How Do Drought, Heat Stress, and Their Combination Impact Stem Reserve Mobilization in Wheat Genotypes?

Author:

Vaezi Behrouz12,Arzani Ahmad2ORCID,Roberts Thomas H.34ORCID

Affiliation:

1. Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Dryland Agricultural Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Gachsaran 7589172050, Iran

2. Department of Agronomy and Plant Breeding, College of Agriculture, Isfahan University of Technology, Isfahan 8415683111, Iran

3. School of Life and Environmental Sciences, Faculty of Science, University of Sydney, Camperdown, NSW 2006, Australia

4. Sydney Institute of Agriculture, University of Sydney, Eveleigh, NSW 2015, Australia

Abstract

Drought and heat stresses represent the primary agricultural challenges in arid and semiarid regions globally. In wheat, among the most vulnerable stages to these stresses is the grain-filling process. This critical phase relies heavily on photosynthesis during the late growth stage and the mobilization of stem reserves. This study evaluated 60 spring wheat lines from the CIMMYT-Mexico Core Germplasm (CIMCOG) panel alongside four Iranian wheat cultivars under normal, drought, heat, and combined drought and heat stress conditions in two growing seasons. Several agronomic traits, including those associated with stem reserve mobilization, were assessed during the study. The combined analysis of variance revealed significant impacts of both independent and combined drought and heat stresses on the measured traits. Moreover, these stresses influenced the inter-relationships among the traits. High-yielding genotypes were identified through a combination of ranking and genotype and genotype by environment (GGE) biplot analysis. Among the top 40 genotypes, 21 were identified as environment-specific, while 19 remained common across at least two environments. Environmental dependence of grain yield responses to the sinks including stem reserve mobilization and spike reserve mobilization was found. Utilizing a machine learning algorithm, a regression tree analysis unveiled specific traits—including grain filling and canopy temperature—that contributed significantly to the high-yielding features of the identified genotypes under the various environmental conditions. These traits can serve as indirect selection criteria for enhancing yield under stressful conditions and can also be targeted for manipulation to improve wheat stress tolerance.

Publisher

MDPI AG

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3