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Body weight prediction of Belgian Blue crossbred using random forest

Lisa Praharani, Chalid Talib, Diana Andrianita Kusumaningrum, Yeni Widiawati, Santiananda Arta Asmarasari, Supardi Rusdiana, Zultinur Muttaqin, Ria Sari Gail Sianturi, Elizabeth Wina, Endang Sopian, Aqdi Faturahman Arrazy, Umi Adiati, Ferdy Saputra.


Objective: The aim of this study was to predict the body weight (BW) of a Belgian Blue X Friesian Holstein (BB X FH) crossbred in Indonesia based on morphometrics using random forest.
Materials and Methods: A total of 26 BB X FH crossbreds were observed for BW, chest weight (CW), body length (BL), hip height (HH), wither height (WH), and chest girth (CG) from 0, 30, 60, 90, 120, 150, 180, 210, 240, 270, and 300 days of age. Stepwise regression and random forest were performed using R 3.6.1.
Results: The random forest results show that CG is an important variable in estimating BW, with an important variable value of 24.49%. Likewise, the results obtained by stepwise regression show that CG can be an indicator of selection for the BB X FH crossbred. The R squared value obtained from the regression is 0.83, while the R squared value obtained from the random forest (0.86) is greater than the regression.
Conclusion: In conclusion, random forest produces a better model than stepwise regression. However, a good simple equation to use to estimate BW is CG.

Key words: Random forest; Belgian blue crossbred; body weight; morphometrics.

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