Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Author:

Roy Bishal12ORCID,Sagan Vasit123ORCID,Haireti Alifu1ORCID,Newcomb Maria4ORCID,Tuberosa Roberto5ORCID,LeBauer David6ORCID,Shakoor Nadia7ORCID

Affiliation:

1. Taylor Geospatial Institute, Saint Louis, MO 63108, USA

2. Department of Earth and Atmospheric Sciences, Saint Louis University, Saint Louis, MO 63104, USA

3. Department of Computer Science, Saint Louis University, Saint Louis, MO 63104, USA

4. United States Forest Service, Forest Health Protection, Missoula, MT 59804, USA

5. Department of Agricultural and Food Sciences, University of Bologna, 40127 Bologna, Italy

6. Arizona Experiment Station, University of Arizona, Tucson, AZ 85724, USA

7. Donald Danforth Plant Science Center, Saint Louis, MO 63132, USA

Abstract

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.

Funder

Advanced Research Projects Agency-Energy (ARPA-E) within the U.S. Department of Energy

NSF/USDA

U.S. Geological Survey

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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