Multivariate Analysis of Agronomic Traits in M4 Generation of Aromatic Rice Lines
Author(s) -
A M Okasa,
Rinaldi Sjahril,
M Riadi,
Meta Mahendrada
Publication year - 2022
Publication title -
pakistan journal of biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.268
H-Index - 43
eISSN - 1812-5735
pISSN - 1028-8880
DOI - 10.3923/pjbs.2022.182.190
Subject(s) - panicle , randomized block design , aromatic rice , oryza sativa , biology , grain yield , yield (engineering) , trait , horticulture , zoology , agronomy , microbiology and biotechnology , genetics , gene , materials science , computer science , metallurgy , programming language
<b>Background and Objective:</b> Developing rice (<i>Oryza sativa</i> L.) varieties with increased yield potential has been a major concern for genetic improvement. This study aimed to evaluate aromatic rice lines and the relationship among their twelve agronomic traits using heatmap Pearson correlation and multivariate analysis to identify high yield lines using grain yield as a marker-trait. <b>Materials and Methods:</b> Twelve aromatic rice genotypes (eleven mutant lines and one control) were evaluated in the M<sub>4</sub> generation. The experiment was conducted at Tana Toraja regency following Randomized Complete Block Design (RCBD) with two replications. <b>Results:</b> The darker and lighter colour scale produced by heatmap revealed contrasting nature of genotypes. A significant positive correlation observed for yield was the number of fertile grains and grain weight per panicle, while a negative correlation was days to flowering. The first four components account for 83.46% of the total cumulative variation. Cluster analysis grouped 11 lines and one control into three clusters. <b>Conclusion:</b> The results concluded that the PB-A.5.3.45 line could be used for hybridization programs to develop high-yielding mutant-derived aromatic rice varieties for further improvement.
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