期刊
ANIMAL
卷 1, 期 1, 页码 57-65出版社
ELSEVIER
DOI: 10.1017/S1751731107657784
关键词
growth models; nutrition; nutrients; poultry; prediction
Predicting the response of poultry to nutrients has progressed to a stage where it is now not only possible to predict voluntary feed intake accurately, but broiler feeds and feeding programmes may now be optimised using the more advanced simulation models. Development of such prediction models has stimulated useful and purposeful research targeted at filling the gaps in our knowledge of critical aspects of the theory incorporated into these models. The aim of this paper was to review some of these past developments, discuss the controversy that exists in designing and interpreting response experiments, and highlight some of the most recent challenges related to the prediction of responses to nutrients by poultry. These latter include differences, brought about by selection for diverse goals, that have become apparent between modem broiler strains in their responses in feed intake and mortality, which are not independent of level of feeding or strain of broiler, as was previously believed. Uniformity an important quality criterion in broiler processing, is also not independent of level of feeding, and the effect may now be predicted using stochastic models. It is not yet clear whether breast meat yield, the carcass component of broilers yielding the highest returns, is a function of the strain of broiler or simply that of the protein weight of the bird when processed. An important aspect of response prediction is dealing with constraints to performance: whereas it is relatively straightforward to simulate the potential performance of a broiler such performance is often constrained by the physical, social and infectious environment, among others, providing a challenge to modellers attempting to predict actual performance. Some of these constraints to potential performance have not yet been adequately described, but are now receiving attention, suggesting that nutrient responses in poultry have the potential to be more accurately predicted in the future.
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