Nirmalaruban Rajamani, Yadav Rajbir, Sugumar Subramani, Alekya Meda, Mazumder Amit Kumar, Babu Prashanth, Kumar Manjeet, Gaikwad Kiran B, Bainsla Naresh Kumar, Singh Shiv Kumar, Mandal Pranab Kumar
Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
ICAR-National Institute of Plant Biotechnology, New Delhi, India.
BMC Plant Biol. 2025 Apr 21;25(1):493. doi: 10.1186/s12870-025-06523-9.
To ensure food security amid unpredictable climatic conditions and depleting natural resources, larger and stable genetic gain have to be realised in wheat. Adapting to these challenges requires focus on both above-ground and below-ground traits. Root anatomy reveals the functional adaptations of the root system. Despite their potential, root anatomical traits remain underutilized but hold promise as breeding targets for developing efficient and resilient crops. Our study aims to identify highly plastic wheat genotypes with superior yield stability and robust root anatomical traits, enabling them to thrive under diverse and challenging environmental conditions. By leveraging advanced multi-trait stability indices and models, we seek to provide breeders with valuable insights for enhancing wheat resilience and productivity.
In this study, 150 wheat genotypes were evaluated across three diverse environments for 10 root anatomical traits along with phenological observation and grain yield. The results show significant positive correlations between root traits, such as axial hydraulic conductance based on the central metaxylem area and total xylem area, with grain yield. This highlights the critical role of these less explored root traits in yield formation. Central metaxylem area was able to explain more than 14 per cent variation in yield over all the three environments. Although the polynomial equation did not significantly improve data fitness, it clearly indicates no sign of yield saturation at the highest CMXA levels. Modern tools like GGE and AMMI though highly effective in reducing the dimensions but do not effectively rank genotypes on the basis of different trait values simultaneously. Advanced models such as BLUP, WAASB, and multi-trait stability indices (MTSI, MGIDI, and FAI-BLUP) have the power to overcome the collinearity in different variables and use the trait values to identify superior genotypes. Genotypes such as G97 and G18 (both being derivative from the cross HDCSW18/CSW1), G112, G144 (both CIMMYT material) and G131 (31ESWYT135/CSW23) consistently exhibited high yield and stability and were picked up by all models. The study demonstrated a moderate coincidence index of 22.72% among these models, confirming the value of selected genotypes. Positive correlations between traits like axial hydraulic conductance and yield highlighted the importance of efficient water transport, nutrient exchange and hydraulic safety of crop.
Central metaxylem area based axial hydraulic conductance is explaining more than 14 per cent of variation in the yield across the environment and this along with whole root area and proper phenological adjustment can play key role in yield consolidation with high resilience under more likely uncertain production condition in the future. Three out of five genotypes consistently being picked by different stability models are derivative of HDCSW18, a variety released for conservation agriculture condition and with very strong root system and biomass. High biomass accumulation facilitated by early seeding of the genotypes with mild vernalisation requirement with high root central metaxylem area can sustain higher seed production under challenging climates and thus the findings contribute to strategies for improving wheat resilience.
为了在不可预测的气候条件和自然资源日益枯竭的情况下确保粮食安全,小麦必须实现更大且稳定的遗传增益。应对这些挑战需要关注地上和地下性状。根系解剖结构揭示了根系系统的功能适应性。尽管根系解剖性状具有潜力,但仍未得到充分利用,但有望成为培育高效且有韧性作物的育种目标。我们的研究旨在识别具有卓越产量稳定性和强健根系解剖性状的高可塑性小麦基因型,使其能够在多样且具有挑战性的环境条件下茁壮成长。通过利用先进的多性状稳定性指数和模型,我们旨在为育种者提供有价值的见解,以增强小麦的韧性和生产力。
在本研究中,对150个小麦基因型在三种不同环境下进行了评估,涉及10个根系解剖性状以及物候观测和籽粒产量。结果表明,根系性状之间存在显著正相关,例如基于中央后生木质部面积和总木质部面积的轴向导水率与籽粒产量之间的关系。这突出了这些较少被研究的根系性状在产量形成中的关键作用。中央后生木质部面积能够解释在所有三种环境下超过14%的产量变异。尽管多项式方程并未显著提高数据拟合度,但它清楚地表明在最高中央后生木质部面积水平上没有产量饱和的迹象。像GGE和AMMI这样的现代工具虽然在降维方面非常有效,但不能同时根据不同性状值有效地对基因型进行排名。诸如BLUP、WAASB和多性状稳定性指数(MTSI、MGIDI和FAI - BLUP)等先进模型有能力克服不同变量中的共线性,并利用性状值来识别优良基因型。基因型如G97和G18(均源自杂交组合HDCSW18/CSW1)、G112、G144(均为国际玉米小麦改良中心材料)和G131(31ESWYT135/CSW23)始终表现出高产和稳定性,并被所有模型选中。该研究表明这些模型之间的一致性指数为22.72%,证实了所选基因型的价值。轴向导水率等性状与产量之间的正相关突出了作物高效水分运输、养分交换和水力安全的重要性。
基于中央后生木质部面积的轴向导水率在整个环境中解释了超过14%的产量变异,这与整个根系面积以及适当的物候调整一起,在未来更可能出现的不确定生产条件下,对于以高韧性巩固产量可能发挥关键作用。五个基因型中有三个始终被不同稳定性模型选中,它们源自HDCSW18,这是一个为保护性农业条件而发布的品种,具有非常强大的根系系统和生物量。对于具有温和春化需求且根系中央后生木质部面积大的基因型进行早播,有助于促进高生物量积累,从而在具有挑战性的气候条件下维持更高的种子产量,因此这些发现有助于提高小麦韧性的策略。