Vol. 25 No. 3 (2025): Juli-September
Open Access
Peer Reviewed

Heterogeneity of M5 Red Rice Mutants Irradiated With 200 and 300 Gy Based on Agronomic Traits Using Hierarchical Clustering Analysis

Authors

A. A. Ketut Sudharmawan

DOI:

10.29303/jbt.v26i3.13089

Published:

2025-07-23

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Abstract

Gamma-ray irradiation can broaden phenotypic variation in rice, making assessment of genotype heterogeneity important in advanced generations. This study evaluated the heterogeneity of M5 red rice mutants derived from 200 and 300 Gy irradiation based on agronomic traits using Hierarchical Clustering. The study involved 20 M5 mutant genotypes, comprising 10 genotypes from 200 Gy and 10 from 300 Gy, evaluated in three replications with Gamagora 7 as a check. Eleven agronomic traits were analyzed; maturity was excluded from clustering because all mutant genotypes had maturity of 107 days after transplanting. Genotype means were standardized and analyzed using Euclidean distance and Ward linkage. Cluster number was determined using silhouette, Calinski–Harabasz, Davies–Bouldin, and cophenetic correlation, while PCA was used to clarify variation. Five traits differed significantly: plant height, flowering time, maturity, grains per panicle, and filled grains per panicle. Three clusters provided the most informative structure, with a silhouette score of 0.324 and a cophenetic correlation coefficient of 0.732. The smallest Euclidean distance was 0.981 between G13 (12-2-8) and G63 (5-14-10), whereas the largest was 8.771 between G27 (1-20-19) and G27 (17-10-12). Internal dispersion was higher at 300 Gy than at 200 Gy, although multivariate centroids did not differ significantly between doses.

Keywords:

red rice; phenotypic heterogeneity; gamma irradiation; M5; Hierarchical Clustering; PCA.

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Author Biography

A. A. Ketut Sudharmawan, Universitas Mataram

Author Origin : Indonesia

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How to Cite

Sudharmawan, A. A. K. (2025). Heterogeneity of M5 Red Rice Mutants Irradiated With 200 and 300 Gy Based on Agronomic Traits Using Hierarchical Clustering Analysis. Jurnal Biologi Tropis, 25(3), 4764–4770. https://doi.org/10.29303/jbt.v26i3.13089

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