scholarly journals Variability in size and shape in muscovy duck with age: Principal component analysis

2014 ◽  
Vol 30 (1) ◽  
pp. 125-136 ◽  
Author(s):  
D.M. Ogah ◽  
M. Kabir
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Dependence Structure ◽  
Muscovy Duck ◽  
Body Measurements ◽  
Male And Female ◽  
Size And Shape

Body weight and six linear body measurements, body length (BL), breast circumference (BCC), thigh length (TL), shank length (SL), total leg length (TLL) and wing length were recorded on 150 male and female muscovy ducklings and evaluated at 3, 5, 10, 15 and 20 weeks of age. Principal component analysis was used to study the dependence structure among the body measurements and to quantify sex differences in morphometric size and shape variations during growth. The first principal components at each of the five ages in both sexes accounted between 71.54 to 92.95% of the variation in the seven measurements and provided a linear function of size with nearly equal emphasis on all traits. The second principal components in all cases also accounted for between 6.7 to 16.17% of the variations in the dependence structure of the system in the variables as shape, the coefficient for the PCs at various ages were sex dependent with males showing higher variability because of spontaneous increase in size and shape than females. Contribution of the general size factor to the total variance increase with age in both male and female ducklings, while shape factor tend to be stable in males and inconsistent in females.

scholarly journals Variability in size and shape in muscovy duck with age: Principal component analysis

2013 ◽  
Vol 29 (3) ◽  
pp. 493-504
Author(s):  
D.M. Ogah ◽  
M. Kabir
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Dependence Structure ◽  
Muscovy Duck ◽  
Body Measurements ◽  
Male And Female ◽  
Size And Shape

Body weight and six linear body measurements, body length (BL), breast circumference (BCC), thigh length (TL), shank length (SL), total leg length (TLL) and wing length were recorded on 150 male and female muscovy ducklings and evaluated at 3, 5, 10, 15 and 20 weeks of age. Principal component analysis was used to study the dependence structure among the body measurements and to quantify sex differences in morphometric size and shape variations during growth. The first principal components at each of the five ages in both sexes accounted between 71.54 to 92.95% of the variation in the seven measurements and provided a linear function of size with nearly equal emphasis on all traits. The second principal components in all cases also accounted for between 6.7 to 16.17% of the variations in the dependence structure of the system in the variables as shape, the coefficient for the PCS at various ages were sex dependent with males showing higher variability because of spontaneous increase in size and shape than females. Contribution of the general size factor to the total variance increase with age in both male and female ducklings, while shape factor tend to be stable in males and inconsistent in females.

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.

scholarly journals Principal component analysis of the exterior traits in dairy cows

2017 ◽  
Vol 19 (79) ◽  
Author(s):  
S. Kramarenko ◽  
N. Kuzmicheva ◽  
A. Kramarenko
Keyword(s):  
Principal Component Analysis ◽  
Dairy Cows ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Chest Circumference ◽  
State Enterprise ◽  
Body Measurements ◽  
Generalized Variance ◽  
Diagonal Length

The present study was undertaken to study the relationship between different body measurements and to develop unobservable factors (latent) to define which of these measurements best represent body conformation in the dairy cows. Biometrical observations were recorded on 109 Red Steppe dairy cows randomly selected from State Enterprise «Breeding reproducer «Stepove» (Mykolayiv region, Ukraine) during the 2001–2014. Principal Component Analysis (PCA) was used to account for the maximum portion of variation present in the original set of variables (body traits in cow) with a minimum number of composite variables through STATISTICA software. Most of the pairwise phenotypic correlations among the exterior traits in dairy cows were positive and significant. The Pearson’s correlation coefficients of the body measurements ranged from 0.215 (chest depth – cannon circumference) to 0.889 (height at withers – rump height). In factor solution of the Principal Component Analysis, two (latent) which explained 48.5% of the generalized variance were extracted. The first principal component (PC1) explained general body confirmation and explained 33.5% variation. It was represented by significant positive loading for height at withers, rump height, diagonal length from point of shoulder to pin bone, chest depth, chest circumference etc.). The second principal component (PC2) accounted for an additional 15.0% of the generalized variance and was interpreted as an indicator of body shape (e.g., endomorphic vs. ectomorphic). It was represented by significant negative loadings for height at withers, rump height, diagonal length from point of shoulder to pin bone, but significant positive loadings for chest width, chest depth, chest circumference and cannon circumference. The study also revealed that factors extracted from the present investigation could be used in breeding programs of the dairy cattle.

scholarly journals Evaluasi Ukuran-Ukuran Tubuh pada Sapi Belgian Blue, Peranakan Ongole dan Silangannya

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Aminurrahman Aminurrahman ◽  
Rudy Priyanto ◽  
Jakaria Jakaria
Keyword(s):  
Principal Component Analysis ◽  
Measurement Data ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Body Measurements ◽  
Body Measurement ◽  
Slope Length ◽  
Depth Index ◽  
Index 2

ABSTRAK. Penelitian ini bertujuan mengevaluasi dan menganalisis ukuran-ukuran tubuh pada sapi Belgian Blue, Peranakan Ongole dan silangannya. Sapi yang digunakan dalam penelitian ini sebanyak 30 ekor terdiri atas 7 ekor sapi Belgian Blue (BB), 8 ekor sapi Peranakan Ongole (PO) dan 15 ekor silangannya (BBxPO) yang dipelihara di Balai Embrio Ternak (BET) Cipelang Bogor, Indonesia. Peubah ukuran-ukuran tubuh yang diamati adalah panjang badan, tinggi pundak, dalam dada, lebar dada, lingkar dada, tinggi pinggul dan lebar pinggul, sedangkan indeksasi yang dihitung adalah weight, height slope, length index 1, length index 2, width slope, depth index dan foreleg length. Data ukuran-ukuran tubuh pada setiap bangsa sapi dikoreksi berdasarkan umur dan jenis kelamin. Selanjutnya data ukuran-ukuran tubuh dan nilai indeksasi dianalisis menggunakan analisis ragam (ANOVA) dengan program SAS 9.4. Analisis Komponen Utama (AKU) dengan pendekatan biplot dianalisis menggunakan program XLSTAT. Hasil penelitian menunjukkan bahwa ukuran-ukuran tubuh dan indeksasi pada setiap bangsa sapi berbeda (P0.05). Hasil analisis komponen utama memperlihatkan bahwa ketiga bangsa sapi yang dianalisis secara jelas terpisah baik sapi BB, PO dan silangannya. Bangsa sapi BB dan silangannya (BBPO) memiliki karakter peubah spesifik dan menjadi penciri pada setiap bangsa sapi. Dengan demikian arah seleksi dapat mengacu pada karakter yang diinginkan sebagai sapi penghasil tipe pedaging.  Evaluation of the Body Measurements on Belgian Blue, Peranakan Ongole and Its Crossbreed Cattle ABSTRACT. This study was aimed to evaluate and analyze body measurements in Belgian Blue (BB), Ongole Breed (PO) and its crossbreed (BBPO) cattle. The number of cattle used in the study were 30 heads, with 7 heads of Belgian Blue cattle, 8 heads of Ongole breed cattle, and 15 heads of its crossbreed cattle were kept in the Animal Embryo Centre (BET) Cipelang Bogor. The variables observed were body length, withers height, chest depth, chest width, girth depth, rump height, and hip-width and the calculated indexations were weight, height slope, length index 1, length index 2, width slope, depth index, and foreleg length. The body measurement data on each breed of cattle was corrected by age and sex. Furthermore, analysis of body measurement and indexing was using Analysis of variance (ANOVA) with SAS program 9.4. As for Principal Component Analysis (PCA) with a biplot approach analyzed using XLStat program. The result showed that body measurement and indexing on each breed of cattle was different (P0.05). The result of principal component analysis (PCA) suggested that the three breeds analyzed to separate the BB, PO, and it's a crossbreed. The BB and its crossbreed had specific character and became an identifying mark in every breed of cattle. Thus, the direction of the selection can refer to the qualities desired as producing beef cattle type.

scholarly journals A functional approach to the body condition assessment of lactating donkeys as a tool for welfare evaluation

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3001 ◽  
Author(s):  
Emanuela Valle ◽  
Federica Raspa ◽  
Marzia Giribaldi ◽  
Raffaella Barbero ◽  
Stefania Bergagna ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Body Condition ◽  
Negative Correlation ◽  
Body Condition Score ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Abdominal Circumference ◽  
Body Measurements ◽  
Positive Correlation

BackgroundThe breeding of lactating donkeys is increasing in Western Europe; with it the evaluation of body condition is growing in importance since it is considered a key principle for their welfare. However, assessment of body condition is a complex task, since several factors are involved. The aim of the present study is to investigate which animal-based indicators are the most reliable to describe the body condition of lactating donkeys. For this purpose, new animal-based indicators, which are easy to measure in field conditions (including body measurements, fatty neck score (FNS), dental score), are recorded and their relationship with BCS (a proxy measure for overall adiposity) was assessed. The ones that reveal an association with the BCS are included in an integrated principal component analysis to understand which are the most related to BCS.MethodsFifty-three healthy lactating donkeys of various breeds, including 7 Martina Franca, 10 Ragusano, 2 Romagnolo and 34 crossbreeds, were evaluated. The animal-based indicators that were recorded were: length (OP, olecranon tuber-pinbone and SH, shoulder-hip), heart girth (HG), abdominal circumference (AC), neck length (NL), neck height (NH) and neck thickness (NT) at 0.50 and neck circumference (NC) at 0.25, 0.50 and 0.75, body condition score (BCS) and fatty neck score (FNS). The owners’ evaluation of the BCS was also considered. A dental assessment was performed and the month of lactation and age of each animal was recorded.ResultsNo correlation was found between BCS and the other morphometric body measurements. On the contrary the FNS was correlated with the morphometric measurements of the neck (positive correlation to 0.50 NH and 0.50 NT, 0.50 NC, 0.75 mean NC, and negative correlation to the mean NC:NH and mean NC:NT, 0.50 NC:NT and 0.50 NC:NH ratios). A significant inverse relationship was identified between BCS and dental score. A Principal Component analysis (PCA) separated the BCS classes on the first principal component (PC1). PC1 revealed a meaningful positive correlation between the BCS and the neck measurements (NT, NH and FNS), with high positive loadings, while a negative correlation was found for dental abnormalities. The owners’ evaluation of BCS was different from the expert evaluator’ assessment, since they tended to give higher score that was slightly but significantly correlated to AC.DiscussionA new scoring system, called Fatty Neck Score (FNS), has been proposed for the judgement of the adiposity status of donkey neck. The results suggest that caregivers might use the proposed animal based indicators (BCS, FNS and dental scores) together as a tool for the evaluation of the body condition of lactating donkeys. Our findings highlight that caregivers need to be trained in order to be able to properly record these indicators. Ultimately use of these indicators may help to improve the welfare of lactating donkeys.

Stormwater inflow prediction using radar rainfall data compressed by principal component analysis

2006 ◽  
Vol 1 (1) ◽  
Author(s):  
K. Katayama ◽  
K. Kimijima ◽  
O. Yamanaka ◽  
A. Nagaiwa ◽  
Y. Ono
Keyword(s):  
Principal Component Analysis ◽  
Prediction Model ◽  
Principal Components ◽  
Prediction Method ◽  
Principal Component ◽  
Component Analysis ◽  
Rainfall Data ◽  
Radar Rainfall ◽  
Input Variables ◽  
Inflow Prediction

This paper proposes a method of stormwater inflow prediction using radar rainfall data as the input of the prediction model constructed by system identification. The aim of the proposal is to construct a compact system by reducing the dimension of the input data. In this paper, Principal Component Analysis (PCA), which is widely used as a statistical method for data analysis and compression, is applied to pre-processing radar rainfall data. Then we evaluate the proposed method using the radar rainfall data and the inflow data acquired in a certain combined sewer system. This study reveals that a few principal components of radar rainfall data can be appropriate as the input variables to storm water inflow prediction model. Consequently, we have established a procedure for the stormwater prediction method using a few principal components of radar rainfall data.

The Design of Index about Corporate Governance Based on PCA Method

2014 ◽  
Vol 926-930 ◽  
pp. 4085-4088
Author(s):  
Chuan Jun Li
Keyword(s):  
Principal Component Analysis ◽  
Corporate Governance ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Contribution Rate ◽  
Variance Contribution ◽  
Pca Method

This article uses the PCA method (Principal component analysis) to evaluate the level of corporate governance. PCA is used to analyze the correlation among 10 original indicators, and extract some principal components so that most of the information of the original indicators is extracted. The formulation of the index of corporate governance can be got by calculating the weight based on the variance contribution rate of the principal component, which can comprehensively evaluate corporate governance.

Identification of Liquor Brands Based on near Infrared Spectroscopy

2013 ◽  
Vol 834-836 ◽  
pp. 935-938
Author(s):  
Lian Shun Zhang ◽  
Chao Guo ◽  
Bao Quan Wang
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Principal Components ◽  
Near Infrared ◽  
Scatter Correction ◽  
Principal Component ◽  
Component Analysis ◽  
Correction Method ◽  
Variance Contribution

In this paper, the liquor brands were identified based on the near infrared spectroscopy method and the principal component analysis. 60 samples of 6 different brands liquor were measured by the spectrometer of USB4000. Then, in order to eliminate the noise caused by the external factors, the smoothing method and the multiplicative scatter correction method were used. After the preprocessing, we got the revised spectra of the 60 samples. The difference of the spectrum shape of different brands is not much enough to classify them. So the principal component analysis was applied for further analysis. The results showed that the first two principal components variance contribution rate had reached 99.06%, which can effectively represent the information of the spectrums after preprocessing. From the scatter plot of the two principal components, the 6 different brands of liquor were identified more accurate and easier than the spectra curves.

scholarly journals Grouping sunflower genotypes for yield, oil content, and reaction to Alternaria leaf spot using GGE biplot

2015 ◽  
Vol 50 (8) ◽  
pp. 649-657 ◽  
Author(s):  
Regina Maria Villas Bôas de Campos Leite ◽  
Maria Cristina Neves de Oliveira
Keyword(s):  
Principal Component Analysis ◽  
Disease Severity ◽  
Principal Components ◽  
Leaf Spot ◽  
Oil Content ◽  
Principal Component ◽  
Component Analysis ◽  
High Yield ◽  
Gge Biplot ◽  
Alternaria Leaf Spot

Abstract:The objective of this work was to evaluate the suitability of the multivariate method of principal component analysis (PCA) using the GGE biplot software for grouping sunflower genotypes for their reaction to Alternaria leaf spot disease (Alternariaster helianthi), and for their yield and oil content. Sixty-nine genotypes were evaluated for disease severity in the field, at the R3 growth stage, in seven growing seasons, in Londrina, in the state of Paraná, Brazil, using a diagrammatic scale developed for this disease. Yield and oil content were also evaluated. Data were standardized using the software Statistica, and GGE biplot was used for PCA and graphical display of data. The first two principal components explained 77.9% of the total variation. According to the polygonal biplot using the first two principal components and three response variables, the genotypes were divided into seven sectors. Genotypes located on sectors 1 and 2 showed high yield and high oil content, respectively, and those located on sector 7 showed tolerance to the disease and high yield, despite the high disease severity. The principal component analysis using GGE biplot is an efficient method for grouping sunflower genotypes based on the studied variables.

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