ASSESSMENT OF AGRO-MORPHOLOGICAL VARIABILITY IN RICE USING MULTIVARIATE ANALYSIS

  • Verica Ilieva
  • Natalija Markova Ruzdik
  • Ljupco Mihajlov
  • Mite Ilievski

Abstract

The research was carried out to assessment the agro-morphological variability in fourteen rice varieties using principal component analysis, linear correlation and cluster analysis. All rice varieties have Italian origin and were grown in 2014 and 2015 under agro-ecological conditions in Kocani, the Republic of North Macedonia. Principal component analysis was utilized to examine the variation and to estimate the contribution of traits for total variability. Three components in the PCA analysis with Eigen value > 1 contributed 75.59% variability existing in the rice varieties for yield contributing traits. PC1 accounted 30.81% of the total variability, contributed by traits like 1 000 grain weight, panicle length, weight of grains per panicle and plant height. PC2 had the contribution from the traits like number of plants per m2, plant height and panicle length which accounted for 25.08% of the total variation. Grain yield and panicle length had contributed 19.71% of the total variation in PC3. Only Ulisse and San Andrea showed positive values among all three main components. Grain yield showed positive correlation with number of plants per m2 (r= 0.185). On the other side, number of plants per m2 was in negative correlation with weight of grains per panicle (r= -0.593). Also, negative correlation was established between number of grains per panicle and 1 000 grain weight (r= -0.752). Using cluster analysis, two main cluster groups with subgroups were extracted. The results revealed existance of variability in the studied varieties which can help breeders to achieve higher yield in rice.

Published
Jul 2, 2019
How to Cite
ILIEVA, Verica et al. ASSESSMENT OF AGRO-MORPHOLOGICAL VARIABILITY IN RICE USING MULTIVARIATE ANALYSIS. Journal of Agriculture and Plant Sciences, [S.l.], v. 17, n. 1, p. 79-85, july 2019. ISSN 2545-4455. Available at: <http://js.ugd.edu.mk/index.php/YFA/article/view/2891>. Date accessed: 16 july 2019.

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