Study of carcass, organ, muscle, fat tissue weight, and concentration in rats fed CLA or its precursors by principal component analysis

2004 ◽  
Vol 84 (3) ◽  
pp. 537-543 ◽  
Author(s):  
L. A. Goonewardene ◽  
P. S. Mir ◽  
Z. Wang ◽  
E. K. Okine ◽  
Z. Mir ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Linoleic Acid ◽  
Soybean Oil ◽  
Conjugated Linoleic Acid ◽  
Total Variation ◽  
Sunflower Oil ◽  
Principal Component ◽  
Component Analysis ◽  
Fat Tissue ◽  
Muscle Weight

Carcass, organ and muscle weight, and fat tissue data were obtained from 30 weaned male Wistar rats fed one of three diets, (10 rats/diet) over a period of 60 d. The diets were base with synthetic conjugated linoleic acid (CLA), sunflower oil or beef enriched CLA. The CLA diet contained the base diet and 18.2 g kg-1 of synthetic CLA (53% cis 9, trans 11 and 44% trans 10, cis 12) replacing 26% of the soybean oil, the sunflower oil diet contained the base plus 70 g kg-1 of sunflower oil replacing all the soybean oil, and the CLA-enriched diet contained the base plus 200 g kg-1 of beef enriched bio-formed CLA replacing the casein. Data were subjected to a principal component analysis (PCA). The first principal component (PC) extracted carcass weight, organ and muscle weight variables and accounted for 41.3% of the total variation. The second principal component included all of the fat tissue variables and accounted for 20.5% of the total variation. The rats fed the synthetic CLA diet were associated with high carcass, liver, kidney, heart, gastrocnemius and soleus muscle weights, and low retroperitoneal and inguinal fat weights, and adipocyte numbers in the fat tissues. In rat models, short periods of synthetic CLA feeding may have a greater impact on decreasing fat accretion in selected fat tissues than feeding CLA-enriched meat. The PC analysis provides means of combining into one or a few components traits that have similar responses, each component being orthogonal to all other components, whereas, in a conventional univariate analysis of variance each dependent variable is analyzed separately in relation to one or more independent variable. Key words: Conjugated linoleic acid, feeding, principal component analysis, fat, muscle, accretion

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.

scholarly journals Evaluation of the Adulteration of Edible and Cosmetic Sunflower Oils by GC-FID and ESI-MS

2021 ◽  
Author(s):  
Luciana Manin ◽  
Jessica Pizzo ◽  
Adriela Rydlewski ◽  
Patrícia Santos ◽  
Marília Galuch ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Sunflower Oil ◽  
Principal Component ◽  
Component Analysis ◽  
Ionization Mass ◽  
Esi Ms ◽  
Flame Ionization ◽  
Sunflower Oils ◽  
Complementary Techniques ◽  
Real Composition

Sunflower oil has several properties that are valuable to the human skin and health; however, they are target of adulterations. In this study, in order to evaluate the authenticity of edible and cosmetics based on sunflower oils, the triacylglycerol (TAG) profiles using direct infusion electrospray ionization mass spectrometry (ESI-MS), the fatty acid (FA) composition by gas chromatography with flame ionization detection (GC-FID) and principal component analysis, of seven commercial samples were determined and the results obtained were compared with the pure sunflower and soybean oils. Of the seven brands analyzed, just one sample presented only sunflower oil in its composition; two stated in the label soybean addition; and four did not present the real composition of the product in the label. Therefore, GC-FID and ESI-MS analysis in conjunction with principal component analysis (PCA) demonstrated that they are complementary techniques and could be applied in food industries to assess the quality of vegetable oils, since results showed the need for stricter quality control for this product.

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.

scholarly journals Key Determinants of Indonesia’s Banks Financial Performance

2019 ◽  
Vol 21 (2) ◽  
pp. 58-67
Author(s):  
Martin Panggabean ◽  
Stefan Batara Panggabean
Keyword(s):  
Principal Component Analysis ◽  
Financial Performance ◽  
Total Variation ◽  
Principal Components ◽  
Principal Component ◽  
Component Analysis ◽  
Financial Indicators ◽  
Balance Sheets ◽  
Conventional Banks

Depositors, investors, as well as public in general need easily accessible indicators that are important to differentiate various banks. This research addresses simultaneously two important issues: analyzing and identifying which key publicly available financial indicators of banks are important, as well as approximating the weight of the aforementioned indicators when banks’ comparisons are to be made. Utilizing the recent 2017 database from 90 conventional banks, this study analyzes 17 banking ratios using the method of principal component analysis. The calculations show that five components explain around 75 percent of total variation in the data. Those five components represent indicators on profitability, quality of capital, quality of loans, fee-based activities, and liquid assets in the balance sheets. Further, by combining five principal components, the result shows that even small banks can achieve good financial performances.

scholarly journals Grouping and clustering of maize Lancaster germplasm inbreds according to the results of SNP-analysis

2017 ◽  
Vol 8 (3) ◽  
pp. 343-348 ◽  
Author(s):  
K. V. Derkach ◽  
T. M. Satarova ◽  
V. V. Borysova ◽  
V. Y. Cherchel ◽  
B. V. Dzyubeckiy
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Total Variation ◽  
Inbred Line ◽  
Gene Diversity ◽  
Principal Component ◽  
Component Analysis ◽  
Inbred Lines ◽  
Snp Markers ◽  
Snp Analysis

The objective of this article is grouping and clustering of maize inbred lines based on the results of SNP-genotyping for the verification of a separate cluster of Lancaster germplasm inbred lines. As material for the study, we used 91 maize (Zea mays L.) inbred lines, including 31 Lancaster germplasm lines and 60 inbred lines of other germplasms (23 Iodent inbreds, 15 Reid inbreds, 7 Lacon inbreds, 12 Mix inbreds and 3 exotic inbreds). The majority of the given inbred lines are included in the Dnipro breeding programme. The SNP-genotyping of these inbred lines was conducted using BDI-III panel of 384 SNP-markers developed by BioDiagnostics, Inc. (USA) on the base of Illumina VeraCode Bead Plate. The SNP-markers of this panel are biallelic and are located on all 10 maize chromosomes. Their range of conductivity equals >0.6. The SNP-analysis was made completely in automated regime on Illumina BeadStation equipment at BioDiagnostics, Inc. (USA). The grouping of the studied set of 91 inbred lines according to allelic state of SNP-markers and identifying cluster of Lancaster germplasm inbred lines in general selection of inbreeds used principal component analysis. The clustering and determining hierarchy in 31 Lancaster germplasm inbreds used quantitative cluster analysis. The share of monomorphic markers in the studied set of 91 inbred lines equaled 0.7%, and the share of dimorphic markers equaled 99.3%. Minor allele frequency (MAF) > 0.2 was observed for 80.6% of dimorphic markers, the average indicator of shift of gene diversity equaled 0.2984, PIC on average reached 0.3144. The index of gene diversity of markers varied from 0.1701 to 0.1901, pairwise genetic distances between inbred lines ranged from 0.0316–0.8000, the frequencies of major alleles of SNP-markers were within 0.5085–0.9821, and the frequencies of minor alleles were within 0.0179–0.4915. The average homozygosity of inbred lines was 98.8%. The principal component analysis of SNP-distances confirmed the isolation of the Lancaster group within the general set of analyzed inbred lines. Two-dimensional component analysis showed that the first principal component (PCA1) accounted for 36.0% of total variation and divided the investigated set of 91 inbred lines into two fractions, while all the inbred lines which are considered Lancaster based on pedigree information were included in one of the fractions. The second principal component (PCA2), which accounted for 12.1% of total variation, separated most of the Lancaster germplasm inbred lines from the others in this fraction, although the overlapping of the locations of Lancaster and non-Lancaster inbred lines was observed. Qualitative cluster analysis of 31 Lancaster germplasm inbred lines allowed us to identify two clusters: the first one includes 23 inbred lines of Ukrainian selection and the well known Mo17 (77.4% of total number of analysed lines) inbred line, and the second cluster included 6 inbred lines of Ukrainian selection and the well known Oh43 (22.6% of total number of analysed lines) inbred line. The isolation of two clusters within Lancaster germplasm indicates the genetic diversity in this plasm. The evaluation of genome similarities through allelic states of SNP-markers can successfully be used as a data source for classification and systematization of the gene pool of maize inbred lines.

scholarly journals Morphological diversity in growth characteristics of Jatropha curcas l. accessions from South- West Nigeria

2021 ◽  
Vol 38 (1) ◽  
pp. 109-119
Author(s):  
G.A. Adebusuyi ◽  
O.F. Oyedeji ◽  
V.I. Alaje ◽  
I.L. Sowunmi ◽  
Y.A. Dunmade
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Total Variation ◽  
Jatropha Curcas ◽  
Principal Component ◽  
Morphological Diversity ◽  
Component Analysis ◽  
Southwestern Nigeria ◽  
Breeding Programmes ◽  
Cluster 2

Jatropha curcas is a multi-purpose tree with significant economic importance that has not been fully exploited due to lack of adequate breeding programme in Nigeria. Consequently upon this, 31 accessions collected from 4 states in Southwestern Nigeria were assessed for their morphological diversity in order to establish this as a bed rock for further breeding programmes. Data were collected on plant height, numbers of leaves and collar diameter; these were subjected to analysis of variance, principal component analysis and cluster analysis using Minitab version 17. The results showed significant differences (p≤0.05) among the 31 accessions assessed. Principal component analysis indicated that the first three axes contributed 97.8% of the total variation observed. The first axis accounted for 68% of the total variation while the second and third axes accounted for 24.7% and 5.1%, respectively, of the total variation recorded. Cluster analysis as well as the dendrogram revealed three distinct clusters of genetic similarities and differences. High genetic similarities were observed among accessions collected from the different states whereas some accessions collected from similar regions had low genetic similarities. Cluster 1 consisted of 21 genotypes with their characters falli ng below the grand mean. Cluster 2 had nine genotypes, they produced the highest values for all the characters assessed. Cluster 3 with only one genotype has its values below the ground mean. Members of cluster 2 have proven to be superior. The existence of morphological diversity offers potential for selection among the accessions in the breeding of J. curcas from southwestern Nigeria.

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