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Joining smallholder farmers’ traditional knowledge with metric traits to select better varieties of Ethiopian wheat

ربط المعرفة التقليدية لصغار المزارعين بسمات مترية لاختيار أصناف أفضل من القمح الإثيوبي
Authors: Chiara Mancini; Yosef G. Kidane; Dejene K. Mengistu; null Amit; null Letegabriel; null Tsedal; B. Tinasu; +59 Authors

Joining smallholder farmers’ traditional knowledge with metric traits to select better varieties of Ethiopian wheat

Abstract

AbstractSmallholder farming communities face highly variable climatic conditions that threaten locally adapted, low-input agriculture. The benefits of modern crop breeding may fail to reach their fields when broadly adapted genetic materials do not address local requirements. To date, participatory methods only scratched the surface of the exploitability of farmers’ traditional knowledge in breeding. In this study, 30 smallholder farmers in each of two locations in Ethiopia provided quantitative evaluations of earliness, spike morphology, tillering capacity and overall quality on 400 wheat genotypes, mostly traditional varieties, yielding altogether 192,000 data points. Metric measurements of ten agronomic traits were simultaneously collected, allowing to systematically break down farmers’ preferences on quantitative phenotypes. Results showed that the relative importance of wheat traits differed by gender and location. Farmer traits were variously contributed by metric traits, and could only partially be explained by them. Eventually, farmer trait values were used to produce a ranking of the 400 wheat varieties identifying the trait combinations most desired by farmers. The study scale and methods lead to a better understanding of the quantitative basis of Ethiopian smallholder farmer preference in wheat, broadening the discussion for the future of local, sustainable breeding efforts accommodating farmers’ knowledge.

Countries
France, Italy, France
Keywords

Metric (unit), Scale (ratio), Trait, Plant Science, Breeding, Crop, Agricultural and Biological Sciences, wheat, Genetic Diversity and Breeding of Wheat, Business, Marketing, Multidisciplinary, Geography, Ecology, Q, Statistics, R, Life Sciences, Agriculture, smallholders, Programming language, World Wide Web, climate change, Citizen journalism, Genetic Architecture of Quantitative Traits, Agricultural science, participatory approaches, Wheat, Medicine, Biotechnology, Cartography, Science, Article, Preference, FOS: Economics and business, Biochemistry, Genetics and Molecular Biology, Machine learning, plant breeding, Genetics, FOS: Mathematics, Agroforestry, Biology, Ranking (information retrieval), plant genetics, Computer science, Agronomy, FOS: Biological sciences, Viral RNA Silencing and Plant Immunity, indigenous knowledge, Mathematics

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