Hasan Md Mehedi, Mia Md Abdul Baset, Ahmed Jalal Uddin, Karim M Abdul, Islam A K M Aminul, Mohi-Ud-Din Mohammed
Department of Crop Botany, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur-1706, Bangladesh.
Department of Crop Botany and Tea Production Technology, Sylhet Agricultural University, Sylhet-3100, Bangladesh.
Heliyon. 2024 Sep 27;10(19):e38623. doi: 10.1016/j.heliyon.2024.e38623. eCollection 2024 Oct 15.
Elevated atmospheric heat is considered as one of the bottlenecks for global wheat production. Screening potential wheat genotypes against heat stress and selecting some suitable indicators to assist in understanding thermotolerance could be crucial for sustaining wheat cultivation. Accordingly, 80 diverse bread wheat genotypes were evaluated in controlled lab condition by imposing a week-long heat stress (35/25 C D/N) at the seedling stage. The response of heat stress was evaluated using multivariate analysis techniques on 20 morpho-physiological traits. Results showed significant variations in the studied traits due to the imposition of heat stress. Eleven seedling traits that contributed significantly to the genotypic variability were identified using principal component analysis (PCA). A substantial correlation between most of the selected seedling attributes was observed. Hierarchical cluster analysis identified three distinct clusters among the tested wheat genotypes. Cluster 1, consisting of 33 genotypes, exhibited the highest tolerance to heat stress, followed by Cluster 2 (18 genotypes) with moderate tolerance and Cluster 3 (29 genotypes) showing susceptibility. Linear discriminant analysis (LDA) approved that nearly 93 % of the wheat genotypes were appropriately ascribed to each cluster. The squared distance analysis confirmed the distinct nature of the clusters. Using multi-trait genotype-ideotype distance index (MGIDI), all 12 identified tolerant genotypes (BG-30, BD-468, BG-24, BD-9908, BG-32, BD-476, BD-594, BD-553, BD-488, BG-33, BD-495, and AS-10627) originated from Cluster 1. Selection gain in MGIDI analysis, broad-sense heritability, and multiple linear regression analysis together identified shoot and root dry and fresh weights, chlorophyll contents ( and total), shoot tissue water content, root-shoot dry weight ratio, and efficiency of photosystem II (PS II) as the most vital discriminatory factors explaining heat stress tolerance of 80 wheat genotypes. The identified genotypes with superior thermotolerance would offer resourceful genetic tools for breeders to improve wheat yield in warmer regions. The traits found to have greater contribution in explaining heat stress tolerance will be equally important in prioritizing future research endeavors.
大气热量升高被认为是全球小麦生产的瓶颈之一。筛选潜在的耐热小麦基因型并选择一些合适的指标来辅助理解耐热性,对于维持小麦种植至关重要。因此,在控制的实验室条件下,对80个不同的面包小麦基因型在幼苗期施加为期一周的热胁迫(35/25℃昼/夜)进行评估。使用多变量分析技术对20个形态生理性状评估热胁迫的响应。结果表明,由于热胁迫的施加,所研究的性状存在显著差异。使用主成分分析(PCA)确定了对基因型变异有显著贡献的11个幼苗性状。观察到大多数所选幼苗属性之间存在显著相关性。层次聚类分析在测试的小麦基因型中识别出三个不同的聚类。聚类1由33个基因型组成,对热胁迫表现出最高耐受性,其次是具有中等耐受性的聚类2(18个基因型)和表现出敏感性的聚类3(29个基因型)。线性判别分析(LDA)证实,近93%的小麦基因型被正确地归入每个聚类。平方距离分析证实了聚类的独特性质。使用多性状基因型-理想型距离指数(MGIDI),所有12个鉴定出的耐性基因型(BG-30、BD-468、BG-24、BD-9908、BG-32、BD-476、BD-594、BD-553、BD-488、BG-33、BD-495和AS-10627)均来自聚类1。MGIDI分析中的选择增益、广义遗传力和多元线性回归分析共同确定地上部和根部干重与鲜重、叶绿素含量(叶绿素a和叶绿素总量)、地上部组织含水量、根冠干重比以及光系统II(PS II)效率是解释80个小麦基因型耐热性的最重要判别因素。鉴定出的具有优异耐热性的基因型将为育种者提供丰富的遗传工具,以提高温暖地区的小麦产量。发现对解释耐热性有更大贡献的性状在确定未来研究重点方面同样重要。