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利用基因型×产量*性状双标图技术,通过高光谱反射率和农业生理性状对耐盐小麦基因型进行田间鉴定。

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

作者信息

Elfanah Ahmed M S, Darwish Mohamed A, Selim Adel I, Elmoselhy Omnya M A, Ali Abdelraouf M, El-Maghraby Maher A, Abdelhamid Magdi T

机构信息

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

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

出版信息

Front Plant Sci. 2023 Aug 2;14:1165113. doi: 10.3389/fpls.2023.1165113. eCollection 2023.

Abstract

INTRODUCTION

Salinity 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.

METHODS

Therefore, 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.

RESULTS

The results presented significant differences (P≤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.

DISCUSSION

Therefore, 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.

摘要

引言

盐度是全球范围内降低粮食产量的非生物障碍。盐渍化是由自然条件(如气候变化)或人类活动(如灌溉和管理不善)导致的。为应对盐度问题,需改善作物生长环境或利用作物/小麦育种(通过表型分析),特别是在大面积田间条件下。例如,埃及约33%的种植面积受盐度影响。

方法

因此,本研究于2019/20和2020/21季节在埃及北部的萨卡研究站,在对比盐度的田间条件下对40个面包小麦基因型进行了评估。为鉴定耐盐基因型,测定了生理参数,如Fv/Fm、CCI、Na⁺和K⁺,光谱反射指数(SRIs),如NDVI、MCARI和SR,并根据测试年份非盐渍土壤和盐渍土壤地点的籽粒产量估算了耐盐指数。同时对这些性状(参数)和籽粒产量进行分析以生成GYT双标图。

结果

结果表明,在四个环境中评估的籽粒产量(GY)在环境、基因型及其相互作用之间存在显著差异(P≤0.01)。在对比盐度环境下的第一季,性状、籽粒产量(GY)、株高(PH)、收获指数(HI)、叶绿素含量指数(CCI)、叶绿素荧光参数Fv/Fm、归一化植被指数(NDVI)存在显著差异。此外,在环境、基因型及其相互作用之间,籽粒产量以及光谱反射指数(SRIs),如蓝/绿指数(BIG2)、曲率指数(CI)、归一化植被指数(NDVI)、修正简单比值(MSR)也存在显著差异。根据基因型加基因型×环境(GGE)方法,基因型34和1在盐渍化地点表现最佳。从基因型×胁迫耐受指数(GSTI)双标图来看,基因型1和29以及基因型34表现最佳。从基因型×产量*性状(GYT)方法结合光谱反射指数来看,基因型1表现最佳。

讨论

因此,根据GSTI和SRIs的GYT结果,我们可以将基因型1鉴定为耐盐基因型,并建议其参与受盐影响土壤的盐度育种计划。总之,光谱反射指数能有效识别基因型差异。

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