scholarly journals MULTIVARIATE ANALYSIS OF MORPHOLOGICAL TRAITS AND THE MOST IMPORTANT PRODUCTIVE TRAITS OF WHEAT IN EXTREME WET CONDITIONS

2020 ◽  
Vol 18 (4) ◽  
pp. 5857-5871
Author(s):  
K. LUKOVIĆ ◽  
S. PRODANOVIĆ ◽  
V. PERIŠIĆ ◽  
M. MILOVANOVIĆ ◽  
V. PERIŠIĆ ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Morphological Traits ◽  
Productive Traits

Multivariate analysis in mungbean [Vigna radiata (L.) Wilczek] to identify the genetic donors for pubescence and agro-morphological traits

2015 ◽  
Vol 38 (6) ◽  
Author(s):  
Chandra Mohan Singh ◽  
S. B. Mishra ◽  
Anil Pandey ◽  
Madhuri Arya
Keyword(s):  
Multivariate Analysis ◽  
Seed Yield ◽  
Morphological Traits ◽  
Branch Angle ◽  
High Contribution ◽  
Genotypic Cluster ◽  
Biological Yield ◽  
Total Divergence ◽  
Beak Length ◽  
Selection Of

The present investigation was conducted with 36 genotypes of mungbean on 26 agro-morphological traits including seed yield and pubescence traits to access the degree of divergence for mungbean improvement during <italic>zaid</italic> 2012. These mungbean genotypes were grouped into seven clusters. Cluster IV comprised of 14 genotypes, forming the largest cluster followed by cluster VI comprised eight genotypes, cluster I comprised seven genotypes and cluster II comprised four genotypes. Three clusters <italic>viz.</italic>, cluster III, V & VII formed mono genotypic cluster. All the pubescence traits contributed towards total divergence. Among the agro-morphological traits, high contribution towards total divergence was recorded for beak length, average intermodal length, primary branch angle with main stem, biological yield, seed yield and pods per cluster, indicated the possibility of selection of parent(s) for hybridization to manipulate the targeted trait(s) for mungbean improvement.

scholarly journals Multivariate analysis and character association for agro-morphological traits in elite rice germplasm

2022 ◽  
Vol 13 (3) ◽  
Author(s):  
Kunta Mounika ◽  
Darmagaru Shivani ◽  
Farzana Jabeen ◽  
Kasarla Chaitanya ◽  
Mushyam Chiranjeevi ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Morphological Traits ◽  
Rice Germplasm ◽  
Character Association

Multivariate analysis for morphological traits of the Hamra goat population in two regions of Morocco

2016 ◽  
Vol 59 ◽  
pp. 55-62
Author(s):  
B. Hilal ◽  
S. El Otmani ◽  
M. Chentouf ◽  
I. Boujenane
Keyword(s):  
Factor Analysis ◽  
Multivariate Analysis ◽  
Discriminant Analysis ◽  
Variance Component ◽  
Morphological Traits ◽  
Head Width ◽  
Body Measurements ◽  
Morphometric Traits ◽  
Goat Population ◽  
Two Populations

SummaryThe goal of this study was to characterize the Hamra goat population and to determine if Hamra goats of Beni Arouss and Rommani regions belong to the same population. Eleven morphometric traits of 157 Hamra animals (94 from Beni Arouss and 63 from Rommani) were used for this study. Overall, heart girth, body length, height at withers (HaW), height at rump (HS), chest depth (ChD), pelvis width (PW), chest width (CW), cannon circumference, head length (HeL), head width (HeW) and horn length (HL) of Hamra goats averaged 81.3, 61.5, 64.8, 65.3, 40.9, 19.3, 20.2, 9.67, 28.0, 26.3 and 23.4 cm, respectively. The effect of region was significant only on HaW, PW, HeL, HeW and HL, indicating certain homogeneity among goats of the two regions. Moreover, the inter region variance component ranged from 0 percent (absence of variability) for HS, CW, ChD and ChD to 18.5 percent for HeL, suggesting that the variability of body measurements between Beni Arouss and Rommani regions is very low. The factor analysis revealed four factors, which accounted for 73.5 percent of the total variance. The most discriminant variables between the two populations were HeL, HeW, PW and CW. The Mahalanobis distance between the two populations was 1.197, suggesting that there was genetic exchange between the two populations. The discriminant analysis showed that 80.9 percent of Rommani and 50.0 percent of Beni Arouss individuals were classified into their respective population. Results obtained will help in developing improvement and preservation strategies for the Hamra goat population.

scholarly journals Multivariate Analysis and its Application for Screening Mungbean [Vigna radiata (L.) Wilczek] Landraces

2022 ◽  
Author(s):  
Berk Benlioglu ◽  
Ugur Ozkan
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Vigna Radiata ◽  
Morphological Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Multivariate Statistical ◽  
Breeding Programs ◽  
High Level

Background: Mungbean [Vigna radiata (L.) Wilczek] is known as one of the important crop of the Vigna group. In order to determine morphological traits of mungbean, multivariate analysis will provide important advantages in the selection phase of future breeding programs. Multivariate statistical analysis was used to determine and classify these traits. Multivariate analysis, that includes principal component analysis (PCA) and cluster analysis (CA), is considered the best tool for selecting promising genotypes in the future breeding programs. Methods: Eighteen landraces and two species were used to classify morphological traits in this study. Nine different morphological traits were observed during the research period. These are; days to 50% flowering (DFT), plant height (PH), branches per plant (BPP), clusters per plant (CPP), number of pods per cluster (PPC), seed yield per plot (SYPP), biomass yield per plot (BYPP), harvest index (HI), 1000 seed weight (SW). Result: Principal component analysis (PCA) revealed a high level of variation among the genotypes. Therefore, high variability was observed in DFT (36-59 day), PH (39-76 cm), BPP (3-7), CPP (4-21), SYPP (231-824 g), BYPP (3300-10300 g), HI (6.77-11.25%) and 1000 SW (19.95-50.50 g). According to cluster analysis, landraces with the least genetic diversity distance between them in terms of morphological traits examined were determined as 2 and 3.

Extent and pattern of genetic diversity in linseed(Linum usitatissimum L) under irrigated ecology

2018 ◽  
Vol 5 (01) ◽  
Author(s):  
M. P. CHAUHAN ◽  
H. K. SINGH ◽  
JAY KUMAR YADAV ◽  
M K. MAURYA
Keyword(s):  
Genetic Diversity ◽  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Analysis Of Variance ◽  
Linum Usitatissimum ◽  
Morphological Traits ◽  
Field Data ◽  
Relative Importance ◽  
Linum Usitatissimum L ◽  
Phenotypic Divergence

Sixty six genotypes of linseed were analysed for the morphological traits to investigate the genetic diversity between and within the genotypes. The field data was initially subjected to analysis of variance. There were highly significant differences among the genotypes for all the traits indicating the presence of variability among the genotypes and the possibility to undertake cluster analysis. The phenotypic divergence and relative importance were estimated by multivariate analysis. The cluster analysis classified linseed genotypes in to nine major groups. The maximum intercluster diversity was observed between cluster VIII and V. Based on mean performance of the genotypes and intercluster distance the crosses between ICAR Sel-1 and L-9, NDC 2005-34, H660, LCK 87042, NDL2005-22, GS335 is recommended to get use full transgressive sergeants in linseed.

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