Multivariate Analysis of Diversity of Landrace Rice Germplasm

Abstract

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 72.24% of the total variation among the 10 characters. The results of canonical discriminant analysis and PCA suggested that traits such as plant height, 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.

Rice Diversity Panel Evaluated for Agro-Morphological Diversity by Multivariate Analysis

“…Similar type of clustering based on phenology and morphological characteristics was reported by Sanni et al, (2012) in 434 landraces of rice collected from African continent. In his study, the late maturing landraces has clustered in 4, 5 and 6 clusters and early maturing accessions in cluster 2 and the total number of tillers was lowest in cluster 7 and cluster 3 has classified based on grain characteristics.…”

“…The higher the coefficients, regardless of the sign, the more effective they will be in discriminating between accessions. There are no inferential tests to prove significance of proper values and the coefficients (Sanni et al, 2012). The current study was based on the Proportion of Variance Criterion by O' Rourke and Hatcher (2013).…”

“…Multivariate analysis has been used in various crops i.e., Rice (Sanni et al, 2012, Chakravorthy et al, 2013, soybean (Bhawana Sharma and Brijvirsingh, 2012), coconut (Odewale et al, 2012), safflower, sorghum and oil palm to study the pattern of variation. The study aimed to determine level of germplasm variation and identify and classify variation for grouping the accessions by taking into account several characteristics and relationship between them.…”

Genetic variation and heritability of yield and related traits in promising rice genotypes (Oryza sativa L.)

“…The demand for rice in SSA is expected to grow substantially as the population is currently growing at the rate of 3 to 4% per annum and rice consumption is growing faster than that of any major food. However, self-sufficiency in African rice production is declining as demand increases, driving the urgent need to increase and improve the continent's production of rice to satisfy the high demand (Sanni et al, 2012). To attain rice self-sufficiency and meet the future demand resulting from population growth, development of high yielding genotypes with desirable agronomic traits for diverse ecosystem is therefore, a necessity (Ogunbayo et al, 2007;Akinwale et al, 2011;Mulugeta et al, 2012).…”

ASSESSMENT OF TAXONOMIC AFFINITY OF INDONESIAN PUMMELO (<i>CITRUS MAXIMA</i> (BURM.) MERR.) BASED ON MORPHOLOGICAL CHARACTERS

“…Their contribution was indicated by their eigen value of higher than 0.3 on both axis 1 and axis 2 of the PCA result ( Table 3). The use of eigen value >0.3 as a criteria for marking characters with high diagnostic function referred to Sanni et al (2010). These 6 characters comprised of 3 from leaves (L07, L08 and L10) and 3 from fruit (F02, F04 and F11).…”