Leveraging intercropping system and genomics for breeding of allogamous crops towards sustainable agriculture

Abstract

As agriculture transitions toward sustainable systems, breeding must prioritize not only yield but also persistence and ecological function. This study integrates whole-genome re-sequencing (WGR) and near-infrared spectroscopy (NIRS) phenotyping to inform breeding strategies in allogamous forage and cover crops within intercropping systems. We developed genomic resources for Trifolium incarnatum by resequencing 45 primary accessions at ~50x coverage, identifying 542,790 high-confidence SNPs. Additional replicates were sequenced at ~2x coverage, revealing approximately 2,411,468 high-confidence SNPs. The 2x and 50x datasets were aligned and annotated separately, providing high-quality SNP catalogs that can serve as a foundation for reduced-representation, low-cost genotyping platforms in the future. Population structure and genetic diversity analyses revealed partial regional clustering but have low genetic differentiation and a core allele set shared across improvement levels. Concurrently, we evaluated 26 Alfalfa (Medicago sativa) genotypes intercropped with Kernza® (Thinopyrum intermedium) across four U.S. locations. Forage quality traits, including crude protein (CP), lignin, ADF, NDF, and dNDF48 were assessed using NIRS and analyzed via mixed models. Although environmental effects dominated trait variation, consistent genetic signals in CP and lignin highlight potential for selection. Principal component analysis (PCA) revealed key trade-offs between nutritional (protein-related) and structural (fiber) traits. Understanding the interplay and trade-offs among these traits is essential for informed breeding decisions in alfalfa- Kernza® intercropping systems. Together, these findings establish both a genomic foundation and phenomics insight for the improvement of these agriculturally important legume species.