UAV-derived canopy traits as heritable proxies for seedling vigor: genetic mapping and genomic prediction in mungbean (Vigna radiata L.)

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Authors: Venkata Naresh Boddepalli, Yanben Shen, Somak Dutta, Arti Singh
Cited by: 1

Abstract

Mungbean (Vigna radiata L.) is a protein-rich legume whose crop establishment relies on early seedling vigor (SVG), a complex trait traditionally assessed by subjective visual scoring. To overcome this bottleneck, we integrated UAV-based RGB imagery, spatial field correction, multi-model GWAS, haplotype analysis, and genomic prediction to characterize SVG in the Iowa Mungbean Diversity (IMD) panel (372 genotypes, six environments). From 17 UAV-derived indices, five digital traits: canopy height (CHT), canopy coverage (CC), canopy volume index (CVI), ExGR, and NGRDI, were selected alongside manual SVG scores. Spatial correction with SpATS revealed field heterogeneity explaining 9.5-77.8% of raw phenotypic variance, underscoring the necessity of pre-analysis correction. Post-correction broad-sense heritability ranged from 0.65 (CVI) to 0.77 (CHT), comparable to manual SVG (H² = 0.72). UAV-derived CHT was validated against manual ground-truth measurements (r = 0.86, p < 0.001), confirming the reliability of the HTP platform. Multi-model GWAS (FarmCPU, BLINK, SVEN) mapped against the telomere-to-telomere Vigna radiata reference genome (Weilv-9) identified 55 unique significant SNPs across all 11 chromosomes, including 11 pleiotropic loci associated with multiple vigor components. Haplotype analysis at two major-effect QTLs on chromosomes 5 and 2 resolved favorable alleles at low population frequency (14-20%), implicating LONGIFOLIA 1-like (organ elongation) and an AP2-like ethylene-responsive transcription factor (hormone signaling) as causal candidates. Genomic prediction accuracy ranged from 0.48 to 0.67, with an augmented gBLUP+SNP model improving accuracy by up to 0.07. Three pleiotropic loci co-localized with previously reported QTLs for seed size and pod traits. These results validate UAV-derived digital traits as objective, heritable proxies for SVG and establish a framework for marker-assisted and genomic selection in mungbean.

Fields of Study & Subjects

Soybean genetics and cultivation Genetics and Plant Breeding Genetic Mapping and Diversity in Plants and Animals

Publication details

Publisher
Wiley
Publication date
29 June 2026
Document type
Preprint