or adapted original designs and methods that allow farmers to compare several populations on their farms, to select the most adapted and to pursue the process over several years [6][7][8][9]. To facilitate the implementation of experimental designs suitable for on farm evaluation and selection and the analysis of data generated by PPB programs, an R package, PPBstats, is under development to implement many of these statistical analyses for agronomic and molecular data, organoleptic tests, and seed circulation networks [10].…”

“…Little literature reports on all aspects of the PPB programs, from the emergence of new organization among actors, to specific experimental designs and statistical methods developed, and to populations or varieties developed and cultivated by farmers in their fields for production. Such a PPB approach has been applied on bread wheat in France since 2006 in a partnership among the research team DEAP (Diversity, Evolution, and Adaptation of Population) at the Quantitative Genetics and Evolution Lab (GQE-Le Moulon), in France and groups of the farmers' organization Réseau Semences Paysannes (RSP) [12,13] In this program, specific protocols, experimental designs, and statistical methods have been developed for on-farm trials [6,7]. Moreover, a collective organization among farmers, facilitators, and the research team has been set up [13].…”

Semences et transition agroécologique : initiatives paysannes et sélection participative comme innovations de rupture

“…Cependant les scientifiques avaient besoin de faire des analyses statistiques pour comparer les populations au sein d'une ferme et entre fermes. Après un ou deux ans de tâtonnements et discussions, un compromis a été trouvé qui repose sur l'optimisation de quelques témoins répétés et le développement de nouvelles méthodes d'analyse statistique (approche bayésienne, Rivière et al, 2015a). De nombreux exemples pourraient être donnés de ces efforts de co-construction.…”

“…Soc. 25, S55-S59 (2017) S57 populations, construction de mélanges...) (Rivière et al, 2013(Rivière et al, , 2015a.…”