Penelitian ini bertujuan untuk mengetahui hubungan antara total digestible nutrient (TDN) dengan komposisi nutrien hijauan (rumput dan legum) dan untuk menentukan prediksi persamaan TDN yang menunjukkan kualitas hijauan pakan tropis. Komposisi nutrien berasal dari data hasil penelitian yang telah dipublikasikan yang terdiri dari 52 hijauan (29 rumput (R) dan 23 legum (L)) meliputi kadar abu, protein kasar (PK), lemak kasar (LK), serat kasar (SK), bahan ekstrak tanpa nitrogen (BETN), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemiselulosa, selulosa dan TDN (%BK) digunakan dalam penelitian ini. Data yang diperoleh dianalisis dengan Korelasi Pearson dan regresi linier berganda untuk menentukan model pendugaan TDN. Model dengan koefisien determinasi dan probabilitas paling tinggi akan divalidasi dengan menggunakan mean absolute deviation (MAD), root mean square error (RMSE), mean absolute percentage error (MAPE). Hasil penelitian menunjukkan bahwa komposisi nutrien dapat digunakan untuk menentukan TDN pada hijauan tropis yaitu pada rumput dan legum. Hal tersebut ditunjukkan oleh nilai MAD, RMSE dan MAPE yang lebih rendah dibandingkan dengan rumus TDN lain. Model pendugaan TDN yang diperoleh yaitu TDNR+L = 49,866-3,488 Abu + 0,112 Abu*PK + 0,056 Abu*BETN; TDNR = 49,875 + 0,031 Abu*PK; dan TDNL = 15,212 + 5,084 LK + 0,070 Abu*BETN. Berdasarkan hasil penelitian, maka dapat disimpulkan bahwa model pendugaan TDN dapat diestimasi secara akurat dari komposisi nutrien sehingga dapat digunakan untuk merepresentasikan TDN berdasarkan basis data hijauan tropis. Model pendugaan TDN yang dapat digunakan yaitu TDNR+L dan TDNL.
The objective of this study was to investigate the relationship between dry matter digestibility (DMD) and nutrient composition parameters in tropical forage (grass, legume, and a combination of both) and determining prediction equation for dry matter digestibility using nutrient composition variables as the predictor. The nutrient composition consists of 62 forages (31 grasses and 31 legumes), included of ash, crude protein (CP), ether extract (EE), crude fiber (CF), nitrogen-free extract (NFE), neutral detergent fiber (NDF), acid detergent fiber (ADF), hemicellulose, cellulose and DMD, all expressed as a percentage of dry matter.. Multiple linear regression analysis was used to measure DMD estimated models. Models were validated with the coefficient of determination (R2), mean absolute deviation (MAD), root mean square error (RMSE), mean absolute percentage error (MAPE), were taken into consideration. Our result confirm that the nutrient composition can be efficiently used to determine the DMD of tropical forages, grasses, and legumes Prediction equation DMD in tropical forage, grass and legume were DMD = 104.267 - 0.918 ADF - 0.374 Hemicellulose, DMD = 110.409 - 1.363 ADF, DMD = 102.864 - 1.336 NDF + 0.602 Hemicellulose + 0.938 Cellulose, respectively.
Penelitian ini bertujuan untuk mengetahui hubungan antara lama penyimpanan silase pakan komplit berbasis batang pisang terhadap kandungan protein kasar dan serat kasar. Rancangan yang digunakan pada penelitian ini yaitu Rancangan Acak Lengkap (RAL) yang terdiri dari 4 perlakuan dengan 4 ulangan. Setiap perlakuan terdiri dari pakan komplit berbasis batang pisang dengan perlakuan P0 (lama penyimpanan 0 hari), P1 (lama penyimpanan 7 hari), P2 (lama penyimpanan 14 hari), dan P3 (lama penyimpanan 21 hari). Peubah yang diamati pada penelitian ini adalah kandungan protein kasar dan serat kasar. Hasil penelitian menunjukkan bahwa lama penyimpanan memberikan pengaruh yang sangat signifikan (P<0,01) dalam menurunkan serat kasar namun tidak memberikan pengaruh yang signifikan (P>0,05) dalam meningkatkan protein kasar. Berdasarkan hasil penelitian dapat disimpulkan bahwa silase pakan komplit dengan lama penyimpanan selama 14 dan 21 hari dapat mempertahankan protein kasar dan menurunkan serat kasar.Kata Kunci: Batang Pisang, Lama Penyimpanan, Protein Kasar, Serat Kasar, Silase Pakan Komplit.
The metabolizable energy (ME) of tropical forages measured by in vivo method in ruminants had a high degree of accuracy but requires a long time and is expensive. One method that can be done is the ME estimation model. The objectives of the present study were carried out to investigate the relationship between tropical forage nutrient content and ME for ruminants as well as determine and validate a model for estimating ME of tropical forage based on nutrient content. A total of 26 forage samples consisting of 14 types of grass and 12 legumes were obtained after data pre-processing or data cleaning and data normalization. Forage samples will be grouped into 3, Grass + Legume (G+L=26), grass (R=14), and legume (L=12). The database used is Crude Protein (CP), Extract Ether (EE), Neutral Detergent Fiber (NDF), Acid Detergent Fiber (ADF), and hemicellulose as well as ME with in vivo experiments. The initial stage is preprocessing data. Nutrient content and ME were analyzed using Pearson Correlation and followed by multiple linear regression to determine the ME estimation model. However, validated used the mean absolute deviation (MAD), root means square error (RMSE), and mean absolute percentage error (MAPE). The results showed that there was a significant and highly significantly correlated between nutrient composition and ME in the Grass + Legume, Grass, and Legume groups so it could be used to determine ME. There are 9 regression equations with significance and have high R2 and after being validated with the lowest MAD, RMSE, and MAPE values, three regression equations are obtained with one each for each group Grass + Legume (G+L), Grass (R), and Legumes (L). It is concluded that the regression equation of ME of tropical forage is MER+L = 12.429 – 0.122 ADF for Grass + Legume, EMR = 15.609 – 0.115 NDF for Grass, and EML = 3.726 – 0.186 CP for Legume.
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