Evaluation of Wheat Genotypes under Water Regimes Using Hyperspectral Reflectance and Agro-Physiological Parameters via Genotype by Yield*Trait Approaches in Sakha Station, Delta, Egypt

Mohamed A. Darwish, Ahmed F. Elkot, Ahmed M. S. Elfanah, Adel I. Selim, Mohamed M. M. Yassin, Elsayed A. Abomarzoka, Maher A. El-Maghraby, Nazih Y. Rebouh and Abdelraouf M. Ali ()
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Mohamed A. Darwish: Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Ahmed F. Elkot: Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Ahmed M. S. Elfanah: Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Adel I. Selim: National Authority for Remote Sensing and Space Sciences (NARSS), Elnozha El-Gedidah, Cairo 11843, Egypt
Mohamed M. M. Yassin: Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Elsayed A. Abomarzoka: Crop Physiology Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Maher A. El-Maghraby: Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt
Nazih Y. Rebouh: Department of Environmental Management, RUDN University, 6 Miklukho-Maklaya St., 117198 Moscow, Russia
Abdelraouf M. Ali: National Authority for Remote Sensing and Space Sciences (NARSS), Elnozha El-Gedidah, Cairo 11843, Egypt

Agriculture, 2023, vol. 13, issue 7, 1-20

Abstract: Drought is an environmental abiotic stress that diminishes wheat production worldwide. In the present study, we evaluated fifty bread wheat genotypes (arranged in alpha lattice design) under two main water regimes, water-deficit (two surface irrigations) and well-watered (four irrigations), at different sites in two consecutive cropping seasons, 2019/20 and 2020/21. To identify the drought-tolerant genotypes, utilized several selection/phenotyping criteria, including agronomic traits, e.g., grain yield (GY) and yield components (SM); physiological parameters such as canopy temperature (CT), leaf transpiration rate (TRN), intercellular CO 2 concentration (INCO); spectral reflectance indices, e.g., Leaf Chlorophyll Index (LCI), curvature index (CI), and normalized difference vegetation index (NDVI); and stress tolerance indices (STI) were determined concurrently with the grain yield. The results revealed significant differences ( p ≤ 0.01) among the environments, genotypes, and their interaction for grain yield (GY), days to heading (DH), days to maturity (DM), grain filling period (GFP), grain filling rate (GFR), Normalized difference vegetation index (NDVI), plant height (PH), and spikes per square meter (SM). The genotype plus genotype by environment (GGE) and genotype by yield*trait (GYT) biplot techniques indicated that Genotype 37 (Sakha 95) and Genotype 45 performed best under well-watered and water-deficit environments. Furthermore, the same genotypes were the best from the genotype by stress tolerance indices (GSTI) approach view. Genotype 37 (Sakha 95) was superior to the GYT selection method, with physiological parameters and spectral reflectance indices. Likewise, we can identify this genotype as low-water-tolerant based on GSTI, GYT, and SRI results and recommend involving it in the drought breeding program.

Keywords: digital agriculture; spectral reflectance indices; drought tolerance; remote sensing; wheat breeding; stress tolerance indices (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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