Morphological Structure of South African Non-Descript Does Raised in Syferkuil Farm , Capricorn District of Limpopo Province Using Factor Analysis

| Goat is one of important livestock in Africa for meat and milk productions. This research was aimed to characterize the morphological structure in South African non-descript does (1-2 years of age). Two body parameters including body measurements (14 variables) and body indices (11 variables) were used in this study and taken from fifty (n = 50) does. The data of two body parameters were used to characterize the animal’s morphological structure. Factor analysis including Pearson’s correlations, Principal Component Analysis (PCA) and multiple regression analysis were used for evaluations. Results of Pearson’s correlation analysis of body measurements indicated that body weight had a positive and highly statistical association with body length (r = 0.84, P<0.01). While in body indices the body weight had a positive and highly statistical correlation with area index (r = 0.83, P<0.01). PCA results showed that two body parameters in this study were explained about 80% of total variance in animal’s morphological structure. Despite, three PC’s of body indices in does have very high correlation with body weight (R2 = 0.82). Meanwhile, four PC’s of body measurements in does have moderate correlation with body weight (R2 = 0.59). It can be concluded that six body measurements (bicostal diameter, ear length, head width, head length, heart girth, cannon circumference) and six body indices (length index, depth index, conformation index, proportionality, thoracic development, cannon thickness index) were classified into first component that explain about 30.06% in body measurements and 48.88% in body indices. The results revealed that the first component in the body indices can be used as the criteria for South African non-descript goat because it represents the animal’s morphological structure and body weight.


Advances in Animal and Veterinary Sciences
April 2021 | Volume 9 | Issue 4 | Page 556 phological traits of South African non-descript indigenous goats using Pearson correlation and simple regression analyses. However, based to the level of our knowledge there are no literature on the use factor analysis to assess morphostructure of South African non-descript goats and their relationships with body weight. Hence, the objective of the study was to characterize the morphological structure of South African non-descript does using body measurements and body indices. This study will help indigenous goat farmers to select the best morphological traits that might be used for improving body weight during breeding season.

research siTe and animals
The study was conducted at the University of Limpopo experimental farm (Syferkuil) Limpopo province, South Africa as presented in Figure 1. The farm is located 10 km in the north-west of university of Limpopo. The university lies upon the latitude of 27.55 ºS and longitude 24.77 ºE. Temperature around the area is above 32 °C during summer and between 5 and 25 °C during winter seasons.

sTaTisTical analysis
Data was analyzed using Statistical Packages for Social Sciences version 26 (IBM SPSS, 2019). Descriptive statistics such as mean, standard deviation (SD), coefficient of variation (CV), minimum and maximum values were computed. Pearson's coefficient of correlation (r) and Principal Component Analysis (PCA) were computed as described by Yakubu, (2011). The following PCA equation was used: PCp = a1p x1 + a2p x2 + + anp xn where, PCp is the p th principal component; anp is the n th vector Eigen of the p th principal component and xn is

Advances in Animal and Veterinary Sciences
April 2021 | Volume 9 | Issue 4 | Page 557  the n th observed variables. Kaiser-Meyer-Olkin (KMO) measures of sampling adequacy, Bartlett's test of sphericity and communality were computed as the test validity. The KMO statistics ranges between 0 and 1. The value close to 0 indicates that there are large partial correlations compared to the total of correlations. A value close to 1 indicates that the sampling is appropriate. It was possible to accept a measure of sampling adequacy greater than 0.50. The varimax criterion of the orthogonal rotation method was employed in the rotation of the factor matrix to enhance the interpretability of the factor analysis. In addition, multiple linear regression was performed to identify the accuracy level in all principal components (PC's) when used as BW predictors. Hence, the best multiple linear regression was based on the coefficient of determination (R 2 ) value. Thus, the R 2 value has three categories of very low (R 2 <0.20), low (0.20<R 2 <0.40), moderate (040<R 2 <0.60), high (0.60<R 2 <0.80) and very high (0.80<R 2 <1.00).

rESuLtS And dIScuSSIon body WeighT
The average of body weight and morphological traits of South African non-descript does are presented in Table  1. The average of BW in south African non-descript does was 32.92 kg and higher than Malaysian Katjang (23.65 kg); Indonesian Katjang (27.11 kg); Assam Hill (24.86 kg) and Black Bengal (12.4 kg) does. (Khandoker et al., 2016;Putra and Ilham, 2020;Khargharia et al., 2015;Paul et al., 2011). Therefore, the average of BW in South-African non-descript does was closed to Zulu (33.39 kg); Barcha (36.9 kg) and Atlas (38.           (Elmaz et al., 2016;Legaz et al., 2011). All the variations in the BW among goat breeds might be due to environmental and breed differences.

body indices
The average of body indices in South African non-descript does was presented in Table 2. The average of BI, DTI and TD in South African non-descript does were 87.43 (medigline); 14.48 (heavy meat animal) and 129.97 (good performance) respectively. Putra and Ilham (2020) reported that Indonesian Katjang does was categorized into medigline animal (BI=86.95) and have a good performance (TD = 124) and light meat type of animal (DTI = 10.24). Chacon et al. (2011) reported that Cuban Creole does was categorized into medigline animal (BI = 85.29) and light type of animal (DTI = 9.58). Khargharia et al. (2015) reported that Assam Hill does was categorized into medigline animal (BI = 86.87), light type of animal (DTI = 9.82) and have a good performance (TD = 132). Moreover, Hankamo et al. (2020) reported that Ethiopian indigenous does were categorized into light type of animal (BI = 93.37) and have lower performance than South African non-descript does (TD = 109). The body indices of goat can be affected by genetic factor.

Pearson's coefficienT of correlaTion
Pearson's coefficient of correlation (r) between BW and BL in South African non-descript does was 0.84 and included of very high category (r>0.80) as presented in Table  1. Meanwhile, the r value between BW and HG in South African non-descript does was 0.48 and included of moderate category (0.40<r<0.60). Previous studies reported that BW and BL had very high category in Malaysian Katjang (0.83) and Afar (0.83) does and similar to the present study (Khandoker et al., 2016;Tekle, 2014). Despite, the r value between BW and AI in South African non-descript does was 0.83 (very high category) as presented in Table   NE US

Advances in Animal and Veterinary Sciences
April 2021 | Volume 9 | Issue 4 | Page 561 4. Putra and Ilham (2020) reported that BW and AI in Indonesian Katjang does had r value of 0.64 and included of high category (0.60<r<0.80). Our findings suggest that when BL and AI increase the BW might also increase. Therefore, BL and AI might be used as selection criterion to improve BW in South African non-descript goats.

PrinciPal comPonenT analysis
Total of four principal components (PC's) of body measurements (Table 5) and three PC's of body indices were obtained in this study. Hence, four PC's of body measurements and three PC's of body indices were explained in total variance about 80% of animal's morphostructure. Moreover, the KMO value in PCA of both parameters were higher than 0.05 and reveal that the results of PCA in this study is accurate. In addition, the Bartlett's test of sphericity value in PCA of both parameters were lower than 0.01 and reveal that the results of PCA in this study is accurate. Putra and Ilham (2020) Yakubu et al., 2011;Shoyombo et al., 2015). Six body measurements of BD, EL, HW, HL, HG and CC were identified as the first component (PC1) in body measurements of South African non-descript does that explain about 30% of total variance in animal's morphostructure. Meanwhile, six body indices of LI, DI, CI, Pr, TD and CTI were identified as the PC1 of body indices in South African non-descript does that explain about 49% of total variance in animal's morphostructure. All the body measurements and body indices in PC1 are important for selection criteria in the livestock (Putra and Ilham, 2020).

mulTiPle linear regression
The multiple linear regression equations to predict BW in South African non-descript does were presented in Table  5 (body measurements) and

concLuSIon
The current study was conducted to investigate the characterization of morphological structure of South African non-descript goats using body measurements and indices. Pearson's correlation was used first to investigate the relationship between measured traits. Relationship findings suggest that BL and AI had a highly statistical significant correlation with BW of South African non-decript goats. Principal component analysis was used to characterize the morphological structure and the results suggest that six body measurements (bicostal diameter, ear length, head width, head length, heart girth, cannon circumference) and six body indices (length index, depth index, conformation index, proportionality, thoracic development, cannon thickness index) were classified into first component that explain about 30.06% in body measurements and 48.88% in body indices. The results revealed that the first component in the body indices can be used as the criteria for South African non-descript goat because it represents the animal's morphological structure and body weight.

AcKnoWLEdGEMEnt
Authors express appreciation to the University of Limpopo Experimental Farmworkers and Department of Agricultural Economics and Animal Production, the University of Limpopo for data collection and financial support (National Research Foundation Thuthuka Grant No: 121987).

AutHor contrIButIonS
TLT and WPBP designed the experiment, analyzed the data and wrote the manuscript.

conFLIct oF IntErESt
The Authors have declared no conflict of interest.