AI-assisted Image-Based Phenotyping Reveals Genetic Architecture of Pod Traits in Mungbean (Vigna radiata L.)

Abstract

Abstract Mungbean ( Vigna radiata (L.) R. Wilczek) is a vital source of digestible proteins and is well-suited for the plant-based protein industry. In this study, we analyzed pod morphological traits in the Iowa Mungbean Diversity (IMD) panel with 372 genotypes (2022-23) with AI-assisted image phenotyping using 2,418 pod images. Pod morphological traits were extracted using deep learning image analysis, achieving excellent agreement with manual measurements (r>0.96 for pod length and seed per pod). Four complementary GWAS models identified 45 significant SNPs associated with pod curvature, length, width, and seed per pod traits. Notably, a significant SNP (5_35265704) on chromosome 1 was linked to pod dimensional traits, length, width, and curvature. A candidate gene, Vradi01g00001116 , was located within the linkage disequilibrium (LD) region of this SNP, is part of the GH3 gene family, and has an Arabidopsis ortholog ( AT4G27260 ) known for influencing organ elongation, pod, and seed development. Another SNP, 5_210437 on chromosome 2, has been found to be significantly associated with both pod length and seed per pod. A candidate gene, Vradi02g00003971 , located in the LD region of this SNP, belongs to the potassium transporter family and shares homology with the HAK5 gene family ( AT4G13420 ) in Arabidopsis , which influences pod and seed growth. Image-based measurements achieved genomic prediction accuracies ranging from 0.61 to 0.85 across various traits, exhibiting an improvement of 12-22% over manual methods. These results demonstrate the potential of AI-assisted phenomics integrated with genomic tools to accelerate selection for improved pod architecture in mungbean breeding programs across the Midwestern United States and globally.

Plant phenotyping relevance

AI画像解析による莢形態形質の抽出と手測定との技術検証が研究の中心であり、GWAS応用も行っているため含める。

Code and data availability

The supplied blocks describe the AI-assisted pod phenotyping pipeline (2,418 scanned pod images, U-Net/DeepLabV3 models, GWAS and genomic prediction) but contain no data or code availability statement, no public deposit of images, phenotypic datasets, trained models, or author analysis code. The LIS and TAIR URLs cited

No evidence-backed public reproduction asset is currently recorded.