An economic comparison of several models fitted to nutritional response data

Nutritional requirements are typically estimated based on feeding trials with animals or birds offered several amounts of the critical nutrient(s). A nutrient response function is then fitted to data from the feeding trials. Modern computer techniques allow for a variety of functional forms to be used as nutrient response functions. However, the performance of these models is almost undistinguishable from a purely statistical perspective. This paper approaches the issue of determining nutrient requirements from an economic prospective. Crude protein amounts that would maximize profits were calculated for combinations of corn, soybean meal, and live broilers prices using several nutrient response models fitted to technical data from a trial with several balanced CP amounts fed to broiler chickens. Under certain combinations of input prices, differences between the models were between 1.5 and 3.0% CP. No model consistently predicted the greatest or least CP amounts or net profits, emphasizing that the (tangential) slopes of the models change at different rates over the range of nutrient (CP) amounts studied. Models providing adequate statistical fits to research data do not necessarily provide functions that are clearly most appropriate for maximizing producer profits.