Evaluating Selection of a Quantitative Trait: Snow Mold Tolerance in Winter Wheat. Issue 1 (1st October 2019)

• Record Type: Journal Article
• Authors: Kruse, Erika B.; Esvelt Klos, Kathy L.; Marshall, Juliet M.; Murray, Timothy D.; Ward, Brian P.; Carter, Arron H.
• Is Part Of: Agrosystems, geosciences & environment. Volume 2:Issue 1(2019)
• Page Start: 1
• Page End: 8
• Publication Date: 2019-10-01
• Subjects: Agriculture -- Periodicals; Agriculture -- Environmental aspects -- Periodicals; Soil science -- Periodicals; Food science -- Periodicals; Food science; Agriculture; Agriculture -- Environmental aspects; Electronic journals; Periodicals; 630
• DOI: 10.2134/age2019.07.0059
• Languages: English
• ISSNs: 2639-6696

Abstract

Abstract : Core Ideas: Six quantitative trait loci for snow mold tolerance were detected in a winter wheat recombinant inbred line population. Marker‐assisted selection to incorporate QTL is unlikely to help breed for highly quantitative traits. Genomic selection could replace initial phenotyping for quantitative traits. Selection for snow mold tolerance (SMT) in winter wheat ( Triticum aestivum L.) is complicated by the influence of numerous quantitative trait loci (QTL) and of environmental conditions. The goals of this study were to identify QTL for SMT, determine the effectiveness of marker‐assisted selection (MAS), and model the effectiveness of genomic prediction for SMT. Quantitative trait loci analysis of a recombinant inbred line (RIL) subpopulation, derived from a cross between Xerpha and Münstertaler, detected six unique QTL. Progeny from the same cross were advanced by MAS and compared with the unselected subpopulation to evaluate the efficacy of MAS. No significant difference was found between the SMT means ( p = 0.41). Similarly, genomic selection had very poor accuracy (−0.07) in the Xerpha–Münstertaler (XM) RIL subpopulation. This contrasts with the apparent effectiveness of genomic selection (0.65) in a Finch–Eltan RIL population, also evaluated for SMT. The failure of selection tools to improve SMT in the XM population is likely due to the challenges of rating a quantitative trait that requires highly specific environmental conditions for phenotype development.