Identifying canopy wilting QTLs and evaluating remote sensing approaches for selecting drought-tolerant soybean

Authors: BURNER, NATHANIEL - University Of Georgia; AKIINA, PRICE - University Of Wyoming; Song, Qijian; HARRIS, DONNA - University Of Wyoming; LI, ZENGLU - University Of Georgia

Submitted to: Theoretical and Applied Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/3/2025
Publication Date: 10/14/2025
Citation: Burner, N., Akiina, P., Song, Q., Harris, D., Li, Z. 2025. Identifying canopy wilting QTLs and evaluating remote sensing approaches for selecting drought-tolerant soybean. Theoretical and Applied Genetics. 138(11). Article e276. https://doi.org/10.1007/s00122-025-05063-y.
DOI: https://doi.org/10.1007/s00122-025-05063-y

Interpretive Summary: Drought is the most damaging environmental stress for soybean production, causing significant yield losses and financial setbacks. However, progress in developing drought-tolerant soybean cultivars has been limited due to the complex genetic nature of drought tolerance and challenges in accurate phenotyping. This study addresses these gaps by investigating the genetic basis of the ultra-slow canopy wilting (CW) trait in soybean using a population derived from the cross of an ultra-slow canopy wilting parent and a high canopy wilting parent. Over three years of field testing under natural drought conditions, the study identified seven genomic regions associated with CW, including a major region on chromosome 3. Importantly, remote sensing metrics showed moderate correlations with CW, suggesting their potential as efficient, non-destructive phenotyping tools. While molecular markers determined for CW and remote sensing traits were inconsistently detected across years, their co-localization in genome supports the genetic link between drought response and canopy traits. These findings highlight the genetic complexity of drought tolerance and the potential of remote sensing to enhance breeding efficiency. The slow CW lines developed in this study can serve as valuable breeding stocks for improving drought resilience in soybean. Researchers, breeders, and agricultural stakeholders can use these insights to increase phenotyping efficiency and accelerate the development of more drought-tolerant soybean varieties.

Technical Abstract: Drought is the most damaging abiotic stress for soybean yield, however, there have been few released cultivars with improved drought tolerance. PI 603535 previously was identified as an ultra-slow canopy wilting (CW) line in a genome-wide association study but the number of quantitative trait loci (QTL) underlying this phenotype have not been determined. In this study, a recombinant inbred line (RIL) population derived from Benning × PI 603535 was evaluated for three years under rain-fed conditions. CW was rated following extended periods of drought when CW variation was present. Aerial multispectral and thermal imagery was also captured in conjunction with ratings to explore the feasibility of implementing remote sensing to improve the efficiency and objectivity of drought evaluations. The normalized difference vegetation index (NDVI) and green-based NDVI (GNDVI) exhibited the strong, significant correlations (|r| = 0.42-0.44) with CW across years. CW scores and the remote sensing traits were used as phenotypes for QTL mapping. Overall, CW QTLs were identified across six chromosomes in the combined analysis, with NDVI and GNDVI QTLs generally colocalizing with the CW QTLs with the highest percent variation explained (PVE). However, the QTLs were not consistently identified among individual years, highlighting the complex genetics and gene expression of drought tolerance. Gene models with annotations associated with stress responses were identified within the vicinity of the major CW QTLs. The instability and low additive effect estimates of individual QTL imply difficulty of improving drought tolerance through the selection of a few QTLs. However, the slow CW RILs developed in this study can serve as valuable breeding stocks for future drought improvement breeding efforts and genetic studies.