Evidence map›Paper›PMID 42401807›Full record

ArticleBMC ecology and evolution2026

Multivariate assessment of morphological diversity in Moringa oleifera Lam. across agro-climatic zones of Rajasthan.

Rajpal Choudhary, Vikram Jeet Singh Tanwar, Rohit Jain, Sumita Kachhwaha, Shanker Lal Kothari

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Article in BMC ecology and evolution, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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5 authors.

Rajpal ChoudharyDepartment of Biosciences, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India.
Vikram Jeet Singh TanwarDepartment of Biosciences, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India.
Rohit JainDepartment of Biosciences, Manipal University Jaipur, Jaipur, Rajasthan, 303007, India. rohit.jain@jaipur.manipal.edu.ORCID 0000-0001-5245-4627
Sumita KachhwahaDepartment of Botany, University of Rajasthan, Jaipur, Rajasthan, 303004, India.
Shanker Lal KothariDepartment of Biotechnology, Amity Institute of Biotechnology, Amity University, Jaipur, Rajasthan, 303002, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the agro-climatic structure of morphological diversity is essential for the effective utilization and improvement of drumstick (Moringa oleifera Lam.), a multipurpose tree species of high nutritional and economic value. The present study aimed to evaluate morphological diversity and phenotypic variation of M. oleifera across ten agro-climatic zones of Rajasthan, India, and to identify key traits and morphotypes relevant for breeding, conservation, and climate-resilient cultivation. A total of 367 accessions were characterized using 17 morphological traits, including eight quantitative and nine qualitative descriptors. Quantitative traits were analyzed using non-parametric statistics and Principal Component Analysis (PCA), while qualitative traits were evaluated through Multiple Correspondence Analysis (MCA). An integrated approach using Factor Analysis of Mixed Data (FAMD) was employed to assess overall variation, followed by hierarchical and FAMD-based clustering. Correlation analysis was conducted to identify relationships among traits. The results revealed significant variations among agro-climatic zones for all quantitative traits (Kruskal-Wallis, p < 0.01), with moderate to high effect sizes (ε² = 0.07-0.26). PCA indicated that the first two components explained 56.9% of total variance, primarily driven by stem girth and leaf-related traits. MCA showed that qualitative variation was largely influenced by stem morphology, canopy size, and branching density. FAMD further confirmed the integration of qualitative and quantitative traits, with the first two dimensions explaining 56.4% of total variability. Correlation analysis demonstrated strong positive associations among leaf traits, indicating a coordinated leaf development system. Clustering analysis grouped the accessions into distinct morphotypes, with substantial overlap across agro-climatic zones, suggesting that morphological variation is governed by both environmental factors and inherent genetic diversity. Two major groups identified through FAMD represented broadly adapted and high growth morphotypes. From an applied perspective, accessions with larger canopy and higher leaf area are recommended for biomass-oriented breeding and cultivation in favourable environments, while stable, moderate-growth accessions are suitable for arid and semi-arid regions. The study also highlights leaf traits as reliable selection indices and emphasizes the need for stratified germplasm conservation across agro-climatic zones. This study provides a robust framework for understanding morphological diversity in M. oleifera and offers practical insights for its genetic improvement, conservation and climate-resilient utilization.

Indexed as

Moringa oleiferaClimateIndiaMultivariate AnalysisPhenotypePrincipal Component AnalysisDrumstickFactor analysis of mixed dataMorphological traitsMorphotypesMultiple correspondence analysisPrincipal component analysis

Identifiers

PMID42401807
PMCPMC13343757

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