Genomic prediction of forage nutritive value in perennial ryegrass  

作　　者：Agnieszka Konkolewska Michael Dineen Rachel Keirse Patrick Conaghan Dan Milbourne Susanne Barth Aonghus Lawlor Stephen Byrne 

机构地区：[1]Teagasc,Crop Science Department,Carlow,Ireland [2]Insight SFI Research Centre for Data Analytics,School of Computer Science,University College Dublin,Dublin,Ireland [3]VistaMilk SFI Research Centre,Moorepark,Fermoy,Co.Cork,Ireland [4]Teagasc,Grassland Science Research Department,Animal and Grassland Research and Innovation Centre,Moorepark,Fermoy,Ireland [5]Teagasc,Grassland Science Research Department,Animal and Grassland Research and Innovation Centre,Carlow,Ireland

出　　处：《Grassland Research》2024年第4期331-346,共16页草地研究(英文)

基　　金：Irish Department of Agriculture Food and the Marine,Grant/Award Number:RSF 11/S/109;Science Foundation Ireland,Grant/Award Number:16/RC/3835(VistaMilk);H2020 Marie Sklodowska-Curie Actions,Grant/Award Number:841882(GenSPaD)。

摘　　要：Background: Despite its importance to animal production potential, geneticgain for forage nutritive value has been limited in perennial ryegrass (Loliumperenne L.) breeding. The objective of this study was to phenotype a trainingpopulation and develop prediction models to assess the potential of predictingorganic matter digestibility (OMD) and neutral detergent fiber (NDF) withgenotyping-by-sequencing data.Methods: Near infra-red reflectance spectroscopy calibrations for OMD andNDF were developed and used to phenotype a spaced plant training populationof n = 1606, with matching genotype-by-sequencing data, for developinggenomic selection models. F2 families derived from the training populationwere also evaluated for OMD and NDF in sward plots and used to empiricallyvalidate prediction models.Results: Sufficient genotypic variation exists in breeding populations toimprove forage nutritive value, and spectral bands contributing to calibrationswere identified. OMD and NDF can be predicted from genomic data withmoderate accuracy (predictive ability in the range of 0.51-0.59 and 0.33-0.57,respectively) and models developed on individual plants outperform thosedeveloped from family means. Encouragingly, genomic prediction modelsdeveloped on parental plants can predict OMD in subsequent generationsgrown as competitive swards.Conclusions: These findings suggest that genetic improvement in foragenutritive value can be accelerated through the application of genomic predictionmodels.

关 键 词：grass nutritive value plant breeding precision agriculture 

分 类 号：S81[农业科学—畜牧学]