Spectral Reflectance Indices’ Performance to Identify Seawater Salinity Tolerance in Bread Wheat Genotypes Using Genotype by Yield*Trait Biplot Approach

Author:

Elfanah Ahmed M. S.12ORCID,Darwish Mohamed A.1,Selim Adel I.3,Shabana Mahmoud M. A.4,Elmoselhy Omnya M. A.1,Khedr Rania A.5,Ali Abdelraouf M.36ORCID,Abdelhamid Magdi T.78ORCID

Affiliation:

1. Wheat Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt

2. Food Crops Research Institute, Yunnan Academy of Agricultural Sciences, Kunming 650205, China

3. National Authority for Remote Sensing and Space Sciences (NARSS), Elnozha El-Gedidah, Cairo 11843, Egypt

4. Soils, Water and Environment Research Institute, Agricultural Research Center, Giza 12112, Egypt

5. Crops Physiology Research Department, Field Crops Research Institute, Agricultural Research Center, Giza 12619, Egypt

6. Department of Environmental Management, Institute of Environmental Engineering, People’s Friendship University of Russia (RUDN University), 6 Mikluko–Maklaya St., 117198 Moscow, Russia

7. Botany Department, National Research Centre, 33 El Behouth Steet, Dokki, Cairo 12622, Egypt

8. Department of Soil and Crop Sciences, Texas A&M University, 370 Olsen Blvd., College Station, TX 77843-2474, USA

Abstract

Salinity stress harms crop yield and productivity worldwide. This study aimed to identify genotypes with higher grain yield and/or salinity tolerance from forty bread wheat genotypes evaluated under seawater diluted at 4.0, 8.0, or 12.0 dS/m or control (0.4 dS/m) in the 2019/20 and 2020/21 seasons. Six elite genotypes, namely 6, 16, 31, 33, 34, and 36, were chosen and tested in a lysimeter under diluted seawater stress in 2020/21. The results showed significant differences (p ≤ 0.01) among the genotypes for the traits grain yield (GY), harvest index (HI), chlorophyll content index (CCI), chlorophyll fluorescence parameter Fv/Fm, and their interaction with salinity treatments. Additionally, significant differences (p ≤ 0.01) were detected among ten genotypes for all agronomic traits along with spectral reflectance indices (SRI), e.g., curvature index (CI), normalized difference vegetation index (NDVI), triangular vegetation index (TVI), modified chlorophyll absorption reflectance index (MCARI), and their interaction with salinity treatments. Genotype by traits (GT) and genotype by yield*trait (GYT) biplots are useful for genotypes screening and selection based on grain yield and other associated traits (agronomic, physiological traits, and spectral reflectance indices combinations) as well as genotypes by stress tolerance indices (GSTI). In conclusion, this study identified that genotypes 6, 16, 31, 33, 34, and 36 in the 2019/20 season and genotypes 2 and 1 performed better than Kharchia 65 and Sakha 8 in the 2020/21 season, which detected as superior genotypes and might be recommended for sowing and/or inclusion in the breeding program in salt-affected soils. It was possible to draw the conclusion that spectral reflectance indices were efficient at identifying genotypic variance.

Publisher

MDPI AG

Subject

Agronomy and Crop Science

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