Hua, K., Birkett, S., De Lange, C.F.M., and Bureau, D.P. (2010) Adaptation of a non-ruminant nutrient-based growth model to rainbow trout (Oncorhynchus mykiss Walbaum). Journal of Agricultural Science, 148 (1). pp. 17-29.

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Abstract

Models that accurately describe and predict growth and nutrient utilization of fish call be useful in developing strategies to improve the economic and environmental sustainability of aquaculture operations. Current bioenergetics models are not sufficiently flexible to be applied to the wide range of conditions encountered in aquaculture. There is a need to move from bioenergetics approaches to more mechanistic approaches based oil nutrient utilization by fish. A non-ruminant nutrient-based growth model hits been Successfully used in pig production. The model explicitly describes the utilization of energy-yielding nutrients and metabolites for body protein deposition (Pd) and body lipid deposition (Ld) at the whole animal level. Partitioning of intake of energy-yielding nutrients between Pd and Ld is governed by a minimum ratio (minLP) of the body lipid mass (L) to protein mass (P), a maximum daily rate of Pd (PdMax), or maximum efficiency of using intake of the first limiting dietary essential amino acid (AA) for body Pd. The growth model was adapted to rainbow trout (Oncorhynchus mykiss (Walbaum 1792)) through parameterization and various modifications consistent with its framework. The fish nutrient-based model was evaluated by comparing model simulations With data from Various experiments carried out with rainbow trout. Significant discrepancies between model predictions and experimental observations were observed. The model predicted energy retention well but did not always accurately predict growth rate, nor Pd and Ld. Overall, the model underestimated growth rate (expressed as thermal-unit growth coefficient (TGC)) by 37% and Pd by 15 OX, and overestimated Ld by 13%. These discrepancies are probably attributable to differences in nutrient utilization and partitioning mechanisms between fish and pigs. The development of more reliable models requires better understanding of the nutritional and endogenous determinants of fish growth.

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