Model Pendugaan Total Digestible Nutrient (TDN) pada Bahan Pakan Konsentrat Tropis

Abstract

Penelitian ini bertujuan untuk membuat model pendugaan TDN dari data analisis komposisi kimia bahan pakan konsentrat asal negara tropis dan memvalidasi pendugaan yang telah dibuat dengan model pendugaan TDN yang umum digunakan di Indonesia. Data komposisi nutrient dalam satuan persen bahan kering (BK) seperti kadar abu, PK, LK, SK, BETN, neutral detergent fiber (NDF), acid detergent fiber (ADF), hemiselulosa, lignin dan TDN dari 46 data bahan pakan konsentrat asal tanaman tropis yang dikelompokkan menjadi bahan pakan konsentrat tropis sumber energi (n=22) dan bahan pakan sumber protein (n=24). Data dianalisis korelasi Pearson, regresi linier berganda dan uji asumsi klasik untuk menentukan model pendugaan TDN. Model kemudian divalidasi dengan menggunakan uji F, mean absolute deviation (MAD), root mean square error (RMSE), dan juga mean absolute percentage error (MAPE). Hasil menunjukkan bahwa model pendugaan yang dihasilkan dalam penelitian ini memiliki nilai MAD, RMSE dan MAPE yang lebih kecil dibandingkan dengan nilai MAD, RMSE dan MAPE dari model pendugaan TDN lain yang umum digunakan di Indonesia.

The objective of this study was to determine a model equation to predict TDN using nutrient composition variables of tropical concentrate feeds as the predictor and validates the model prediction of TDN that has been made with other TDN model prediction that commonly used in Indonesia. The nutrient composition which all expressed as a percentage of dry matter such as ash, crude protein (CP), ether extract (EE), crude fiber (CF), nitrogen‐free extract (NFE), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose, lignin and TDN of 46 concentrate feeds were collected in this study. Those 46 concentrate feeds were divided into two groups: concentrate energy source (n=22) and concentrate protein source (n=24). Pearson correlation and multiple linear regression analysis were used to measure TDN estimated models. Then models were validated with F-test, mean absolute deviation (MAD), root mean square error (RMSE), and mean absolute percentage error (MAPE). The result of this study shows that the TDN model prediction of this study has the smallest MAD, RMSE, and MAPE score compared to other TDN model predictions.