Toward Sustainable Aquaculture: Microalgae Fully Replace Fishmeal and Fish Oil in Rainbow Trout Diets While Maintaining Growth, Nutritional Quality, and Cost Viability

Toward Sustainable Aquaculture: Microalgae Fully Replace Fishmeal and Fish Oil in Rainbow Trout Diets While Maintaining Growth, Nutritional Quality, and Cost Viability | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Toward Sustainable Aquaculture: Microalgae Fully Replace Fishmeal and Fish Oil in Rainbow Trout Diets While Maintaining Growth, Nutritional Quality, and Cost Viability Pallab K. Sarker, Manuel J. Labbe, Benjamin V. Schoffstall, Anne R. Kapuscinski, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8642818/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract As global demand for affordable, high-quality protein continues to rise, commercial aquaculture has emerged as a critical solution. However, the industry's reliance on ocean-derived fishmeal (FM) and fish oil (FO) for aquafeed poses sustainability concerns. Marine microalgae offer a promising alternative due to their comparable nutrient profiles and potential for large-scale, sustainable production. In this study, we conducted a nutritional feeding experiment with juvenile rainbow trout to evaluate the efficacy of fish-free, microalgae-based diets formulated with protein-rich Nannochloropsis oculata (defatted biomass) and DHA- and antioxidant-rich Schizochytrium sp. (either whole-cell or oil), combined with canola oil as replacements for FM and FO. Diets included a reference diet and three experimental diets with partial or full FMFO replacements: 75% inclusion of N. oculata and Schizochytrium whole-cell (NSW75), 100% inclusion of both (NSW100), and 100% inclusion of N. oculata with Schizochytrium oil (NSO100). The fully fish-free diet, NSW100, supported growth, feed conversion, and survival rates comparable to the FMFO control. Whole-body fatty acid profiles reflected dietary inclusion levels, with similar total n-3 long-chain polyunsaturated fatty acids (LC-PUFA), including DHA, for fish fed the microalgal and reference diets but reduced EPA in fish fed the microalgal diets. No significant differences were observed across treatments in amino acid profiles, macronutrients, or mineral deposition. Notably, cost analysis revealed that fish-free diets had the lowest values, though not significantly, for formulated feed costs and economic conversion ratios (ECR), highlighting their commercial potential. These findings demonstrate that microalgae-based aquafeeds combining N. oculata and Schizochytrium sp. can viably replace FMFO without compromising fish performance, nutritional quality, or production economics—marking a key advance towards more sustainable aquaculture. Biological sciences/Biotechnology Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Ocean sciences Aquaculture feed Microalgae Nannochloropsis oculata co-product Schizochytrium sp. Ocean-derived fishmeal and fish oil Sustainability Rainbow trout Growth Nutritional quality cost viability Figures Figure 1 1. Introduction Aquaculture has rapidly become a key pillar of global food production, surpassing capture fisheries for the first time in 2022 with 94 million tons of output (FAO, 2024 ). By 2030, over 60% of seafood is projected to come from aquaculture, making it essential to food security, nutrition, and economic development (Costello et al., 2020 ; FAO, 2020 ). This growth is driven by rising population, incomes, health-conscious diets, and declining wild fish stocks (Béné et al., 2015 ; Naylor et al., 2021 ). However, aquaculture’s reliance on fishmeal (FM) and fish oil (FO), primarily derived from wild-caught marine species such as sardines, anchovies, herring, and mackerel, poses a significant sustainability challenge (Tacon & Metian, 2015, Liu et al., 2025 ). Each year, approximately 16 million tons of wild forage fish—largely edible—are converted into FM and FO, with aquaculture consuming 87% of global fishmeal and 74% of fish oil (Costello et al., 2020 ; Majluf et al., 2024 ).This dependence contributes to overfishing, disrupts marine ecosystems, exacerbates food insecurity in low-income regions, and exposes the industry to environmental and economic instability due to resource scarcity, climate change, and price volatility (Béné et al., 2016 ; FAO, 2016 ; Naylor et al., 2021 , Liu et al., 2025 ). Moreover, the production and use of FM and FO exacerbate environmental impacts, including greenhouse gas emissions and nutrient pollution (Pelletier et al., 2018 ; Sarker et al., 2024 ). The urgent need for sustainable and cost-effective alternatives has driven extensive research in aquaculture (Hua et al., 2019 ; Klinger & Naylor, 2012 ; Naylor et al., 2021 , Liu et al., 2025 ), and feed producers are increasingly exploring more environmentally sustainable substitutes for fishmeal and fish oil. Replacing FM and FO is especially critical for carnivorous species like rainbow trout, which require high levels of digestible protein and omega-3 fatty acids. Terrestrial plant-based alternatives such as soy, corn, and canola oil, have become more commonplace, but require large-scale land use; contributing to land-use deforestation (Galford et al., 2010 ), fresh-water pollution from fertilizer runoff (Klinger and Naylor, 2012 ; Troell et al., 2014 ), and other issues caused by industrial farming (Boissy et al., 2011 ). Furthermore, terrestrial crops contain anti-nutritional factors and lack essential amino acids, n3 LC-PUFA, and cholesterol, resulting in compromised growth and health in farmed salmonids (He et al., 2013 ; Li et al., 2009 ; Sarker et al., 2020a ; Sarker et al., 2025a ; Sprague, Dick, and Tocher 2016 , Willer et al., 2024 ). A promising solution lies in microalgae, which can be cultivated sustainably and offer high-quality protein, amino acids, and omega-3s (Stokvis et al., 2021 ). Specifically, marine microalgae are proving to be more viable replacements for FM and FO as they contain good amino acids and fatty acids profiles (Belanger-Lamonde et al., 2018; Gong et al., 2018 ; Tibaldi et al., 2015 ; Sarker et al., 2020b ; Sarker et al., 2025a ; Sorensen et al., 2017; Walker and Belinsky, 2011, Willer et al., 2024 ). Microalgae are also becoming more readily available; as nutraceutical and biofuel industries grow, companies seek markets for the leftover, microalgal co-product. Our recent research shows that underutilized by-products from Nannochloropsis can support healthy growth in rainbow trout without FM (Sarker et al., 2025a ). Building on these findings, this study aims to formulate cost-viable, fish-free feeds for rainbow trout—advancing a more sustainable future for aquaculture. We designed a feeding experiment comparing three microalgal diets to a reference diet containing FM and FO in commercial rainbow trout feed. The microalgal diets included defatted biomass of N. oculata co-product to replace fishmeal, and either antioxidant-rich and DHA-rich Schizochytrium sp. whole cell or DHA-extracted Schizochytrium sp. oil to replace FO (Sarker et al., 2016 ; Xing et al. 2020 ; Xu et al. 2021 ). We measured the effects of the four diets on growth, feed conversion ratio (FCR), protein efficiency ratio (PER), and whole body and fillet deposition of macronutrients, amino acids, and n-3 long chain polyunsaturated fatty acids (PUFAs). Furthermore, we estimated the formulated feed cost and the economic feed conversion ratio (ECR) of the three different experimental diets and the reference diet. 2. Materials and Methods We designed an 84-day growth experiment incorporating the replacement of fish meal with N. oculata defatted biomass and the replacement of fish oil with Schizochytrium sp. whole cells and oil. We performed our experiment at the Center for Agroecology at the University of California, Santa Cruz, and the Institutional Animal Care and Use Committee (IACUC) approved our experimental design and the fish use protocol. 2.1 Diet formulation and nutritional feeding experiment To meet the complete nutritional requirements of juvenile rainbow trout, four experimental diets were formulated to be iso-nitrogenous, iso-energetic, and iso-lipidic, ensuring consistency in protein, energy, and lipid content across treatments (Table 1 ) (Sarker et al., 2020b ; Sarker et al., 2025a ). The experimental diets were formulated to include Nannochloropsis oculata co-product (N) and exclude fish oil, incorporating either dried Schizochytrium sp. whole cells (SW) at two inclusion levels or extracted Schizochytrium oil (SO) at one inclusion level. This resulted in three distinct co-product diets supplemented with Schizochytrium (Sc), alongside a reference diet containing neither Schizochytrium nor the co-product. The three test feeds were formulated as shown in Table 1 as follows: NSW75 which replaced 75% of fishmeal (FM) with co-product meal and 75% of fish oil (FO) with a blend of Sc whole cells and canola oil; NSW 100 which fully replaced FM with co-product meal and fully replaced FO with a combination of Sc whole cells and canola oil; and NSO100 which fully replaced FM with co-product meal and fully replaced FO with a combination of Sc extracted oil and canola oil. Canola oil was incorporated into the test diets to meet the lipid and energy requirements of rainbow trout and to support normal physiological functions, compensating for the reduced or absent contribution of fish oil. Table 2 reports the proximate and amino acid composition; Table A1 shows the fatty acid content; and Table A2 reports the macromineral and trace element composition of the dietary treatments. Table 1 Formulation (g/100g diet) and essential amino acids (% in the weight of diet) of four experimental diets for juvenile rainbow trout Ingredient (%) g Diet Reference a NSW75 b NSW100 c NSO100 d Fish meal e 7.5 1.875 0 0 Fish oil 14 3.5 0 0 N.oculata extruded co-product 0 6 8 8 Schizochytrium (whole cells) 0 5 5 0 Schizochytrium (oil) 0 0 0 2.8 Canola oil 0 9 12 12 Feather meal 15 15 15 15 Blood meal 7 7 7 7 Corn gluten meal 20 20 20 20 Soy protein Concentrate 20 20 20 20 Wheat gluten 5 5 5 5 CaHPO4 1 1 1 1 Vitamin-mineral premix f 0.6 0.6 0.6 0.6 Lysine 1 1 1 1 Methionine 0.2 0.2 0.2 0.2 Choline chloride 0.5 0.5 0.5 0.5 Wheat flour 4.5 0.58 1 3.2 Ascorbic acid 0.2 0.2 0.2 0.2 Astaxanthin 0.05 0.05 0.05 0.05 Soy lecithin 3 3 3 3 Taurine 0.5 0.5 0.5 0.5 a Reference: no replacement of fish meal (FM) and fish oil (FO). b Replacement of 75% FMFO replaced with N. oculata and Schizo. flake c Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil e Omega Protein, Inc. Houston, Texas 77042, as manufacturer specification, the guaranteed gross composition analysis: crude protein, 60%; crude fat, 6%; fiber, 2%. f Mineral premix (mg kg -1 dry diet unless otherwise stated):ferrous sulphate, 0.13; NaCl, 6.15; copper sulphate, 0.06; manganese sulphate, 0.18; potassium iodide, 0.02; zinc sulphate, 0.3; carrier (wheat middling or starch). g Data reported in Sarker et al., 2025b Table 2 Proximate composition and essential amino acids of dietary treatments Diets a Reference b NSW75 c NSW100 d NSO100 e Proximate composition (%) Moisture g 17.37 16.03 17.02 18.46 Crude protein g 47.32 47.58 46.82 46.4 Lipid g 15.28 16.2 15.39 15.52 Ash g 4.92 4.84 4.6 4.25 Fiber 1.14 1.65 1.66 1.63 Carbohydrates 15.11 15.36 16.18 15.36 Energy fg 3443.33 3521.67 3454.67 3424.33 Essential amino acids (%) Arginine 2.69 2.53 2.65 2.37 Lysine 2.73 2.67 2.71 2.78 Isoleucine 1.87 1.68 1.84 1.5 Leucine 4.61 4.53 4.6 4.4 Histidine 1.16 1.05 1.06 .98 Methionine 0.77 0.85 0.83 0.83 Phenylalanine 2.53 2.53 2.51 2.46 Threonine 1.94 1.97 1.92 1.79 Tryptophan 0.42 0.38 0.41 0.35 Valine 2.75 2.53 2.64 2.00 a Values are means of three replicate groups (n = 3). b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil f Energy = Kcal/kg g Data reported in Sarker et al., 2025b We purchased dried Schizochytrium sp. from Algamac™, Aquafauna Bio-marine, Inc., Hawthorne, CA, USA; and menhaden FO from Double Liquid Feed Service, Inc., Danville, IL, USA. Qualitas Health Inc., which markets EPA-rich oil extracted from N. oculata as a human supplement (Sarker et al., 2020a ) and seeks uses for tons of under-utilized defatted biomass from its large-scale production facilities, donated the N. oculata defatted biomass. We purchased Schizochytrium sp. DHA oil from Algarithm, Bay of Fundy, Nova Scotia, Canada. Table A3 reports proximate compositions and amino acid profiles of N. oculata defatted co-product and Schizochytrium sp.; Table A4 reports total fatty acid profile by percentage of the defatted biomass, Schizochytrium sp. whole cells ingredient, and Schizochytrium sp. oil; and Table A5 reports macro-mineral and trace element composition of ingredients. Each diet contained Yttrium oxide (Y2O3), an indigestible marker sourced from Thermo Scientific, Waltham, MA, USA, in the basal diet at a rate of 1.0%. To create the feed, we first mixed all micro-ingredients followed by macro-ingredients, which were slowly added and thoroughly mixed into the feed to maintain a homogenous texture. Diets were manufactured at the Kapuscinski-Sarker Lab space in Natural Sciences II (University of California, Santa Cruz, CA, USA) using a single-screw extruder (TT-100 tabletop lab scale extruder from Akron Tool and Die, Akron, Ohio, USA). During extrusion, the diet was exposed to an average target temperature in the barrels at 90°C and passed through the extruder for 18s exposure. Relevant diets were top coated with fish oil or microalgal oil using a rotating mixer (SUNCOO 4/5HP Electric Concrete Cement Mixer 5 Cu Ft Mortar Mixing Stucco Seeds Portable Barrow Machine) and 24-mm mercury pressure. We carried out mixing for 15 minutes. After mixing, we dried the feed overnight to reduce the moisture content in the range of 16–18% in a fume hood. The pellets were then sieved and stored at − 20°C. Initially, we used pellets 2.0 mm in size, but as the fish grew, we increased the pellet size to 4.0 mm to meet the nutritional demands of the larger fish. 2.2 Fish husbandry and experimental design We used a recirculating aquaculture system at the University of California, Santa Cruz, CA, USA, consisting of sixteen 200-gallon tanks, each containing 40 juvenile rainbow trout with an average weight of 0.85 g each. Following placement in the tanks, we allowed the fish to acclimatize for seven days. After the acclimation period, we randomly assigned the three experimental diets and reference diet to the 16 tanks and fed fish until apparent satiation twice a day, in the morning and afternoon, six days a week, for 84 days. A total of 16 tanks were used, with four replicate tanks per diet. We monitored each tank to maintain the recommended conditions for rainbow trout. Dissolved oxygen, dissolved oxygen saturation, temperature, and pH were sampled daily using a handheld YSI Pro1020 multiparameter meter to keep dissolved oxygen at or above 8.7mg/L, the water temperature no higher than 15.4°C, and pH no higher than 8.6. We sampled ammonia, nitrite, nitrate, and alkalinity of the water weekly using a benchtop YSI 9500 spectrophotometer to maintain total ammonia nitrogen at or below 0.2mg/L, nitrite nitrogen at or below 0.1mg/L, and nitrate nitrogen at or below 26.8 at mg/L. We collected fish fecal samples before feeding daily using a radial flow settler. We collected intact fecal matter at the bottom of the system by installing a radial flow settler between the culture tank outflow and the sump tank inflow. We prevented contamination by siphoning out uneaten feed pellets from the radial flow settler. We used pipettes to gently remove intact solid fecal matter from a separate collection bin. We placed the fecal matter in a 50mL Falcon tube (BD Falcon™) and allowed the fecal matter to settle at the bottom of the tube. We then removed supernatant water at the top using a pipette once the fecal samples settled at the bottom of the tube. Then, we froze the filtered-out fecal matter samples at -20°C. We pooled fecal samples from every collection from each specific tank during the experiment. At the end of the experiment, we lyophilized, finely ground, and stored samples at -20°C for nutrient analysis. 2.3 Growth Calculations We quantified growth, weight gain percentage, FCR, and survival rate for each dietary treatment. We calculated these parameters as follows: Growth: Whole body final wt . - Whole body initial wt.) Weight gain percent: (Whole body final wt . - Whole body initial wt .) / Whole body final wt x 100 FCR: Feed intake (as fed basis) / Weight gain Survival rate: (Final number of fish / Initial number of fish) x 100 2.4 Macronutrient and trace element analysis and Digestibility calculations We determined the nutrient composition after homogeneously grinding and freezing ingredients, diets, feces, and whole-body fish to -20°C. We then prepared the samples for ICP-AES analysis using the EPA Method 3050b for acid digestion (U.S. EPA, 1996). We then analyzed the digested material for elemental composition by ICP OES (Thermo iCap 7400 radial view ICP-OES, Optical Emission Spectroscopy conducted at UC Santa Cruz Plasma Analytical Laboratory, RRID:SCR_021925). Once we determined the concentration of the phosphorus and yttrium levels of the diets and feces, we calculated the apparent digestibility coefficient (ADC) of protein. We used the following equation to determine the ADC for the four diets (Cho et al. 1982 ): ADC = (1 - ((%Protein feces / %Protein feed ) / (%Y 2 O 3 feed / %Y 2 O 3 feces ))) * 100) 2.5 Economic Conversion Ratio We used the Cruz Aquafeed Sustainability Tool (CAST; https://cast.sites.ucsc.edu/ , accessed November 2025) to calculate the economic conversion ratio (ECR), employing market prices from the CAST database to estimate ingredient costs (McKuin et al., 2023 ; Sarker et al., 2025a ). In CAST, we selected the option to apply the experimental feed conversion ratios (FCRs) obtained in this study rather than the default algorithm-generated values. The market prices of the experimental diets from the CAST database were obtained from a variety of sources (Table A6). The median values and 95% confidence intervals of market prices in CAST were estimated using non-parametric bootstrapping in RStudio (v.1.2.5033), based on 10,000 replicates and applying the adjusted bootstrap percentile method. The fish production cost was then expressed as the ECR following Sarker et al. ( 2020b ): ECR ( $ /kg fish) = FCR ((kg diet fed)/(kg weight gain)) × price of diet (USD $ /kg diet) Where ECR represents the economic conversion ratio, and FCR denotes the feed conversion ratio. 2.6 Statistical analysis We used the one-way ANOVA function in IBM SPSS Statistics Version 27 when determining the significance among treatment groups. If there was a significant difference (p < 0.05) between treatment groups, we included a Tukey post hoc test in determining the similarities and differences between treatments when p < 0.05. We used different superscripts beside each treatment value to denote which treatments were similar statistically and which were not. 3. Results We conducted the experiment to determine the effects of replacing a reference diet of fishmeal (FM) and fishoil (FO) with different percentages of N. oculata to replace FM, and either whole cell Schizochytrium sp. or Schizochytrium oil to replace FO. 3.1 Growth and Feed Performance We measured growth and monitored health across dietary treatment groups (Fig. 1 ). Rainbow trout fed experimental diets had similar feed conversion ratio (FCR) to the trout fed the reference diet of fishmeal and fish oil (FMFO). Apparent Digestibility Coefficient (ADC) of crude protein was significantly higher (p 0.05) between the reference group (34.2 g ± 0.24) and NSW75 (32.2 g ± 0.77), where FMFO were partially replaced, and NSW100 (33.4 g ± 0.51), where FMFO were fully replaced with N. oculata and Schizochytrium sp. whole cells. However, growth was significantly higher (p < 0.05) in the reference group compared to the NSO100 group (32.0 g ± 0.25), where FO was replaced with Schizochytrium sp. oil rather than Schizochytrium sp. whole cells. Trout appeared healthy at the end of the experiment with no signs of illness or deformities and there was no difference in survival between the dietary treatment groups. 3.2 Fish whole body proximate composition and fatty acid content We compared the whole body proximate composition across all dietary treatment groups (Table 3 ). Trout fed the fish-free diets (NSW100 and NSO100) did not differ significantly in moisture content from either the reference (FMFO) or the partial-replacement (NSW75) diets. Trout fed fish-free diets (NSW100, NSO100) had similar whole-body protein as those fed the reference diet, but significantly more protein than the partial-replacement diet (NSW75). The protein content ranged from 48.36–53.06 percent; highest in the NSW100 group where FMFO was fully replaced. Fat content ranged from 34.60–36.87 percent; highest in the NSW75 group where FMFO was partially replaced. Table 3 Whole body proximate composition (dry weight basis) of rainbow trout after 84 days on the experimental diets. Proximate composition (%) Whole body a ANOVA Reference b NSW75 c NSW100 d NSO100 e F Value P value Moisture 76.89 ± 1.18 74.91 ± 2.13 78.89 ± 0.5 82.68 ± 1.73 3.248 .060 Protein 50.06 ± 0.99 fg 48.36 ± 0.72 f 53.06 ± 0.62 g 52.77 ± 0.66 g 8.791 .002 Fat 34.6 ± 0.58 36.87 ± 0.96 35.02 ± 0.7 34.29 ± 0.38 2.804 .085 Fiber 1.42 ± 0.28 1.68 ± 0.64 1.34 ± 0.28 2.01 ± 0.54 0.421 .741 Ash 5.02 ± 0.18 5.22 ± 0.25 4.9 ± 0.17 4.78 ± 0.2 0.835 .500 a Values are means ± standard errors of four replicate groups (n = 4). b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake. c Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake. e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil. f, g Mean values not sharing a superscript letter in the same row differ significantly (P < 0.05) from Tukey’s HSD test. The fatty acid profile of whole body fish is presented in Table 4 . The fatty acid content of diets differed, content is presented in Table A1. Trout fed the reference diet had significantly higher (p < 0.05) saturated fatty acids (SFA), but significantly lower (p < 0.05) monounsaturated fatty acids (MUFA) compared to trout fed the experimental diets. For SFA, the reference group had significantly higher (p < 0.05) myristic (14:0), pentadecanoic (15:0), palmitic (16:0), heptadecanoic (17:0), stearic acid (18:0), and significantly less arachidic acid (20:0) compared to treatment groups. Between treatment groups, NSW100 had the highest arachidic acid (20:0) content, and NSO100 had significantly lower heptadecanoic acid (17:0) compared to reference and NSW75. For MUFA, the reference group had significantly higher (p < 0.05) Palmitoleic (16:1n9), Palmitoleic (16:1n7), Oleic (18:1n7), and significantly lower (p < 0.05) Oleic (18:1n9), Eicosanoic (20:1n9), Erucic (22:1n9) compared to treatment groups. Between treatment groups, NSW75 had significantly higher (p < 0.05) Palmitoleic (16:1n7) and Oleic (18:1n9) than NSW100 and NSO100, significantly lower (p < 0.05) Eicosanoic acid (20:1n9) and Total MUFA compared to NSW75. SFA ranged from 47.98% of TFA for the reference to 25.84% of TFA for NSO100. MUFA ranged from 45.39% of TFA for reference to 65.77% of TFA for NSW100. Table 4 Fatty acid content of whole body rainbow trout after 84 days on experimental diets. Fatty acid (% TFA) a Whole Body ANOVA Reference b NSW75 c NSW100 d NSO100 e F Value P value 14:0 7.18 ± 0.37 r 2.59 ± 0.12 s 1.68 ± 0.1 t 0.93 ± 0.08 t 191.619 < .001 15:0 0.68 ± 0.04 r 0.25 ± 0.02 s 0.19 ± 0.01 s 0.16 ± 0.01 s 112.803 < .001 16:0 30.96 ± 1.18 r 21.46 ± 0.39 s 19.18 ± 0.46 s 18.57 ± 0.64 s 61.113 < .001 17:0 0.74 ± 0.04 r 0.28 ± 0.01 s 0.21 ± 0.01st 0.19 ± 0.02 t 147.417 < .001 18:0 7.36 ± 0.34 r 5.81 ± 0.22 s 5.37 ± 0.11 s 4.91 ± 0.19 s 21.31 < .001 20:0 0.45 ± 0.02 r 0.52 ± 0.02 s 0.55 ± 0.01 s 0.52 ± 0.02 s 6.609 0.007 22:0 0.28 ± 0.01 0.29 ± 0.01 0.3 ± 0.01 0.28 ± 0.01 0.841 0.497 24:0 0.21 ± 0.01 0.26 ± 0.02 0.24 ± 0.02 0.25 ± 0.03 1.169 0.362 Total SFA f 47.98 ± 2 r 31.51 ± 0.75 s 27.72 ± 0.55st 25.84 ± 0.88 t 72.194 < .001 16:1ω9 0.35 ± 0.01 r 0.3 ± 0.01 s 0.31 ± 0.01 s 0.3 ± 0.01 s 8.133 0.003 16:1ω7 10.54 ± 0.29 r 3.25 ± 0.04 s 1.82 ± 0.12 t 1.51 ± 0.12 t 624.081 < .001 18:1ω9 26.25 ± 0.67 r 50.68 ± 0.32 s 55.67 ± 0.38 t 55.33 ± 0.88 t 536.128 < .001 18:1ω7 4.54 ± 0.06 r 3.54 ± 0.06 s 3.33 ± 0.04st 3.25 ± 0.03 t 139.064 < .001 20:1ω9 1.78 ± 0.06 r 2.3 ± 0.08st 2.51 ± 0.05 s 2.15 ± 0.09 t 18.471 < .001 20:1ω7 0.39 ± 0.09 0.67 ± 0.09 0.66 ± 0.04 0.59 ± 0.1 2.399 0.119 22:1ω11 0.14 ± 0.05 0.2 ± 0.02 0.22 ± 0.08 0.24 ± 0.02 0.678 0.582 22:1ω9 0.5 ± 0.05 r 0.68 ± 0.05 rs 0.75 ± 0.03 s 0.76 ± 0.05 s 7.35 0.005 24:1ω9 0.46 ± 0.03 0.39 ± 0.04 0.37 ± 0.02 0.41 ± 0.03 1.307 0.317 Total MUFA g 45.39 ± 0.37 r 62.18 ± 0.42 s 65.77 ± 0.39 t 64.62 ± 1.05st 231.291 < .001 18:2ω6 4.19 ± 1.28 4.89 ± 0.72 5.13 ± 0.4 7.43 ± 1.47 1.76 0.208 18:3ω6 0.02 ± 0.02 0 ± 0 0 ± 0 0.06 ± 0.02 3.134 0.066 20:2ω6 0.22 ± 0.07 0.26 ± 0.03 0.32 ± 0.01 0.37 ± 0.06 1.673 0.225 20:3ω6 0.05 ± 0.03 0.01 ± 0.01 0.04 ± 0.02 0.08 ± 0.03 1.086 0.392 20:4ω6 ARA h 0.11 ± 0.05 0.14 ± 0.02 0.13 ± 0.01 0.14 ± 0.01 0.256 0.855 22:4ω6 0 ± 0 0 ± 0 0 ± 0 0 ± 0 . . 22:5ω6 0.02 ± 0.02 0.1 ± 0.04 0.11 ± 0.02 0.1 ± 0.02 2.41 0.118 Total ω6 PUFA i 4.61 ± 1.45 5.41 ± 0.78 5.73 ± 0.46 8.18 ± 1.62 1.699 0.22 18:3ω3 ALA j 0.23 ± 0.1 0.24 ± 0.05 0.22 ± 0.04 0.49 ± 0.14 2.1 0.154 18:4ω3 0.07 ± 0.04 0 ± 0 0 ± 0 0.01 ± 0.01 2.097 0.154 20:3ω3 0 ± 0 0.02 ± 0.02 0 ± 0 0 ± 0 1 0.426 20:4ω3 0.03 ± 0.03 0 ± 0 0 ± 0 0 ± 0 1 0.426 20:5ω3 EPA k 0.38 ± 0.11 r 0.07 ± 0.01 s 0 ± 0 s 0.02 ± 0.02 s 8.767 0.002 22:5ω3 0.06 ± 0.06 0 ± 0 0 ± 0 0 ± 0 1 0.426 22:6ω3 DHA l 0.91 ± 0.2 0.58 ± 0.04 0.55 ± 0.02 0.79 ± 0.06 2.644 0.097 Total ω3 PUFA m 1.67 ± 0.53 0.91 ± 0.02 0.78 ± 0.06 1.32 ± 0.23 1.952 0.175 Total PUFA n 6.63 ± 2.07 6.32 ± 0.78 6.51 ± 0.51 9.54 ± 1.81 1.11 0.383 Total ω6 LC PUFA o 0.4 ± 0.16 0.51 ± 0.06 0.6 ± 0.06 0.68 ± 0.12 1.208 0.349 Total ω3 LC PUFA p 1.38 ± 0.4 0.67 ± 0.05 0.55 ± 0.02 0.82 ± 0.08 3.091 0.068 ω3 / ω6 PUFA q 0.37 ± 0.03 r 0.18 ± 0.03 s 0.14 ± 0 s 0.17 ± 0.01 s 23.598 < .001 a Total fatty acids (TFA) (%); Mean ± standard error for 4 replicates per diet (pooled whole tissues of 4 fish/replicate). b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil f Saturated fatty acids (SFA) is the sum of all fatty acids without double bonds. g Monounsaturated fatty acids (MUFA) is the sum of all fatty acids with a single bond. h Arachidonic acid (ARA). i Omega-6 (n-6) Polyunsaturated fatty acids (PUFAs) (sum of all fatty acids with ≥ 2 double bonds (18:2, 18:3, 20:2, 20:3, 20:4, 2:4, 22:5). j Alpha-linolenic acid (ALA). k Eicosapentaenoic acid (EPA). l Docosahexaenoic acid (DHA). m Omega-3 (n-3) PUFAs (18:3, 18:4, 20:3, 20:4, 20:5, 22:5, 22:6). n Polyunsaturated fatty acids (PUFA) is the sum of all fatty acids with two or more double bonds. o n-6 long-chain (LC) PUFA (20:2, 20:3, 20:4, 22:4, 22:5). p n-3 LCPUFA(20:3, 20:4, 20:5, 22:5, 22:6). q Ratio calculated for total n-3 PUFA: total n-6 PUFA (n-3/n-6). r s t Mean values across the row not sharing a common superscript were significantly different as determined by Tukey’s HSD test, P < 0.05 Total polyunsaturated fatty acids (PUFA) content was similar across groups. We found no significant difference in total n-6 PUFA (Omega-6), including Arachidonic acid (ARA, 20:4n6), linoleic acid (LA,18:2n6), and total n-6 LC PUFA content; each ranged from lowest in the reference group to highest in the NSO100 group (Table A8). Similarly, we found no significant difference in total n-3 PUFA (Omega-3) between groups, including no significant difference in alpha-linoleic acid (ALA, 18:3n3), docosahexaenoic acid (DHA, 22:6n3), and total n-3 LC PUFA. However, we detected significantly higher (p < 0.05) eicosapentaenoic acid (EPA) content in the reference group compared to the experimental groups. The n-3/n-6 PUFA ratio (n-3/n-6) was significantly higher (p < 0.05) in the reference group compared to the experimental groups. 3.3 Fillet Proximate and Amino Acid Profile We compared the fillet proximate composition across all dietary treatment groups (Table 5 ). We found no significant difference (p>.05) in moisture, protein, fat, fiber or ash between groups. The lipid content ranged from 14.30 to 20.37 percent across groups; found to be highest in the NSO100 group. The protein content ranged from 69.70 to 75.85 percent across groups; highest in the NSW100 group. Table 5 Proximate fillet composition (dry weight basis) of rainbow trout fed experimental diets for 84 days. Proximate composition (%) Fillet a ANOVA Reference b NSW75 c NSW100 d NSO100 e F Value P Value Moisture 81.06 ± 0.75 81.13 ± 1.76 83.74 ± 1.58 81.08 ± 0.78 1.088 0.391 Protein 69.9 ± 1.33 74.43 ± 1.01 75.85 ± 1.75 69.7 ± 3.01 2.650 .096 Fat 15.6 ± 1.34 14.68 ± 1.54 14.3 ± 1.26 20.37 ± 3.02 2.118 .151 Fiber 1.52 ± 0.8 0.45 ± 0.18 1.23 ± 0.55 0.58 ± 0.2 1.051 .406 Ash 5.18 ± 0.12 5.18 ± 0.12 5.15 ± 0.18 4.74 ± 0.12 2.441 .115 a Mean ± Standard Error (pooled whole tissues of 4 fish/replicate). b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil The amino acid content was similar across groups (Table 6 ). The fillet of the reference group had slightly lower levels of methionine, phenylalanine, leucine, threonine, and histidine when compared to the experimental groups. The content of methionine ranged from 1.85 to 2.00 percent; phenylalanine from 2.62 to 2.80 percent; leucine from 4.98 to 5.14 percent; threonine from 3.05 to 3.11 percent; histidine from 2.02 to 2.13 percent. Table 6 Essential amino acid content (wet weight basis) of fillets from rainbow trout after 84 days on the experimental diets. Essential amino acids (%) Fillet a ANOVA Reference b NSW75 c NSW100 d NSO100 e F Value P Value Methionine 1.85 ± 0.06 2 ± 0.06 2 ± 0.08 1.94 ± 0.05 1.189 0.355 Lysine 5.87 ± 0.16 5.89 ± 0.35 6.01 ± 0.33 5.85 ± 0.54 0.037 0.990 Phenylalanine 2.62 ± 0.04 2.69 ± 0.14 2.7 ± 0.12 2.8 ± 0.11 0.474 0.706 Leucine 4.98 ± 0.09 5.06 ± 0.26 5.14 ± 0.24 5.02 ± 0.4 0.064 0.978 Isoleucine 2.57 ± 0.21 2.45 ± 0.38 2.24 ± 0.3 2.35 ± 0.5 0.159 0.922 Threonine 3.05 ± 0.07 3.11 ± 0.21 3.08 ± 0.19 3.06 ± 0.26 0.017 0.997 Valine 2.9 ± 0.22 2.89 ± 0.34 2.7 ± 0.27 2.99 ± 0.36 0.158 0.922 Histidine 2.02 ± 0.03 2.06 ± 0.09 2.13 ± 0.09 2.06 ± 0.09 0.305 0.821 Arginine 4.09 ± 0.1 4.21 ± 0.24 4.18 ± 0.2 3.97 ± 0.37 0.183 0.906 a Mean ± Standard Error (pooled whole tissues of 4 fish/replicate). b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil 3.4 Fillet Macro Minerals and Trace Element Content We did not find any significant differences in the macro mineral composition of the fillets (Table 7 ). The reference group had a higher percentage of phosphorus, calcium, and magnesium, but a lower percentage of potassium and sulfur comparatively. The percentage of phosphorus ranged from 1.31 to 2.57 percent; calcium from 0.93 to 5.82 percent; magnesium from 0.30 to 1.51% percent; potassium from 0.04 to 1.45 percent; sulfur from 0.64 to 1.98 percent. Table 7 Macro minerals and trace elements content (wet weight basis) of Whole Body from Rainbow Trout after 84 days on the experimental diets. Whole Body a ANOVA Reference b NSW75 c NSW100 d NSO100 e F Value P Value Macro minerals (%) Phosphorus 2.01 ± 0.12 2.15 ± 0.06 2.21 ± 0.13 1.99 ± 0.11 0.913 0.464 Calcium 1.36 ± 0.18 1.69 ± 0.14 1.57 ± 0.19 1.2 ± 0.2 1.461 0.274 Magnesium 0.16 ± 0.01 0.16 ± 0 0.17 ± 0.01 0.17 ± 0 1.332 0.31 Potassium 2.1 ± 0.08 2.08 ± 0.06 2.26 ± 0.05 2.22 ± 0.04 2.306 0.129 Sulfur 1.27 ± 0.04 1.31 ± 0.03 1.38 ± 0.04 1.38 ± 0.02 2.624 0.098 Trace elements (mg kg − 1 ) Copper f ND ND ND ND . . Iron 0.03 ± 0 0.05 ± 0.01 0.04 ± 0 0.04 ± 0 1.342 0.307 Manganese f ND ND ND ND . . Selenium f ND ND ND ND . . Zinc 0.03 ± 0 0.04 ± 0 0.05 ± 0.01 0.07 ± 0.03 1.221 0.345 Arsenic f ND ND ND ND . . Boron f ND ND ND ND . . Aluminum f ND 0.01 ± 0.01 0.01 ± 0 0.01 ± 0 1.707 0.218 Mercury 0.01 ± 0 0.01 ± 0 0.01 ± 0 0.01 ± 0 1.069 0.399 Lead f ND ND ND ND . . Molybdenum f ND ND ND ND . . a Values are means ± standard errors of four replicate groups (n = 4); each replicate involves pooled whole tissues of 5 fish. b Reference: no replacement of fish meal (FM) and fish oil (FO). c Replacement of 75% FMFO replaced with N. oculata and Schizo. flake d Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake e Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil f Not detectable (ND) (< 0.00 mg/kg). We found no significant difference in the trace element composition of the fillets. We found a higher percentage of copper in the reference diet, and a lower percentage of iron compared to the experimental groups. Iron was highest in the NSW100 and NSO100 groups, ranging from 0.20 to 0.41 percent. Zinc was highest in NSW100, ranging from 0.04 to 0.21 percent. Amounts of selenium, arsenic, mercury, and lead were below the level of detection of the instrument. 3.5 Economic Conversion Ratio In Table 8 , we found that the feed conversion ratio, FCR and economic conversion ratio (ECR) did not differ significantly (p > 0.05) between diets. NSW100 had both the lowest ECR and formulated feed cost (FFC); ECR ranged from 0.77 to 0.86 USD per kg of trout and FFC ranged from 0.87 to 0.97 USD per kg of feed. NSO100 had the highest (worst) feed conversion ratio; feed conversion ranged from 0.89 to 0.98 gram feed intake per gram wt. gain. Table 8 Formulated feed cost, feed conversion ratio, and economic conversion ratio of rainbow trout production Cost Metrics Scenario a Anova Reference e NSW75 f NSW100 g NSO100 h F Value P Value Formulated Feed cost b 0.97 0.92 0.87 0.88 N/A N/A FCR c 0.88 ± 0.03 0.93 ± 0.03 0.89 ± 0.02 0.98 ± 0.03 2.776 0.087 ECR d 0.86 ± 0.03 0.85 ± 0.03 0.77 ± 0.02 0.86 ± 0.02 2.544 0.105 a Mean ± standard error for 4 replicates per diet. b Formulated Feed cost (FFC) = cost of feed ( $ ) / kg feed c Feed conversion ratio (FCR) = feed intake (g) /Wt. gain (g) d ECR ( $ /kg fish) = FCR (kg) ((kg feed intake)/(kg weight gain))×price of diet (USD $ /kg diet) e Reference: no replacement of fish meal (FM) and fish oil (FO). f Replacement of 75% FMFO replaced with N. oculata and Schizo. flake g Replacement of 100% of FMFO replaced with N. oculata and Schizo. flake h Replacement of 100% of FMFO replaced with N. oculata and Schizo. oil 4. Discussion This study provides the first evidence that rainbow trout can achieve comparable growth, FCR, and survival when fed a fully fish-free diet that simultaneously replaces 100% of both fishmeal (FM) and fish oil (FO with microalgal biomass)—while remaining cost viable. A blend of defatted Nannochloropsis oculata biomass and DHA-rich Schizochytrium sp. whole cells served as effective replacements for FM and FO, with no loss in performance and a lower economic conversion ratio (ECR). Moreover, the 100% fish-free diets showed higher protein digestibility than the FMFO reference diet. While these diets altered whole-body fatty acid profiles—reducing saturated fatty acids (SFA) and one n-3 LC-PUFA, EPA, and increasing monounsaturated fatty acids (MUFA)—they did not compromise growth outcomes, highlighting their potential as a sustainable, high-performing alternative for trout aquafeeds. 4.1 Effects of microalgal feeds on growth, protein digestibility, and feed performance Our findings are novel, demonstrating for the first time that a microalgal-based diet can entirely replace traditional FMFO in juvenile rainbow trout diets without adversely affecting growth, feed conversion ratio and economic conversion ratio. These results underscore the potential of sustainable microalgal ingredients as viable alternatives in aquaculture, with promising implications for both environmental sustainability and economic feasibility. While prior studies have successfully replaced either fishmeal (FM) or fish oil (FO) individually, full replacement of both FM and FO has frequently resulted in compromised performance due to low feed palatability, poor digestibility, or nutrient deficiencies (Burr et al., 2012 ; Cardinaletti et al., 2022 ; Katerina et al., 2020 ; Kousoulaki et al., 2022 ; Sarker, et al. 2020; Zatti et al., 2023 ). Our initial attempt to formulate fish-free feed for rainbow trout using a microalgal blend was unsuccessful, primarily due to reduced feed intake and poor palatability (Sarker et al., 2020b ). In this study in contrast, our NSW75 and NSW100 diets, combining N. oculata and Schizochytrium sp. whole-cell biomass, supported equivalent growth, feed conversion ratio (FCR), and survival compared to the FMFO reference diet. Notably, protein digestibility was highest in the 100% fish-free diets, suggesting efficient nutrient absorption and a potential synergistic effect between the two microalgal ingredients. The apparent protein digestibility and amino acid profiles observed in this study are consistent with previous findings on microalgal feeds used to replace FM or FMFO in rainbow trout (Sarker et al., 2020b ; Sarker et al., 2025a ) and Atlantic salmon (Gong et al. 2018 ; Liu et al. 2022 ; Sørensen et al. 2017 ). These results underscore the ability of a well-formulated microalgal diet to meet the essential nutritional requirements of rainbow trout, supporting the viability of fully fish-free aquafeeds without compromising physiological performance. A key factor likely contributing to the improved outcomes in this study is the inclusion of taurine in all treatment diets. Taurine, a known feeding stimulant, has been shown to enhance palatability and nutrient absorption in fishmeal-free diets (Egerton et al., 2020 ; El-Sayed et al., 2013; Qi et al., 2012 ). In our recent work, taurine supplementation significantly improved performance in rainbow trout fed FM-free microalgal diets (Sarker et al., 2025a ), and it likely played a similar role here by supporting consistent feed intake and utilization in the absence of FM and FO. We also compared Schizochytrium sp. oil (NSO100) with its whole-cell counterpart as a DHA-rich replacement for FO. While NSO100 had the highest DHA content (6.11% of TFA), and high protein digestibility, fish in this group had lower growth compared to the FMFO group. This was unexpected, as previous studies have found that DHA-rich diets often enhance growth performance in salmonids (Katerina et al., 2020 ; Zatti et al., 2023 ). A potential explanation for the reduced growth in fish fed the NSO100 diet is its slightly lower EPA content (0.24% of TFA), which may contribute to imbalanced fatty acid profiles and reduced growth in trout and other carnivorous fish. This underscores the importance of maintaining an optimal DHA:EPA ratio, rather than maximizing DHA alone, for achieving favorable growth outcomes. The NSW100 diet contained a somewhat higher EPA level (0.34% of TFA), which may have played a minor role in the improved final weight and weight gain observed. However, it is likely that the primary growth benefits of the NSW100 diet stemmed from the presence of antioxidants and other bioactive compounds in the whole-cell biomass, rather than this relatively small difference in EPA content. Although algal oil lacks the indigestible cell wall that can hinder nutrient utilization (Lee et al., 2022 ), the performance of the NSO100 treatment did not surpass that of the whole-cell Schizochytrium sp. treatments. This outcome suggests that bioactive compounds inherent in the whole-cell biomass—such as tocopherols, carotenoids, structural lipids, and other functional molecules—may elicit additional physiological benefits not provided by purified oil alone. The incorporation of whole-cell biomass introduces a broader antioxidant profile, potentially enhancing cellular protection and improving oxidative stability (Xing et al., 2020 ; Xu et al., 2021 ; Zhao et al., 2021 ). Schizochytrium sp., a marine microalga, has emerged as a promising source of natural antioxidants due to its high content of phenolic compounds, antioxidant peptides, carotenoids (e.g., astaxanthin), and tocopherols—all of which have been shown to retain activity following processing and digestion (Sarker et al., 2016 ; Siddik et al., 2024 ; Xing et al., 2020 ). These compounds are increasingly linked to improved oxidative stability and enhanced immune function in aquafeeds (Xing et al., 2020 ; Zhao et al., 2021 ). Although antioxidant status was not directly evaluated in this study, our findings underscore the potential value of whole-cell Schizochytrium sp. in aquafeed formulations. This warrants further investigation, particularly as oxidative stability becomes a critical factor in the development of high-PUFA aquafeeds. Beyond its well-known role in salmonid pigmentation, compounds like astaxanthin from Schizochytrium sp. offer broader health and welfare benefits, affirming the microalga’s relevance as a multifunctional, sustainable feed ingredient in modern aquaculture (Mueller et al. 2023 ). 4.2 Effects of Fish-free and microalgal Diets on Muscle Fatty Acids, Amino Acids, and Mineral Content In addition to evaluating growth performance, this study aimed to identify a fish-free feed alternative that maintains the nutritional quality of the fish. Previous research on plant-based aquafeeds has reported reduced deposition of essential fatty acids in fish tissues (He et al., 2013 ; Li et al., 2009 ; Sprague, Dick, and Tocher 2016 ). In the present study, the fatty acid profiles of whole-body samples closely reflected the fatty acid composition of the respective dietary treatments. Specifically, the microalgal-based diets exhibited lower saturated fatty acid (SFA) and higher monounsaturated fatty acid (MUFA) levels compared to the FMFO diet (Table A1) with corresponding patterns observed in fish tissue deposition (Table 4 ). Given that sources low in saturated fatty acids (SFA) and high in monounsaturated fatty acids (MUFA) are considered beneficial for human health—particularly cardiovascular health (Cao et al., 2022 ; Kris-Etherton, 1999 )—the fatty acid profile observed in fish fed microalgal diets may represent a favorable nutritional outcome. Given the consistent pattern of SFA and MUFA levels between the experimental diets and whole-body samples—specifically, lower SFA and higher MUFA contents in both the test diets and the fish fed these diets compared with the reference group (Tables S1 and 5)—the observed differences in tissue composition likely reflect the fatty acid profiles of the respective feeds. With respect to polyunsaturated fatty acids (PUFA), this study found comparable levels of n-3 LC-PUFA (omega-3), n-6 LC-PUFA (omega-6), and docosahexaenoic acid (DHA) in the whole-body samples of fish fed fish-free, microalgal-based diets relative to those fed the FMFO-based reference diet. However, eicosapentaenoic acid (EPA) levels were significantly lower in the microalgal treatment groups. These whole-body fatty acid profiles closely mirrored the fatty acid composition of the respective diets (Table A1). The lower EPA levels in the microalgal diets were likely due to the use of Nannochloropsis co-product, from which a substantial portion of EPA had been extracted for human nutraceutical applications prior to feed formulation. Adequate dietary levels of n-3 LC PUFA and n-6 LC-PUFA are critical to fish growth and health (Tocher, DR, 2015 ). Despite the higher inclusion levels of n-3 long-chain polyunsaturated fatty acids (LC-PUFA) in the FMFO diet, no significant differences were observed in whole-body n-3 LC-PUFA content between treatment groups. This suggests either a higher digestibility and retention of n-3 LC-PUFA in the microalgal diets or a lower bioavailability of these fatty acids in the FMFO aquafeed. The findings on DHA and EPA content in this study align with previous research on trout fed microalgal replacement diets, where increasing levels of microalgae led to a reduction in EPA content while DHA levels remained unaffected (Osmond et al., 2021 ; Serrano et al., 2021 ). The role of eicosapentaenoic acid (EPA) in fish growth and health is complex and species-specific. In Atlantic salmon, for instance, diets rich in docosahexaenoic acid (DHA) but low in EPA have been shown to impair growth when EPA levels fall below 1.3% of total fatty acids (TFA) (Katerina et al., 2020 ). In contrast, recent studies on rainbow trout have reported that diets containing EPA levels as low as 0.2–0.3% of TFA—similar to those in the microalgal-based diets used in this study—did not negatively impact growth performance, feed intake, survival, pigmentation, welfare indicators, histology, or fillet quality (Zatti et al., 2023 ). Despite these findings, the reduced growth observed in the NSO100 group compared to the FMFO reference group may suggest a growth-limiting role of EPA, particularly as NSO100 had the lowest dietary and whole-body EPA levels of all treatments and was one order of magnitude lower than in NSW75 and reference diets (Table A1). Notably, our data showed no evidence of retro-conversion of DHA to EPA, which has been previously reported as limited in salmonids but may increase under essential fatty acid (EFA) deficiency (Ruyter and Thomassen, 1999 ). Additionally, high dietary DHA levels are known to inhibit the conversion of α-linolenic acid (ALA) to EPA and reduce EPA retention in fish tissues (Bou et al., 2017a b ), which could partly explain the observed EPA shortfall in the NSO100 group. However, our results did not indicate an overall EFA deficiency in the microalgal diets. Collectively, these findings underscore the need for further investigation into the specific roles and optimal levels of EPA in trout nutrition. Future research should focus on optimizing EPA inclusion in fish-free microalgal diets—particularly in relation to DHA content—to retain the growth performance and improved protein utilization efficiency observed with the NSW100 diet, while enhancing EPA deposition in the fish. We found no difference in essential amino acids, proximate composition, minerals, or trace elements in rainbow trout muscle between dietary treatment groups. These findings support previous research demonstrating that microalgal-based diets perform favorably compared to conventional plant-based and fishmeal–fish oil (FMFO) diets. While plant-based diets have often been associated with deficiencies in essential amino acids (He et al., 2013 ; Li et al., 2009 ), microalgae offer a more balanced amino acid profile, meeting the nutritional requirements of carnivorous fish species. Furthermore, unlike FMFO diets, which are prone to higher levels of toxic trace elements such as arsenic and mercury due to biomagnification through the marine food web (Sarker et al. 2020a ; Sele et al. 2014 ; Sissener et al. 2012 ; Sloth et al., 2003 ) microalgal diets present a cleaner and potentially safer alternative. The absence of elevated contaminants, combined with adequate nutrient composition, highlights the potential of microalgae as a sustainable and nutritionally sound feed ingredient for aquaculture. 4.3 Effects of microalgae on Economic Conversion Ratio Our fish-free diets had the lowest formulated feed cost, with NSW100 also yielding the lowest ECR, showing that fish-free feed using combinations of microalgal biomass could be a cost-competitive, large-scale alternative to FMFO for trout. Historically, microalgae replacement diets have not been a cost competitive replacement for FMFO, in large part due to the high cost of microalgal oil. For example, in this study, cost ranged from 1.68 USD per kg for FO, 2.38 USD per kg for Schizochytrium sp. whole cell, and 4.41 USD per kg for Schizochytrium sp. oil. Nevertheless, despite the higher cost of microalgal oil, the overall formulated feed cost for microalgae-based diets was lower, primarily due to the relatively high prices of fishmeal (1.54 USD/kg) and fish oil (1.68 USD/kg) compared to the significantly lower costs of N. oculata co-product (0.54 USD/kg) and canola oil (0.88 USD/kg) (Table A6), and the higher quantities of FO required in reference diet compared to the DHA-rich microalgae diets (Table 1 ). As microalgae are increasingly sourced as underutilized co-products from adjacent industries such as biofuels and nutraceuticals, their production costs are expected to decline (Bryant et al., 2012 ; Bose et al., 2020 ; Sarker et al., 2018 ; Sarker et al., 2020). These cost dynamics suggest that the economic feasibility of microalgal feeds will improve with wider industrial integration and scale-up. Cost projections aside, microalgal diets composed of N. oculata and Schizochytrium sp. have already been shown to outcompete FMFO, corroborating the results in this study (Sarker et al., 2020a ). Compared to other replacement diets, the estimated cost of the microalgal feed used in this study is more competitive than insect meal—estimated to be 50% more expensive than fishmeal—yet remains less competitive than plant-based diets, which have an estimated formulated feed cost of 0.64 USD/kg compared to 0.87 USD/kg for the most cost-effective microalgal diet, NSO100, in this study (Arru et al. 2019 ; Nagappan et al. 2021 ; Sarker et al. 2020a ). In our recent study on fishmeal replacement using N. oculata feed, the fully FM-replacing diet exhibited the lowest formulated feed cost ( $ 0.88/kg feed) and economic conversion ratio (ECR) of $ 0.86 per kg of rainbow trout produced (Sarker et al. 2025). It is anticipated that with the development of large-scale production facilities, the cost of microalgal biomass and corresponding feeds will decrease, enhancing their competitiveness in aquafeed formulations. The cost of plant-based feeds often excludes the broader expenses associated with the entire life cycle of their ingredients. For instance, the cultivation of plant-based ingredients typically does not account for additional costs related to eutrophication, greenhouse gas emissions, or the increased land requirements necessary for their production (Gaber et al., 2022 ; McKuin et al. 2022 ; McKuin et al. 2023 ). Furthermore, the cultivation of marine photosynthetic microalga like N. oculata can utilize waste streams from other industries, positioning it as a more sustainable alternative to plant-based aquafeeds (Craggs et al. 2011 ; Fortier et al. 2014 ; Gaber et al., 2022 ; Handler et al., 2014 ; Quiroz Arita et al., 2015 ). The future of microalgae as novel feed ingredients in aquaculture hinges largely on their production cost and the economic advantages they offer when incorporated into salmonid diets. While microalgae-based feeds currently remain more expensive than currently dominant ingredients such as fishmeal, fish oil, or plant-based proteins (Hua et al. 2019 ), this landscape is shifting. The price of fishmeal has surged by over two hundred percent in the past two decades (Trevi et al. 2023 ), narrowing the cost gap. Meanwhile, advances in cultivation technologies are driving down the production costs of microalgae, improving its economic feasibility (Torres et al. 2020). As production methods continue to become more efficient, microalgae-based aquafeeds are expected to become increasingly cost-competitive (Sarker et al. 2020a ). One notable example is the widespread industry adoption of Schizochytrium sp., a heterotrophic, DHA-rich, and antioxidant-rich microalga, as a fish oil alternative in salmon feeds. This transition reflects both technological innovation and growing consumer and market demand for sustainable sources of omega-3 fatty acids. Moreover, the cost of feed ingredients is closely tied to production scale; as adoption increases, economies of scale are likely to further reduce costs. Several major players in the aquafeed and agribusiness sectors—including Corbion, BioMar, Archer Daniels Midland (ADM), and Veramaris—have significantly expanded their efforts to develop and commercialize fish oil substitutes based on Schizochytrium sp (Sarker et al., 2023 ; Tocher et al. 2019 , Willer et al., 2024 ). Unlike photosynthetic microalgae, Schizochytrium can be grown heterotrophically in industrial bioreactors without the need for sunlight or carbon dioxide, thereby reducing production costs (Lewis et al. 1999 ; Tocher et al. 2019 ) and reduces certain though not all life-cycle environmental impacts (McKuin et al, 2022 ). Its cultivation is performed in controlled environments, which limits ecological disruption and enhances sustainability (Sarker et al. 2020b ; Wang et al. 2021 ). An open environmental life-cycle analysis showed that Schizochytrium -based omega-3 production offers two environmental benefits: elimination of dependency on wild-caught forage fish and lower greenhouse gas emissions (Mckuin et al. 2022 ). These advantages position Schizochytrium as a cornerstone of future aquafeed formulations and align closely with the broader goals of ecological stewardship and responsible aquaculture. The findings of this study underscore the cost-competitiveness and practical viability of fish-free microalgal diets in aquaculture. However, one limitation of this study in estimating the ECR is that the CAST tool does not account for the costs of certain minor ingredients, such as taurine and lecithin, used in this experiment. Additionally, expenses related to feed manufacturing labor, transportation, and equipment were excluded from the analysis, and projected ingredient prices may not fully reflect actual market conditions. While the ECR values derived in this study are encouraging, achieving cost competitiveness of microalgal ingredients relative to conventional feed components remains a key challenge. Ultimately, large-scale production and cost reductions through technological innovation and industrial scale-up will be critical to realizing the commercial viability of microalgae-based aquafeeds. Expanding the portfolio of microalgal raw materials through innovative approaches presents significant opportunities to improve formulation flexibility—prioritizing optimal nutrition, sustainability, availability, and affordability (Nagappan et al., 2021 ). Realizing the full potential of microalgae as a sustainable feed ingredient depends on scaling up production processes to balance environmental responsibility with economic viability. The inherent biological advantages of microalgae, combined with mounting evidence supporting their effectiveness as a replacement protein and lipid source across diverse aquaculture species, position them as a promising alternative in the sector. Nonetheless, large-scale, continuous production of high-quality microalgal biomass remains challenged by technical, biological, and economic barriers—particularly in optimizing downstream processing and ensuring consistent biomass quality (Acién Fernández et al., 2019 ; Hoffman et al., 2017 ). 5. Conclusion This study demonstrates that fish-free diets formulated with Nannochloropsis oculata defatted biomass and DHA-rich Schizochytrium sp. whole cells can fully replace traditional fishmeal and fish oil (FMFO) in juvenile rainbow trout aquafeeds—with similar growth performance, protein digestibility (which actually increased), feed conversion ratio (FCR), and nutrient deposition. Importantly, our cost analysis reveals that these microalgae-based diets are already cost-competitive with conventional FMFO feeds—even before projected cost reductions associated with industry-scale production of algal ingredients. This challenges the long-standing assumption that microalgal feeds are prohibitively expensive and positions them as a practical solution for commercial adoption. Together, these findings reinforce the transformative potential of microalgae as a sustainable, nutritionally adequate, and economically viable alternative to FMFO in aquaculture. However, unlocking the full value of this innovation requires sustained research and technological refinement. Future efforts should focus on optimizing inclusion levels, improving processing efficiency, and expanding the portfolio of algal co-products available for feed formulation. To truly catalyze a shift toward more sustainable aquaculture, it is critical that microalgae-based diets be tested under commercially relevant conditions. Only through such real-world validation can their full economic, environmental, and operational benefits be realized at scale—supporting not only aquaculture productivity but also the global imperative to reduce dependence on wild-caught forage fish and promote a more resilient, ocean-friendly food system. Authorship contribution statement Conceived and designed the experiments: Pallab K. Sarker and Anne R. Kapuscinski; Performed the experiments: Devin Fitzgerald, Connor Greenwood, Benjamin V. Schoffstall, Kira O'Shelski, Duncan Gwynne, Diego Gonzalez Orcajo, Emily Noelle Pasion; Contributed materials/analysis: Devin Fitzgerald, Benjamin V. Schoffstall, Brandi McKuin, Pallab K. Sarker; Wrote-original draft: Pallab K. Sarker, Manuel J. Labbe; Wrote-review & editing: Pallab K. Sarker, Anne R. Kapuscinski, Benjamin V. Schoffstall, Brandi McKuin, Duncan Gwynne. All authors approved the submitted version for publication. Declarations Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution Conceived and designed the experiments: Pallab K. Sarker and Anne R. Kapuscinski; Performed the experiments: Devin Fitzgerald, Connor Greenwood, Benjamin V. Schoffstall, Kira O'Shelski, Duncan Gwynne, Diego Gonzalez Orcajo, Emily Noelle Pasion; Contributed materials/analysis: Devin Fitzgerald, Benjamin V. Schoffstall, Brandi McKuin, Pallab K. Sarker; Wrote-original draft: Pallab K. Sarker, Manuel J. Labbe; Wrote-review & editing: Pallab K. Sarker, Anne R. Kapuscinski, Benjamin V. Schoffstall, Brandi McKuin, Duncan Gwynne. All authors approved the submitted version for publication. Acknowledgement We thank the California Sea Grant Award (grant no. NA18OAR 4170073) (to Pallab Sarker), Agriculture and Food Research Initiative Competitive Grant award no. 2021-67016-33394 from the USDA NIFA and Agriculture and Food Research Initiative Competitive Grant no. 2021-69014-34501 from the USDA NIFA (to Pallab Sarker). We thank Cynthia and George Mitchell Foundation (to Pallab Sarker) for partial funding to support the work. We would like to thank the University of California Santa Cruz, Dean of Social Sciences and Executive Vice Chancellor. We also thank Rebecca White at Qualitas Health, Inc. for donating under-utilized Nannochloropsis oculata defatted biomass for this research. 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P., & Coley, M. L. (2016). Towards sustainable aquafeeds: Complete substitution of fish oil with marine microalga Schizochytrium sp. Improves growth and fatty acid deposition in juvenile Nile tilapia (Oreochromis niloticus). PLoS ONE, 11(6), 0156684. https://doi.org/10.1371/journal.pone.0156684 Sarker, P. K., Kapuscinski, A. R., McKuin, B., Fitzgerald, D. S., Nash, H. M., & Greenwood, C. (2020a). Microalgae-blend tilapia feed eliminates fishmeal and fish oil, improves growth, and is cost viable. Scientific Reports, 10(1), 19328. https://doi.org/10.1038/s41598-020-75289-x Sarker, P. K., Kapuscinski, A. R., Vandenberg, G. W., Proulx, E., & Sitek, A. J. (2020b). Towards sustainable and ocean-friendly aquafeeds: Evaluating a fish-free feed for rainbow trout (Oncorhynchus mykiss) using three marine microalgae species. Elementa: Science of the Anthropocene, 8, 5. https://doi.org/10.1525/elementa.404 Sarker, P. K., Schoffstall, B. V., Kapuscinski, A. R., McKuin, B., Fitzgerald, D., Greenwood, C., O’Shelski, K., Pasion, E. N., Gwynne, D., Gonzalez Orcajo, D., Andrade, S., Nocera, P., & San Pablo, A. M. (2025a). Towards Sustainable Aquafeeds: Microalgal (Nannochloropsis sp. QH25) Co-Product Biomass Can Fully Replace Fishmeal in the Feeds for Rainbow Trout (Oncorhynchus mykiss). Foods, 14(5), Article 5. https://doi.org/10.3390/foods14050781 Sarker, P. K., Rodriguez, E., Schoffstall, B. V., Kapuscinski, A. R., McKuin, B., Fitzgerald, D., Greenwood, C., O’Shelski, K., Pasion, E. N., Gwynne, D., Orcajo, D. G. (2025b) Evaluating Emission Reduction and Sustainability Impacts of Microalgae as a Substitute for Fishmeal and Fish Oil in Rainbow Trout Aquaculture. Science of The Total Environment (Under Revision) Sele, V., Sloth, J. J., Holmelid, B., Valdersnes, S., Skov, K., & Amlund, H. (2014). Arsenic-containing fatty acids and hydrocarbons in marine oils—Determination using reversed-phase HPLC-ICP-MS and HPLC-qTOF-MS. 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Aquaculture Nutrition, 19(4), 555–572. https://doi.org/10.1111/anu.12007 Sloth, J. J., Larsen, E. H., & Julshamn, K. (2003). Determination of organoarsenic species in marine samples using gradient elution cation exchange HPLC-ICP-MS. Journal of Analytical Atomic Spectrometry, 18(5), 452–459. https://doi.org/10.1039/b300508a Sørensen, M., Gong, Y., Bjarnason, F., Vasanth, G. K., Dahle, D., Huntley, M., & Kiron, V. (2017). Nannochloropsis oceania-derived defatted meal as an alternative to fishmeal in Atlantic salmon feeds. PLoS One, 12(7), 0179907. https://doi.org/10.1371/journal.pone.0179907 Sprague, M., Dick, J. R., & Tocher, D. R. (2016). Impact of sustainable feeds on omega-3 long-chain fatty acid levels in farmed Atlantic salmon, 2006–2015. Scientific Reports, 6(1), Article 1. https://doi.org/10.1038/srep21892 Stokvis, L., van Krimpen, M. M., Kwakkel, R. P., & Bikker, P. (2021). Evaluation of the nutritional value of seaweed products for broiler chickens’ nutrition. Animal Feed Science and Technology, 280, 115061. https://doi.org/10.1016/j.anifeedsci.2021.115061 Tacon, A. G. J., & Metian, M. (2015). Feed Matters: Satisfying the Feed Demand of Aquaculture. Reviews in Fisheries Science & Aquaculture. https://www.tandfonline.com/doi/abs/ 10.1080/23308249.2014.987209 Tibaldi, E., Chini Zittelli, G., Parisi, G., Bruno, M., Giorgi, G., Tulli, F., Venturini, S., Tredici, M. R., & Poli, B. M. (2015). Growth performance and quality traits of European sea bass (D. labrax) fed diets including increasing levels of freeze-dried Isochrysis sp. (T-ISO) biomass as a source of protein and n-3 long chain PUFA in partial substitution of fish derivatives. Aquaculture, 440, 60–68. https://doi.org/10.1016/j.aquaculture.2015.02.002 Tocher, D. R. (2015). Omega-3 long-chain polyunsaturated fatty acids and aquaculture in perspective. Aquaculture, 449, 94–107. https://doi.org/10.1016/j.aquaculture.2015.01.010 Tocher, D. R., Betancor, M. B., Sprague, M., Olsen, R. E., & Napier, J. A. (2019). Omega-3 Long-Chain Polyunsaturated Fatty Acids, EPA and DHA: Bridging the Gap between Supply and Demand. Nutrients, 11(1), 89–89. https://doi.org/10.3390/nu11010089 Torres-Tiji, Y., Fields, F. J., & Mayfield, S. P. (2020). Microalgae as a future food source. Biotechnology Advances, 41, 107536. https://doi.org/10.1016/j.biotechadv.2020.107536 Trevi, S., Uren Webster, T., Consuegra, S., & Garcia de Leaniz, C. (2023). Benefits of the microalgae Spirulina and Schizochytrium in fish nutrition: A meta-analysis. Scientific Reports, 13(1), 2208. https://doi.org/10.1038/s41598-023-29183-x Troell, M., Naylor, R. L., Metian, M., Beveridge, M., Tyedmers, P. H., Folke, C., Arrow, K. J., Barrett, S., Crépin, A. S., Ehrlich, P. R., Gren, Å., Kautsky, N., Levin, S. A., Nyborg, K., Österblom, H., Polasky, S., Scheffer, M., Walker, B. H., Xepapadeas, T., & De Zeeuw, A. (2014). Does aquaculture add resilience to the global food system? Proceedings of the National Academy of Sciences of the United States of America, 111(37), 13257–13263. https://doi.org/10.1073/pnas.1404067111 US EPA, O. (1996). EPA Method 3050B: Acid Digestion of Sediments, Sludges, and Soils [Data and Tools]. https://www.epa.gov/esam/epa-method-3050b-acid-digestion-sediments-sludges-and-soils Walker, A. B., & Berlinsky, D. L. (2011). Effects of partial replacement of fish meal protein by microalgae on growth, feed intake, and body composition of Atlantic cod. North American Journal of Aquaculture, 73(1), 76–83. https://doi.org/10.1080/15222055.2010.549030 Wang, Z., Hartline, C. J., Zhang, F., & He, Z. (2021). Enhanced microalgae cultivation using wastewater nutrients extracted by a microbial electrochemical system. Water Research, 206, 117722. https://doi.org/10.1016/j.watres.2021.117722 Willer, D.F., Newton, R., Malcorps, W., Kok, B., Little, D., Lofstedt, A., de Roos, B., Robinson, J.P.W., 2024. Wild fish consumption can balance nutrient retention in farmed fish. Nature Food 5, 221–229. https://doi.org/10.1038/s43016-024-00932-z Xing, J., Xiao, F., Luo, X., Sun, J., Li, H., Yuan, X., & Ji, H. (2020). Effect of dietary Schizochytrium sp. oil as an n-3 long‐chain polyunsaturated fatty acid source on growth performance, lipid metabolism and antioxidant status in juvenile grass carp (Ctenopharyngodon idellus): A comparative study with fish oil. Aquaculture Research, 51(11). https://doi.org/10.1111/are.14800 Xu, C., Zhang, S., Sun, B., Xie, P., Liu, X., Chang, L., Lu, F., & Zhang, S. (2021). Dietary Supplementation with Microalgae (Schizochytrium sp.) Improves the Antioxidant Status, Fatty Acids Profiles and Volatile Compounds of Beef. Animals : An Open Access Journal from MDPI, 11(12), 3517. https://doi.org/10.3390/ani11123517 Zatti, K. M., Ceballos, M. J., Vega, V. V., & Denstadli, V. (2023). Full replacement of fish oil with algae oil in farmed Atlantic salmon (Salmo salar) – Debottlenecking omega 3. Aquaculture, 574, 739653. https://doi.org/10.1016/j.aquaculture.2023.739653 Zhao, Y.-S., Eweys, A. S., Zhang, J.-Y., Zhu, Y., Bai, J., Darwesh, O. M., Zhang, H.-B., & Xiao, X. (2021). Fermentation Affects the Antioxidant Activity of Plant-Based Food Material through the Release and Production of Bioactive Components. Antioxidants, 10(12), 2004. https://doi.org/10.3390/antiox10122004 Additional Declarations No competing interests reported. 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Schoffstall","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"V.","lastName":"Schoffstall","suffix":""},{"id":587514023,"identity":"c0f5c307-18c8-4759-95a5-4375dfb7117d","order_by":3,"name":"Anne R. Kapuscinski","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Anne","middleName":"R.","lastName":"Kapuscinski","suffix":""},{"id":587514024,"identity":"40bfc9db-aedc-4596-8fbf-4d12d794fd62","order_by":4,"name":"Brandi McKuin","email":"","orcid":"","institution":"University of California Merced","correspondingAuthor":false,"prefix":"","firstName":"Brandi","middleName":"","lastName":"McKuin","suffix":""},{"id":587514026,"identity":"60536409-1629-4c92-a652-5e96486216a1","order_by":5,"name":"Devin Fitzgerald","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Devin","middleName":"","lastName":"Fitzgerald","suffix":""},{"id":587514027,"identity":"bd7c64a4-e618-4bbb-9991-f3a1f68c4d1f","order_by":6,"name":"Connor Greenwood","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Connor","middleName":"","lastName":"Greenwood","suffix":""},{"id":587514032,"identity":"a7231fe0-9bb1-4ede-a033-30099271a8d1","order_by":7,"name":"Kira O'Shelski","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Kira","middleName":"","lastName":"O'Shelski","suffix":""},{"id":587514033,"identity":"d7bb3bd8-226e-4cf2-895b-ffe4ac6587e6","order_by":8,"name":"Emily Noelle Pasion","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Emily","middleName":"Noelle","lastName":"Pasion","suffix":""},{"id":587514034,"identity":"2f4cacde-27ed-481e-9517-6bd076fb3e51","order_by":9,"name":"Duncan Gwynne","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Duncan","middleName":"","lastName":"Gwynne","suffix":""},{"id":587514036,"identity":"b1b3b7c0-e6e1-4b1a-861b-4fe3f2a9d8d7","order_by":10,"name":"Diego Gonzalez Orcajo","email":"","orcid":"","institution":"University of California, Santa Cruz","correspondingAuthor":false,"prefix":"","firstName":"Diego","middleName":"Gonzalez","lastName":"Orcajo","suffix":""}],"badges":[],"createdAt":"2026-01-19 20:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8642818/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8642818/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102341452,"identity":"36240a73-aa3e-4735-83e4-73170823474b","added_by":"auto","created_at":"2026-02-10 16:47:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77520,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Growth (g), Weight gain (%), FCR (Feed Conversion Ratio), and Survivability of the Reference (no replacement of fish meal (FM) and fish oil (FO)), NSW75 (Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003esp. whole cells), NSW100 (Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003esp. whole cells), and NSO100 (Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003esp. oil) diets.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8642818/v1/4fccb174c16842ac77e5e7c6.png"},{"id":102397523,"identity":"c6c97bad-59a5-4599-aa7e-04e6ce5ee348","added_by":"auto","created_at":"2026-02-11 10:17:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1932280,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8642818/v1/d42ff316-47b5-4dc2-977b-d896a1506f81.pdf"},{"id":102341451,"identity":"bf9bb8b5-fd94-43ff-814c-7558210e5f29","added_by":"auto","created_at":"2026-02-10 16:47:58","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":47398,"visible":true,"origin":"","legend":"","description":"","filename":"fishfreefeedgrwothnutritionECRSupplementaryMaterialsnpjScienceofFood.docx","url":"https://assets-eu.researchsquare.com/files/rs-8642818/v1/5db7cd848435381f82930c10.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Toward Sustainable Aquaculture: Microalgae Fully Replace Fishmeal and Fish Oil in Rainbow Trout Diets While Maintaining Growth, Nutritional Quality, and Cost Viability","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAquaculture has rapidly become a key pillar of global food production, surpassing capture fisheries for the first time in 2022 with 94\u0026nbsp;million tons of output (FAO, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). By 2030, over 60% of seafood is projected to come from aquaculture, making it essential to food security, nutrition, and economic development (Costello et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; FAO, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This growth is driven by rising population, incomes, health-conscious diets, and declining wild fish stocks (B\u0026eacute;n\u0026eacute; et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Naylor et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, aquaculture\u0026rsquo;s reliance on fishmeal (FM) and fish oil (FO), primarily derived from wild-caught marine species such as sardines, anchovies, herring, and mackerel, poses a significant sustainability challenge (Tacon \u0026amp; Metian, 2015, Liu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Each year, approximately 16\u0026nbsp;million tons of wild forage fish\u0026mdash;largely edible\u0026mdash;are converted into FM and FO, with aquaculture consuming 87% of global fishmeal and 74% of fish oil (Costello et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Majluf et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).This dependence contributes to overfishing, disrupts marine ecosystems, exacerbates food insecurity in low-income regions, and exposes the industry to environmental and economic instability due to resource scarcity, climate change, and price volatility (B\u0026eacute;n\u0026eacute; et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; FAO, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Naylor et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Liu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, the production and use of FM and FO exacerbate environmental impacts, including greenhouse gas emissions and nutrient pollution (Pelletier et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The urgent need for sustainable and cost-effective alternatives has driven extensive research in aquaculture (Hua et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Klinger \u0026amp; Naylor, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Naylor et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Liu et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and feed producers are increasingly exploring more environmentally sustainable substitutes for fishmeal and fish oil.\u003c/p\u003e \u003cp\u003eReplacing FM and FO is especially critical for carnivorous species like rainbow trout, which require high levels of digestible protein and omega-3 fatty acids. Terrestrial plant-based alternatives such as soy, corn, and canola oil, have become more commonplace, but require large-scale land use; contributing to land-use deforestation (Galford et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), fresh-water pollution from fertilizer runoff (Klinger and Naylor, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Troell et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), and other issues caused by industrial farming (Boissy et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Furthermore, terrestrial crops contain anti-nutritional factors and lack essential amino acids, n3 LC-PUFA, and cholesterol, resulting in compromised growth and health in farmed salmonids (He et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e; Sprague, Dick, and Tocher \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Willer et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA promising solution lies in microalgae, which can be cultivated sustainably and offer high-quality protein, amino acids, and omega-3s (Stokvis et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Specifically, marine microalgae are proving to be more viable replacements for FM and FO as they contain good amino acids and fatty acids profiles (Belanger-Lamonde et al., 2018; Gong et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Tibaldi et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e; Sorensen et al., 2017; Walker and Belinsky, 2011, Willer et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Microalgae are also becoming more readily available; as nutraceutical and biofuel industries grow, companies seek markets for the leftover, microalgal co-product. Our recent research shows that underutilized by-products from \u003cem\u003eNannochloropsis\u003c/em\u003e can support healthy growth in rainbow trout without FM (Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBuilding on these findings, this study aims to formulate cost-viable, fish-free feeds for rainbow trout\u0026mdash;advancing a more sustainable future for aquaculture. We designed a feeding experiment comparing three microalgal diets to a reference diet containing FM and FO in commercial rainbow trout feed. The microalgal diets included defatted biomass of \u003cem\u003eN. oculata\u003c/em\u003e co-product to replace fishmeal, and either antioxidant-rich and DHA-rich \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cell or DHA-extracted \u003cem\u003eSchizochytrium\u003c/em\u003e sp. oil to replace FO (Sarker et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Xing et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xu et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). We measured the effects of the four diets on growth, feed conversion ratio (FCR), protein efficiency ratio (PER), and whole body and fillet deposition of macronutrients, amino acids, and n-3 long chain polyunsaturated fatty acids (PUFAs). Furthermore, we estimated the formulated feed cost and the economic feed conversion ratio (ECR) of the three different experimental diets and the reference diet.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe designed an 84-day growth experiment incorporating the replacement of fish meal with \u003cem\u003eN. oculata\u003c/em\u003e defatted biomass and the replacement of fish oil with \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells and oil. We performed our experiment at the Center for Agroecology at the University of California, Santa Cruz, and the Institutional Animal Care and Use Committee (IACUC) approved our experimental design and the fish use protocol.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Diet formulation and nutritional feeding experiment\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo meet the complete nutritional requirements of juvenile rainbow trout, four experimental diets were formulated to be iso-nitrogenous, iso-energetic, and iso-lipidic, ensuring consistency in protein, energy, and lipid content across treatments (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (Sarker et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e). The experimental diets were formulated to include \u003cem\u003eNannochloropsis oculata\u003c/em\u003e co-product (N) and exclude fish oil, incorporating either dried \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells (SW) at two inclusion levels or extracted \u003cem\u003eSchizochytrium\u003c/em\u003e oil (SO) at one inclusion level. This resulted in three distinct co-product diets supplemented with \u003cem\u003eSchizochytrium\u003c/em\u003e (Sc), alongside a reference diet containing neither \u003cem\u003eSchizochytrium\u003c/em\u003e nor the co-product. The three test feeds were formulated as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e as follows: NSW75 which replaced 75% of fishmeal (FM) with co-product meal and 75% of fish oil (FO) with a blend of Sc whole cells and canola oil; NSW 100 which fully replaced FM with co-product meal and fully replaced FO with a combination of Sc whole cells and canola oil; and NSO100 which fully replaced FM with co-product meal and fully replaced FO with a combination of Sc extracted oil and canola oil. Canola oil was incorporated into the test diets to meet the lipid and energy requirements of rainbow trout and to support normal physiological functions, compensating for the reduced or absent contribution of fish oil. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports the proximate and amino acid composition; Table A1 shows the fatty acid content; and Table A2 reports the macromineral and trace element composition of the dietary treatments.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulation (g/100g diet) and essential amino acids (% in the weight of diet) of four experimental diets for juvenile rainbow trout\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIngredient (%)\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDiet\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish meal \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFish oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eN.oculata\u003c/em\u003e extruded co-product\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSchizochytrium\u003c/em\u003e (whole cells)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSchizochytrium\u003c/em\u003e (oil)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCanola oil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeather meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCorn gluten meal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy protein Concentrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheat gluten\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaHPO4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin-mineral premix \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLysine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethionine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholine chloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWheat flour\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscorbic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAstaxanthin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoy lecithin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaurine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eReference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Omega Protein, Inc. Houston, Texas 77042, as manufacturer specification, the guaranteed gross composition analysis: crude\u003c/p\u003e \u003cp\u003eprotein, 60%; crude fat, 6%; fiber, 2%.\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e Mineral premix (mg kg\u003csup\u003e-1\u003c/sup\u003e dry diet unless otherwise stated):ferrous sulphate, 0.13; NaCl, 6.15; copper sulphate, 0.06; manganese sulphate, 0.18; potassium iodide, 0.02; zinc sulphate, 0.3; carrier (wheat middling or starch).\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003eData reported in Sarker et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProximate composition and essential amino acids of dietary treatments\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eDiets\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eProximate composition (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCrude protein\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipid\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy\u003csup\u003efg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3443.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3521.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3454.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3424.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEssential amino acids (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArginine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLysine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsoleucine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeucine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistidine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethionine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenylalanine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThreonine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTryptophan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Values are means of three replicate groups (n\u0026thinsp;=\u0026thinsp;3).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e Energy\u0026thinsp;=\u0026thinsp;Kcal/kg\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003eData reported in Sarker et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2025b\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWe purchased dried \u003cem\u003eSchizochytrium\u003c/em\u003e sp. from Algamac\u0026trade;, Aquafauna Bio-marine, Inc., Hawthorne, CA, USA; and menhaden FO from Double Liquid Feed Service, Inc., Danville, IL, USA. Qualitas Health Inc., which markets EPA-rich oil extracted from \u003cem\u003eN. oculata\u003c/em\u003e as a human supplement (Sarker et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e) and seeks uses for tons of under-utilized defatted biomass from its large-scale production facilities, donated the \u003cem\u003eN. oculata\u003c/em\u003e defatted biomass. We purchased \u003cem\u003eSchizochytrium\u003c/em\u003e sp. DHA oil from Algarithm, Bay of Fundy, Nova Scotia, Canada. Table A3 reports proximate compositions and amino acid profiles of \u003cem\u003eN. oculata\u003c/em\u003e defatted co-product and \u003cem\u003eSchizochytrium\u003c/em\u003e sp.; Table A4 reports total fatty acid profile by percentage of the defatted biomass, \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells ingredient, and \u003cem\u003eSchizochytrium\u003c/em\u003e sp. oil; and Table A5 reports macro-mineral and trace element composition of ingredients.\u003c/p\u003e \u003cp\u003eEach diet contained Yttrium oxide (Y2O3), an indigestible marker sourced from Thermo Scientific, Waltham, MA, USA, in the basal diet at a rate of 1.0%. To create the feed, we first mixed all micro-ingredients followed by macro-ingredients, which were slowly added and thoroughly mixed into the feed to maintain a homogenous texture. Diets were manufactured at the Kapuscinski-Sarker Lab space in Natural Sciences II (University of California, Santa Cruz, CA, USA) using a single-screw extruder (TT-100 tabletop lab scale extruder from Akron Tool and Die, Akron, Ohio, USA). During extrusion, the diet was exposed to an average target temperature in the barrels at 90\u0026deg;C and passed through the extruder for 18s exposure. Relevant diets were top coated with fish oil or microalgal oil using a rotating mixer (SUNCOO 4/5HP Electric Concrete Cement Mixer 5 Cu Ft Mortar Mixing Stucco Seeds Portable Barrow Machine) and 24-mm mercury pressure. We carried out mixing for 15 minutes. After mixing, we dried the feed overnight to reduce the moisture content in the range of 16\u0026ndash;18% in a fume hood. The pellets were then sieved and stored at \u0026minus;\u0026thinsp;20\u0026deg;C. Initially, we used pellets 2.0 mm in size, but as the fish grew, we increased the pellet size to 4.0 mm to meet the nutritional demands of the larger fish.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Fish husbandry and experimental design\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe used a recirculating aquaculture system at the University of California, Santa Cruz, CA, USA, consisting of sixteen 200-gallon tanks, each containing 40 juvenile rainbow trout with an average weight of 0.85 g each. Following placement in the tanks, we allowed the fish to acclimatize for seven days. After the acclimation period, we randomly assigned the three experimental diets and reference diet to the 16 tanks and fed fish until apparent satiation twice a day, in the morning and afternoon, six days a week, for 84 days. A total of 16 tanks were used, with four replicate tanks per diet. We monitored each tank to maintain the recommended conditions for rainbow trout. Dissolved oxygen, dissolved oxygen saturation, temperature, and pH were sampled daily using a handheld YSI Pro1020 multiparameter meter to keep dissolved oxygen at or above 8.7mg/L, the water temperature no higher than 15.4\u0026deg;C, and pH no higher than 8.6. We sampled ammonia, nitrite, nitrate, and alkalinity of the water weekly using a benchtop YSI 9500 spectrophotometer to maintain total ammonia nitrogen at or below 0.2mg/L, nitrite nitrogen at or below 0.1mg/L, and nitrate nitrogen at or below 26.8 at mg/L.\u003c/p\u003e \u003cp\u003eWe collected fish fecal samples before feeding daily using a radial flow settler. We collected intact fecal matter at the bottom of the system by installing a radial flow settler between the culture tank outflow and the sump tank inflow. We prevented contamination by siphoning out uneaten feed pellets from the radial flow settler. We used pipettes to gently remove intact solid fecal matter from a separate collection bin. We placed the fecal matter in a 50mL Falcon tube (BD Falcon\u0026trade;) and allowed the fecal matter to settle at the bottom of the tube. We then removed supernatant water at the top using a pipette once the fecal samples settled at the bottom of the tube. Then, we froze the filtered-out fecal matter samples at -20\u0026deg;C. We pooled fecal samples from every collection from each specific tank during the experiment. At the end of the experiment, we lyophilized, finely ground, and stored samples at -20\u0026deg;C for nutrient analysis.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Growth Calculations\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe quantified growth, weight gain percentage, FCR, and survival rate for each dietary treatment. We calculated these parameters as follows:\u003c/p\u003e \u003cp\u003eGrowth: Whole body \u003csub\u003efinal wt\u003c/sub\u003e. - Whole body \u003csub\u003einitial wt.)\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eWeight gain percent: (Whole body \u003csub\u003efinal wt\u003c/sub\u003e. - Whole body \u003csub\u003einitial wt\u003c/sub\u003e.) / Whole body \u003csub\u003efinal wt\u003c/sub\u003ex 100\u003c/p\u003e \u003cp\u003eFCR: Feed intake (as fed basis) / Weight gain\u003c/p\u003e \u003cp\u003eSurvival rate: (Final number of fish / Initial number of fish) x 100\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Macronutrient and trace element analysis and Digestibility calculations\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe determined the nutrient composition after homogeneously grinding and freezing ingredients, diets, feces, and whole-body fish to -20\u0026deg;C. We then prepared the samples for ICP-AES analysis using the EPA Method 3050b for acid digestion (U.S. EPA, 1996). We then analyzed the digested material for elemental composition by ICP OES (Thermo iCap 7400 radial view ICP-OES, Optical Emission Spectroscopy conducted at UC Santa Cruz Plasma Analytical Laboratory, RRID:SCR_021925).\u003c/p\u003e \u003cp\u003eOnce we determined the concentration of the phosphorus and yttrium levels of the diets and feces, we calculated the apparent digestibility coefficient (ADC) of protein.\u003c/p\u003e \u003cp\u003eWe used the following equation to determine the ADC for the four diets (Cho et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1982\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eADC = (1 - ((%Protein \u003csub\u003efeces\u003c/sub\u003e / %Protein \u003csub\u003efeed\u003c/sub\u003e ) / (%Y\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3 feed\u003c/sub\u003e / %Y\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3 feces\u003c/sub\u003e))) * 100)\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Economic Conversion Ratio\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe used the Cruz Aquafeed Sustainability Tool (CAST; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cast.sites.ucsc.edu/\u003c/span\u003e\u003cspan address=\"https://cast.sites.ucsc.edu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, accessed November 2025) to calculate the economic conversion ratio (ECR), employing market prices from the CAST database to estimate ingredient costs (McKuin et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e). In CAST, we selected the option to apply the experimental feed conversion ratios (FCRs) obtained in this study rather than the default algorithm-generated values. The market prices of the experimental diets from the CAST database were obtained from a variety of sources (Table A6). The median values and 95% confidence intervals of market prices in CAST were estimated using non-parametric bootstrapping in RStudio (v.1.2.5033), based on 10,000 replicates and applying the adjusted bootstrap percentile method. The fish production cost was then expressed as the ECR following Sarker et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e):\u003c/p\u003e \u003cp\u003eECR (\u003cspan\u003e$\u003c/span\u003e/kg fish)\u0026thinsp;=\u0026thinsp;FCR ((kg diet fed)/(kg weight gain)) \u0026times; price of diet (USD\u003cspan\u003e$\u003c/span\u003e/kg diet)\u003c/p\u003e \u003cp\u003eWhere \u003cem\u003eECR\u003c/em\u003e represents the economic conversion ratio, and \u003cem\u003eFCR\u003c/em\u003e denotes the feed conversion ratio.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe used the one-way ANOVA function in IBM SPSS Statistics Version 27 when determining the significance among treatment groups. If there was a significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between treatment groups, we included a Tukey post hoc test in determining the similarities and differences between treatments when p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. We used different superscripts beside each treatment value to denote which treatments were similar statistically and which were not.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe conducted the experiment to determine the effects of replacing a reference diet of fishmeal (FM) and fishoil (FO) with different percentages of \u003cem\u003eN. oculata\u003c/em\u003e to replace FM, and either whole cell \u003cem\u003eSchizochytrium\u003c/em\u003e sp. or \u003cem\u003eSchizochytrium\u003c/em\u003e oil to replace FO.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Growth and Feed Performance\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe measured growth and monitored health across dietary treatment groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Rainbow trout fed experimental diets had similar feed conversion ratio (FCR) to the trout fed the reference diet of fishmeal and fish oil (FMFO). Apparent Digestibility Coefficient (ADC) of crude protein was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in NSW100 and NSO100 treatment groups compared to NSW75 and reference groups (Table A7).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eGrowth and weight gain percent did not significantly differ (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between the reference group (34.2 g\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24) and NSW75 (32.2 g\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77), where FMFO were partially replaced, and NSW100 (33.4 g\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51), where FMFO were fully replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells. However, growth was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the reference group compared to the NSO100 group (32.0 g\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25), where FO was replaced with \u003cem\u003eSchizochytrium\u003c/em\u003e sp. oil rather than \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells.\u003c/p\u003e \u003cp\u003eTrout appeared healthy at the end of the experiment with no signs of illness or deformities and there was no difference in survival between the dietary treatment groups.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Fish whole body proximate composition and fatty acid content\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe compared the whole body proximate composition across all dietary treatment groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Trout fed the fish-free diets (NSW100 and NSO100) did not differ significantly in moisture content from either the reference (FMFO) or the partial-replacement (NSW75) diets. Trout fed fish-free diets (NSW100, NSO100) had similar whole-body protein as those fed the reference diet, but significantly more protein than the partial-replacement diet (NSW75). The protein content ranged from 48.36\u0026ndash;53.06 percent; highest in the NSW100 group where FMFO was fully replaced. Fat content ranged from 34.60\u0026ndash;36.87 percent; highest in the NSW75 group where FMFO was partially replaced.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eWhole body proximate composition (dry weight basis) of rainbow trout after 84 days on the experimental diets.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProximate composition (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eWhole body \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76.89\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.91\u0026thinsp;\u0026plusmn;\u0026thinsp;2.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.99\u003csup\u003efg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.62\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.791\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.741\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.500\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eValues are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors of four replicate groups (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake.\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake.\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil.\u003c/p\u003e \u003cp\u003e \u003csup\u003ef, g\u003c/sup\u003e Mean values not sharing a superscript letter in the same row differ significantly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) from Tukey\u0026rsquo;s HSD test.\u003c/p\u003e \u003cp\u003e The fatty acid profile of whole body fish is presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The fatty acid content of diets differed, content is presented in Table A1. Trout fed the reference diet had significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) saturated fatty acids (SFA), but significantly lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) monounsaturated fatty acids (MUFA) compared to trout fed the experimental diets. For SFA, the reference group had significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) myristic (14:0), pentadecanoic (15:0), palmitic (16:0), heptadecanoic (17:0), stearic acid (18:0), and significantly less arachidic acid (20:0) compared to treatment groups. Between treatment groups, NSW100 had the highest arachidic acid (20:0) content, and NSO100 had significantly lower heptadecanoic acid (17:0) compared to reference and NSW75. For MUFA, the reference group had significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) Palmitoleic (16:1n9), Palmitoleic (16:1n7), Oleic (18:1n7), and significantly lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) Oleic (18:1n9), Eicosanoic (20:1n9), Erucic (22:1n9) compared to treatment groups. Between treatment groups, NSW75 had significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) Palmitoleic (16:1n7) and Oleic (18:1n9) than NSW100 and NSO100, significantly lower (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) Eicosanoic acid (20:1n9) and Total MUFA compared to NSW75. SFA ranged from 47.98% of TFA for the reference to 25.84% of TFA for NSO100. MUFA ranged from 45.39% of TFA for reference to 65.77% of TFA for NSW100.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFatty acid content of whole body rainbow trout after 84 days on experimental diets.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFatty acid (% TFA)\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eWhole Body\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003csup\u003et\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003csup\u003et\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e191.619\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e112.803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.96\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e61.113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01st\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003et\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e147.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.81\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd 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colname=\"c7\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24:1ω9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.317\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal MUFA\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003csup\u003et\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64.62\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05st\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e231.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18:2ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.208\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18:3ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:2ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:3ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:4ω6 ARA\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.855\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22:4ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22:5ω6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal ω6 PUFA\u003csup\u003ei\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.61\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.18\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.699\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18:3ω3 ALA\u003csup\u003ej\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18:4ω3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.154\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:3ω3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:4ω3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20:5ω3 EPA\u003csup\u003ek\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22:5ω3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22:6ω3 DHA\u003csup\u003el\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal ω3 PUFA\u003csup\u003em\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal PUFA\u003csup\u003en\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.63\u0026thinsp;\u0026plusmn;\u0026thinsp;2.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.54\u0026thinsp;\u0026plusmn;\u0026thinsp;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal ω6 LC PUFA\u003csup\u003eo\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.349\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal ω3 LC PUFA\u003csup\u003ep\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω3 / ω6 PUFA\u003csup\u003eq\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003er\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003csup\u003es\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Total fatty acids (TFA) (%); Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error for 4 replicates per diet (pooled whole tissues of 4 fish/replicate).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e Saturated fatty acids (SFA) is the sum of all fatty acids without double bonds.\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003e Monounsaturated fatty acids (MUFA) is the sum of all fatty acids with a single bond.\u003c/p\u003e \u003cp\u003e \u003csup\u003eh\u003c/sup\u003e Arachidonic acid (ARA).\u003c/p\u003e \u003cp\u003e \u003csup\u003ei\u003c/sup\u003e Omega-6 (n-6) Polyunsaturated fatty acids (PUFAs) (sum of all fatty acids with \u0026ge;\u0026thinsp;2 double bonds (18:2, 18:3, 20:2, 20:3, 20:4, 2:4, 22:5).\u003c/p\u003e \u003cp\u003e \u003csup\u003ej\u003c/sup\u003e Alpha-linolenic acid (ALA).\u003c/p\u003e \u003cp\u003e \u003csup\u003ek\u003c/sup\u003e Eicosapentaenoic acid (EPA).\u003c/p\u003e \u003cp\u003e \u003csup\u003el\u003c/sup\u003e Docosahexaenoic acid (DHA).\u003c/p\u003e \u003cp\u003e \u003csup\u003em\u003c/sup\u003e Omega-3 (n-3) PUFAs (18:3, 18:4, 20:3, 20:4, 20:5, 22:5, 22:6).\u003c/p\u003e \u003cp\u003e \u003csup\u003en\u003c/sup\u003e Polyunsaturated fatty acids (PUFA) is the sum of all fatty acids with two or more double bonds.\u003c/p\u003e \u003cp\u003e \u003csup\u003eo\u003c/sup\u003e n-6 long-chain (LC) PUFA (20:2, 20:3, 20:4, 22:4, 22:5).\u003c/p\u003e \u003cp\u003e \u003csup\u003ep\u003c/sup\u003e n-3 LCPUFA(20:3, 20:4, 20:5, 22:5, 22:6).\u003c/p\u003e \u003cp\u003e \u003csup\u003eq\u003c/sup\u003e Ratio calculated for total n-3 PUFA: total n-6 PUFA (n-3/n-6).\u003c/p\u003e \u003cp\u003e \u003csup\u003er s t\u003c/sup\u003e Mean values across the row not sharing a common superscript were significantly different as determined by Tukey\u0026rsquo;s HSD test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003eTotal polyunsaturated fatty acids (PUFA) content was similar across groups. We found no significant difference in total n-6 PUFA (Omega-6), including Arachidonic acid (ARA, 20:4n6), linoleic acid (LA,18:2n6), and total n-6 LC PUFA content; each ranged from lowest in the reference group to highest in the NSO100 group (Table A8). Similarly, we found no significant difference in total n-3 PUFA (Omega-3) between groups, including no significant difference in alpha-linoleic acid (ALA, 18:3n3), docosahexaenoic acid (DHA, 22:6n3), and total n-3 LC PUFA. However, we detected significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) eicosapentaenoic acid (EPA) content in the reference group compared to the experimental groups. The n-3/n-6 PUFA ratio (n-3/n-6) was significantly higher (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the reference group compared to the experimental groups.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Fillet Proximate and Amino Acid Profile\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe compared the fillet proximate composition across all dietary treatment groups (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). We found no significant difference (p\u0026gt;.05) in moisture, protein, fat, fiber or ash between groups. The lipid content ranged from 14.30 to 20.37 percent across groups; found to be highest in the NSO100 group. The protein content ranged from 69.70 to 75.85 percent across groups; highest in the NSW100 group.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProximate fillet composition (dry weight basis) of rainbow trout fed experimental diets for 84 days.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eProximate composition (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFillet \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoisture\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e81.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e81.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e83.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e81.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.391\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e69.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e74.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e75.85\u0026thinsp;\u0026plusmn;\u0026thinsp;1.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e69.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.650\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e14.68\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e20.37\u0026thinsp;\u0026plusmn;\u0026thinsp;3.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e0.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Error (pooled whole tissues of 4 fish/replicate).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003cp\u003eThe amino acid content was similar across groups (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The fillet of the reference group had slightly lower levels of methionine, phenylalanine, leucine, threonine, and histidine when compared to the experimental groups. The content of methionine ranged from 1.85 to 2.00 percent; phenylalanine from 2.62 to 2.80 percent; leucine from 4.98 to 5.14 percent; threonine from 3.05 to 3.11 percent; histidine from 2.02 to 2.13 percent.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEssential amino acid content (wet weight basis) of fillets from rainbow trout after 84 days on the experimental diets.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEssential amino acids (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eFillet \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethionine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e1.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e1.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLysine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e6.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e5.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenylalanine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeucine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e5.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e5.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e5.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIsoleucine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThreonine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e3.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistidine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e2.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e2.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArginine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e4.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard Error (pooled whole tissues of 4 fish/replicate).\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Fillet Macro Minerals and Trace Element Content\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eWe did not find any significant differences in the macro mineral composition of the fillets (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The reference group had a higher percentage of phosphorus, calcium, and magnesium, but a lower percentage of potassium and sulfur comparatively. The percentage of phosphorus ranged from 1.31 to 2.57 percent; calcium from 0.93 to 5.82 percent; magnesium from 0.30 to 1.51% percent; potassium from 0.04 to 1.45 percent; sulfur from 0.64 to 1.98 percent.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMacro minerals and trace elements content (wet weight basis) of Whole Body from Rainbow Trout after 84 days on the experimental diets.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eWhole Body\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eANOVA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100 \u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100 \u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eF\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMacro minerals (%)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhosphorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.21\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.22\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSulfur\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.31\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.624\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTrace elements (mg kg\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u0026minus;\u0026thinsp;1\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCopper\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManganese\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelenium \u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZinc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArsenic\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoron\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAluminum\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMercury\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLead\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMolybdenum\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eValues are means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors of four replicate groups (n\u0026thinsp;=\u0026thinsp;4); each replicate involves pooled whole tissues of 5 fish.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e Not detectable (ND) (\u0026lt;\u0026thinsp;0.00 mg/kg).\u003c/p\u003e \u003cp\u003eWe found no significant difference in the trace element composition of the fillets. We found a higher percentage of copper in the reference diet, and a lower percentage of iron compared to the experimental groups. Iron was highest in the NSW100 and NSO100 groups, ranging from 0.20 to 0.41 percent. Zinc was highest in NSW100, ranging from 0.04 to 0.21 percent. Amounts of selenium, arsenic, mercury, and lead were below the level of detection of the instrument.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Economic Conversion Ratio\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e In Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, we found that the feed conversion ratio, FCR and economic conversion ratio (ECR) did not differ significantly (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) between diets. NSW100 had both the lowest ECR and formulated feed cost (FFC); ECR ranged from 0.77 to 0.86 USD per kg of trout and FFC ranged from 0.87 to 0.97 USD per kg of feed. NSO100 had the highest (worst) feed conversion ratio; feed conversion ranged from 0.89 to 0.98 gram feed intake per gram wt. gain.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFormulated feed cost, feed conversion ratio, and economic conversion ratio of rainbow trout production\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCost Metrics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eScenario\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eAnova\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003csup\u003ee\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNSW75\u003csup\u003ef\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNSW100\u003csup\u003eg\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNSO100\u003csup\u003eh\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eF Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFormulated Feed cost\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFCR\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.98\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eECR\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003e Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error for 4 replicates per diet.\u003c/p\u003e \u003cp\u003e \u003csup\u003eb\u003c/sup\u003e Formulated Feed cost (FFC) = cost of feed (\u003cspan\u003e$\u003c/span\u003e) / kg feed\u003c/p\u003e \u003cp\u003e \u003csup\u003ec\u003c/sup\u003e Feed conversion ratio (FCR) = feed intake (g) /Wt. gain (g)\u003c/p\u003e \u003cp\u003e \u003csup\u003ed\u003c/sup\u003e ECR (\u003cspan\u003e$\u003c/span\u003e/kg fish)\u0026thinsp;=\u0026thinsp;FCR (kg) ((kg feed intake)/(kg weight gain))\u0026times;price of diet (USD\u003cspan\u003e$\u003c/span\u003e/kg diet)\u003c/p\u003e \u003cp\u003e \u003csup\u003ee\u003c/sup\u003e Reference: no replacement of fish meal (FM) and fish oil (FO).\u003c/p\u003e \u003cp\u003e \u003csup\u003ef\u003c/sup\u003e Replacement of 75% FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003eg\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e flake\u003c/p\u003e \u003cp\u003e \u003csup\u003eh\u003c/sup\u003e Replacement of 100% of FMFO replaced with \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizo.\u003c/em\u003e oil\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study provides the first evidence that rainbow trout can achieve comparable growth, FCR, and survival when fed a fully fish-free diet that simultaneously replaces 100% of both fishmeal (FM) and fish oil (FO with microalgal biomass)\u0026mdash;while remaining cost viable. A blend of defatted \u003cem\u003eNannochloropsis oculata\u003c/em\u003e biomass and DHA-rich \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells served as effective replacements for FM and FO, with no loss in performance and a lower economic conversion ratio (ECR). Moreover, the 100% fish-free diets showed higher protein digestibility than the FMFO reference diet. While these diets altered whole-body fatty acid profiles\u0026mdash;reducing saturated fatty acids (SFA) and one n-3 LC-PUFA, EPA, and increasing monounsaturated fatty acids (MUFA)\u0026mdash;they did not compromise growth outcomes, highlighting their potential as a sustainable, high-performing alternative for trout aquafeeds.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Effects of microalgal feeds on growth, protein digestibility, and feed performance\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur findings are novel, demonstrating for the first time that a microalgal-based diet can entirely replace traditional FMFO in juvenile rainbow trout diets without adversely affecting growth, feed conversion ratio and economic conversion ratio. These results underscore the potential of sustainable microalgal ingredients as viable alternatives in aquaculture, with promising implications for both environmental sustainability and economic feasibility. While prior studies have successfully replaced either fishmeal (FM) or fish oil (FO) individually, full replacement of both FM and FO has frequently resulted in compromised performance due to low feed palatability, poor digestibility, or nutrient deficiencies (Burr et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Cardinaletti et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Katerina et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Kousoulaki et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sarker, et al. 2020; Zatti et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our initial attempt to formulate fish-free feed for rainbow trout using a microalgal blend was unsuccessful, primarily due to reduced feed intake and poor palatability (Sarker et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study in contrast, our NSW75 and NSW100 diets, combining \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole-cell biomass, supported equivalent growth, feed conversion ratio (FCR), and survival compared to the FMFO reference diet. Notably, protein digestibility was highest in the 100% fish-free diets, suggesting efficient nutrient absorption and a potential synergistic effect between the two microalgal ingredients. The apparent protein digestibility and amino acid profiles observed in this study are consistent with previous findings on microalgal feeds used to replace FM or FMFO in rainbow trout (Sarker et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e) and Atlantic salmon (Gong et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; S\u0026oslash;rensen et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These results underscore the ability of a well-formulated microalgal diet to meet the essential nutritional requirements of rainbow trout, supporting the viability of fully fish-free aquafeeds without compromising physiological performance.\u003c/p\u003e \u003cp\u003eA key factor likely contributing to the improved outcomes in this study is the inclusion of taurine in all treatment diets. Taurine, a known feeding stimulant, has been shown to enhance palatability and nutrient absorption in fishmeal-free diets (Egerton et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; El-Sayed et al., 2013; Qi et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In our recent work, taurine supplementation significantly improved performance in rainbow trout fed FM-free microalgal diets (Sarker et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025a\u003c/span\u003e), and it likely played a similar role here by supporting consistent feed intake and utilization in the absence of FM and FO.\u003c/p\u003e \u003cp\u003eWe also compared \u003cem\u003eSchizochytrium\u003c/em\u003e sp. oil (NSO100) with its whole-cell counterpart as a DHA-rich replacement for FO. While NSO100 had the highest DHA content (6.11% of TFA), and high protein digestibility, fish in this group had lower growth compared to the FMFO group. This was unexpected, as previous studies have found that DHA-rich diets often enhance growth performance in salmonids (Katerina et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zatti et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). A potential explanation for the reduced growth in fish fed the NSO100 diet is its slightly lower EPA content (0.24% of TFA), which may contribute to imbalanced fatty acid profiles and reduced growth in trout and other carnivorous fish. This underscores the importance of maintaining an optimal DHA:EPA ratio, rather than maximizing DHA alone, for achieving favorable growth outcomes. The NSW100 diet contained a somewhat higher EPA level (0.34% of TFA), which may have played a minor role in the improved final weight and weight gain observed. However, it is likely that the primary growth benefits of the NSW100 diet stemmed from the presence of antioxidants and other bioactive compounds in the whole-cell biomass, rather than this relatively small difference in EPA content. Although algal oil lacks the indigestible cell wall that can hinder nutrient utilization (Lee et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), the performance of the NSO100 treatment did not surpass that of the whole-cell \u003cem\u003eSchizochytrium\u003c/em\u003e sp. treatments. This outcome suggests that bioactive compounds inherent in the whole-cell biomass\u0026mdash;such as tocopherols, carotenoids, structural lipids, and other functional molecules\u0026mdash;may elicit additional physiological benefits not provided by purified oil alone. The incorporation of whole-cell biomass introduces a broader antioxidant profile, potentially enhancing cellular protection and improving oxidative stability (Xing et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xu et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eSchizochytrium\u003c/em\u003e sp., a marine microalga, has emerged as a promising source of natural antioxidants due to its high content of phenolic compounds, antioxidant peptides, carotenoids (e.g., astaxanthin), and tocopherols\u0026mdash;all of which have been shown to retain activity following processing and digestion (Sarker et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Siddik et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Xing et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These compounds are increasingly linked to improved oxidative stability and enhanced immune function in aquafeeds (Xing et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhao et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although antioxidant status was not directly evaluated in this study, our findings underscore the potential value of whole-cell \u003cem\u003eSchizochytrium\u003c/em\u003e sp. in aquafeed formulations. This warrants further investigation, particularly as oxidative stability becomes a critical factor in the development of high-PUFA aquafeeds. Beyond its well-known role in salmonid pigmentation, compounds like astaxanthin from \u003cem\u003eSchizochytrium\u003c/em\u003e sp. offer broader health and welfare benefits, affirming the microalga\u0026rsquo;s relevance as a multifunctional, sustainable feed ingredient in modern aquaculture (Mueller et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Effects of Fish-free and microalgal Diets on Muscle Fatty Acids, Amino Acids, and Mineral Content\u003c/h2\u003e \u003cp\u003eIn addition to evaluating growth performance, this study aimed to identify a fish-free feed alternative that maintains the nutritional quality of the fish. Previous research on plant-based aquafeeds has reported reduced deposition of essential fatty acids in fish tissues (He et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Sprague, Dick, and Tocher \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In the present study, the fatty acid profiles of whole-body samples closely reflected the fatty acid composition of the respective dietary treatments. Specifically, the microalgal-based diets exhibited lower saturated fatty acid (SFA) and higher monounsaturated fatty acid (MUFA) levels compared to the FMFO diet (Table A1) with corresponding patterns observed in fish tissue deposition (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Given that sources low in saturated fatty acids (SFA) and high in monounsaturated fatty acids (MUFA) are considered beneficial for human health\u0026mdash;particularly cardiovascular health (Cao et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kris-Etherton, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1999\u003c/span\u003e)\u0026mdash;the fatty acid profile observed in fish fed microalgal diets may represent a favorable nutritional outcome. Given the consistent pattern of SFA and MUFA levels between the experimental diets and whole-body samples\u0026mdash;specifically, lower SFA and higher MUFA contents in both the test diets and the fish fed these diets compared with the reference group (Tables S1 and 5)\u0026mdash;the observed differences in tissue composition likely reflect the fatty acid profiles of the respective feeds.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eWith respect to polyunsaturated fatty acids (PUFA), this study found comparable levels of n-3 LC-PUFA (omega-3), n-6 LC-PUFA (omega-6), and docosahexaenoic acid (DHA) in the whole-body samples of fish fed fish-free, microalgal-based diets relative to those fed the FMFO-based reference diet. However, eicosapentaenoic acid (EPA) levels were significantly lower in the microalgal treatment groups. These whole-body fatty acid profiles closely mirrored the fatty acid composition of the respective diets (Table A1). The lower EPA levels in the microalgal diets were likely due to the use of \u003cem\u003eNannochloropsis\u003c/em\u003e co-product, from which a substantial portion of EPA had been extracted for human nutraceutical applications prior to feed formulation. Adequate dietary levels of n-3 LC PUFA and n-6 LC-PUFA are critical to fish growth and health (Tocher, DR, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite the higher inclusion levels of n-3 long-chain polyunsaturated fatty acids (LC-PUFA) in the FMFO diet, no significant differences were observed in whole-body n-3 LC-PUFA content between treatment groups. This suggests either a higher digestibility and retention of n-3 LC-PUFA in the microalgal diets or a lower bioavailability of these fatty acids in the FMFO aquafeed. The findings on DHA and EPA content in this study align with previous research on trout fed microalgal replacement diets, where increasing levels of microalgae led to a reduction in EPA content while DHA levels remained unaffected (Osmond et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Serrano et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe role of eicosapentaenoic acid (EPA) in fish growth and health is complex and species-specific. In Atlantic salmon, for instance, diets rich in docosahexaenoic acid (DHA) but low in EPA have been shown to impair growth when EPA levels fall below 1.3% of total fatty acids (TFA) (Katerina et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In contrast, recent studies on rainbow trout have reported that diets containing EPA levels as low as 0.2\u0026ndash;0.3% of TFA\u0026mdash;similar to those in the microalgal-based diets used in this study\u0026mdash;did not negatively impact growth performance, feed intake, survival, pigmentation, welfare indicators, histology, or fillet quality (Zatti et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite these findings, the reduced growth observed in the NSO100 group compared to the FMFO reference group may suggest a growth-limiting role of EPA, particularly as NSO100 had the lowest dietary and whole-body EPA levels of all treatments and was one order of magnitude lower than in NSW75 and reference diets (Table A1). Notably, our data showed no evidence of retro-conversion of DHA to EPA, which has been previously reported as limited in salmonids but may increase under essential fatty acid (EFA) deficiency (Ruyter and Thomassen, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Additionally, high dietary DHA levels are known to inhibit the conversion of α-linolenic acid (ALA) to EPA and reduce EPA retention in fish tissues (Bou et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017a\u003c/span\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003eb\u003c/span\u003e), which could partly explain the observed EPA shortfall in the NSO100 group. However, our results did not indicate an overall EFA deficiency in the microalgal diets. Collectively, these findings underscore the need for further investigation into the specific roles and optimal levels of EPA in trout nutrition. Future research should focus on optimizing EPA inclusion in fish-free microalgal diets\u0026mdash;particularly in relation to DHA content\u0026mdash;to retain the growth performance and improved protein utilization efficiency observed with the NSW100 diet, while enhancing EPA deposition in the fish.\u003c/p\u003e\u003cp\u003eWe found no difference in essential amino acids, proximate composition, minerals, or trace elements in rainbow trout muscle between dietary treatment groups. These findings support previous research demonstrating that microalgal-based diets perform favorably compared to conventional plant-based and fishmeal\u0026ndash;fish oil (FMFO) diets. While plant-based diets have often been associated with deficiencies in essential amino acids (He et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), microalgae offer a more balanced amino acid profile, meeting the nutritional requirements of carnivorous fish species. Furthermore, unlike FMFO diets, which are prone to higher levels of toxic trace elements such as arsenic and mercury due to biomagnification through the marine food web (Sarker et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e; Sele et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sissener et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Sloth et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) microalgal diets present a cleaner and potentially safer alternative. The absence of elevated contaminants, combined with adequate nutrient composition, highlights the potential of microalgae as a sustainable and nutritionally sound feed ingredient for aquaculture.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Effects of microalgae on Economic Conversion Ratio\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOur fish-free diets had the lowest formulated feed cost, with NSW100 also yielding the lowest ECR, showing that fish-free feed using combinations of microalgal biomass could be a cost-competitive, large-scale alternative to FMFO for trout. Historically, microalgae replacement diets have not been a cost competitive replacement for FMFO, in large part due to the high cost of microalgal oil. For example, in this study, cost ranged from 1.68 USD per kg for FO, 2.38 USD per kg for \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cell, and 4.41 USD per kg for \u003cem\u003eSchizochytrium\u003c/em\u003e sp. oil. Nevertheless, despite the higher cost of microalgal oil, the overall formulated feed cost for microalgae-based diets was lower, primarily due to the relatively high prices of fishmeal (1.54 USD/kg) and fish oil (1.68 USD/kg) compared to the significantly lower costs of \u003cem\u003eN. oculata\u003c/em\u003e co-product (0.54 USD/kg) and canola oil (0.88 USD/kg) (Table A6), and the higher quantities of FO required in reference diet compared to the DHA-rich microalgae diets (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As microalgae are increasingly sourced as underutilized co-products from adjacent industries such as biofuels and nutraceuticals, their production costs are expected to decline (Bryant et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Bose et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sarker et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sarker et al., 2020). These cost dynamics suggest that the economic feasibility of microalgal feeds will improve with wider industrial integration and scale-up. Cost projections aside, microalgal diets composed of \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003e sp. have already been shown to outcompete FMFO, corroborating the results in this study (Sarker et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCompared to other replacement diets, the estimated cost of the microalgal feed used in this study is more competitive than insect meal\u0026mdash;estimated to be 50% more expensive than fishmeal\u0026mdash;yet remains less competitive than plant-based diets, which have an estimated formulated feed cost of 0.64 USD/kg compared to 0.87 USD/kg for the most cost-effective microalgal diet, NSO100, in this study (Arru et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Nagappan et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sarker et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). In our recent study on fishmeal replacement using \u003cem\u003eN. oculata\u003c/em\u003e feed, the fully FM-replacing diet exhibited the lowest formulated feed cost (\u003cspan\u003e$\u003c/span\u003e0.88/kg feed) and economic conversion ratio (ECR) of \u003cspan\u003e$\u003c/span\u003e0.86 per kg of rainbow trout produced (Sarker et al. 2025). It is anticipated that with the development of large-scale production facilities, the cost of microalgal biomass and corresponding feeds will decrease, enhancing their competitiveness in aquafeed formulations. The cost of plant-based feeds often excludes the broader expenses associated with the entire life cycle of their ingredients. For instance, the cultivation of plant-based ingredients typically does not account for additional costs related to eutrophication, greenhouse gas emissions, or the increased land requirements necessary for their production (Gaber et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; McKuin et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; McKuin et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, the cultivation of marine photosynthetic microalga like \u003cem\u003eN. oculata\u003c/em\u003e can utilize waste streams from other industries, positioning it as a more sustainable alternative to plant-based aquafeeds (Craggs et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Fortier et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gaber et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Handler et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Quiroz Arita et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe future of microalgae as novel feed ingredients in aquaculture hinges largely on their production cost and the economic advantages they offer when incorporated into salmonid diets. While microalgae-based feeds currently remain more expensive than currently dominant ingredients such as fishmeal, fish oil, or plant-based proteins (Hua et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), this landscape is shifting. The price of fishmeal has surged by over two hundred percent in the past two decades (Trevi et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), narrowing the cost gap. Meanwhile, advances in cultivation technologies are driving down the production costs of microalgae, improving its economic feasibility (Torres et al. 2020). As production methods continue to become more efficient, microalgae-based aquafeeds are expected to become increasingly cost-competitive (Sarker et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). One notable example is the widespread industry adoption of \u003cem\u003eSchizochytrium\u003c/em\u003e sp., a heterotrophic, DHA-rich, and antioxidant-rich microalga, as a fish oil alternative in salmon feeds. This transition reflects both technological innovation and growing consumer and market demand for sustainable sources of omega-3 fatty acids. Moreover, the cost of feed ingredients is closely tied to production scale; as adoption increases, economies of scale are likely to further reduce costs.\u003c/p\u003e \u003cp\u003eSeveral major players in the aquafeed and agribusiness sectors\u0026mdash;including Corbion, BioMar, Archer Daniels Midland (ADM), and Veramaris\u0026mdash;have significantly expanded their efforts to develop and commercialize fish oil substitutes based on \u003cem\u003eSchizochytrium\u003c/em\u003e sp (Sarker et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tocher et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Willer et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Unlike photosynthetic microalgae, \u003cem\u003eSchizochytrium\u003c/em\u003e can be grown heterotrophically in industrial bioreactors without the need for sunlight or carbon dioxide, thereby reducing production costs (Lewis et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Tocher et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and reduces certain though not all life-cycle environmental impacts (McKuin et al, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Its cultivation is performed in controlled environments, which limits ecological disruption and enhances sustainability (Sarker et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). An open environmental life-cycle analysis showed that \u003cem\u003eSchizochytrium\u003c/em\u003e-based omega-3 production offers two environmental benefits: elimination of dependency on wild-caught forage fish and lower greenhouse gas emissions (Mckuin et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These advantages position \u003cem\u003eSchizochytrium\u003c/em\u003e as a cornerstone of future aquafeed formulations and align closely with the broader goals of ecological stewardship and responsible aquaculture.\u003c/p\u003e \u003cp\u003eThe findings of this study underscore the cost-competitiveness and practical viability of fish-free microalgal diets in aquaculture. However, one limitation of this study in estimating the ECR is that the CAST tool does not account for the costs of certain minor ingredients, such as taurine and lecithin, used in this experiment. Additionally, expenses related to feed manufacturing labor, transportation, and equipment were excluded from the analysis, and projected ingredient prices may not fully reflect actual market conditions. While the ECR values derived in this study are encouraging, achieving cost competitiveness of microalgal ingredients relative to conventional feed components remains a key challenge. Ultimately, large-scale production and cost reductions through technological innovation and industrial scale-up will be critical to realizing the commercial viability of microalgae-based aquafeeds. Expanding the portfolio of microalgal raw materials through innovative approaches presents significant opportunities to improve formulation flexibility\u0026mdash;prioritizing optimal nutrition, sustainability, availability, and affordability (Nagappan et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Realizing the full potential of microalgae as a sustainable feed ingredient depends on scaling up production processes to balance environmental responsibility with economic viability. The inherent biological advantages of microalgae, combined with mounting evidence supporting their effectiveness as a replacement protein and lipid source across diverse aquaculture species, position them as a promising alternative in the sector. Nonetheless, large-scale, continuous production of high-quality microalgal biomass remains challenged by technical, biological, and economic barriers\u0026mdash;particularly in optimizing downstream processing and ensuring consistent biomass quality (Aci\u0026eacute;n Fern\u0026aacute;ndez et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hoffman et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study demonstrates that fish-free diets formulated with \u003cem\u003eNannochloropsis oculata\u003c/em\u003e defatted biomass and DHA-rich \u003cem\u003eSchizochytrium\u003c/em\u003e sp. whole cells can fully replace traditional fishmeal and fish oil (FMFO) in juvenile rainbow trout aquafeeds\u0026mdash;with similar growth performance, protein digestibility (which actually increased), feed conversion ratio (FCR), and nutrient deposition. Importantly, our cost analysis reveals that these microalgae-based diets are already cost-competitive with conventional FMFO feeds\u0026mdash;even before projected cost reductions associated with industry-scale production of algal ingredients. This challenges the long-standing assumption that microalgal feeds are prohibitively expensive and positions them as a practical solution for commercial adoption.\u003c/p\u003e \u003cp\u003eTogether, these findings reinforce the transformative potential of microalgae as a sustainable, nutritionally adequate, and economically viable alternative to FMFO in aquaculture. However, unlocking the full value of this innovation requires sustained research and technological refinement. Future efforts should focus on optimizing inclusion levels, improving processing efficiency, and expanding the portfolio of algal co-products available for feed formulation. To truly catalyze a shift toward more sustainable aquaculture, it is critical that microalgae-based diets be tested under commercially relevant conditions. Only through such real-world validation can their full economic, environmental, and operational benefits be realized at scale\u0026mdash;supporting not only aquaculture productivity but also the global imperative to reduce dependence on wild-caught forage fish and promote a more resilient, ocean-friendly food system.\u003c/p\u003e \u003cp\u003eAuthorship contribution statement Conceived and designed the experiments: Pallab K. Sarker and Anne R. Kapuscinski; Performed the experiments: Devin Fitzgerald, Connor Greenwood, Benjamin V. Schoffstall, Kira O'Shelski, Duncan Gwynne, Diego Gonzalez Orcajo, Emily Noelle Pasion; Contributed materials/analysis: Devin Fitzgerald, Benjamin V. Schoffstall, Brandi McKuin, Pallab K. Sarker; Wrote-original draft: Pallab K. Sarker, Manuel J. Labbe; Wrote-review \u0026amp; editing: Pallab K. Sarker, Anne R. Kapuscinski, Benjamin V. Schoffstall, Brandi McKuin, Duncan Gwynne. All authors approved the submitted version for publication.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceived and designed the experiments: Pallab K. Sarker and Anne R. Kapuscinski; Performed the experiments: Devin Fitzgerald, Connor Greenwood, Benjamin V. Schoffstall, Kira O'Shelski, Duncan Gwynne, Diego Gonzalez Orcajo, Emily Noelle Pasion; Contributed materials/analysis: Devin Fitzgerald, Benjamin V. Schoffstall, Brandi McKuin, Pallab K. Sarker; Wrote-original draft: Pallab K. Sarker, Manuel J. Labbe; Wrote-review \u0026amp; editing:\u0026nbsp; Pallab K. Sarker, Anne R. Kapuscinski, Benjamin V. Schoffstall, Brandi McKuin, Duncan Gwynne. All authors approved the submitted version for publication.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the California Sea Grant Award (grant no. NA18OAR 4170073) (to Pallab Sarker), Agriculture and Food Research Initiative Competitive Grant award no. 2021-67016-33394 from the USDA NIFA and Agriculture and Food Research Initiative Competitive Grant no. 2021-69014-34501 from the USDA NIFA (to Pallab Sarker). We thank Cynthia and George Mitchell Foundation (to Pallab Sarker) for partial funding to support the work. We would like to thank the University of California Santa Cruz, Dean of Social Sciences and Executive Vice Chancellor. We also thank Rebecca White at Qualitas Health, Inc. for donating under-utilized Nannochloropsis oculata defatted biomass for this research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated for this study are included in the article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAci\u0026eacute;n Fern\u0026aacute;ndez, F. G., Fern\u0026aacute;ndez Sevilla, J. M., \u0026amp; Molina Grima, E. (2019). Chapter 21\u0026mdash;Costs analysis of microalgae production. In A. Pandey, J.-S. Chang, C. R. Soccol, D.-J. Lee, \u0026amp; Y. Chisti (Eds.), Biofuels from Algae (Second Edition) (pp. 551\u0026ndash;566). 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S., Zhang, J.-Y., Zhu, Y., Bai, J., Darwesh, O. M., Zhang, H.-B., \u0026amp; Xiao, X. (2021). Fermentation Affects the Antioxidant Activity of Plant-Based Food Material through the Release and Production of Bioactive Components. Antioxidants, 10(12), 2004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/antiox10122004\u003c/span\u003e\u003cspan address=\"10.3390/antiox10122004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-science-of-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjscifood","sideBox":"Learn more about [npj Science of Food](http://www.nature.com/npjscifood/)","snPcode":"41538","submissionUrl":"https://submission.springernature.com/new-submission/41538/3","title":"npj Science of Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Aquaculture feed, Microalgae Nannochloropsis oculata co-product, Schizochytrium sp., Ocean-derived fishmeal and fish oil, Sustainability, Rainbow trout, Growth, Nutritional quality, cost viability","lastPublishedDoi":"10.21203/rs.3.rs-8642818/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8642818/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAs global demand for affordable, high-quality protein continues to rise, commercial aquaculture has emerged as a critical solution. However, the industry's reliance on ocean-derived fishmeal (FM) and fish oil (FO) for aquafeed poses sustainability concerns. Marine microalgae offer a promising alternative due to their comparable nutrient profiles and potential for large-scale, sustainable production. In this study, we conducted a nutritional feeding experiment with juvenile rainbow trout to evaluate the efficacy of fish-free, microalgae-based diets formulated with protein-rich \u003cem\u003eNannochloropsis oculata\u003c/em\u003e (defatted biomass) and DHA- and antioxidant-rich \u003cem\u003eSchizochytrium\u003c/em\u003e sp. (either whole-cell or oil), combined with canola oil as replacements for FM and FO. Diets included a reference diet and three experimental diets with partial or full FMFO replacements: 75% inclusion of \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003e whole-cell (NSW75), 100% inclusion of both (NSW100), and 100% inclusion of \u003cem\u003eN. oculata\u003c/em\u003e with \u003cem\u003eSchizochytrium\u003c/em\u003e oil (NSO100). The fully fish-free diet, NSW100, supported growth, feed conversion, and survival rates comparable to the FMFO control. Whole-body fatty acid profiles reflected dietary inclusion levels, with similar total n-3 long-chain polyunsaturated fatty acids (LC-PUFA), including DHA, for fish fed the microalgal and reference diets but reduced EPA in fish fed the microalgal diets. No significant differences were observed across treatments in amino acid profiles, macronutrients, or mineral deposition. Notably, cost analysis revealed that fish-free diets had the lowest values, though not significantly, for formulated feed costs and economic conversion ratios (ECR), highlighting their commercial potential. These findings demonstrate that microalgae-based aquafeeds combining \u003cem\u003eN. oculata\u003c/em\u003e and \u003cem\u003eSchizochytrium\u003c/em\u003e sp. can viably replace FMFO without compromising fish performance, nutritional quality, or production economics\u0026mdash;marking a key advance towards more sustainable aquaculture.\u003c/p\u003e","manuscriptTitle":"Toward Sustainable Aquaculture: Microalgae Fully Replace Fishmeal and Fish Oil in Rainbow Trout Diets While Maintaining Growth, Nutritional Quality, and Cost Viability","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-10 16:47:48","doi":"10.21203/rs.3.rs-8642818/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T19:12:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-26T12:51:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-24T00:44:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-21T22:23:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T15:01:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T10:50:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T10:12:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115273017210619493053282849469951947410","date":"2026-02-12T12:21:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298148907549100434362145122562032782561","date":"2026-02-10T17:22:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"333340727246998631313810784284869428332","date":"2026-02-06T18:30:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"296738891859675593409259856480030248661","date":"2026-02-06T08:50:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"178690835636879254813058517195310622488","date":"2026-02-05T23:19:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"287282796288745460491439933899978804417","date":"2026-02-05T23:09:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263104932726863726716259944484621142612","date":"2026-02-05T22:53:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280695426104031786897166017302337629244","date":"2026-02-05T16:04:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-05T15:54:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-26T19:00:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-26T05:11:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Science of Food","date":"2026-01-19T20:06:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-science-of-food","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjscifood","sideBox":"Learn more about [npj Science of Food](http://www.nature.com/npjscifood/)","snPcode":"41538","submissionUrl":"https://submission.springernature.com/new-submission/41538/3","title":"npj Science of Food","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8f325ba0-82c6-45f9-a23a-6177e12c92bf","owner":[],"postedDate":"February 10th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62513283,"name":"Biological sciences/Biotechnology"},{"id":62513284,"name":"Biological sciences/Ecology"},{"id":62513285,"name":"Earth and environmental sciences/Ecology"},{"id":62513286,"name":"Earth and environmental sciences/Environmental sciences"},{"id":62513287,"name":"Earth and environmental sciences/Ocean sciences"}],"tags":[],"updatedAt":"2026-05-01T00:24:16+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-10 16:47:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8642818","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8642818","identity":"rs-8642818","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}