Comparison of different spatial strategies for sampling a core collection of natural populations of fodder crops

Abstract

Seven different strategies for sampling a core collection are compared in large collections of natural populations of two fodder crop species (Lolium perenne and Medicago truncatula) previously evaluated for agronomic traits. The first five strategies consist of random or stratified sampling methods with one level of classification of the population (classification based on agronomic traits with or without a geographic contiguity constraint, based on the country or region of origin, or on spatial structures of populations). The last one of these strategies is based on geostatistical analysis, which allows studies of the spatial pattern of genetic diversity. The two remaining strategies are based on the principal component score strategy (PCSS), which consists of maximising a distance criterion between populations, this criterion being applied to agronomic traits of the populations or to their spatial components after geostatistical analysis. The different strategies are compared using two criteria: i) their capacity to capture the phenotypic diversity of the whole collection, as measured by the Shannon index; ii) their ability to restore the spatial structuration of the initial collection, measured by distance between maps for agronomic traits. The comparisons for the two species show that strategies that take into account spatial structuration of diversity give the best results for both criteria.