Exploratory Principal Component Analysis of Body Morphometric Traits as Affected by Age and Sex in Donkeys

2021 ◽  
Author(s):  
Onoruoyiza Asuku Ibrahim ◽  
Kayode Anthony Olutunmogun ◽  
Mallam Iliya ◽  
Chima Martin Umego ◽  
Opeyemi Rachel Alao ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Tail Length ◽  
Component Analysis ◽  
Head Width ◽  
Research Station ◽  
Age Group ◽  
Morphometric Traits ◽  
Production Research ◽  
Age And Sex

Abstract An experiment was conducted to determine the principal component analysis of body morphometric traits as affected by age and sex in donkeys reared on a research station in the National Animal Production Research Institute, Shika-Zaria, Nigeria. This was based on the objective of classifying age and sex using the multivariant method of principal component analysis (PCA) on morphometric traits of donkeys. Data were collected from a total of 101 donkeys based on age and sex on body wright, heart girth, body length, height at withers, tail length, shoulder width, head width, ear length, head length, neck circumference and neck length. The data obtained were subjected to multivariate factor analysis with varimax rotation using IBM® SPSS® Version 21. The results obtained revealed that the age group ≤ 1 year had one PCA, 2–3 years age group had four PCA, 4–5 years group had three PCA while those ≥ 6 years had two PCA. Most of the variables in combination with age largely formed the block of PC1 while other PCA had one or two variables correlating with them. Most of the variables formed PC1 for the Jacks while head width (HW) and ear length (EL) formed PC2. The Jennies had its entire variable in one PCA. Therefore, PC1 had the highest loading for the variables both by age and by sex as the animals are relatively well adapted to their environment. It can be concluded that donkeys between 2-3years have more PC correlation proportions.

scholarly journals Principal Component Analysis of Morphometric Traits of West African Dwarf Goats

2019 ◽  
Vol 1 ◽  
pp. 26-32 ◽  
Author(s):  
I O Dudusola ◽  
S O Oseni ◽  
M A Popoola ◽  
A Jenyo
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Total Variation ◽  
Age Groups ◽  
Principal Component ◽  
Component Analysis ◽  
West African ◽  
Age Group ◽  
Morphometric Traits ◽  
West African Dwarf

The study was conducted to evaluate the principal component analysis of phenotypic attributes of West African Dwarf (WAD) goat. Data collected on the live body weight and twelve morphometric traits of the goats which were categorised into four age groups based on their dentition. The age groups were: less than 2years old, 2- 3years old, 3-4 years old and 4 years old. The data were subjected to a PCA and Cluster analyses using the multivariate procedure components of SAS (2003). Result revealed that highest values of morphometric traits were obtained in goats that of 4 years old. The rate of increase in body weight and other morphometric traits was high in age group of ˂2 years to age 2-3years compared to differences observed in others across the age group. Heart Girth had the highest correlation with body weight. Foreleg, neck, ear and hind leg lengths; wither height and rump height were weakly correlated with the body weight of the goats. Result revealed that two Principal components were retained in the first age group (age group˂2years) which accounted for 72.99% of the total variation. The first PC alone accounted for 63.13% of the total variation while PC2 accounted for the remaining 9.86%. From this study, it was concluded that there is interdependence among body weight and morphometric traits and that morphometric traits can be used in predicting live weight of WAD goats; PCA and Cluster could be exploited in breeding and selection programmes to acquire highly coordinated animal bodies using fewer measurements.

↵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.

scholarly journals Redescription of Leporinus jamesi (Characiformes: Anostomidae), a poorly known species of Leporinus from the lowlands of the central Amazon, Brazil

2014 ◽  
Vol 12 (2) ◽  
pp. 317-326 ◽  
Author(s):  
Júlio C. Garavello ◽  
Heraldo A. Britski ◽  
José L. O. Birindelli
Keyword(s):  
Principal Component Analysis ◽  
Lateral Line ◽  
Principal Component ◽  
Component Analysis ◽  
Species Description ◽  
Single Specimen ◽  
Morphometric Traits ◽  
Caudal Peduncle ◽  
Central Amazon

The poorly known Leporinus jamesiis redescribed. The species was originally described based on a single specimen collected in the rio Solimões at Manacapuru, in the central Amazon, Brazil. The holotype went missing before the species description was finished and published, and remained lost for more than a hundred years. Leporinus jamesi is distinguished from its congeners by having pectoral and pelvic fins dark, 42 to 45 scales on the lateral line, 16 scale series around the caudal peduncle, a body with two conspicuous dark midlateral blotches (the blotch on the caudal peduncle absent or inconspicuous), and four teeth on the premaxilla and dentary, including a bicuspid symphyseal tooth on the premaxilla. A principal component analysis on morphometric traits between combined samples of L. jamesi and L. amazonicus was performed showing significant morphometric differences between these species. In addition, inaccuracies in Borodin's descriptions of various species of the genus Leporinus are discussed.

scholarly journals Principal component analysis of the conformation traits of Yankasa sheep

2013 ◽  
Vol 29 (1) ◽  
pp. 65-74 ◽  
Author(s):  
A. Yakubu
Keyword(s):  
Body Height ◽  
Age Groups ◽  
Principal Component ◽  
Tail Length ◽  
The Body ◽  
Head Width ◽  
Principal Component Factor Analysis ◽  
Body Measurements ◽  
Age Group ◽  
Leg Length

This study was preformed to evaluate the biometric traits of 227 Yankasa sheep in northern Nigeria under a multivariate approach. The body measurements taken were: withers height, rump height, body length, heart girth, tail length, face length, shoulder width, head width, rump width, ear length, foreleg length, hind leg length and rump length. The animals were divided into two age groups: <15.5 and 15.5 - 28.3 months old, respectively. General linear model was used to study age group effect while principal component factor analysis was performed to define body shape upon the correlation matrix of the thirteen body measurements. Age group significantly (P<0.05) affected the morphological characters except ear length. Pearson?s coefficients of correlation were positive and significant in both age groups. In <15.5 months old sheep, four principal components (factors) were extracted (ratio of variance = 89.27). The first factor accounted for 73.03% of the total variance and was interpreted as a measure of general size. The second factor which explained 7.61% of the generalized variance tended to describe flesh dimensions (shoulder width and rump width), while the third factor had its loadings for tail length and ear length. The fourth factor was influenced by head width. In 15.5-28.3 months old sheep, three factors (ratio of variance=75.21) were identified. These seven extracted factors could be considered in breeding programmes to improve body conformation of sheep since variation in meat traits was not associated with body height.

scholarly journals Principal component analysis of linear measures of young horses national champions of Mangalarga Marchador breed

2020 ◽  
Vol 50 (12) ◽  
Author(s):  
Mariana de Castro Sellani ◽  
Adalgiza Souza Carneiro de Rezende ◽  
Emmanuel Arnhold ◽  
Adriana Santana do Carmo ◽  
Arthur dos Santos Mascioli ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Age Groups ◽  
Principal Component ◽  
Component Analysis ◽  
Age Group ◽  
Linear Measurements ◽  
Morphometric Measurements ◽  
National Champions ◽  
Young Horses

ABSTRACT: The conformation is directly related to the quality of the movements, and can direct the selection by equine aptitude. This study aimed to identify which are the morphometric measurements that explain the total variance available in the marcha batida and picada gaits of young Mangalarga Marchador horses. Analyses were performed by evaluating 20 linear measurements of 420 champion horses. Measures were separated by gender (male-M and female-F), type of marcha, (batida-MB e picada-MP) and divided into eight age groups. Principal component analysis (PCA) was used to identify which measurements were most important in determining marcha variance by selecting principal component (PC) which sum of eigenvalues was able to explain the minimum percentage of 80% of the total variation. The PC number varied randomly according to age groups, being 2 to 3 in both genders in MP, 3 to 4 for M-MB, and up to 5 for F-MB, suggesting lower overall variability in MP, and higher in F-MB. There was no defined pattern concerning the amount of PC per age group, demonstrating that each category may have independent variations. Although, some repetitions of variables occurred similarly in different ages, sexes, and marcha types, the responsibility for the highest occurrence of variation was the posterior cannon and gaskin length. The significant variance in the length of these segments, regardless of gender, age, and marcha, and the fact they are not measured daily suggested there is not only a lack of standardization of these segments, but there is also size compensation among them since the group evaluated is composed of breed champions.

scholarly journals Developmental effects on pattern visual evoked potentials characterized by principal component analysis

2020 ◽  
Author(s):  
Carlyn Patterson Gentile ◽  
Nabin R Joshi ◽  
Kenneth Ciuffreda ◽  
Kristy Arbogast ◽  
Christina Master ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Time Course ◽  
Principal Component ◽  
Component Analysis ◽  
Training Dataset ◽  
Pattern Reversal ◽  
Age Related ◽  
Significant Difference ◽  
Age And Sex ◽  
Visual Evoked

Purpose: Peak amplitude and latency in the pattern reversal visual evoked potential (prVEP) vary with maturation. We considered that principal component analysis (PCA) may be used to describe age-related variation over the entire prVEP time course and provide a means of modeling and removing variation due to developmental age. Methods: prVEP was recorded from 155 healthy subjects ages 11-19 years during two sessions (spaced 0.7 to 17 months apart). We created a model of the prVEP by identifying principal components (PCs) that explained >95% of the variance in a training dataset of 40 subjects. We examined the ability of the PCs to explain variance in an age- and sex-matched test subject group (n=40) and calculated the intra-subject reliability of the PC coefficients between the two sessions. We then explored the effect of subject age and sex upon the PC coefficients. Results: Seven PCs accounted for 96.0% of the variability. The model was generalizable (training vs. test coefficient distributions p>0.36 for all PCs) with good within-subject reliability (R>0.7 for all PCs). The PCA model did not show a significant difference between males and females (F(7,147)=1.69, p=0.12), but showed a significant effect of subject age (F(7,147)=4.37, p=0.0002). Conclusions: PCA is a generalizable, reliable, and unbiased method of analyzing prVEP that can quantify and remove developmental variability present in the global temporal VEP signal. Translational relevance: We describe a novel application of PCA to characterize developmental changes of prVEP in youth that can be used to compare healthy and pathologic pediatric cohorts.

scholarly journals Principal components for the in vivo and carcass conformations of Anglo-Nubian crossbred goats

2018 ◽  
Vol 48 (6) ◽  
Author(s):  
Marta Jeidjane Borges Ribeiro ◽  
Luís Fernando Batista Pinto ◽  
Ana Carla Borges Barbosa ◽  
Gladston Rafael de Arruda Santos ◽  
Ana Paula Gomes Pinto ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Body Condition ◽  
Principal Components ◽  
Carcass Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Total Variance ◽  
Morphometric Traits

ABSTRACT: This study aimed to identify the principal components (PC) that explain the highest percentages of total variance and best characterize the in vivo and carcass morphologies of Anglo-Nubian crossbred goats. Nineteen carcass morphometric traits and six in vivo morphometric traits were measured in 28 kids at eight months of age. Principal component analysis indicated that five PC were able to explain 83.57% of the total variance in the 19 original carcass traits. Those components were termed PC1-Carcass Size, PC2 - Body Condition, PC3-Carcass Width, PC4-Chest Depth, and PC5 - Hindquarter. For in vivo morphometric traits, the first two principal components explained 78.86% of the total variance. These components were called PC1-In vivo Size and PC2-In vivo Conformation.

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