Evidence map›Paper›PMID 40259220›Full record

ArticleBMC plant biology2025

Rooting for resilience: central metaxylem area as a breeding target for yield gain and resilience in wheat (Triticum aestivum L.).

Rajamani Nirmalaruban, Rajbir Yadav, Subramani Sugumar, Meda Alekya, Amit Kumar Mazumder, Prashanth Babu, Manjeet Kumar, Kiran B Gaikwad, Naresh Kumar Bainsla, Shiv Kumar Singh and 1 more

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Article in BMC plant biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Rajamani NirmalarubanDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.ORCID http://orcid.org/0000-0001-9534-4196
Rajbir YadavDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India. rajbiryadav@yahoo.com.
Subramani SugumarDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
Meda AlekyaDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
Amit Kumar MazumderDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.ORCID http://orcid.org/0009-0000-9262-8580
Prashanth BabuDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
Manjeet KumarDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
Kiran B GaikwadDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.ORCID http://orcid.org/0000-0002-9076-8640
Naresh Kumar BainslaDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.ORCID http://orcid.org/0000-0002-7585-8648
Shiv Kumar SinghDivision of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India.
Pranab Kumar MandalICAR-National Institute of Plant Biotechnology, New Delhi, India.

Funding

This work was partially supported from the collaborative Project on "Application of Next-Generation Breeding, Genotyping and Digitalization Approaches for Improving the Genetic Gain in Indian Staple Crops" by the Indian Council of Agricultural Research (ICAR) and Bill and Melinda Gates Foundation (BMGF) ICAR-IARI project code: 12-229
6 · The paper itself

Abstract

backgroundTo 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.

resultsIn 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.

conclusionCentral 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.

Indexed as

Plant BreedingPlant RootsTriticumCrops, AgriculturalGenotypeMulti-trait stability modelsRoot anatomical traitsSeminal rootsYield resilience

Identifiers

PMID40259220
PMCPMC12010689

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.