A population panel of 192 rice genotypes comprising traditional landraces and exotic genotypes from 12 countries was evaluated for 12 agro - morphological traits by principal component analysis for determining the pattern of genetic diversity and relationship among individuals. Twelve quantitative characters i.e. plant height, leaf length, number of productive tillers, panicle length, number of filled grains, spikelet fertility, days to 50% flowering; days to harvest maturity, grain length, grain width, grain length width ratio, and single plant yield were measured. The largest variation was observed for number of productive tillers with Coefficient of Variation (CV) of 28.03% followed by number of filled grains per panicle, single plant yield, leaf length , grain length width ratio. Days to maturity has shown the least variation with the CV of 9.74%. Principal component analysis was utilized to examine the variation and to estimate the relative contribution of various traits for total variability. In the current study, Component 1 had the contribution from the traits such as days to 50% flowering, leaf length, plant height, panicle length, days to maturity and number of filled grains which accounted 28.46% of the total variability. Grain width and grain length width ratio has contributed 16.8% of total variability in component 2. The remaining variability of 14.4%, 11.7% and 9.3% was consolidated in component 3, component 4 and component 5 by various traits such as spikelet fertility, single plant yield, grain length and number of productive tillers. The cumulative variance of 80.56% of total variation among 12 characters was explained by the first five axes. Thus the results of principal component analysis used in the study have revealed the high level of genetic variation and the traits contributing for the variation was identified. Hence this population panel can be utilized for trait improvement in breeding programs for the traits contributing for major variation.

Evaluation of Rice Genetic Diversity and Variability in a Population Panel by Principal Component Analysis

Optimization of water and fertilizer coupling system based on rice grain quality

Sorghum [Sorghum bicolor (L.) Moench] is an important staple food crop in northern Benin. In order to assess its diversity in Benin, 142 accessions of landraces collected from Northern Benin were grown in Central Benin and characterised using 10 qualitative and 14 quantitative agromorphological traits. High variability among both qualitative and quantitative traits was observed. Grain yield (0.72-10.57 tons/ha), panicle weight (15-215.95 g), days to 50% flowering (57-200 days), and plant height (153.27-636.5 cm) were among traits that exhibited broader variability. Correlations between quantitative traits were determined. Grain yield for instance exhibited highly positive association with panicle weight (r = 0.901, P = 0.000) and 100 seed weight (r = 0.247, P = 0.000). UPGMA cluster analysis classified the 142 accessions into 89 morphotypes. Based on multivariate analysis, twenty promising sorghum genotypes were selected. Among them, AT41, AT14, and AT29 showed early maturity (57 to 66 days to 50% flowering), high grain yields (4.85 to 7.85 tons/ha), and shorter plant height (153.27 to 180.37 cm). The results obtained will help enhancing sorghum production and diversity and developing new varieties that will be better adapted to the current soil and climate conditions in Benin.

/pdf/genetic-divergence-in-northern-benin-sorghum-sorghum-bicolor-4nn8hpiamb.pdf

Genetic divergence in northern Benin sorghum (Sorghum bicolor L. Moench) landraces as revealed by agromorphological traits and selection of candidate genotypes.

Inability of total antioxidant activity assays to accurately assess the phenolic compounds of date palm fruit (Phoenix dactylifera L.)

Twenty diverse cultivars of rice were studied for variation and correlation. Highly significant differences were presented among the genotypes for all the traits. Among the traits days to heading, days to maturity, number of productive tillers, 1000-grain weight showed highly significant positive correlation with grain yield per plant whereas, flag leaf area, plant height and panicle length showed highly significant negative correlation with grain yield per plant. Number of grains per panicle was non significant positively correlated with grain yield per plant. Cluster analysis revealed that maximum genetic diversity was present between Cluster I and Cluster VI. Minimum genetic diversity was found between Cluster III and Cluster IV. It was concluded that traits like number of productive tillers, number of grains per panicle and 1000-grain weight was useful for direct selection criteria for higher grain yield. Cultivars like IRRI-3, IRRI-4, KSK-133, SR-57, IRRI-5, SRS-64 might be used for rice hybridization and improve programs for developing new rice varieties.

Correlation and Cluster Analysis of Some Yield and Yield Related Traits in Rice (Oryza Sativa)

This study gave empirical evidence on sixteen agro-morphological data that were collected from one hundred and twenty three rice germplasm comprising of Oryza sativa and Oryza glaberrima lines including checks. The data was collected from thirteen villages in two States in Nigeria and were characterized using ANOVA model. Among the studied traits, high coefficients of variation were observed for number of unfilled grain per head (45.8%), grain weight (29.1%), 1000 grain weight (23.0%), tiller number at three weeks after planting (22.5%), and tiller number at maturity (20.9%). Seven out of the sixteen phenotypic traits measured were statistically significant at (P = 0.001 and P = 0.05), and 7 phenotypic variables also showed significant differences when subjected to univariate statistics at (P = 0.001 and P = 0.05). The association of all morphological traits was estimated by phenotypic correlation coefficient and showed that eight dependent variables were positively related. Cluster analysis using Ward's method classified the 123 populations into seven distinct groupings. A large number of genotypes was placed in cluster 5 (65 genotypes) followed by cluster 1 (20), cluster 4 (14) and cluster 3 (9), cluster 2 (8) and cluster 6 (7). Cluster 6 includes five checks with few sativa lines, cluster 5 with large grouping of sativa lines with only FARO 56 in that group. Cluster 1 consists of only the O. glaberrima. Clusters 2, 3 and 4 consisted of only O. sativa groups indicating no association between clustering pattern and eco-geographical distribution of genotypes. The maximum inter-cluster distance was observed between clusters indicating the possibility of high heterosis if individuals from these clusters are cross-bred. Principal component analysis resulted in the first two components with Eigen value greater than 1 accounting for 78% of the total variation. The results of Principal Component Analysis (PCA) were closely in line with those of the cluster analysis. These results can now be used by breeders to develop high yielding rice varieties and new breeding protocols for rice improvement.

	 

	Key words: Principal component analysis, germplasm characterization, correlation coefficient, correlation matrix, cluster analysis, genetic variability.

A T Maji

Papers

Application of principal component analysis for rice germplasm characterization and evaluation