Toward Sustainable Rainbow Trout Lipid Nutrition: A Systematic Review of Lipid Optimization Strategies in Controlled Conditions

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Abstract
Replacing fish oil (FO) in feeds remains a challenge for aquaculture sustainability. While experimental studies have evaluated the effects of alternative lipids on fillet long‐chain polyunsaturated fatty acids (LC‐PUFA) in rainbow trout, a quantitative synthesis of these effects is lacking. Here, 119 experimental diets from 29 controlled studies were synthesized through a statistical framework combining linear mixed‐effects models (LMM), generalized additive models (GAM), and leave‐one‐study‐out validation. Dietary docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA) consistently predicted fillet DHA and EPA concentrations, independent of growth rate and not significantly influenced by temperature or lipid level. While growth performance was unaffected by FO replacement, LC‐PUFA deposition was not equivalent across lipid origins: FO and vegetable‐based diets supported steeper diet‐to‐fillet transfer slopes compared to animal‐derived lipids. GAMs revealed non‐linear thresholds, with active deposition occurring only when dietary LC‐PUFA exceeded near 10 mg g −1 and the dietary n‐6:n‐3 ratio remained below approximately 4. Temperature, modelled linearly, showed no significant effect on fillet LC‐PUFA deposition within the analysed dataset. These results demonstrate that FO can be reduced without compromising growth, but not without reformulating LC‐PUFA supply and precursor balance. Successful FO replacement is therefore a formulation problem rather than an ingredient substitution issue. Emerging sources such as algal oils or engineered oilseeds represent a viable pathway toward sustainable feeds delivering nutritionally valuable fillets. The identified dietary thresholds provide practical guidance for feed formulation by defining minimum LC‐PUFA inclusion levels and n‐6:n‐3 ratios required to achieve target fillet EPA and DHA concentrations under controlled temperature conditions.

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