scholarly journals Variability, Genetic Diversity and Principal Component Analysis in Indian Mustard (Brassica juncea (L.) Czern.& Coss.) for Seed Yield and Attributing Traits

2021 ◽  
Vol 10 (2) ◽  
pp. 1769-1777
Author(s):  
Bhupendra Singh Yadav Hariom Kumar Sharma ◽  
Ajay Pal Yadav Bhagirath Ram
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Brassica Juncea ◽  
Seed Yield ◽  
Indian Mustard ◽  
Principal Component ◽  
Component Analysis

scholarly journals Evaluation and diversity analysis in Indian mustard [Brassica juncea (L.) Czern & Coss.] germplasm accessions on the basis of principal component analysis

2017 ◽  
Vol 9 (4) ◽  
pp. 2485-2490
Author(s):  
Ram Avtar ◽  
Manmohan Manmohan ◽  
Minakshi Jattan ◽  
Babita Rani ◽  
Nisha Kumari ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Total Variation ◽  
Brassica Juncea ◽  
Seed Yield ◽  
Oil Content ◽  
Indian Mustard ◽  
Principal Component ◽  
Component Analysis ◽  
Principal Factor ◽  
Germplasm Accessions

Principal component analysis was carried out with 20 morphological traits (including quantitative as well as qualitative) among 96 germplasm lines of Indian mustard [Brassica juncea (L.) Czern & Coss.]. Principal factor analysis led to the identification of eight principal components (PCs) which explained about 70.41% variability. The first principal component (PC1) explained 16.21% of the total variation. The remaining PC’s explained progressively lesser and lesser of the total variation. Varimax Rotation enabled loading of similar type of variables on a common principal factor (PF) permitting to designate them as yield factor, maturity factor and oil factor etc. Based on PF scores and cluster mean values the germplasm accessions viz., RC2, RC32 and RC51 (cluster I), RC95 and RC96 (cluster X) were found superior for seed yield/plant and yield related factors like primary and secondary branches/plant; while the accessions RC34, RC185 and RC195 (cluster III) and RC53 (cluster VIII) were found superior for oil content. These accessions may further be utilized in breeding programmes for evolving mustard varieties having high seed yield and oil content. Hierarchical cluster analysis resulted into ten clusters containing two to 26 accessions. The results of cluster and principal factor analyses were in confirmation of each other.

↵Genetic Diversity and Principal Component Analysis in Mungbean [Vigna radiata (L.) Wilczek] under Rainfed Condition

2021 ◽  
Author(s):  
Deepak Gupta ◽  
Suresh Muralia ◽  
N.K. Gupta ◽  
Sunita Gupta ◽  
M.L. Jakhar ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Seed Yield ◽  
Agricultural Research ◽  
Principal Component ◽  
Component Analysis ◽  
Grain Legume ◽  
Research Station ◽  
Rainfed Condition

Background: Mungbean is a short duration grain legume widely grown in south and Southeast Asia. The extent of variability through Principal Component Analysis (PCA) and cluster analysis in promising mungbean genotypes should be known for possible yield improvement. A study was undertaken to work out the extent of variability among twenty four mungbean genotypes through cluster analysis and Principal Component Analysis (PCA). Methods: The experiment was laid out in a randomized block design with three replications during kharif 2018 and 2019 at the experimental field of Agricultural Research Station, Navgaon (Alwar) under rainfed condition. Result: Principal component analysis revealed that the first three main PCAs amounted 78.80% of the total variation among genotypes for different traits. Out of total principal components, PC1 accounts for maximum variability in the data with respect to succeeding components. Number of branches per plant (28.62%), number of clusters per plant (23.55%) and seed yield (15.58%) showed maximum per cent contribution towards total genetic divergence on pooled basis. Cluster analysis showed that genotypes fall into seven different clusters and their inter and intra cluster distance showed genetic diversity between different genotypes. The maximum number of genotypes i.e., 8 was found in cluster II followed by cluster III comprising of 6 genotypes. Genotypes RMG-1138 and IPM-02-03 representing the mono genotypic cluster signifies that it can be the most diverse variety and it would be the appropriate genotype for hybridization with ones present in other clusters to tailor the agriculturally important traits and ultimately to boost the seed yield in mungbean under rainfed conditions.

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

2021 ◽  
Author(s):  
S.R. Singh ◽  
S. Rajan ◽  
Dinesh Kumar ◽  
V.K. Soni
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Single Linkage ◽  
Pod Yield ◽  
Diversity Assessment ◽  
Single Linkage Cluster ◽  
Linkage Cluster

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

Genetic diversity based on cluster and principal component analysis in wheat and triticale genotypes

2015 ◽  
Vol 16 (4) ◽  
pp. 712
Author(s):  
Bhanu Priya ◽  
Sunil Diyali ◽  
Subhra Mukherjee ◽  
M. Srinivasarao
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis

scholarly journals Estimation of Genetic Diversity among Genotypes of Fodder Oat based on Principal Component Analysis

2017 ◽  
Vol 8 (6) ◽  
pp. 807-810
Author(s):  
Monica Jyoti Kujur ◽  
◽  
A. K. Mehta ◽  
S. K. Bilaiya ◽  
Prakarti Patil ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis

scholarly journals Genetic Diversity Studies in Drought Tolerant Rice (Oryza sativa L.) Genotypes

2021 ◽  
Author(s):  
A. Sheeba ◽  
S. Mohan
Keyword(s):  
Genetic Diversity ◽  
Principal Component Analysis ◽  
Association Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Large Set ◽  
Panicle Length ◽  
Rice Varieties ◽  
Drought Tolerant ◽  
Rice Genotypes

Background: Assessing the genetic diversity and relationship among breeding materials isan invaluable aid for any crop improvement programme. Principal component analysis (PCA) is a multivariate statistical technique attempt to simplify and analyze the inter relationship among a large set of variables in term of a relatively a small set of variables or components without losing any essential information of original data set. Methods: The present investigation was carried out to study the genetic diversity and relationship among the sixty five rice genotypes including popular rice varieties of Tamil Nadu, drought tolerant rice varieties, aerobic rice genotypes and land races. These genotypes were raised at Rice Research Station, Tiruvallur, during kharif, 2015 in randomized block design with three replications under aerobic condition. Data on eight yield and yield attributing traits were recorded and subjected to principal component analysis and association analysis. Result: In principal component analysis, PC1accounted for 22.91% and PC2 accounted for 19.53% of the total variation. The traits panicle length, no. of grains per panicle, plant height, days to 50% flowering, no of productive tillers per plant from the first two principal components accounted for major contribution to the total variability. Cluster analysis grouped the genotypes into six discrete clusters. The association analysis revealed that the traits viz., no. of productive tillers/plant, panicle length and hundred seed weight had positive association with higher direct effect on plot yield which could be used as selection criteria for developing high yielding rice varieties. The results of the present study have revealed the high level of genetic variation existing in the genotypes studied and explains the traits contributing for this diversity.

Application of Principal Component Analysis (PCA) for Blackgram [Vigna mungo (L.) Hepper] Germplasm Evaluation under Normal and Water Stressed Conditions

2020 ◽  
Author(s):  
V.A. Mohanlal ◽  
K. Saravanan ◽  
T. Sabesan
Keyword(s):  
Principal Component Analysis ◽  
Water Stress ◽  
Seed Yield ◽  
Cropping Systems ◽  
Principal Component ◽  
Component Analysis ◽  
Vigna Mungo ◽  
Yield Potential ◽  
Positive Interaction ◽  
Drought Tolerant

Background: Blackgram [Vigna mungo (L.) Hepper] is a popularly known pulse crop in India for its nutritional quality and adaptability to many cropping systems. The crop is mostly cultivated in areas experiencing water stress which reduces the yield potential. Thus, it is imperative to assess the genetic variability present in the existing blackgram germplasm under drought condition. For this, principal component analysis was carried to visualize the complex dataset. This study was aimed to identify key traits and drought tolerant genotypes. Methods: Twenty-one blackgram genotypes were screened in the field condition for water stress where the experiment was laid out in RBD with two replications. Principal component analysis was carried out with thirteen traits in twenty-one genotypes of blackgram under normal and water stressed conditions.Result: In T0 and T1, more than 75% of total variability among thirteen traits was explained by five and four principal component axes respectively. Under water stress, pod length was highly correlated with seed yield per plant. Based on the interaction vectors and PC scores of genotypes, VBG-12062 had a positive interaction with seed yield. Thus, VBG-12062 can be a reliable candidate for breeding high yielding drought tolerant variety.

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