Department of Crop Botany, Bangladesh Agricultural University, Mymensingh, Bangladesh.
Department of Crop Botany, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, Bangladesh.
PeerJ. 2022 Nov 25;10:e14421. doi: 10.7717/peerj.14421. eCollection 2022.
Drought stress is a major issue impacting wheat growth and yield worldwide, and it is getting worse as the world's climate changes. Thus, selection for drought-adaptive traits and drought-tolerant genotypes are essential components in wheat breeding programs. The goal of this study was to explore how spectral reflectance indices (SRIs) and yield traits in wheat genotypes changed in irrigated and water-limited environments. In two wheat-growing seasons, we evaluated 56 preselected wheat genotypes for SRIs, stay green (SG), canopy temperature depression (CTD), biological yield (BY), grain yield (GY), and yield contributing traits under control and drought stress, and the SRIs and yield traits exhibited higher heritability (H) across the growing years. Diverse SRIs associated with SG, pigment content, hydration status, and aboveground biomass demonstrated a consistent response to drought and a strong association with GY. Under drought stress, GY had stronger phenotypic correlations with SG, CTD, and yield components than in control conditions. Three primary clusters emerged from the hierarchical cluster analysis, with cluster I (15 genotypes) showing minimal changes in SRIs and yield traits, indicating a relatively higher level of drought tolerance than clusters II (26 genotypes) and III (15 genotypes). The genotypes were appropriately assigned to distinct clusters, and linear discriminant analysis (LDA) demonstrated that the clusters differed significantly. It was found that the top five components explained 73% of the variation in traits in the principal component analysis, and that vegetation and water-based indices, as well as yield traits, were the most important factors in explaining genotypic drought tolerance variation. Based on the current study's findings, it can be concluded that proximal canopy reflectance sensing could be used to screen wheat genotypes for drought tolerance in water-starved environments.
干旱胁迫是影响全球小麦生长和产量的主要问题，随着世界气候变化，情况变得越来越糟。因此，选择耐旱适应性特征和耐旱基因型是小麦育种计划的重要组成部分。本研究的目的是探讨在灌溉和水分限制环境下，小麦基因型的光谱反射率指数（SRIs）和产量性状如何变化。在两个小麦生长季节，我们评估了 56 个预先选择的小麦基因型的 SRIs、绿叶持续时间（SG）、冠层温度下降（CTD）、生物产量（BY）、籽粒产量（GY）和产量构成性状，在对照和干旱胁迫下，SRIs 和产量性状在生长年份表现出较高的遗传力（H）。与 SG、色素含量、水合状态和地上生物量相关的不同 SRIs 表现出对干旱的一致响应，并与 GY 有很强的关联。在干旱胁迫下，GY 与 SG、CTD 和产量构成因素的表型相关性强于对照条件。层次聚类分析得出了三个主要聚类，聚类 I（15 个基因型）的 SRIs 和产量性状变化最小，表明其耐旱性相对较高，而聚类 II（26 个基因型）和聚类 III（15 个基因型）则较低。基因型被适当地分配到不同的聚类中，线性判别分析（LDA）表明聚类之间存在显著差异。发现主成分分析中前五个成分解释了 73%的性状变异，植被和水分指数以及产量性状是解释基因型耐旱性变异的最重要因素。基于本研究的结果，可以得出结论，近地表冠层反射率感应可用于在缺水环境中筛选耐旱性小麦基因型。
