Prediction of digestible energy value of extruded dog food: comparison of methods

M Hervera, M D Baucells, C Torre, A Buj, C Castrillo
Journal of Animal Physiology and Animal Nutrition 2008, 92 (3): 253-9
The proposal of National Research Council (NRC), based on the use of modified Atwater factors, is nowadays the widely used method to estimate digestible energy (DE) content of pet foods. Recently, alternative methods have been suggested for predicting energy content of commercial canine dry food. Factorial equations including food fibre content as estimator, in vitro digestions methods or near-infrared spectroscopy (NIRS) techniques have been considered as good approaches to predict the energy content of dog foods. The aim of this study was to compare the accuracy of some of those estimation methods. Seventeen samples of commercial extruded dog food were used to validate and compare some estimation methods of energy digestibility (Ed, %) and DE value [MJ/kg dry matter (DM)]. The apparent Ed and DE of each food were previously determined by in vivo trials. In vivo Ed and DE of foods ranged from 79.30% to 91.05% and from 16.25 to 21.82 MJ/kg DM, respectively, and their crude fibre (CF) content ranged from 0.72% to 3.28% (in DM base). The % Ed of each sample was estimated by the factorial equation (% Ed = 91.2 - 1.43 x CF %) and by the in vitro digestion method [% Ed(in vitro) = -2.45 + 0.98 organic matter (OM) disappearance(in vitro)%]. The set of samples also was analysed by NIRS, using a calibration equation developed from a set of 69 samples of commercial extruded dog food (0.76 and 0.89 cross-validation r(2) and 2.33 and 0.61 cross-validation SE for Ed and DE respectively). The in vitro method gave better estimations of Ed in vivo than NIRS and factorial methods, although all the methods assessed showed a very good and similar accuracy in the prediction of DE value. These three methods showed a slight better accuracy than that previously proposed by the NRC. To consider constant digestibility values of nutrient content of food can result in bias and error in the estimated energy values. The alternative prediction methods used in this study take into account differences of ingredient composition and availability of nutrients of different extruded dog foods thus could be better systems of valuating energy content in a wider range of different kind of foods than in use method.

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