4.5 Article

Response of white clover genotypes to evaluation environments of dense and spaced planting, and implications for selection

Journal

EUPHYTICA
Volume 111, Issue 2, Pages 111-120

Publisher

SPRINGER
DOI: 10.1023/A:1003898913594

Keywords

forage yield; genetic correlations; genotype x environment interaction; selection efficiency; seed yield; Trifolium repens

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Twelve genotypes were grown for two years as monocultures in the evaluation environments (EE) of spaced planting (SP) and dense planting (DP). Dry matter (DM) yield, seed yield and their contributing traits were recorded. The environments were compared for: i) genotype performance, and selection efficiency for the target environment of DP, and ii) estimates of genetic correlations between traits. DP was obtained by close transplanting of clonal cuttings. EE x G interaction occurred for DM yield over harvests, and stolon density, petiole length, inflorescence production and number of florets per inflorescence averaged over repeated measurements. Interaction effects leading to relatively higher DM yield in SP tended to be associated positively with those for the other traits and featured the genotypes with greater ability to colonize bare soil by stolon production. The interaction effects decreased with time and generally disappeared (p < 0.05) by the end of the experiment, when the environments reached a similar DM yield and stolon density. EE x G interaction also occurred for seed yield (p < 0.08), recorded at the second year. Indirect selection in SP for performance in DP was predicted to be less efficient for DM yield (-40%), seed yield (-23%) and the other traits subject to EE x G interaction, compared with direct selection in DP. Evaluation under SP led to identification of several genetic correlations that were not confirmed under DP. DP compared with the traditional SP evaluation technique is more labour-demanding but allows for i) increasing the selection efficiency and/or decreasing the time needed for a reliable evaluation, and ii) obtaining a more reliable estimation of genetic correlations for ordinary agricultural environments.

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