Genetic variability, principal component and cluster analyses in black gram under Foot-hills conditions of Manipur

2018 ◽  
Author(s):  
M. Samuel Jeberson ◽  
K. S. Shashidhar ◽  
Amit Kumar Singh
Keyword(s):  
Genetic Variability ◽  
Path Analysis ◽  
Quantitative Traits ◽  
Principal Component ◽  
Yield Attributes ◽  
Eigen Values ◽  
Correlation And Path Analysis ◽  
And Cluster Analysis ◽  
100 Seed Weight ◽  
Selection Of

Analysis of genetic variability, heritability, correlation, path analysis, principal component and cluster analysis was carried for 25 blackgram genotypes grown in the foothills of Manipur. The results showed that phenotypic coefficients of variability recorded were higher than the genotypic coefficients of variability, irrespective of traits, demonstrating the effect of environment thereon. The present study revealed that the heritability (bs) estimates were maximum (>50%) for the traits such as days taken to attain the 50% flowering, number of clusters/plant, number of pods/plant and 100 seed weight. The correlation and path analysis proved the selection of the yield attributes in blackgram based on the characters, viz., number of pods/plant and number of cluster/plants. The first three principal components, having the Eigen values more than 1, contributed 84.52% towards variability among the 25 genotypes screened for quantitative traits. Based on the average linkage, 25 genotypes were grouped into five (5) clusters.

scholarly journals Evaluation of bunch quality components in Dura x Dura progenies of Zambia and Camaroon sources of oil palm germplasm

2021 ◽  
Vol 42 (6) ◽  
pp. 1567-1677
Author(s):  
A. Pedapati ◽  
◽  
R.K. Mathur ◽  
G. Ravichandran ◽  
B.K. Babu ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Path Analysis ◽  
Oil Palm ◽  
Principal Component ◽  
Analysis Data ◽  
Correlation And Path Analysis ◽  
Positive Direct ◽  
Positive Significant Correlation ◽  
Selection Of

Aim: The present study was conducted to evaluate oil palm dura progenies developed from Zambia and Cameroon germplasm sources for bunch components for the selecting of high oil yielding mother palms. Methodology: Total 77 dura genotypes were evaluated by considering 15 different bunch components. Bunch analysis data were collected from tenth year onwards after planting. The genetic diversity, Principal component analysis, correlation and path analysis of the genotypes were estimated. Results: Study revealed that oil-to bunch ratio depends on fruit-to-bunch ratio and mesocarp-fruit ratio. The ANOVA value showed a significant variability among the genotypes for most of the bunch traits and the identified genotype P35 (24.53 %) was highest oil yielder. Positive significant correlation (p≤ 0.01) of mesocarp-to-fruit ratio and oil-to-dry mesocarp with oil-to-bunch ratio were noted in this study. Based on path analysis, the information obtained from this study is the oil-to-wet mesocarp ratio (0.697) showed the highest significant positive direct effect on oil-to-bunch ratio followed by mesocarp-to-fruit ratio (0.570). Interpretation: This study may support for the future selection of mother palms to utilize in oil palm improvement programmes. Introgression into existing breeding materials and breeding for seed production utilising selected palms.

scholarly journals Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm

Genetika ◽  
2014 ◽  
Vol 46 (2) ◽  
pp. 545-559 ◽  
Author(s):  
Mirjana Jankulovska ◽  
Sonja Ivanovska ◽  
Ana Marjanovic-Jeromela ◽  
Snjezana Bolaric ◽  
Ljupcho Jankuloski ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Vegetative Growth ◽  
Quantitative Traits ◽  
Principal Component ◽  
Breeding Program ◽  
Oil Yield ◽  
Growth Duration ◽  
Data Set ◽  
Combined Application ◽  
Selection Of

In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP). NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes? clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods can assist in deciding how, and based on which traits to select the genotypes, especially in early generations, at the beginning of a breeding program.

scholarly journals Phenotypic correlations and path analysis for plant architecture traits and grain production in three generations of cowpea

Revista CERES ◽  
2016 ◽  
Vol 63 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Hugo Leonardo Coelho Ribeiro ◽  
Carlos Antônio Fernandes Santos ◽  
Laerte da Silva Diniz ◽  
Layana Alves do Nascimento ◽  
Edna Deodato Nunes
Keyword(s):  
Grain Yield ◽  
Path Analysis ◽  
Plant Architecture ◽  
Statistical Significance ◽  
Phenotypic Correlation ◽  
Cowpea Cultivars ◽  
Phenotypic Correlations ◽  
Three Generations ◽  
Correlation And Path Analysis ◽  
Selection Of

ABSTRACT The objective of this study was to analyze the phenotypic correlation and path analysis of traits related to plant architecture, earliness and grain yield in F2, BC1 and BC2 generations, from crosses between cowpea cultivars BRS Carijó and BR14 Mulato. Most phenotypic correlations of the examined traits were concordant in statistical significance, with approximate values among the examined generations. For the trait seed weight, significant and positive phenotypic correlations were observed in the three generations only for the trait number of secondary branches. The values of the direct effects were in agreement with the values of the phenotypic correlations, which indicate true association by the phenotypic correlation among the traits of grain yield examined. Path analysis indicated that the selection of productive plants will result in early plants and an increased number of secondary branches. In F2, plants with shorter length of the main branch and shorter length of secondary branches can be obtained. The causal model explained 15 to 30% of the total variation in grain weight in relation to the traits examined. The analyses indicated the possibility of selecting plants with a higher and early grain yield, shorter length of primary branches and lower number of nodes, which are important variables for mechanical or semi-mechanical harvesting.

scholarly journals Principal Component Analysis of Some Quantitative and Qualitative Traits in Iranian Spinach Landraces

2017 ◽  
Vol 71 (4) ◽  
pp. 307-310
Author(s):  
Mehdi Mohebodini ◽  
Naser Sabaghnia ◽  
Farhad Behtash ◽  
Mohsen Janmohammadi
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Quantitative Traits ◽  
Agronomic Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Leaf Width ◽  
Petiole Length ◽  
Qualitative Traits ◽  
Eigen Values

Abstract Landraces of spinach in Iran have not been sufficiently characterised for their morpho-agronomic traits. Such characterisation would be helpful in the development of new genetically improved cultivars. In this study 54 spinach accessions collected from the major spinach growing areas of Iran were evaluated to determine their phenotypic diversity profile of spinach genotypes on the basis of 10 quantitative and 9 qualitative morpho-agronomic traits. High coefficients of variation were recorded in some quantitative traits (dry yield and leaf area) and all of the qualitative traits. Using principal component analysis, the first four principal components with eigen-values more than 1 contributed 87% of the variability among accessions for quantitative traits, whereas the first four principal components with eigen-values more than 0.8 contributed 79% of the variability among accessions for qualitative traits. The most important relations observed on the first two principal components were a strong positive association between leaf width and petiole length; between leaf length and leaf numbers in flowering; and among fresh yield, dry yield and petiole diameter; a near zero correlation between days to flowering with leaf width and petiole length. Prickly seeds, high percentage of female plants, smooth leaf texture, high numbers of leaves at flowering, greygreen leaves, erect petiole attitude and long petiole length are important characters for spinach breeding programmes.

scholarly journals Genetic Variability and Diversity Analysis in Pod and Seed Characters of Some Neglected and Underutilized Legumes (NULs)

2019 ◽  
pp. 1-8
Author(s):  
J. O. Agbolade ◽  
T. P. Olakunle ◽  
K. M. Popoola ◽  
J. A. Idowu ◽  
A. I. Isiaka ◽  
...  
Keyword(s):  
Genetic Variability ◽  
Principal Component ◽  
Morphological Characters ◽  
Morphological Data ◽  
Diversity Analysis ◽  
International Institute ◽  
Mean Values ◽  
The Mean ◽  
Pod Length ◽  
100 Seed Weight

In response to the paucity of information challenge on the neglected and underutilized legumes, this paper explored pods and seeds morphological data of the twenty-four accessions of these crops with a view to establishing the occurrence of genetic variability and diversity analysis among the studied taxa. Twenty-four accessions of neglected and underutilized legumes (NULs) obtained from International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria were assessed for genetic variability and diversity analysis through Pod and seed morphological characters. Each accession was planted into plot of 5 ridges of 5 meter long, spaced 1 meter apart and replicated three times at the teaching and research farm of the Federal University Oye Ekiti, Ekiti State, Nigeria. Descriptive statistics was employed to evaluate differences in the mean values of the accessions while discriminatory traits among accessions were identified by Principal Component Analysis (PCA). Similarities among the studied plants were assessed by cluster analysis. The first two principal component axes explained 72% of the total variation. Pod length, pod width and 100-seed weight were traits that contributed most of the variations in the legume accessions. There was a display of intra-species similarities and inter-specific genetic diversity among the studied accessions.

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