Evidence map›Paper›PMID 42008580›Full record

ArticlePloS one2026

Phenotypic variability and trait-specific selection in Aegle marmelos Correa genotypes based on morphological and quality traits.

A K Singh, Vikas Yadav, Lalu Prasad Yadav, K Gangadhara, Anil Pawar, Jagadish Rane, P Ravat, A Sahil, Prashant Kaushik, Ali Khadivi and 1 more

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Article in PloS one, 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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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

A K SinghICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
Vikas YadavICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
Lalu Prasad YadavICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
K GangadharaICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
Anil PawarICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
Jagadish RaneICAR-Central Institute for Arid Horticulture, Bikaner, Rajasthan, India.
P RavatICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
A SahilICAR- Central Horticultural Experiment Station (CIAH R.S.,) Godhra, Gujarat, India.
Prashant KaushikChaudhary Charan Singh Haryana Agricultural University, Hisar, Haryana, India.
Ali KhadiviDepartment of Horticultural Sciences, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran.ORCID https://orcid.org/0000-0001-6354-445X
Yazgan TunçRepublic of Türkiye, Ministry of Agriculture and Forestry, General Directorate of Agricultural Research and Policies, Hatay Olive Research Institute Directorate, Hassa, Hatay, Türkiye.ORCID https://orcid.org/0000-0002-3228-8657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to assess the genetic variability in Aegle marmelos Correa to develop trait-specific genotypes based on morphological and qualitative traits. The evaluation focused on both morphological and qualitative characteristics within the gene pool of this species. High phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed for traits such as shell weight, fruit weight, and pulp weight, indicating substantial genetic diversity and strong potential for selective breeding within the germplasm. Heritability estimates ranged widely, with fruit weight showing a low 0.07% and shell weight a high 92.23%, reflecting the significant impact of environmental factors on trait expression. Principal Component Analysis (PCA) revealed that the first principal component (PC1) explained 40.19% of the total variation, with an eigenvalue of 8.12. The first six principal components collectively accounted for 80.77% of total variability. Genotypes CHESB-25 and CHESB-29 exhibited the highest positive PC scores for PC1 and PC2, identifying them as superior selections. Cluster analysis identified six distinct clusters of genotypes, with Cluster V being the largest and Cluster VI the smallest. This clustering highlights the genetic diversity among the bael genotypes and provides a basis for breeding and selection strategies. Cluster IV emerged as the most promising, consistently showing the highest values for key attributes such as shell weight, fruit weight, and fruit yield per plant. Therefore, prioritizing Cluster IV is recommended for selecting superior varieties and developing new cultivars. The study also noted that fruit yield per plant positively correlated with traits like shell weight and fruit weight, emphasizing the importance of these traits for yield improvement. Conversely, negative correlations with seed percent, shell percent, and phenolic content suggest these traits may be less beneficial for enhancing yield. The hierarchical clustering heat map of the 101 bael germplasms offers a detailed perspective on the relationships between various traits and germplasms. The results offer vital information for creating A. marmelos cultivars with higher yields and better quality. For breeding programs, targeted selection is made possible by the discovery of important clusters and superior genotypes (CHESB-25 and CHESB-29). Given the high level of genetic variation found, hybridization may be able to improve desired characteristics like fruit output and weight. Overall, the findings offer important insights for selecting elite genotypes and advancing breeding programs.

Indexed as

AegleSelection, GeneticCluster AnalysisFruitGenetic VariationGenotypePhenotypePlant BreedingPrincipal Component Analysis

Identifiers

PMID42008580
PMCPMC13095130

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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.