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

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.

Keywords: Electronic sheet, linear programming, nutrient requirement, stochastic programming.

Abstract published in Journal of Animal Physiology and Animal Nutrition. https://doi.org/10.1111/jpn.13653.