Dakhlan, A. and Hamdani, M Dima Iqbal and Putri, Delsi Rusitaimi and Sulastri, Sulastri and Qisthon, Arif (2021) Prediction of body weight based on body measurements in female Saburai goat. Biodiversitas Journal of Biological Diversity, 22 (3). pp. 1391-1396. ISSN 1412-033X


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Official URL: https://smujo.id/biodiv/article/view/7785/4662


Saburai goat is a new composite breed in Lampung Province with little information on its performance. This research aimed to predict body weight based on body measurements, namely body length (BL), chest girth (CG), and shoulder height (SH) in female Saburai goats. This study used 42 female Saburai goats aged 3-4 years. The method used in this study was a survey, namely all-female Saburai goats aged 3-4 years were used for this research. The data obtained were analyzed using correlation and simple and multiple linear regression analysis using R program. Coefficient determination (R2), adjusted R2, residual standard error (RSE), Akaike information criterion (AIC), Bayesian information criterion (BIC), and stepwise regression analysis were used to find the best and most parsimonious regression model to predict BW based on body measurements. The results showed that BL, CG, and SH were positively and significantly correlated with BW of female Saburai goats with correlation coefficients of 0.858, 0.956 and 0.862, respectively. Chest girth was the best predictor for BW if using single predictor with regression equation of Ŷ = -31.17 + 0.93X2. However, combination of BL and CG was the best and most parsimonious regression model in predicting BW of female Saburai goat with regression equation of Ŷ = -36.09 + 0.31X1 + 0.72X2 with R2 = 0.941, adjusted R2 = 0.938, RSE = 2.842, AIC = 216.73 and BIC = 223.78. In conclusion, all body measurements in this study (particularly combination of BL and CG) could be used as predictor for BW with high accuracy of prediction. The result of this study suggested that CG and BL could be as indirect criteria to improve BW of female Saburai goats.

Item Type: Article
Subjects: S Agriculture > SF Animal culture
Divisions: Fakultas Pertanian (FP) > Prodi Peternakan
Depositing User: Dr. Akhmad Dakhlan
Date Deposited: 01 Mar 2021 04:52
Last Modified: 01 Mar 2021 04:52
URI: http://repository.lppm.unila.ac.id/id/eprint/28081

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