Regression Model and Correlation Analysis to Predict Body Weight of Rural Area Female Kacang Goat Based on Body Measurement
Regression Model and Correlation Analysis to Predict Body Weight of Rural Area Female Kacang Goat Based on Body Measurement
Lendrawati*, Tinda Afriani, Eli Ratni
ABSTRACT
This study aimed to determine the optimal model for predicting the body weight of adult female Kacang goats based on certain body measurements and to investigate correlation and regression. This study used 91 heads of Kacang Does collected from Talawi village from 2021-2022. The body weight (BW) data was regressed and associated with body dimensions (body length = BL, chest girth = GH and shoulder height = SH) using the SPSS program. The Pearson correlation (r) between body weight and measurements was calculated and the degree of fit of the models was assessed using the coefficient of determination (R2), Adj R2 and root mean squared error (RMSE). Body weight had a highly significant (P< 0.01) correlation with BL (r = 0.723), CG (r = 0.814), and SH (r = 0.549). The optimal estimation of body weight was achieved through a blend of chest circumference and body length, as indicated by the regression model: BW = -15.705 + 0.133BL + 0.457CG.0.457CG with the highest r (0.822), R2 (0.676) and adjusted R2 (0.668) and the lowest RMSE (13.427). These findings suggested that chest girth and body length can be used as predictors for body weight of adult female Kacang goats in rural areas. The findings could help farmers in adult female Kacang goat breeding by estimating body weight from body measurements.
Keywords | Does, Morphometric, Regression model, Rural farm
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May 2024
Vol. 12, Iss. 5, pp. 802-993
