气候变化领域集成服务门户(CCPortal): Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

CCPortal

DOI	10.3390/rs16010155
	Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing
	Roy, Bishal; Sagan, Vasit; Haireti, Alifu; Newcomb, Maria; Tuberosa, Roberto; Lebauer, David; Shakoor, Nadia
发表日期	2024
EISSN	2072-4292
起始页码	16
结束页码	1
卷号	16 期号:1
英文摘要	Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.
英文关键词	hyperspectral imaging; drought-stress detection; wheat genotypes; water-use efficiency; climate change adaptation in agriculture
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:001140392400001
来源期刊	REMOTE SENSING
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/304614
作者单位	Saint Louis University; Washington University (WUSTL); Saint Louis University; United States Department of Agriculture (USDA); United States Forest Service; University of Bologna; University of Arizona; Donald Danforth Plant Science Center
推荐引用方式 GB/T 7714	Roy, Bishal,Sagan, Vasit,Haireti, Alifu,et al. Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing[J],2024,16(1).
APA	Roy, Bishal.,Sagan, Vasit.,Haireti, Alifu.,Newcomb, Maria.,Tuberosa, Roberto.,...&Shakoor, Nadia.(2024).Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing.REMOTE SENSING,16(1).
MLA	Roy, Bishal,et al."Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing".REMOTE SENSING 16.1(2024).