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Turkish Journal of Agriculture and Forestry

Author ORCID Identifier

KAZI SAFATH: 0000-0003-4709-393X

UMAKANTA SARKER: 0000-0002-6814-8816

JAHIDUL HASSAN: 0000-0002-3040-0991

JAWAHER ALKAHTANI: 0000-0002-0697-9016

MOHAMMAD AZAM: 0000-0001-8038-8954

REZA RAHMATALLAHI: 0000-0001-8972-4125

SHINYA OBA: 0000-0002-8623-7070

DOI

10.55730/1300-011X.3218

Abstract

Datashak (Amaranthus lividus) are climate-smart, stress-resistant, C4 leafy vegetables. Fourteen datashak genotypes were evaluated in three replicates during summer season at Bangabandhu Shiekh Mujibur Rahman Agricultural University. Results revealed highly significant differences among datashak indicating a wide range of variability. Considering genetic parameters selection could be performed based on total biomass per plant (TBPP), shoot weight (SW), stem weight (StW), and shoot length (SL) for improving the biological yield (BY) of datashak. The correlation results revealed that almost all the features showed a significant increase in the BY of datashak. StW, root length, leaf weight, and SW demonstrated a strong direct and positive effect and a noteworthy genotypic association on BY, indicating direct choice depending on these traits will be useful for enhancing the BY of datashak. The datashak accessions were divided into four clusters by Euclidean distance matrix using Ward’s statistics method. Clusters II and III datashak might be selected for the next breeding programs based on cluster mean values and distances within the cluster and between clusters since these two clusters had superior mean values for the majority of the characteristics. We could select Redtower and Data (cross) as multi-trait high-performance accessions based on the MGIDI index as these datashak displayed balanced traits related to SW, StW, TBPP, and BY without assigning weights, free from multicollinearity. Lalgolapi, Lolita, and BARI lalshak-1 were more promising than others to have strong positive contributions, therefore choosing these datashak accessions would be better for yield aspects, according to principal component analysis, heatmap, and cluster dendrogram. These datashak accessions could be considered high-yielding, promising varieties for future breeding activities.

Keywords

Phenotypic variation, correlation, box plot, cluster, cluster mean, multi-trait stability index

First Page

775

Last Page

797

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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