Ruminal Degradability and Summative Models Evaluation for Total Digestible Nutrients Prediction of Some Forages and Byproducts in Goats

Rosendo, Oswaldo; Freitez, Luis; López, Rafael

doi:10.1155/2013/532528

Cited by 8 publications

(5 citation statements)

References 29 publications

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“…Formulasi ransum untuk ternak ruminansia dibuat berdasarkan total digestible nutrient (TDN) dan protein kasar (Rosendo et al, 2013). Pemanfaatan TDN dan protein tersebut sangat berpengaruh terhadap produktivitas ternak (Nugroho et al, 2013).…”

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Model Pendugaan Total Digestible Nutrient (TDN) pada Hijauan Pakan Tropis menggunakan Komposisi Nutrien

Indah¹,

Permana

Despal

2020

Si.Pet.

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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.

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Model Pendugaan Total Digestible Nutrient (TDN) pada Hijauan Pakan Tropis menggunakan Komposisi Nutrien

Indah¹,

Permana

Despal

2020

Si.Pet.

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“…The regression slope of the actual values on predicted values at zero intercepts was 0.998, i.e. significantly different from zero, which indicated very high (0.002% over‐prediction) mean proportional bias in overall prediction (Rosendo et al, 2013).…”

Section: Resultsmentioning

confidence: 99%

Nutrient requirement equations for Indian goat by multiple regression analysis and least cost ration formulation using a linear and non‐linear stochastic model

Patil

Gupta

Rajendran

et al. 2021

Animal Physiology Nutrition

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An elaborate multiple regression analysis was done to arrive a nutrient requirement equation for goat including dry matter intake, DMI (kg/day), total digestible nutrient, TDN (g/day) and crude protein, CP (g/day) based on animal body weight (BW) (kg) and average daily gain (ADG)(g/day). The derived equations were highly significant (p < 0.001) and had high R2 (0.99) values. The estimated values of TDN, CP and DMI are compared with NRC (1981), Kearl (Nutrient Requirements of Ruminants in Developing Countries, All Graduate Theses and Dissertations, 1982), as well as ICAR (Livestock Management, 2013). The estimated total TDN and CP requirements at different body weights and ADG are close to the values of recommended feeding standards of Mandal et al. (Small Ruminant Res., 58, 2005, 201). The estimated DMI values are close to the values of ICAR (Livestock Management, 2013) but lower (26.5%–43.8%) as compared to NRC (1981). Regressed values are used to develop a linear programming (LP) model and a stochastic model (SM) for least‐cost ration formulation for the Indian goat breed, whose average BW is about 45 kg and ADG is 130 (g/day), and which is solved using LP simplex and Generalised Reduced Gradient (GRG) nonlinear of Microsoft Excel. The models satisfy the nutrient requirement calculated by regression equations with minimum specified level of variation (usually 5%–10%) in CP and TDN. Both methods adequately meet the nutritional requirements. Therefore, an electronic sheet is developed in Excel to calculate DMI, TDN and CP for different body weights, ADG and formulate the ration by LP and stochastic model.

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“…The feed formulation ratio was calculated based on the crude protein and total digestible nutrient (TDN) since they enormously influence livestock productivity (Nugroho et al, 2017;Rosendo et al, 2013). C. ternatea was found to be a good source of protein (CP = 21.96%) and had the highest TDN (59.81%).…”

Section: Nutrient Composition Of Herbaceous Legumesmentioning

confidence: 99%

Production and Nutritional Values of Herbaceous Legumes in Tropical Climates of Indonesia

Leondro,

Prihandini,

Tribudi

et al. 2024

AAVS

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The high diversity of herbaceous legumes in Indonesia has the potential to be developed as a source of animal feed. This research aims to identify eight herbaceous legumes' productivity and nutritional value. The material used in this research was herbaceous legumes consisting of Clitoria ternatea, Calopogonium mucunoides, Centrosema pubescent, Dolichos lablab, Pueraria javanica, Macroptilium bracteatum, Vigna and Stylosanthes guainensis. The proximate test was used to obtain chemical component values from herbaceous legumes. The results showed that the highest and lowest potential biomass production is C. ternatea and Vigna, respectively. Furthermore, M. bracteatum had a higher DM percentage (29.12%) value than other herbaceous legumes. C. ternatea had the highest CP (21.96 %DM) and TDN (59.81 %DM). In conclusion, the legumes studied have high nutritional content and have the potential to be developed as animal feed, especially in tropical areas.

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Ruminal Degradability and Summative Models Evaluation for Total Digestible Nutrients Prediction of Some Forages and Byproducts in Goats

Cited by 8 publications

References 29 publications

Model Pendugaan Total Digestible Nutrient (TDN) pada Hijauan Pakan Tropis menggunakan Komposisi Nutrien

Model Pendugaan Total Digestible Nutrient (TDN) pada Hijauan Pakan Tropis menggunakan Komposisi Nutrien

Nutrient requirement equations for Indian goat by multiple regression analysis and least cost ration formulation using a linear and non‐linear stochastic model

Production and Nutritional Values of Herbaceous Legumes in Tropical Climates of Indonesia

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