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Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity

Twelve amaranth accessions were evaluated in a randomized complete block design with three replications in the research field of the Institute of Agriculture and Animal Science, Lamjung, Sundarbazar, Lamjung, Nepal from March to July 2021 to assess the phenotypic diversity. Principal Component Analy...

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Detalles Bibliográficos
Autores principales: Bashyal, Saujan, Upadhyay, Ashmita, Ayer, Dipendra Kumar, Dhakal, Prabesh, G.C., Bimochana, Shrestha, Jiban
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674540/
https://www.ncbi.nlm.nih.gov/pubmed/36411935
http://dx.doi.org/10.1016/j.heliyon.2022.e11613
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author Bashyal, Saujan
Upadhyay, Ashmita
Ayer, Dipendra Kumar
Dhakal, Prabesh
G.C., Bimochana
Shrestha, Jiban
author_facet Bashyal, Saujan
Upadhyay, Ashmita
Ayer, Dipendra Kumar
Dhakal, Prabesh
G.C., Bimochana
Shrestha, Jiban
author_sort Bashyal, Saujan
collection PubMed
description Twelve amaranth accessions were evaluated in a randomized complete block design with three replications in the research field of the Institute of Agriculture and Animal Science, Lamjung, Sundarbazar, Lamjung, Nepal from March to July 2021 to assess the phenotypic diversity. Principal Component Analysis (PCA) showed that only two principal components were significant with their eigenvalues >1 and combinedly accounted for 88.3% of the total variance. PC1, which explained 71.9% of the variance, was highly and positively contributed by days to 50% inflorescence, plant height, leaf length, leaf width, petiole length, 1000 seed weight, and grain yield. PC1 was negatively affected by the number of primary branches per plant and the number of leaves per plant. PC2, which explained 16.4% of the variance, distinguished plants with high number of leaves and a higher inflorescence length. The accessions were grouped into 4 clusters. Cluster 2 had the greatest intracluster distance (D(2) = 13.19), while Cluster 3 and 4 had the greatest intercluster distance (D(2) = 21.73), followed by Cluster 2 and 3 (D(2) = 17.37). Cluster 1 had the highest number of leaves per plant and the lowest yield. Cluster 2 had the maximum grain yield and plant height. Cluster 3 had the lowest inflorescence length, and cluster 4 had the highest leaf length and 1000 seed weight.
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spelling pubmed-96745402022-11-20 Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity Bashyal, Saujan Upadhyay, Ashmita Ayer, Dipendra Kumar Dhakal, Prabesh G.C., Bimochana Shrestha, Jiban Heliyon Research Article Twelve amaranth accessions were evaluated in a randomized complete block design with three replications in the research field of the Institute of Agriculture and Animal Science, Lamjung, Sundarbazar, Lamjung, Nepal from March to July 2021 to assess the phenotypic diversity. Principal Component Analysis (PCA) showed that only two principal components were significant with their eigenvalues >1 and combinedly accounted for 88.3% of the total variance. PC1, which explained 71.9% of the variance, was highly and positively contributed by days to 50% inflorescence, plant height, leaf length, leaf width, petiole length, 1000 seed weight, and grain yield. PC1 was negatively affected by the number of primary branches per plant and the number of leaves per plant. PC2, which explained 16.4% of the variance, distinguished plants with high number of leaves and a higher inflorescence length. The accessions were grouped into 4 clusters. Cluster 2 had the greatest intracluster distance (D(2) = 13.19), while Cluster 3 and 4 had the greatest intercluster distance (D(2) = 21.73), followed by Cluster 2 and 3 (D(2) = 17.37). Cluster 1 had the highest number of leaves per plant and the lowest yield. Cluster 2 had the maximum grain yield and plant height. Cluster 3 had the lowest inflorescence length, and cluster 4 had the highest leaf length and 1000 seed weight. Elsevier 2022-11-15 /pmc/articles/PMC9674540/ /pubmed/36411935 http://dx.doi.org/10.1016/j.heliyon.2022.e11613 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Bashyal, Saujan
Upadhyay, Ashmita
Ayer, Dipendra Kumar
Dhakal, Prabesh
G.C., Bimochana
Shrestha, Jiban
Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title_full Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title_fullStr Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title_full_unstemmed Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title_short Multivariate analysis of grain amaranth (Amaranthus spp.) accessions to quantify phenotypic diversity
title_sort multivariate analysis of grain amaranth (amaranthus spp.) accessions to quantify phenotypic diversity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674540/
https://www.ncbi.nlm.nih.gov/pubmed/36411935
http://dx.doi.org/10.1016/j.heliyon.2022.e11613
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