4.7 Article

Optimal Contribution Selection Improves the Rate of Genetic Gain in Grain Yield and Yield Stability in Spring Canola in Australia and Canada

Journal

PLANTS-BASEL
Volume 12, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/plants12020383

Keywords

genetic gain; overall performance; grain yield; yield stability; canola; rapeseed; Brassica napus; pedigree BLUP; estimated breeding values; optimal contributions selection

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Crop breeding needs to achieve higher rates of genetic gain in grain yield and yield stability to meet future food demands in a changing climate. Optimal contributions selection based on an index of key economic traits can increase the rate of genetic gain while minimizing population inbreeding. This study applied optimal contributions selection in a global spring canola breeding program and achieved rapid genetic gain in grain yield and other traits.
Crop breeding must achieve higher rates of genetic gain in grain yield (GY) and yield stability to meet future food demands in a changing climate. Optimal contributions selection (OCS) based on an index of key economic traits should increase the rate of genetic gain while minimising population inbreeding. Here we apply OCS in a global spring oilseed rape (canola) breeding program during three cycles of S-0,S-1 family selection in 2016, 2018, and 2020, with several field trials per cycle in Australia and Canada. Economic weights in the index promoted high GY, seed oil, protein in meal, and Phoma stem canker (blackleg) disease resistance while maintaining plant height, flowering time, oleic acid, and seed size and decreasing glucosinolate content. After factor analytic modelling of the genotype-by-environment interaction for the additive effects, the linear rate of genetic gain in GY across cycles was 0.059 or 0.087 t ha(-1) y(-1) (2.9% or 4.3% y(-1)) based on genotype scores for the first factor (f(1)) expressed in trait units or average predicted breeding values across environments, respectively. Both GY and yield stability, defined as the root-mean-square deviation from the regression line associated with f(1), were predicted to improve in the next cycle with a low achieved mean parental coancestry (0.087). These methods achieved rapid genetic gain in GY and other traits and are predicted to improve yield stability across global spring canola environments.

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