Hyperspectral reflectance and agro-physiological traits for field identification of salt-tolerant wheat genotypes using the genotype by yield*trait biplot technique

被引:2
|
作者
Elfanah, Ahmed M. S. [1 ,2 ]
Darwish, Mohamed A. [1 ]
Selim, Adel I. [3 ]
Elmoselhy, Omnya M. A. [1 ]
Ali, Abdelraouf M. [3 ,4 ]
El-Maghraby, Maher A. [1 ]
Abdelhamid, Magdi T. [5 ,6 ]
机构
[1] Agr Res Ctr, Field Crops Res Inst, Wheat Res Dept, Giza, Egypt
[2] Yunnan Acad Agr Sci, Food Crops Res Inst, Kunming, Peoples R China
[3] Natl Author Remote Sensing & Space Sci NARSS, Cairo, Egypt
[4] RUDN Univ, Peoples Friendship Univ Russia, Inst Environm Engn, Dept Environm Management, Moscow, Russia
[5] Natl Res Ctr, Bot Dept, Cairo, Egypt
[6] Texas A&M Univ, Dept Soil & Crop Sci, College Stn, TX 77843 USA
来源
关键词
salinity tolerance indices; bread wheat; GGE biplots; GYT biplots; physiological traits; hyperspectral reflectance indices; LEAF PIGMENT CONTENT; SPECTRAL REFLECTANCE; SALINITY TOLERANCE; DROUGHT RESISTANCE; STRESS; SELECTION; INDEXES; ANTIOXIDANT; PARAMETERS; CULTIVARS;
D O I
10.3389/fpls.2023.1165113
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
IntroductionSalinity is the abiotic obstacle that diminishes food production globally. Salinization causes by natural conditions, such as climate change, or human activities, e.g., irrigation and derange misuse. To cope with the salinity problem, improve the crop environment or utilize crop/wheat breeding (by phenotyping), specifically in spread field conditions. For example, about 33 % of the cropping area in Egypt is affected by salinity. MethodsTherefore, this study evaluated forty bread wheat genotypes under contrasting salinity field conditions across seasons 2019/20 and 2020/21 at Sakha research station in the north of Egypt. To identify the tolerance genotypes, performing physiological parameters, e.g., Fv/Fm, CCI, Na+, and K+, spectral reflectance indices (SRIs), such as NDVI, MCARI, and SR, and estimated salinity tolerance indices based on grain yield in non-saline soil and saline soil sites over the tested years. These traits (parameters) and grain yield are simultaneously performed for generating GYT biplots. ResultsThe results presented significant differences (P & LE;0.01) among the environments, genotypes, and their interaction for grain yield (GY) evaluated in the four environments. And the first season for traits, grain yield (GY), plant height (PH), harvest index (HI), chlorophyll content index (CCI), chlorophyll fluorescence parameter Fv/Fm, normalized difference vegetation index (NDVI) in contrasting salinity environments. Additionally, significant differences were detected among environments, genotypes, and their interaction for grain yield along with spectral reflectance indices (SRIs), e.g., Blue/Green index (BIG2), curvature index (CI), normalized difference vegetation index (NDVI), Modified simple ratio (MSR). Relying on the genotype plus genotype by environment (GGE) approach, genotypes 34 and 1 are the best for salinity sites. Genotypes 1 and 29 are the best from the genotype by stress tolerance indices (GSTI) biplot and genotype 34. Genotype 1 is the best from the genotype by yield*trait (GYT) method with spectral reflectance indices. DiscussionTherefore, we can identify genotype 1 as salinity tolerant based on the results of GSTI and GYT of SRIs and recommend involvement in the salinity breeding program in salt-affected soils. In conclusion, spectral reflectance indices were efficiently identifying genotypic variance.
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页数:15
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