Abstract
Selection for wheat (Triticum aestivum L.) grain quality is often costly and time-consuming since it requires extensive phenotyping in the last phases of development of new lines and cultivars. The development of high-throughput genotyping in the last decade enabled reliable and rapid predictions of breeding values based only on marker information. Genomic selection (GS) is a method that enables the prediction of breeding values of individuals by simultaneously incorporating all available marker information into a model. The success of GS depends on the obtained prediction accuracy, which is influenced by various molecular, genetic, and phenotypic factors, as well as the factors of the selected statistical model. The objectives of this article are to review research on GS for wheat quality done so far and to highlight the key factors affecting prediction accuracy, in order to suggest the most applicable approach in GS for wheat quality traits.
Highlights
Similar results were reported for flour yield (FY) and alveograph traits, where the decrease of Genomic selection (GS) accuracy in a range of 24% to 35% was observed when comparing LOO and LFO cross-validation methods [65], and for Zeleny sedimentation, grain protein content (GPC), thousand-kernel weight (TKW), and test weight (TW) [64], suggesting that genetic composition of TP is crucial for achieving accurate genomic predictions
It has been proved that incorporating NIR and nuclear magnetic resonance (NMR) data into the multitrait approach increases the accuracy of GS for some wheat quality traits [56]
Genomic selection can be helpful in predicting the performance of lines in early generations and preselecting high-performing lines, boosting trait stability, and efficiently selecting superior genotypes for wheat quality traits
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Studies forCurrently, traits such as grain yield, Fusarium head blight, and brown rus the majority of researchers of GS in wheat consider grainstripe yield and disease resistance as key traits for successful wheat production [17,18,19,20,21] Such a strong focus on sistance, plant height, days to heading, and preharvest sprouting (PHS) tolerance is g grain yield is understandable from a point of view where grain yield is not improving fast by Rutkoski et al [23]. Despite their importance in the context of nutrition, research o enough to fill the gap between production and projected demands in the near future [22]. In this Models context, the objectives of the present study are to
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