A mathematical model to explain variations in estimates of starch digestibility and predict digestible starch content of salmonid fish feeds

摘要

Digestibility of starch in salmonids is reported to be highly variable and affected by a number of factors, such as source or type, dietary inclusion level, and technological treatments of the starch or feed. A model was constructed to explain variation in digestibility of starch across studies and to estimate digestible starch content of salmonid fish feed by integrating data from 26 studies. The relationship between digestible starch content and physico-chemical state (raw and gelatinized starch) was modelled through a multiple regression approach. Multiple regression analysis yielded the following model: Digestible starch content (% of diet)=0.560 raw starch-0.011 raw starchpo +0.904 gelatinized starch-0.009 gelatinized starchpo +0.016 temperature*raw starch+0.009 temperature*gelatinized starch-0.270 fish species*raw starch-0.068*fish species*gelatinized starch-0.158*faeces collection method*gelatinized starch (P <0.0001, R po =0.84; fish species=0 for rainbow trout, 1 for Atlantic salmon; faeces collection method=0 for passive collection, 1 for active collection). The model suggests that the digestibility of raw and gelatinized starches significantly differs and their digestibility is negatively affected by dietary inclusion levels. The model also revealed a significant effect of water temperature on starch digestibility and interspecies differences in the ability to digest starch. Faeces collection method was found to significantly contribute to the variability of starch digestibility reported across studies. The model was validated by an independent group of data, and can potentially be a useful tool for feed formulation.