Methods for predicting the energy value of pet foods

Abstract

The energy value of foods as well as energy requirements of dogs and cats is currently expressed in terms of metabolizable energy (ME). The determination of ME content of foods requires experimental animals and is too expensive and time consuming to be used routinely. Consequently, different indirect methods have been proposed in order to estimate as reliably an accurately as possible the ME content of pet food. This work analyses the main approaches proposed to date to estimate the ME content of foods for cats and dogs. The former method proposed by the NRC estimates the ME content of pet foods from proximal chemical analysis using the modified Atwater factors, assuming constant apparent digestibility coefficients for each analytical fraction. Modified Atwater factors systematically underestimate the ME content of low-fibre foods whereas they overestimate those that are high in fibre. Recently, different equations have been proposed for dogs and cats based in the estimation of apparent digestibility of energy by the crude fibre content, which improve the accuracy of prediction. In any case, whatever the method of analysis used, differences in energy digestibility related with food processing and fibre digestibility are unlikely to be accounted for. A simple in vitro enzymatic method has been recently proposed based in the close relationship that exist between energy digestibility and organic matter disappearance after two consecutive enzymatic (pepsin-pancreatin) incubation of food sample. Nutrient composition and energy value of pet foods can be also accurately and simultaneously predicted using near infrared reflectance spectroscopy (NIRS).