Assessment of Genetic Variability andDivergence in Coriander (Coriandrumsativum L.) Germplasm Using MultivariateStatistical Approaches

he present investigation aimed to assess the genetic variation anddivergence among coriander (Coriandrum sativum L.) genotypesusing various multivariate statistical methods. The study wasconducted in Randomized Block Design, evaluating ten keyquantitative characters to identify promising genotypes. Correlationanalysis revealed significant positive associations, notably betweenumbels per plant and seeds per umbel, as well as between biologicalyield and seed yield, suggesting their potential for indirect selection inbreeding programs. Principal Component Analysis (PCA) identifiedfour principal components that collectively accounted for 87.26% ofthe total variability, with PC1 contributing the highest proportion. Thiscomponent was primarily influenced by plant height, number ofbranches per plant and oil content. Cluster analysis categorized thegenotypes into four groups. Genotypes UD 619, UD 703 and RCr 728showed close genetic affinity, while UD 603 stood out as a distinctgenotype due to its notably high seed yield. Plant height and oilcontent exhibited high heritability coupled with a high geneticadvance as percent of mean, indicating the predominance of additivegene action.

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Publication Details

Journal
International Journal of Seed Spices
Published
2025-09-22
DOI
https://doi.org/10.56093/ijss.v14i2.7
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
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article

Assessment of Genetic Variability andDivergence in Coriander (Coriandrumsativum L.) Germplasm Using MultivariateStatistical Approaches

Shailesh Marker
International Journal of Seed Spices
Genetics and Plant Breeding
article

Assessment of Genetic Variability andDivergence in Coriander (Coriandrumsativum L.) Germplasm Using MultivariateStatistical Approaches

Shailesh Marker
article en

Abstract

he present investigation aimed to assess the genetic variation anddivergence among coriander (Coriandrum sativum L.) genotypesusing various multivariate statistical methods. The study wasconducted in Randomized Block Design, evaluating ten keyquantitative characters to identify promising genotypes. Correlationanalysis revealed significant positive associations, notably betweenumbels per plant and seeds per umbel, as well as between biologicalyield and seed yield, suggesting their potential for indirect selection inbreeding programs. Principal Component Analysis (PCA) identifiedfour principal components that collectively accounted for 87.26% ofthe total variability, with PC1 contributing the highest proportion. Thiscomponent was primarily influenced by plant height, number ofbranches per plant and oil content. Cluster analysis categorized thegenotypes into four groups. Genotypes UD 619, UD 703 and RCr 728showed close genetic affinity, while UD 603 stood out as a distinctgenotype due to its notably high seed yield. Plant height and oilcontent exhibited high heritability coupled with a high geneticadvance as percent of mean, indicating the predominance of additivegene action.

International Journal of Seed SpicesVol. 14(2)
Sri Karan Narendra Agriculture University, Jobner (IN)
Openalex Percentile: Top 81%
Genetics and Plant Breeding
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