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Published on: April 17, 2015
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Identifying canopy wilting QTLs and evaluating remote sensing approaches for selecting drought-tolerant soybean
Nathaniel Burner1, Price Pius Atuah Akiina2, Qijian Song3
1Institute of Plant Breeding, Genetics, and Genomics, and Department of Crop and Soil Sciences, Univ. of Georgia, Athens, GA, USA.
Summary
Researchers identified seven quantitative trait loci (QTLs) for soybean canopy wilting (CW) under drought. Remote sensing traits correlated with CW, aiding in mapping these important drought tolerance QTLs.
Area of Science:
- Plant genetics
- Agronomy
- Crop science
Background:
- Drought is a major abiotic stress impacting soybean yield.
- Developing drought-tolerant soybean cultivars is crucial for food security.
- Quantitative trait loci (QTLs) for ultra-slow canopy wilting (CW) in PI 603535 were previously uncharacterized.
Purpose of the Study:
- To identify the quantitative trait loci (QTLs) associated with ultra-slow canopy wilting (CW) in soybean.
- To evaluate the utility of remote sensing techniques for assessing drought tolerance.
- To develop improved soybean breeding stocks for drought tolerance.
Main Methods:
- A recombinant inbred line (RIL) population from Benning x PI 603535 was evaluated under rain-fed conditions for three years.
- Canopy wilting (CW) was visually rated during drought periods.
- Aerial multispectral and thermal imagery were captured, calculating normalized difference vegetation index (NDVI) and green-based NDVI (GNDVI).
- QTL mapping was performed using CW scores and remote sensing traits as phenotypes.
Main Results:
- Normalized difference vegetation index (NDVI) and green-based NDVI (GNDVI) showed significant correlations with CW (|r|=0.42-0.44).
- Seven CW QTLs were identified across six chromosomes, with several colocalizing with NDVI and GNDVI QTLs.
- QTL identification varied across years, indicating complex genetic control of drought tolerance.
Conclusions:
- The identified QTLs provide insights into the genetic basis of soybean drought tolerance.
- Remote sensing offers a promising approach for objective and efficient drought evaluation.
- The developed slow CW RILs are valuable resources for future breeding and genetic studies.
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