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Hindi Research Article
Phenotypic Diversity Studies on Selected Kenyan and Tanzanian Rice (Oryza sativa L) Genotypes Based on Grain and Kernel Traits
| Mawia Musyoki A1*, Wambua Kioko F1, Agyirifo Daniel1, Nyamai Wavinya D1, Matheri Felix1, Langat Chemtai R1, Njagi Mwenda S1, Arika Arika W1, Gaichu Muthee D1, Ngari Ngithi L1, Ngugi Piero M1 and Karau Muriira G2 | |
| 1Department of Biochemistry and Biotechnology, School of Pure and Applied Sciences, Kenyatta University, P.O. Box 43844-00100, Nairobi, Kenya | |
| 2Molecular Biology Laboratory, Kenya Bureau of Standards, Nairobi, Kenya | |
| Corresponding Author : | Mawia Musyoki A Department of Biochemistry and Biotechnology School of Pure and Applied Sciences Kenyatta University, Nairobi, Kenya Tel: +254 711 953 234 E-mail: amosyokis@gmail.com |
| Received: September 19, 2015; Accepted: October 01, 2015; Published: October 03, 2015 | |
| Citation: Mawia Musyoki A, Wambua Kioko F, Daniel A, Nyamai Wavinya D, Felix M, et al. (2015) Phenotypic Diversity Studies on Selected Kenyan and Tanzanian Rice (Oryza sativa L) Genotypes Based on Grain and Kernel Traits. J Rice Res 3:150. doi:10.4172/2375-4338.1000150 | |
| Copyright: © 2015 Mawia Musyoki A, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
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Abstract
Phenotypic characterization of rice (Oryza sativa L.) provides useful information regarding preservation of diversity and selection of parental genotypes with superior traits in plant breeding program. The main objective of the present study was to characterize 13 selected rice genotypes from Kenya and Tanzania based on 7 grain and kernel traits. Minitab 15.0 software was used to analyze data. The 7 traits showed highly significant differences among the improved and local landraces. A dendrogram was constructed from data set of mean values of grain and kernel traits and showed two super clusters; I and II. Principal component analysis revealed that all the seven quantitative traits significantly influenced the variation in these genotypes.
