Genomic Prediction for Grain Yield and Biotic Stress Resistance in Field Pea

Adnan RiazYongjun LiBabu Ram PandeyAlem GebremedhinShiva AziziniaShimna SudheeshZibei LinJoshua FanningGarry RosewarneMatthew J HaydenSukhjiwan Kaur^*

• Agriculture Victoria, Melbourne, Australia

Field pea (Pisum sativum L.) is a nutritionally rich pulse crop of global importance, contributing to food security, sustainable cropping systems, and the rising demand for plant-based protein. Despite progress through traditional breeding, the rate of genetic improvement in field pea remains too slow to address the challenges posed by climate change, emerging pathogens, and the increasing demand for plant-based protein. Genomic selection (GS) can accelerate the genetic improvement of field pea by reducing the time required to complete the breeding cycle and release varieties. In this study, we evaluated the potential of GS in the National Field Pea Breeding Program using historical phenotypic data from 3,199 advanced breeding lines and commercial cultivars tested for six key traits, including grain yield (GY) and resistance to biotic stresses such as ascochyta blight, bacterial blight, downy mildew, pea seed-borne mosaic virus (PSbMV), and bean leaf roll virus (BLRV). Genotypic data were obtained using a multispecies Pulse 30K SNP array. Using these historical datasets, we evaluated the effectiveness of GS through the genomic best linear unbiased prediction (GBLUP) model, both with and without genotype-by-environment (G × E) interactions. Prediction accuracy was evaluated using five-fold random and leave-one-out by year cross-validation. The average prediction accuracy for individual traits ranged from 0.21 to 0.72. Incorporating G × E interactions improved prediction accuracy for GY by 3.03%. Furthermore, bivariate GBLUP models using biotic traits with GY exhibited comparatively moderate gains in yield prediction accuracy, highlighting the advantages of using bivariate models to improve genomic prediction accuracy. These findings suggest that GS can be effectively integrated into the breeding pipeline, enabling breeders to develop new field pea varieties that combine enhanced grain yield with durable disease resistance more efficiently.