Ilieva, Verica and Markova Ruzdik, Natalija and Mihajlov, Ljupco and Ilievski, Mite (2019) Assessment of agro-morphological variability in rice using multivariate analysis. In: II International Meeting "Agriscience & Practice" 2019, Goce Delcev University, Faculty of Agriculture.
Preview |
Text
Ilieva et al., - Assessment of agro-morphological variability in rice by multivariate analysis.pdf Download (498kB) | Preview |
Preview |
Text
Programme of II International Meeting Agriscience & Practice, 2019.pdf Download (218kB) | Preview |
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 agroecological 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 as number of plants per m 2 , 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 existence of variability in the
studied varieties which can help breeders to achieve higher yield in rice.
Key words: Oryza sativa L., principal component analysis, cluster analysis, linear correlation
| Item Type: | Conference or Workshop Item (Poster) |
|---|---|
| Subjects: | Agricultural Sciences > Agricultural biotechnology |
| Divisions: | Faculty of Agriculture |
| Depositing User: | Natalija Markova Ruzdik |
| Date Deposited: | 15 Jul 2019 08:55 |
| Last Modified: | 15 Jul 2019 08:55 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/22233 |
Actions (login required)
 |
View Item |