Multivariate Analysis of Diversity of Landrace Rice Germplasm

Multivariate analysis is based on a statistical principle involving observation and analysis of more than one statistical variable at a time. The variability of 434 accessions of rice (Oryza sativa L.) germplasm from Côte d’Ivoire was evaluated for 10 agro-morphological traits in upland conditions a...

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Bibliographic Details
Published in:	Crop science Vol. 52; no. 2; pp. 494 - 504
Main Authors:	Sanni, K.A, Fawole, I, Ogunbayo, A, Tia, D, Somado, E.A, Futakuchi, K, Sié, M, Nwilene, F.E, Guei, R.G
Format:	Journal Article
Language:	English
Published:	Madison, WI Crop Science Society of America 01-03-2012 The Crop Science Society of America, Inc American Society of Agronomy
Subjects:	Agronomy. Soil science and plant productions Biological and medical sciences cluster analysis discriminant analysis Experimental design Fundamental and applied biological sciences. Psychology Generalities. Genetics. Plant material genetic improvement Genetic resources, diversity Genetics and breeding of economic plants germplasm heading landraces leaves Multivariate analysis Oryza sativa Plant material principal component analysis Principal components analysis rice tillering Monocotyledones Oryza Gramineae Landrace(plant) Genetic resource Angiospermae Herbaceous plant Spermatophyta Multivariate analysis
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Summary:	Multivariate analysis is based on a statistical principle involving observation and analysis of more than one statistical variable at a time. The variability of 434 accessions of rice (Oryza sativa L.) germplasm from Côte d’Ivoire was evaluated for 10 agro-morphological traits in upland conditions at M’bé, Côte d’Ivoire (7°5′ N, 5°1′ W) in 2002 using augmented experimental design and analyzed with multivariate methods. The unweighted pair group method of the average linkage (UPGMA) cluster analysis, canonical discriminant analysis, and principal component analysis (PCA) were used to analyze the data obtained. This enabled the assessment of the extent and pattern of variation of the germplasm and identification of the major traits contributing to the diversity. Seven cluster groups were obtained from the 10 agro-botanical traits using the UPGMA. Canonical discriminant analysis showed the contribution of each trait to the classification of the rice accessions into different cluster groups. The first three principal components explained about 72.4% of the total variation among the 10 characters. The results of canonical discriminant analysis and PCA suggested that traits such as plant height, leaf length, number of days to heading and maturity, tillering ability, and grain size (weight, length, width, and shape) were the principal discriminatory characteristics. It was concluded that variation exists in the germplasm, which provides opportunities for this collection to be useful for genetic improvement.
Bibliography:	http://dx.doi.org/10.2135/cropsci2010.12.0739 All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher.
ISSN:	1435-0653 0011-183X 1435-0653
DOI:	10.2135/cropsci2010.12.0739