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.

Study of Body Conformation of Carpet Wool Type Chitarangi Sheep of India using Principal Component Analysis

2021 ◽  
Author(s):  
A.K. Mishra ◽  
Anand Jain ◽  
S. Singh ◽  
R.K. Pundir
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Total Variation ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Sheep Population ◽  
Body Conformation ◽  
Face Length ◽  
Minimum Number

Background: The principal component analysis is applied to identify minimum number of combined variables that account for maximum portion of the variance existing in all variables studied. Chitarangi is a lesser known carpet type wool sheep distributed in Fazilka and Muktsar districts of Punjab, Sri Ganganagar district of Rajasthan and the adjoining areas. The information on body biometry is a prerequisite to characterize the lesser known sheep population available in the country. Hence, it is important to describe the body conformation by recording minimum number of biometric traits. Methods: Body biometry traits of Chitarangi sheep, a lesser known carpet quality wool producing sheep population were studied using Principal Component Analysis. The traits studied were body length (BL), height at wither (HW), chest girth (CG), paunch girth (PG), ear length (EL), face length (FL), face width (FW), tail length (TL) and adult body weight (BW). The data were collected on 297 ewes in the breeding tract of Chitarangi sheep. The descriptive statistics were determined for all the traits. The phenotypic correlations between different body biometric traits were estimated using partial correlations. Principal components were estimated using correlation matrix. Principal component analysis (PCA), a multivariate approach, is used when the recorded traits are highly correlated. Rotation of principal components was through the transformation of the components to approximate a simple structure. Factor analysis using oblique (promax) rotation was used. All the analysis was carried out using the SPSS statistical package. Result: The averages for body weight and biometry traits confirmed large size of Chitarangi animals. Most of the phenotypic correlations amongst the studied traits were positive and significant (p less than 0.01). The three components extracted from nine principal components accounted for 69.06% of the total variance. The first component, which described body size of ewes, accounted for 43.68% of the total variation with high loading for BW, CG, PG, HW, BL and FL. The components two and three explained 13.54 and 11.83% of total variance, respectively. The communalities ranged from 0.490 (FL) to 0.888 (PG). The lower communalities for face length indicated lower contribution of the trait to explain the total variation than others. The study indicates that principal components provided a means of reduction in number of biometric traits to explain body confirmation of adult female Chitarangi sheep.

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 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 Bayesian principal component analysis of Nigerian indigenous normal feather chickens' body linear measurements

2020 ◽  
Vol 44 (1) ◽  
pp. 10-20
Author(s):  
A. E. Sonubi ◽  
A. S. Adenaike ◽  
A. A. Dauda ◽  
T. P. Alao ◽  
B. O. Shonubi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Principal Components ◽  
Body Shape ◽  
Principal Component ◽  
Component Analysis ◽  
Body Measurements ◽  
Indigenous Chicken ◽  
Body Dimension ◽  
Linear Measurements

The indigenous chicken is a store house of unique genes that could be used in other parts of the world for improving other breeds. This study was carried out using bayesian principal component analysis and aimed objectively at determining the effect of sex on Nigerian indigenous normal feather chickens' body dimension, describing their body shape, and predicting their body weights from body measurements using orthogonal conformation traits derived from the principal components score. The parameters measured at 16 weeks of age were body weight, body length, breast girth, thigh length, shank length, shank diameter, keel length, wing length, wing span, and tail length on 233 randomly selected adult chickens. Sexual dimorphism was observed in all the traits with higher values recorded for males. Bayesian correlations among body weight and biometric traits were positive (r = 0.09 to 0.651 and 0.017 to 0.579 in male and female chickens respectively). The descriptive statistics showed that the mean body weight was 1.8085 ± 0.263 kg for males and 1.403 ± 0.226 kg for females. The first two principal components (PCs) were extracted for the males, both PCs components account for 72.21%. For the females, three PCs were extracted and they account for 77%. The first PC in each case accounted for the greatest percentage of the total variation. The use of orthogonal body shape characteristics derived from components' scores was more appropriate than the use of original traits in body weight prediction as multi-collinearity problems were eliminated. This led to simultaneous analysis of these body measurements rather than on individual basis. These components could be used as selection criteria for improving body weight of indigenous Nigerian chickens.

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