Dietary protein requirements of fish – a meta‐analysis

Reviews in Aquaculture, 1–33 doi: 10.1111/raq.12391 Dietary protein requirements of fish – a meta-analysis Aires Oliva Teles1,2, Ana Couto1,2 1 2 , Paula Enes1,2 and Helena Peres1,2 Departamento de Biologia, Faculdade de Ci^ encias, Universidade do Porto, Porto, Portugal ~es, Universidade do Porto, CIMAR/CIIMAR – Centro Interdisciplinar de Investigacß~ ao Marinha e Ambiental, Terminal de Cruzeiros do Porto de Leixo Matosinhos, Portugal Correspondence Ana Couto, CIMAR/CIIMAR – Centro ao Marinha e Interdisciplinar de Investigacß~ Ambiental, Universidade do Porto, Terminal de ~es, Av. General Cruzeiros do Porto de Leixo Norton de Matos s/n, 4450-208 Matosinhos, Portugal. Email: [email protected] Received 22 March 2019; accepted 30 September 2019. Abstract There are hundreds of fish reared in aquaculture, but nutrient requirements of the different species are still scarcely studied. Dietary protein is usually one of the first nutrients to be evaluated when considering the nutritional requirements of a novel species for aquaculture. Data on dietary protein requirement are already available for a large number of species, and this study aims to review the available data, enhancing eventual differences due to species, feeding habits, fish size, rearing temperature and water salinity. Overall, dietary protein requirements in the different studies ranged between 24 and 70% of the diet, depending on species and life stanzas. Dietary protein requirements were directly related to fish trophic level and water salinity, and inversely related to rearing temperature. Dietary protein intake was linearly related to weight gain, while protein retention was not affected, averaging 187 g protein kg 1 weight gain. On average, fish require a protein intake of 624 g kg 1 weight gain and dietary protein retention efficiency is close to 32%. Key words: growth, protein requirement, salinity, temperature, trophic level. Introduction Protein is required for plastic purposes, synthesis of enzymes, hormones and other metabolites (NRC 2011). Therefore, from a zootechnical perspective, it is important that diets include an amount of protein that meets animals’ requirements for growth, maintenance, tissue repair and optimal health status. In fish, protein usually constitutes the dietary component that is included at a higher quantity. As proteins are expensive, it usually represents the most expensive dietary component. Therefore, from an economic perspective, it is important that diets do not include proteins in excess. Proteins are not stored in the body in a way similar to that of carbohydrates and lipids. Therefore, an excess of dietary protein is used as an energy source in intermediary metabolism or is converted to glucose or lipids as energy deposits (Dabrowski & Guderley 2002). In either case, the amino acids that constitute proteins need to be deaminated and the ammonia produced is excreted by the gills and urine (Wilson 2002). As nitrogen is one of the main nutrients responsible for water eutrophication (the other one being phosphorus), an excess of dietary protein will negatively impact the environment (Cowey 1995). Thus, from © 2019 Wiley Publishing Asia Pty Ltd zootechnical, economical and environmental perspectives it is important that dietary protein meet but not exceed animals’ requirements. Similar to carbohydrates and lipids, protein can be used as an energy source to meet animals’ energy needs. Thus, the overall dietary energy available cannot be disregarded when considering protein requirements. Indeed, when fed nutritionally balanced diets, animals seem to regulate feed intake to meet energy requirements (Bureau et al. 2002). Therefore, if the diet has low protein: high energy ratio (LP:HE), animals may stop feeding before meeting their protein needs, with negative consequences in terms of growth performance and body composition. On the other hand, if the diet has high protein: low energy ratio (HP:LE) animals will eat an excess of dietary protein, which will be catabolized and used for energy purposes (Wilson 2002). This is particularly relevant in fish, which do not control amino acid catabolism efficiently, and therefore, N losses are high even when dietary protein levels are low (Cowey 1995; Kaushik & Seiliez 2010). When considering dietary protein requirements, protein bioavailability must also be considered. If dietary protein is not well digested, more protein needs to be incorporated in the diet to meet requirements. The dietary protein 1 A. Oliva Teles et al. requirement also depends on the protein essential amino acid (EAA) profile. Dietary proteins with an EAA profile close to that of the ideal protein will be required in lower quantity and will be utilized more efficiently for growth and protein deposition purposes. Thus, dietary protein: energy ratio, digestibility and amino acid profile need to be optimized to maximize zootechnical performance and to decrease economic feed costs and the negative environmental impacts due to feeding. Further, it should be recognized that fish do not have true dietary protein requirements. Instead, fish as other monogastric animals require a well-balanced mixture of both essential amino acid and non-essential amino acid (NEAA) that constitute proteins (Wilson 2002). However, the dietary protein requirement concept is still currently used in fish nutrition, and it is still very practical when considering diet formulation. Indeed, if only the EAA were considered when formulating diets, the requirements of NEAA, or of non-specific N source required to synthesize non-essential amino acids, might not be fulfilled. Further, animals need a balanced EAA-to-NEAA ratio to efficiently synthesize proteins. In fish, for maximum growth performance, dietary protein should have an EAA: NEAA ratio of 50:50 or above. This is different from carnivorous mammals such as the cat where this ratio is only 30:70 (Cowey 1995). Thus, while for the cat a high proportion of dietary protein will meet non-specific N needs, in fish dietary protein is required to meet both EAA and NEAA needs in almost equal amounts (Cowey 1995; Green et al. 2002; Peres & Oliva-Teles 2006). As feedstuffs usually have proteins with an EAA:NEAA ratio close to 50:50, by taking into consideration protein requirement in diet formulation, together with EAA requirements, it will be assured that dietary levels of NEAA or of its non-specific N sources will be guaranteed. Fish requires a higher content of protein in the diet, close to 2 to 4 times higher than farm animals. This, however, does not imply that fish use dietary protein inefficiently for growth purposes. Indeed, fish convert dietary protein to edible product very efficiently, and dietary protein retention in fish is similar to that of monogastric farm animals (Bowen 1987; Cowey 1995). This apparently higher dietary protein requirement of fish compared with that of farm animals is related to the low energy requirements of fish (Cho & Kaushik 1985). Fish are heterothermic animals, and therefore, they do not spend energy in maintaining body temperature, which represents a high amount of energy needs of farm animals. Indeed, maintenance metabolism in fish is around 5% that of farm animals (Brett & Groves 1979; Cho & Kaushik 1985; Bureau et al. 2002). Moreover, fish have neutral buoyancy and therefore spend low energy in maintaining their position in the water. In addition, fish excrete nitrogen mainly as ammonia, and 2 costs of ammonia production and excretion are lower than for urea or uric acid production and excretion (Brafield & Llewellyn 1982; Halver & Hardy 2002). Due to their low energy needs, the quantity of energy required to be provided in the diets is much lower compared with that required by farm animals. If protein needs for growth are similar for both fish and farm animals, while energy needs are lower for fish, this implies that the quantity of dietary protein relative to that of dietary energy is much higher in fish than in farm animals, thus explaining the apparently high dietary protein requirement of fish. There are hundreds of fish exploited in aquaculture, with different feeding habits (carnivorous, omnivorous and herbivorous), living in different habitats (freshwater, saltwater and diadromous) and temperatures (cold, temperate, tropical), and presenting different growth performances (fast, slow growers). All this diversity may be reflected in different nutritional requirements, but information on nutrient requirements of fish is still scarce for most of the aquaculture species (NRC 2011). This implies that diets used for most species are not necessarily the most adequate as they are formulated based on data from other, apparently similar, species. However, extrapolations on nutrient requirements, even for genetically close species with similar feeding habits and living in similar environmental conditions, are not necessarily adequate. For instance, for sea breams belonging to the genus Diplodus, which are omnivorous and live in warm salt waters, dietary protein requirements for juveniles were estimated to range from 27 to 44% (Sa et al. 2008; Ozorio et al. 2009; Coutinho et al. 2012; Coutinho et al. 2015). Protein is usually the first nutrient considered when determining the nutritional requirements of a species, and there is already an abundant amount of data on dietary protein requirements of fish. This study aims to review the available data on dietary protein requirements in fish, aiming to enhance eventual differences between species, feeding habits, fish size and environmental conditions (temperature and salinity). Study characterization We compiled available information on fish dietary protein requirements considering studies where at least three dietary protein levels were tested (Table 1). Overall, data on 336 studies were considered. Data were gathered on species, dietary protein requirement for maximum weight gain, protein retention as percentage of protein intake, trophic level (from FISHBASE), dietary protein sources used, fish weight (initial and final weights), number of dietary protein levels tested, trial duration, rearing water temperature and salinity, and statistical method for evaluating protein requirements. Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 Dietary protein requirement of different fish species Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) 89.2 56.5 44.7 9.3 0.35 1.18 0.76 0.40 90 56 45 45 25 28 18 20.2 FW 29 FW FW 42 41.4 40 45 103.3 395.6 1.58 98 21.8 FW 40 8 3 5 5 3 145.2 4.0 4.1 8.1 19.0 290.4 21.7 8.3 22.3 115.8 1.00 1.99 1.27 1.17 0.95 56 89 70 84 56 19.8 20 19 22 28.5 FW FW FW FW 31.5 40.5 42.5 38.6 47 46 30–55 36–52 40–54 35–53 6 5 4 4 1.9 44.4 23.3 50.7 7.5 161.2 65.9 173.6 1.18 0.92 1.00 1.08 42 50 92 62 18.2 24.5 19 24 SW 25.5 SW 34 45 48 50 43 FM-based 20–50 7 0.0 0.3 2.80 49 29 FW 30.1 31–46 6 3.6 15.0 1.30 56 19.5 34.2 43 2.4 2.4 2.4 FM–SBM–soy protein concentrate–corn gluten Casein–gelatine Casein–gelatine FM–based 20–50 20–40 15–55 7 5 5 0.8 0.9 1.1 7.8 15.0 3.9 1.43 70 1.60 90 2.56 70 27 28 28 FW FW FW 41.7 31.8 35 Bidyanus bidyanus Brachymystax lenok Brachymystax lenok Brycon orbignyanus Carassius auratus 3 3.8 3.8 2.5 2 FM-based FM-based FM–SBM–casein Casein–gelatine Casein 13–55 29–57 40–55 24–42 30–60 8 5 4 6 5 2.7 3.4 11.8 8.4 0.0 11.5 7.0 60.7 31.8 0.1 1.73 1.21 0.83 1.55 1.48 26 14.6 15.5 26.3 24 FW FW FW FW FW 42.1 43.6 45 29 53 Carassius auratus 2 FM-based 21–35 5 0.2 0.5 1.64 42 25 FW 29.9 Carassius auratus 2 FM–casein 21–34 5 0.2 0.6 1.64 42 25.2 FW 28.9 Carassius auratus gibelio Carassius auratus gibelio var. CAS III Carassius auratus gibelio var. CAS III 2 2 FM-based SPC–casein 30–38 3 27.8–50.7 6 4.0 3.2 27.1 12.7 1.22 56 1.58 56 23.5 27.5 FW FW 38 40.2 36.1 28 18.4 23.6 2 SPC–casein 26.1–48.9 6 86.7 158.0 1.32 56 27.5 FW 33.7 51.4 18.7 IBW (g) Trophic level Acanthopagrus berda Acanthopagrus schlegelii Acipenser baeri Acipenser persicus 3.5 3.2 3.3 3.7 FM–SBM–rice bran FM-based FM-based FM–SBM–meat meal 20–50 32–48 25–45 35–45 4 6 5 3 8.1 13.1 22.0 0.6 Acipenser persicus 3.7 40–50 3 Acipenser transmontanus Alosa sapidissima Anabarilius grahami Anguilla rostrata Argyrosomus amoyensis 3.3 3.5 3.2 3.8 4 20–53 30–50 29–49 35–51 40–46 Argyrosomus japonicus Argyrosomus japonicus Argyrosomus regius Argyrosomus regius 4.5 4.5 4.3 4.3 FM–meat meal– bloodmeal Casein FM–corn gluten FM-based FM-based FM–SBM–rapeseed– bloodmeal FM-based FM–SBM–yeast FM-based FM-based Aristichthys nobilis 4.3 Atractoscion nobilis 4.3 Barbodes altus Barbonymus gonionotus Barbonymus gonionotus Diet type Protein range tested FBW (g) 56 70 70 90 20 40 36.4 33 Broken line Quadratic Quadratic ANOVA 18.9 ANOVA Rahim et al. (2016) Zhang et al. (2010) Kaushik et al. (1991) Molla and Amirkolaie (2011) Mohseni et al. (2013) 30.8 25.4 22.1 Broken line Quadratic Broken line ANOVA ANOVA Moore et al. (1988) Murai et al. (1979) Deng et al. (2013a) Tibbetts et al. (2000) Wang et al. (2006) 19.4 ANOVA ANOVA ANOVA ANOVA 24.8 Quadratic Lee et al. (2001a) Chai et al. (2013) Chatzifotis et al. (2012) Velazco-Vargas et al. (2014) Santiago and Reyes (1991) Jirsa et al. (2014) 36.3 37.6 33.1 26.8 ANOVA 32.6 13.8 21.2 40.9 13.6 Reference 17.9 26.2 20.0 23.1 37.8 31.2 Adjustment 20.0 21.1 18.6 Quadratic Broken line ANOVA 27.9 22.7 24.7 15.1 26.1 Broken line Broken line ANOVA Exponential Quadratic 25.5 ANOVA ANOVA ANOVA Broken line / quadratic Broken line / quadratic Elangovan & Shim (1997) Mohanta et al. (2008) Wee and Ngamsnae (1987) Yang et al. (2002) Lee et al. (2001b) Xu et al. (2015) Sa and Fracalossi (2002) Fiogbe and Kestemont (1995) Lochmann and Phillips (1994) Lochmann and Phillips (1994) Zhao et al. (2016) Ye et al. (2015) Ye et al. (2015) 3 Fish protein requirement meta-analysis FCR Protein levels tested Species Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Species Trophic level Carassius auratus gibelio var. CAS III Carassius auratus gibelio var. CAS III Catla catla 2 FM–casein 25–45 6 3.7 25.0 1.04 56 28 FW 41.4 38.5 24.4 Quadratic Ye et al. (2017a) 2 FM–casein 20–45 6 84.8 220.3 1.21 56 25.5 FW 36.5 36 21.5 Quadratic Ye et al. (2017b) 2.8 Casein–gelatine 25–35 3 1.1 1.7 5.50 40 27.2 FW 35 ANOVA Centropristis striata Channa micropeltes Channa punctatus Channa striata 3.9 3.9 3.8 3.4 FM-based FM-based Casein–gelatine FM-PF 36–56 25–56 30–55 35–60 6 8 6 6 6.7 139.6 4.6 0.6 28.9 314.5 12.7 1.8 1.50 56 56 1.48 56 2.10 56 23 28 27 28 33.5 FW FW FW 45.3 52 46.2 55 Channa striatus Chanos chanos Chanos chanos 3.4 2.4 2.4 35–45 20–60 35–45 3 5 5 3.3 0.0 0.3 15.1 0.2 0.6 1.20 56 1.96 30 1.71 70 29 26.5 25 FW 33 25 45 40 40 ANOVA ANOVA ANOVA Chanos chanos 2.4 35–45 5 4.4 73.7 1.50 100 19.5 40 ANOVA Jana et al. (2006) Chelon aurata 2.8 FM–casein Casein FM–casein–groundnut oilcake–rice bran–wheat flour FM–casein–groundnut oilcake–rice bran–wheat flour FM-based Seenappa and Devaraj (1995) Alam et al. (2008) Wee and Tacon (1982) Zehra and Khan (2012) Mohanty and Samantaray (1996) Aliyu-Paiko et al. (2010) Lim et al. (1979) Jana et al. (2006) 25–45 4 50.9 90.7 3.70 140 19 29.9 25 19.1 13.5 ANOVA Chelon ramada 2.3 FM–casein 12–60 5 2.5 9.8 2.48 97 23 38 24 28.2 14.1 ANOVA Cichlasoma urophthalmus 3.9 FM-based 0–45 10 0.3 4.3 1.38 81 28 FW 38.3 31.3 24.9 Broken line Cichlasoma urophthalmus 3.9 FM-based 0–45 10 0.2 4.3 1.38 81 28 FW 38 31.3 24.5 ANOVA Clarias batrachus Clarias batrachus Clarias gariepinus Clarias gariepinus Clarias gariepinus Clarias gariepinus Clarias gariepinus Clarias gariepinus Colossoma macropomum 3.4 3.4 3.8 3.8 3.8 3.8 3.8 3.8 2 FM-based FM-based FM-based FM–SBM FM–SBM FM–SBM FM–SBM Casein–gelatine FM-based 28–40 28–41 15–35 25–40 25–40 25–40 25–35 20–50 30–40 4 4 5 4 4 4 3 7 3 0.2 0.2 39.7 11.0 11.0 11.0 9.9 8.2 18.8 4.0 4.3 82.1 24.6 36.1 47.6 75.8 79.3 284.1 1.16 1.16 2.92 2.50 1.36 0.93 1.58 1.39 2.20 28 32 36 36 30 40 40 40 30 39.2 30 22.4 43.9 43.9 16.2 Quadratic Quadratic ANOVA 23 25 27 26 27.5 24 FW FW FW FW FW FW FW FW FW 22.3 26.6 ANOVA Quadratic ANOVA Colossoma macropomum 2 FM–SBM 17–64 5 1.5 29.1 1.01 28 29.1 FW 50 26.0 ANOVA Colossoma macropomum 2 FM–SBM 17–64 5 30.1 90.2 1.44 28 29.1 FW 40 21.3 ANOVA Karapanagiotidis et al. (2014) PaparaskevaPapoutsoglou (1986) MartINez-Palacios et al. (1996) MartINez-Palacios et al. (1996) Singh et al. (2009) Singh et al. (2009) Omar (1996) Degani et al. (1989) Degani et al. (1989) Degani et al. (1989) Ahmad (2008) Farhat Khan (2011) Merola and Cantelmo (1987) Van der Meer et al. (1995) Van der Meer et al. (1995) 60 60 70 78 78 78 105 56 194 32.6 24.1 33.3 25.1 30.1 24.3 34.9 28.6 31 Adjustment Broken line Broken line Quadratic ANOVA Reference A. Oliva Teles et al. 4 Table 1 (continued) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 (continued) Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) Trophic level Colossoma macropomum 2 FM–SBM 17–64 5 95.9 181.8 1.50 28 29.4 FW 40 Colossoma macropomum Coptodon zillii Coptodon zillii Coptodon zillii Cromileptes altivelis Ctenopharyngodon idella Ctenopharyngodon idella Ctenopharyngodon idella Ctenopharyngodon idella Culter alburnus Cynoglossus semilaevis Cyprinus carpio Cyprinus carpio Cyprinus carpio Cyprinus carpio var. Jian Cyprinus pellegrini Cyprinus pellegrini Dentex Dentex Dicentrarchus labrax 2 2.5 2.5 2.5 4.5 2 2 2 2 3.4 4 3.1 3.1 3.1 3.1 2.7 2.7 4.5 3.5 FM-based Casein Casein Casein FM-based Casein FM–SBM Casein–gelatine FM–casein–gelatine FM–casein FM-based Casein Casein Casein–gelatine FM-based FM-based FM-based FM-based FM-based 20–35 0–65 28–40 21–53 42–53 0–65 20–40 20–45 17–36 35–45 45–55 22–42 0–55 26–34 22–50 29–48 29–49 44–56 36–56 4 8 3 6 3 7 5 6 6 3 3 3 272.6 2.4 2.4 3.4 311.0 0.6 2175.0 19.3 787.3 32.7 92.8 9.4 13.5 15.8 54.2 27.4 27.4 43.9 12.5 48 1.92 1.78 1.20 21 2.00 180 27 25 25 25 FW FW FW FW 22.5 3 6 5 6 3 4 123.7 1.6 1.5 1.8 178.0 0.2 913.0 4.3 264.0 6.5 43.8 4.3 6.0 2.6 16.7 12.4 12.4 20.7 5.6 26.9 28.2 28 26 23 23 25 25 20 20 20 18 FW FW FW FW FW 30.2 FW FW FW FW FW FW 33 34 30 40 35 35 52 43 30 40 28.6 40 55 31 38 34 34.1 39.3 43.6 44.3 48 Dicentrarchus labrax 3.5 FM-based 36–56 4 5.6 28.4 1.32 84 25.2 34 Dicentrarchus labrax Dicentrarchus labrax Dicentrarchus labrax Dicentrarchus labrax Dicentrarchus labrax Dicentrarchus labrax Dicentrarchus labrax Diplodus cervinus 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3 FM-based FM-based FM-based FM-based FM-based FM–bloodmeal FM–bloodmeal FM-based 30–60 30–61 5–55 5–56 44–54 40–55 40–55 5–55 4 4 6 6 3 4 4 9 31.0 37.0 99.0 160.0 77.7 3.1 2.7 7.7 37.9 58.1 146.0 198.0 224.4 18.4 16.7 19.2 2.10 1.56 1.22 1.14 1.75 1.64 1.34 1.61 42 42 42 42 168 90 90 98 15 20 20 20 21.7 26 28 22 Diplodus puntazzo Diplodus puntazzo Diplodus sargus Diplodus sargus Diplodus sargus Diplodus sargus Diplodus vulgaris Diplodus vulgaris Eleginops maclovinus 3.2 3.2 3.4 3.4 3.4 3.4 3.5 3.5 3.5 FM-based FM-based FM-based FM-based FM-based FM–SBM FM-based FM-based FM-based 15–55 15–56 6–49 40–60 38–52 25–45 35–50 5–55 9–44 5 5 5 5 4 3 4 6 6 49.3 49.3 22.0 1.5 40.9 0.6 3.6 6.1 40.0 111.0 108.7 35.4 12.9 71.3 19.9 12.5 17.5 74.0 1.49 1.49 2.38 1.45 1.96 1.24 1.50 1.54 1.89 77 77 56 70 84 70 60 72 98 22 22 22 22 22 27 23.1 24.1 14 0.99 1.35 1.33 1.11 1.03 0.87 1.09 1.56 1.56 1.92 1.52 360 56 56 70 63 28 30 42 45 70 70 60 84 21.3 Adjustment ANOVA 32.8 32.2 28.8 25.3 48.5 26.5 26.3 23.9 48.4 44.8 22.2 27.9 24.6 23.7 25.7 26.7 24.3 24.4 ANOVA No model or ANOVA No model or ANOVA No model or ANOVA ANOVA Broken line ANOVA ANOVA ANOVA ANOVA ANOVA No model or ANOVA Broken line ANOVA Broken line Broken line Quadratic ANOVA ANOVA 48 32.9 24.4 ANOVA SW SW 35 35 17.5 16 16 33 50 50 43.9 43.9 49 45 45 43.8 24.8 24.9 26.3 26.3 22.0 22.0 33 33 34 33 30 35 29.8 32.5 34 42.9 42.9 27 40 38 45 35 35.7 34.7 26.4 26.8 30 27.5 24.1 32.7 Quadratic Quadratic ANOVA ANOVA ANOVA ANOVA ANOVA Curvilinear-plateau model Quadratic Quadratic Exponential ANOVA ANOVA ANOVA ANOVA Quadratic Exponential 24.7 50 26.3 26.9 29.2 23.8 29.9 25.9 27.3 23.9 23.0 26.1 22.4 22.4 21.5 21.3 13.2 19.3 18.5 21.8 17.5 15.9 17.0 Reference Van der Meer et al. 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(2014) 5 Fish protein requirement meta-analysis Species Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (% PI) (%) (days) (g kWG 1)/ Energy intake (kJ kg 1 WG) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Species Trophic level Epinephelus akaara Epinephelus coioides Epinephelus fuscoguttatus Epinephelus malabaricus Epinephelus malabaricus Epinephelus malabaricus Epinephelus malabaricus Fugu rubripes Gadus morhua Gadus morhua Gadus morhua Gadus morhua 4 4 4.1 FM-based FM-based FM-based 32–62 37–63 45–55 6 6 3 7.9 10.7 8.8 37.5 23.6 37.1 1.20 56 2.06 56 1.10 56 27.5 25.5 29 25 22 FW 50.8 48 50 4.1 4.1 4.1 4.1 3.6 4.1 4.1 4.1 4.1 FM-based FM-based FM-based Casein Casein FM-based FM-based FM-based FM-based 44–60 0–56 20–70 24–54 0–80 47–64 36–57 36–58 49–63 4 8 6 6 12 5 5 5 4 17.0 9.2 63.5 3.8 2.0 37.0 608.0 393.0 121.0 70.2 61.5 219.5 13.0 4.4 107.0 770.0 794.0 261.0 1.04 0.80 1.16 1.06 1.13 56 56 84 50 21 125 90 190 56 29 28 29.7 27 25.5 9 9 9 10.3 34 30.5 30.1 32 FW 30 30 30 SW 55 50.2 50 47.8 50 47 36 36 49 33.6 Hemibagrus nemurus Hemibagrus nemurus Hemibagrus nemurus Hemibagrus wyckioides Hemibarbus labeo Hemibarbus maculatus Hemibarbus maculatus Heteropneustes fossilis Heteropneustes fossilis Heterotis niloticus 3.6 3.6 3.6 3.7 3.4 3.5 3.5 3.6 3.6 2.7 FM-based FM-based FM–casein–gelatine FM-based FM–SBM FM–casein FM–casein Casein Casein–gelatine FM–SBM 20–50 27–50 30–40 24–49 32–48 25–50 20–50 0–39 25–50 25–40 7 6 3 6 5 6 7 7 6 4 7.6 25.4 630.6 1.9 7.6 1.6 9.4 0.8 10.0 4.0 17.7 63.0 706.6 10.2 23.8 5.3 22.0 2.5 26.9 14.8 2.08 70 1.40 84 112 0.93 56 1.10 84 1.43 56 1.43 56 1.78 60 1.42 56 1.67 42 26.8 FW FW 20 38.2 36 26 26 26 29 28 28 FW FW FW FW FW FW FW 44 42 35 44.1 44 35 30 35.4 40 31 Heterotis niloticus 2.7 FM–SBM 25–40 4 26.4 58.6 1.42 28 28 FW Heterotis niloticus 2.7 FM–SBM 28–36 3 2.3 21.8 0.88 56 27.6 Hippoglossus hippoglossus Hippoglossus hippoglossus Hippoglossus hippoglossus Hippoglossus hippoglossus Horabagrus brachysoma 4 FM-based 40–52 7 559.0 877.0 1.20 102 4 FM-based 35–47 5 980.0 4 FM-based 41–62 3 4 FM-based 38–58 3.1 Huso huso Huso huso Ictalurus punctatus 4.4 4.4 4.2 SBM–groundnut oil meal FM-based FM–casein–gelatine Egg powder Adjustment Reference 24.2 33.8 22.6 Quadratic Broken line ANOVA Wang et al. (2016) Luo et al. (2004) Shapawi et al. (2014) 26.6 33.3 36.2 24.4 Quadratic Broken line Quadratic ANOVA No model or ANOVA ANOVA ANOVA ANOVA ANOVA 20.9 17.9 23.0 17.2 Broken line ANOVA ANOVA Broken line Broken line ANOVA ANOVA ANOVA Quadratic Broken line 31 17.2 Broken line FW 28 14.3 ANOVA 11 20 41 ANOVA Tuan and Williams (2007) Shiau and Lan (1996) Teng et al. (1978) Chen and Tsai (1994) Kanazawa et al. (1980) Arnason et al. (2010) Arnason et al. (2010) Arnason et al. (2010) Grisdale-Helland et al. (2008) Ng et al. (2001) Khan et al. (1993) Abidin et al. (2006) Deng et al. (2011a) Lv et al. (2016) Chen et al. (2010) Chen et al. (2010) Akand et al. (1989) Siddiqui and Khan (2009) Monentcham et al. (2010a) Monentcham et al. (2010b) Monentcham et al. (2010a) Arnason et al. (2009) 1493.0 1.53 135 11 20 35 ANOVA Arnason et al. (2009) 7.2 556.0 0.73 240 8.2 SW 61.8 ANOVA Aksnes et al. (1996) 4 34.0 314.3 293 9.5 35 58 ANOVA Hjertnes et al. (1993) 25–45 5 2.3 8.5 2.42 84 29.5 FW 39.1 24.0 Quadratic Giri et al. (2011) 30–55 30–55 17–40 6 6 7 1.3 1.3 200.0 76.6 1.10 70 76.6 1.10 70 1140.0 1.10 63 19.8 19.8 26.7 FW FW FW 38.9 38.9 40 19.4 19.4 Broken line Broken line ANOVA Mohseni et al. (2014) Mohseni et al. (2014) Garling and Wilson (1976) 20.1 37.6 28.8 21.7 21.5 18.4 31.7 24.7 48.6 40.9 31.2 A. Oliva Teles et al. 6 Table 1 (continued) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 (continued) Trophic level Ictalurus punctatus Ictalurus punctatus Labeo fimbriatus Labeo rohita Labeo rohita Labeo rohita 4.2 4.2 2 2.2 2.2 2.2 Labeo rohita Larimichthys crocea Larimichthys crocea 2.2 3.7 3.7 Lepomis macrochirus Lepomis macrochirus 3.2 3.2 Leuciscus idus Lutjanus argentimaculatus Lutjanus argentimaculatus Lutjanus argentimaculatus Lutjanus argentimaculatus Lutjanus argentiventris 3.8 3.6 SBM–FM SBM FM–SBM–groundnut cake Casein–gelatine Casein–gelatine FM–SBM–groundnut meal Casein–gelatine FM–yeast FM–casein–mussel meal– squid meal FM-based FM–SBM-poultry byproduct meal– cottonseed meal FM–casein–gelatine FM-based 3.6 Maccullochella peelii peelii Megalobrama amblycephala Megalobrama amblycephala Megalobrama amblycephala Megalobrama terminalis Melanogrammus aeglefinus Melanogrammus aeglefinus Melanogrammus aeglefinus Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Temp Salinity Protein Trial Protein intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) 84 158 60 60 60 360 27–42 26–32 20–40 25–40 25–45 20–40 4 3 5 3 4 5 84.0 69.0 4.8 4.1 4.4 870.0 319.7 337.4 11.1 10.1 11.1 2500.0 1.52 1.50 2.60 2.04 1.30 23.7 FW 29 31.5 28.5 FW FW FW FW 27 26 30.1 40 45 30 25–45 34–47 47–67 4 4 5 5.5 0.6 1.8 13.9 7.5 37.3 1.30 60 1.45 60 30 30.5 22.3 24 FW 23.5 27 21–46 32–44 5 4 1.2 1.8 21.1 13.0 1.00 70 1.28 77 26 29.5 26–51 20–45 6 6 33.0 8.0 79.3 110.2 2.04 60 0.27 90 FM–SBM–squid 35–50 3 24.8 153.6 2.65 100 3.6 FM–SBM–squid 39–49 3 21.1 115.1 2.40 94 3.6 FM–SBM–shrimp meal 28–58 7 12.3 98.1 0.75 90 4 FM–squid meal 31–55 4 18.0 40.2 4.2 FM–SBM 40–60 5 21.5 3.4 Casein 25–53 6 3.4 27–35 3.4 SBM–rapeseed meal– cottonseed meal–wheat bran FM–casein 3.3 4 28.1 25.1 Adjustment Reference ANOVA ANOVA Quadratic ANOVA ANOVA ANOVA Webster et al. (1994) Robinson and Li (1999) Jena et al. (2012) Dalal et al. (2001) Satpathy et al. (2003) Khan et al. (2005) ANOVA ANOVA ANOVA Satpathy and Ray (2009) Duan et al. (2001) Yu et al. (2012) 34.2 19.3 23.5 23.8 40 47 57.1 31.3 23.1 FW FW 42.3 44 34.04 23.1 Broken line ANOVA Yang et al. (2016) Hoagland et al. (2003) 24 24 FW 35.3 36.9 42.8 16.8 23.5 19.1 ANOVA Broken line Ren et al. (2017) Abbas et al. (2012) 28.5 34 42.5 25.9 ANOVA Catacutan et al. (2001) SW 44 23.3 ANOVA Catacutan et al. (2001) 26.6 36.4 43 20.2 Broken line 2.36 95 26 35 55 26.1 ANOVA 66.8 1.05 56 20 FW 50 23.8 ANOVA Abbas and Siddiqui (2013) Maldonado-Garcıa et al. (2012) Gunasekera et al. (2000) 8.1 16.4 1.11 30 26 FW 32.6 Broken line Duan et al. (1989) 3 1.8 21.4 1.34 56 27.5 FW 31 16.7 ANOVA Li et al. (2010) 28–36 5 16.1 40.7 1.77 70 25 FW 34 21.8 ANOVA Habte-Tsion et al. (2013) FM-based FM-based 26–50 35–50 5 4 1.3 23.9 14.2 65.8 1.01 70 0.70 63 26 12.6 FW 30 44 49.9 41.1 48.1 25.3 30.1 ANOVA Broken line Yang et al. (2017) Kim et al. (2001a) 4 FM–casein–krill 45–65 5 6.9 23.0 0.76 42 13 30 45 45 47.8 ANOVA Kim and Lall (2001) 4 FM–crab meal–corn gluten 45–55 3 13.8 61.5 0.68 63 12 29 54.6 32.1 ANOVA Tibbetts et al. (2005) #DIV/0! 7 Fish protein requirement meta-analysis Species Species Trophic level Menidia estor Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) FM-based 25–55 6 69.2 325.7 1.00 56 24.9 5 40.9 25–55 42–47 34–54 42–51 4 3 6 4 0.7 122.1 14.5 8.7 1.7 436.0 22.2 52.4 0.92 2.00 1.01 1.03 25 25.3 25.6 FW FW FW FW 35 47 43.5 48 30–50 3 0.4 1.5 1.40 56 25.1 FW 50 30 336 42 56 20.6 Adjustment Broken line Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd ANOVA ANOVA Broken line ANOVA Martinez-Palacios et al. (2007) Singh et al. (2007) Tidwell et al. (1996) Portz et al. (2001) Huang et al. (2017a) 34.2 ANOVA Yang et al. (2017) 22.4 ANOVA ANOVA ANOVA ANOVA ANOVA Broken line Quadratic ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA No model or ANOVA No model or ANOVA Broken line Broken line ANOVA ANOVA No model or ANOVA Ma et al. (2014) Millikin (1983) Millikin (1982) Woods et al. (1995) de Carvalho et al. (2010) Zhang et al. (2009) Huang et al. (2017b) Lochmann and Phillips (1994) Lochmann and Phillips (1994) Zeiton et al. (1974) Zeiton et al. (1974) Lee and Kim (2001) Kim et al. (1991) Oliva-Teles (1989) Oliva-Teles (1989) Takeuchi et al. (1978) Satia (1974) Zeiton et al. (1973) Zeiton et al. (1973) Cho et al. (1976) Ince et al. (1982) De Long et al. (1958) 55 No model or ANOVA De Long et al. (1958) FW 40 No model or ANOVA De Long et al. (1958) 14.4 FW 55 No model or ANOVA De Long et al. (1958) 20.5 FW 45.2 Broken line Kim et al. (2016) Metynnis hypsauchen Micropterus salmoides Micropterus salmoides Micropterus salmoides 2.9 3.8 3.8 3.8 Misgurnus anguillicaudatus Monopterus albus Morone saxatilis Morone saxatilis Morone saxatilis Mugil liza Myxocyprinus asiaticus Nibea coibor Notemigonus crysoleucas 3.2 FM–casein–egg FM–SBM FM–SBM FM–SBM–poultry byproduct–cottonseed– corn gluten FM–soy concentrate 2.9 4.7 4.7 4.7 2 3.1 3.5 2.7 FM–SBM FM–soy concentrate FM–soy concentrate FM–SBM–other meals FM–casein–gelatine FM-based FM–casein FM-based 35–45 37–57 34–55 35–56 30–50 30–50 36–52 21–34 3 3 3 3 5 6 5 5 65.1 1.4 2.5 241.2 1.2 13.5 75.9 0.2 132.8 9.2 9.4 379.8 4.4 39.1 207.1 1.1 1.60 1.25 1.00 1.20 2.56 1.10 1.31 1.64 70 70 42 84 35 56 49 56 28 20 24.5 22 24 28 27.5 25 FW 7 3 4 29 FW 32 FW 45 47 55 55 35 46.5 45.6 28.9 Notemigonus crysoleucas 2.7 FM–casein 21–34 5 0.2 1.3 1.64 56 25.2 FW 28.9 ANOVA Oncorhynchus kisutch Oncorhynchus kisutch Oncorhynchus masou Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus mykiss Oncorhynchus tshawytscha Oncorhynchus tshawytscha Oncorhynchus tshawytscha Oncorhynchus tshawytscha Oplegnathus fasciatus 4.2 4.2 3.6 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.1 4.4 FM-based Casein FM-based FM-based Casein FM-based Casein–gelatine Casein–gelatine FM–SBM FM-based Casein–gelatine 30–55 30–56 30–50 30–45 35–56 35–56 0–49 30–50 30–60 30–60 25–40 32–53 13–65 6 6 3 4 4 4 5 5 7 7 4 3 4 14.3 14.7 22.1 10.5 0.4 25.0 2.2 3.5 6.2 6.3 3.2 26.6 1.5 21.6 20.9 30.9 25.1 1.7 79.0 5.4 35.5 19.0 20.3 41.6 111.3 2.3 1.28 1.06 1.43 1.43 1.07 1.15 0.87 1.40 1.19 1.11 1.05 1.28 70 70 70 84 90 70 8.5 8.5 15.8 13.5 13.2 9.7 16.5 23 10.5 10.5 15.2 12 8.3 10 20 FW FW FW FW FW FW 10 20 FW FW FW 40 40 40 30 49 35 35 40 40 45 40 43 40 4.4 Casein–gelatine 13–65 4 2.6 7.7 70 14 FW 4.4 Casein–gelatine 25–65 9 5.6 7.2 70 8.3 4.4 Casein–gelatine 25–65 9 5.6 10.2 70 3.6 FM-based 35–60 5 7.1 20.0 1.22 56 70 70 70 42 41 86 Reference 27.2 37.8 24.2 23.8 62.9 35.8 34.6 18.7 37.5 30.2 24.7 28.1 19.4 30.1 41.7 48 22.8 16.3 34.4 24.2 29.5 30.7 26.3 24.0 A. Oliva Teles et al. 8 Table 1 (continued) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 (continued) Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) Trophic level Oplegnathus fasciatus Oplegnathus fasciatus Oreochromis mossambicus Oreochromis niloticus 3.6 3.6 2.2 FM-based FM–casein FM-based 35–50 35–50 0–56 4 4 8 7.1 7.1 1.8 18.7 18.7 8.5 1.29 56 1.29 56 1.46 40 20.5 20.5 27 FW FW FW 45 45 40 2 FM-based 20–50 4 0.2 18.0 0.81 70 26 FW Oreochromis niloticus 2 FM-based 20–51 4 0.2 12.3 1.10 70 26 Oreochromis niloticus 2 FM-based 20–52 4 0.2 16.9 0.86 70 Oreochromis niloticus 2 FM-based 20–53 4 0.2 16.8 Oreochromis niloticus 2 FM-based 30–50 5 0.0 Oreochromis niloticus 2 Casein 5 Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus Oreochromis niloticus 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Casein FM–SBM FM-based FM-based FM-based FM-based Casein FM-based FM-based FM–SBM–yeast FM–SBM–yeast FM–SBM FM–SBM FM–SBM 25–40 20–35 20–50 10–47 10–48 10–49 0–40 20–50 20–50 29–39 29–39 20–30 20–30 25–45 Oreochromis niloticus 2 FM–SBM Oreochromis niloticus 2 Oreochromis niloticus Oreochromis niloticus 2 2 Oreochromis niloticus 2 Oreochromis niloticus 2 26.6 Kim et al. (2017) Kim et al. (2017) Jauncey (1982) 50 25.5 ANOVA 15 40 19.4 ANOVA 26 20 40 18.5 ANOVA 0.87 70 26 25 40 17.7 ANOVA 0.3 1.14 28 26 FW 45 26.9 ANOVA 6.3 15.6 1.05 23 FW 25 13.6 4 4 7 7 7 7 5 4 4 3 3 3 3 3 0.6 0.0 0.0 0.0 0.0 0.0 3.7 0.8 40.0 6.3 12.2 22.9 38.8 0.5 2.1 1.5 0.6 1.4 4.6 3.8 9.7 21.3 163.5 17.4 33.0 206.0 220.0 10.3 1.02 1.86 1.78 2.27 1.45 2.86 0.72 1.89 1.72 1.68 1.56 2.47 1.34 1.49 29 FW 23.5 0 10 5 FW 26 26 26 26 27 FW FW FW FW FW FW 35 35 35 30.4 28 30.4 32.6 40 30 29 39 30 25 45 No model or ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA Larumbe-Moran et al. (2010) Larumbe-Moran et al. (2010) Larumbe-Moran et al. (2010) Larumbe-Moran et al. (2010) El-Sayed and Teshima (1992) Wang et al. (1985a) 25–45 3 19.5 45.2 1.92 70 27 FW FM–SBM 25–45 3 40.0 64.7 2.29 70 27 FM–SBM SBM–bloodmeal–poultry by-product–FM Casein, gelatine, soya bean, cottonseed and rapeseed meals SBM–casein 25–45 28–36 3 3 2.1 34.5 10.1 889.8 1.72 70 1.37 84 25–45 5 3.8 45.7 18–38 6 216.7 580.5 65 30.8 Reference ANOVA ANOVA ANOVA 28 49 56 112 112 112 30.5 38.1 28.2 Adjustment 21.7 33.5 30.1 15.8 13.9 14.3 21.1 32.9 24.1 17.3 23.6 28.6 19.8 23.5 ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA 35 18.8 ANOVA FW 35 18.8 ANOVA 27 28 FW FW 45 36 20.9 23.5 17.8 ANOVA ANOVA Teshima et al. (1985) Santiago et al. (1982) Santiago et al. (1982) De Silva and Perera (1985) De Silva and Perera (1985) De Silva and Perera (1985) Wang et al. (1985b) Siddiqui et al. (1988) Siddiqui et al. (1988) Jover Cerda et al. (1998) Jover Cerda et al. (1998) Sweilum et al. (2005) Sweilum et al. (2005) Abdel-Tawwab et al. (2010) Abdel-Tawwab et al. (2010) Abdel-Tawwab et al. (2010) Abdel-Tawwab (2012) Hooley et al. (2014) 1.29 56 28.5 FW 35 41.6 Quadratic Kpundeh et al. (2015) 1.36 56 31.5 FW 29.3 Quadratic Liu et al. (2017) 98 98 60 60 180 180 70 58.9 15.6 9 Fish protein requirement meta-analysis Species Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) 6.8 23.0 29.0 3.0 1.29 1.20 1.70 1.37 35 77 42 60 25 21.8 28 SW SW 39 SW 52 50.8 49 25 4.5 46.6 0.92 56 29.5 FW 6 4.2 11.1 1.38 60 27.7 35–60 30–60 25–55 25–55 5 5 4 7 0.1 4.1 0.1 2.4 1.4 10.2 0.3 6.5 0.85 0.85 3.24 1.50 FM–SBM–squid 40–50 3 9.5 45.8 FM–soy concentrate– squid meal FM-based 47–55 3 64.4 37–56 5 35–60 40–55 45–55 40–60 35–65 30–60 41–50 25–40 35–60 30–60 40–65 35–65 30–50 35–65 40–50 35–50 30–40 22–38 25–50 25–40 25–50 25–40 6 5 3 3 5 6 4 4 4 6 6 5 3 6 3 4 3 5 6 4 6 4 Diet type IBW (g) Trophic level Pagrus major Pagrus pagrus Pampus argenteus Pangasianodon hypophthalmus Pangasianodon hypophthalmus Pangasianodon hypophthalmus Parachanna obscura Parachanna obscura Paracheirodon innesi Paralabrax maculatofasciatus Paralabrax maculatofasciatus Paralichthys aestuarius 3.7 3.9 3.3 3.1 FM–casein FM-based FM-based FM-based 37–52 40–65 35–55 20–50 3 6 5 7 1.6 2.8 12.5 0.2 3.1 FM-based 34–46 4 3.1 Casein–gelatine 20–45 3.4 3.4 2.9 4.2 FM–casein FM–casein FM–krill–squid Casein 4.2 4.2 Paralichthys dentatus 4.5 Paralichthys lethostigma Paralichthys lethostigma Paralichthys lethostigma Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Paralichthys olivaceus Pelteobagrus ussuriensis Piaractus mesopotamicus Piaractus mesopotamicus Planiliza haematocheila Planiliza haematocheila Planiliza haematocheila Planiliza haematocheila 3.5 3.5 3.5 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 3.7 2 2 2.5 2.5 2.5 2.5 FM-based FM–casein–gelatine FM–squid meal–krill meal FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM–casein FM-based FM–casein–corn gluten FM–SBM FM–SBM Casein Casein Casein Casein Protein range tested Protein levels tested Species FBW (g) Adjustment Reference 22.7 25.4 25.3 Broken line Quadratic ANOVA 45 36 23.6 ANOVA Takeuchi et al. (1991) Schuchardt et al. (2008) Hossain et al. (2010) Chuapoehuk and Pothisoong (1985) Liu et al. (2011) FW 37.1 24.5 18.7 Quadratic Jayant et al. (2018) 27.9 27.8 25 27 FW FW FW 36 55 50 45 55 40 27.1 24.6 21.5 26.8 ANOVA ANOVA ANOVA ANOVA 1.53 93 24 32.5 45 44.2 22.2 ANOVA 85.9 8.00 56 28.5 37.2 47 11.7 28.6 1.20 56 33 56 25 27.3 ANOVA 24.5 32.9 1.1 0.3 4.1 13.3 5.9 8.1 8.1 13.3 22.7 4.1 3.0 4.1 254.0 3.4 42.1 15.5 1.2 23.2 1.2 23.0 80.4 114.5 10.2 316.0 17.6 89.5 29.9 47.2 59.1 89.5 109.9 18.2 12.7 22.3 440.0 12.8 126.8 57.2 10.3 96.1 10.3 104.8 1.96 84 1.75 60 1.29 42 75 0.97 56 0.93 56 1.13 45 0.98 56 0.86 56 0.93 56 1.08 63 0.95 56 1.37 35 0.95 56 1.18 98 1.22 56 2.34 76 1.11 70 1.43 56 1.77 56 1.43 56 1.59 56 6 32 34 30 30 30 32 SW SW 33 34 33 34 33 SW FW FW FW SW SW SW SW 50 51.52 45 60 46 44 50 35 45 44 45 51.2 50 57.7 45 45 35 27 40 25 40 35 52 62.5 32.3 26.0 31.9 Broken line Broken line ANOVA ANOVA Broken line Broken line ANOVA ANOVA ANOVA Broken line ANOVA Broken line ANOVA Quadratic ANOVA ANOVA ANOVA ANOVA ANOVA ANOVA t-test t-test Kpogue et al. (2013a) Kpogue et al. (2013b) Sealey et al. (2009) Anguas Velez et al. (2000) Alvarez Gonzalez et al. (2001) Gonzalez-Felix et al. (2014) Daniels & Gallagher (2000) Gonzalez et al. (2005) Gao et al. (2005) Alam et al. (2009) Kim et al. (2005) Kim et al. (2005) Kim et al. (2005) Yigit et al. (2004) Kim et al. (2004a) Kim et al. (2004b) Kim et al. (2003) Lee et al. (2002a) Kim et al. (2002) Lee et al. (2000) Kim et al. (2002) Kim et al. (2010) Wang et al. (2013a) Merola (1988) Bicudo et al. (2010) Yoshimatsu et al. (1992) Yoshimatsu et al. (1992) Yoshimatsu et al. (1992) Yoshimatsu et al. (1992) 28 45 84 42 24 29 19.8 18.5 18.5 18.5 20 18 18 23 19.2 21.5 21.7 21.5 15.5 24 26.7 28.7 24 25 24 25 ANOVA 26.7 39 40.2 28.4 56.2 34.5 48.1 34.5 46.2 25.0 28.0 26.9 25.9 22.9 29.9 39.8 33.5 25.9 28.7 31.6 14.8 27.0 16.9 A. Oliva Teles et al. 10 Table 1 (continued) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 (continued) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) 30.7 90.0 15.9 3.8 15.9 14.2 2.2 3.4 63.6 16.1 97.1 172.8 34.5 8.3 34.5 30.6 22.7 28.6 200.6 101.9 0.80 1.30 1.92 1.57 1.92 1.60 1.58 1.30 1.08 56 60 58 49 50 84 197 56 56 60 3 3 1.0 0.8 25.8 3.5 25–50 32–59 26–34 30–40 36–60 26–41 6 6 3 3 7 5 0.9 0.1 2.3 1.7 32.5 1.5 Casein–gelatine 26–41 5 3.9 3.2 FM-based FM-based 30–43 32–52 Rutilus kutum Salmo caspius Salmo salar 3.2 3.5 4.5 FM-based FM–SBM–casein FM-based Salmo salar 4.5 Salmo salar Salmo salar Salmo salar Salmo trutta Salvelinus alpinus Salvelinus alpinus Salvelinus alpinus Salvelinus fontinalis Salvelinus fontinalis Trophic level Protein range tested Platichthys stellatus Platichthys stellatus Plecoglossus altivelis Plecoglossus altivelis Plecoglossus altivelis Pleuronectes platessa Pleuronectes plattessa Polydactylus sexfilis Protonibea diacanthus Pseudoplatystoma reticulatum Pseudoplatystoma sp. Pseudopleuronectes americanus Pseudotropheus acei Pseudotropheus socolofi Pterophyllum scalare Pterophyllum scalare Rachycentron canadum Rhamdia quelen 3.6 3.6 2.8 2.8 2.8 3.2 3.2 3.4 3.5 4.2 FM-based FM-based FM-based FM-based FM-based FM-based Casein FM–casein–gelatine FM-based FM-based 40–50 40–60 30–45 38–52 30–45 20–70 20–70 25–45 36–52 30–55 3 5 4 3 4 6 6 5 5 6 3.6 Casein–gelatine FM-based 40–50 40–50 2.7 3.6 3.6 4 3.9 FM-based FM-based SBM–meat meal Casein FM–casein Casein–gelatine Rhamdia quelen 3.9 Rhamdia quelen Rutilus kutum IBW (g) 17.3 16.1 30 34 15.4 23.5 15 15 26 28.5 27 33 SW SW SW 31 32 FW 45 50 40 38 40 50 70 41 48.6 49.2 0.68 56 1.43 12 27.9 FW SW 45 50 2.9 1.2 3.7 3.6 300.0 12.0 2.43 2.83 2.24 1.54 1.18 1.23 84 70 50 60 56 90 26.7 29 26 27.6 28 29.6 FW FW FW FW 32 FW 35 40 26 30 44.5 37.3 1.5 11.7 1.26 90 29.6 FW 32.6 4 5 0.3 0.5 1.5 1.9 0.95 30 1.85 56 21.5 21.5 FW FW 37 41.6 37–57 45–55 41–55 5 3 4 0.5 6.4 80.0 1.9 12.9 211.0 1.85 56 1.86 56 0.64 63 21.4 14.3 10.2 FW FW FW 46.4 50 55 FM-based 52–64 4 80.0 206.0 0.66 63 10.2 FW 4.5 4.5 4.5 3.4 4.4 4.4 FM-based FM-based FM-based Casein/CPSP FM-based FM-based 30–45 37–52 37–52 38–65 23–55 28–44 3 4 4 7 9 3 336.0 1080.0 2490.0 1.2 2.6 19.0 602.4 2920.0 4950.0 3.8 30.9 45.0 1.10 96 0.94 138 1.04 138 52 0.97 84 56 7.6 11.7 11.7 12.7 11.25 10 4.4 3.3 3.3 FM-based FM-based FM-based 34–54 36–58 36–58 3 12 12 4.6 28.4 29.1 47.4 160.4 144.7 1.01 168 0.74 84 0.79 84 12 14.8 19.4 43.9 31 12.5 24.1 25.6 Adjustment Reference 21.5 31.0 25.4 ANOVA ANOVA ANOVA ANOVA ANOVA Quadratic No model or ANOVA Quadratic Broken line Quadratic Wang et al. (2017) Lee et al. (2006) Furuhashi et al. (2004) Lee et al. (2002b) Furuhashi et al. (2004) Cowey et al. (1972) Cowey et al. (1970) Deng et al. (2011b) Li et al. (2016) Cornelio et al. (2014) 24.4 ANOVA ANOVA Arslan et al. (2013) Hebb et al. (2003) 27.9 ANOVA Broken line ANOVA ANOVA Quadratic Broken line 21.3 Broken line 26.1 21.8 ANOVA Quadratic 22.0 35.2 52.9 Quadratic ANOVA ANOVA 55 49.6 ANOVA 30 25 25 FW FW FW 30 48 42 53 33 27.6 42 16.7 52.4 41.3 FW FW FW 54 50 48 46.2 38.8 Guroy et al. (2012) Royes and Murie (2005) Zuanon et al. (2009) Mohanta et al. (2012) Chou et al. (2001) Meyer and Fracalossi (2004) Meyer and Fracalossi (2004) Salhi et al. (2004) Ebrahimi and Ouraji (2012) Ebrahimi et al. (2013) Ramezani (2009) Grisdale-Helland and Helland (1997) Grisdale-Helland and Helland (1997) Sveier et al. (2000) Einen and Roem (1997) Einen and Roem (1997) Arzel et al. (1995) Gurure et al. (1995) Jobling and Wandsvik (1983) Tabachek (1986) Amin et al. (2014) Amin et al. (2014) 27.5 22.4 30.1 35.8 13 39.9 17.3 19.6 15.9 17.3 13.6 19.0 17.0 15.7 31.0 22.0 21.1 ANOVA ANOVA ANOVA ANOVA Broken line No model or ANOVA ANOVA Broken line Broken line 11 Fish protein requirement meta-analysis FBW (g) Diet type Protein levels tested Species Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Protein Temp Salinity Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Species Trophic level Sander vitreus Sciaenochromis fryeri Sciaenops ocellatus Sciaenops ocellatus 4.5 4.2 3.7 3.7 FM-based FM–SBM FM-based FM–casein 37–58 35–50 35–45 35–55 4 4 3 3 14.0 0.6 2.0 3.5 39.5 3.6 28.6 26.4 70 1.82 84 1.02 56 1.85 56 21 26.5 23.2 24 FW FW 5 5.5 51 38.8 40 35 23.8 Sciaenops ocellatus Scophthalmus maximus 3.7 4.4 FM–SBM Casein–gelatine 32–44 38–70 4 4 50.0 10.0 388.9 29.0 1.01 91 0.57 42 28 18 35 SW 44 69.8 40.9 Scophthalmus maximus Scophthalmus maximus Scophthalmus maximus Scophthalmus maximus Scophthalmus maximus Scophthalmus maximus Scophthalmus maximus Sebastes schlegeli Sebastes schlegeli Sebastes schlegeli Sebastes schlegeli 4.4 4.4 4.4 4.4 4.4 4.4 4.4 3.8 3.8 3.8 3.8 47–64 55–65 29–57 45–55 45–55 45–55 45–54 45–55 35–60 35–60 37–47 5 3 5 3 3 3 5 3 5 5 3 38.2 47.0 89.0 4.5 59.1 209.1 34.5 3.2 7.3 7.3 21.9 89.9 74.5 158.1 43.2 143.3 301.8 100.6 12.4 24.4 24.4 59.3 0.63 0.92 0.92 0.60 0.70 0.75 1.31 1.03 1.15 1.50 1.22 56 25 45 63 63 63 88 56 56 56 140 16.5 19.2 20 18 16.5 11.5 15 20.8 20.5 20.5 13 30.2 17 34 30.5 30.5 30.5 26.5 SW SW SW 34 57 55 49.4 55 55 55 50 50 48.6 48.6 42 Sebastes schlegeli. Sebastes schlegeli. Sebastes schlegeli. Sebastes schlegeli. Seriola dumerili Seriola quinqueradiata Seriola quinqueradiata Siganus canaliculatus Siganus canaliculatus Siganus rivulatus Sigunus guttatus Silurus asotus Sinocyclocheilus grahami Solea senegalensis Solea senegalensis 3.8 3.8 3.8 3.8 4.5 4 4 2.8 2.8 2 2.7 4.4 2.9 3.3 3.3 30–55 30–56 35–60 35–61 42–53 30–71 35–52 27–48 27–49 10–60 25–45 20–40 29–49 43–60 44–59 5 5 5 5 3 4 3 3 3 6 3 3 5 5 4 7.3 7.3 7.3 7.3 51.8 65.0 3.7 2.5 11.5 1.5 0.9 7.7 7.6 11.9 5.4 20.7 23.7 23.9 24.8 169.1 201.0 35.9 13.0 34.7 27.7 7.7 78.0 17.0 33.0 21.5 1.39 1.13 1.10 1.07 1.25 1.26 1.03 1.21 2.72 2.50 1.88 1.15 1.54 1.01 0.78 56 56 56 56 40 28 35 70 70 49 56 66 70 84 84 20.5 20.5 20.5 20.5 28 FW FW FW FW SW FW 22 SW 30.5 39 30.5 39 28 34 28.25 FW 25 FW 20 FW 21 32.5 20 33.5 50.9 49.3 46.2 45.1 47 55 52 48 36 40 45 40 38.6 53 59 Solea solea 3.2 39–57 4 10.3 25.4 0.94 84 20 30.5 Sparus aurata Sparus aurata Sparus aurata Spinibarbus hollandi 3.7 3.7 3.7 3.2 FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM-based FM–casein FM–meat meal–SBM– bloodmeal–feather meal FM-based FM-based FM-based FM-based FM-based FM-based FM–casein FM-based FM-based FM-based FM–casein–gelatine FM-based FM-based FM–wheat gluten FM–soy protein concentrate FM–soy protein concentrate FM-based FM-based Casein FM-based 35–65 42–58 10–60 13–55 7 4 6 8 0.8 5.3 2.6 8.5 3.3 28.0 18.0 19.6 1.56 1.61 2.40 1.66 22.1 21.7 21 25 36.6 36.6 34.5 FW 54 57 112 70 27.4 Adjustment ANOVA Broken line ANOVA ANOVA Reference Barrows et al. (1988) Gullu et al. (2008) Serrano et al. (1992) Daniels and Robinson (1986) Thoman et al. (1999) Cacerez-Martinez et al. (1984) Liu et al. (2015) Cho et al. (2005) Lee et al. (2003) Liu et al. (2014) Liu et al. (2014) Liu et al. (2014) Li et al. (2011) Cho et al. (2015) Kim et al. (2001a) Kim et al. (2001b) Lee et al. (2002c) 27.4 33.1 ANOVA ANOVA 27.8 33.3 32.9 25.3 25.3 28 27.0 29.1 29.1 19.3 Broken line ANOVA Broken line ANOVA ANOVA ANOVA ANOVA ANOVA Broken line Broken line ANOVA 41.1 32.7 35.9 29 32.3 28 35.8 29.9 24.8 21.6 24.0 35.5 Broken line Broken line Broken line Broken line ANOVA No model or ANOVA 60.5 30.7 16.2 23.1 27.4 33 35.1 28.2 21.2 20.0 28.1 21.6 25.4 22.2 26.7 ANOVA ANOVA ANOVA ANOVA ANOVA Broken line ANOVA ANOVA Kim et al. (2004a) Kim et al. (2004b) Kim et al. (2004a) Kim et al. (2004b) Takakuwa et al. (2006) Takeda et al. (1975) Takeuchi et al. (1992) Yousif et al. (1996) Yousif et al. (1996) El-Dakar et al. (2011) Parazo (1990) Kim et al. (2012) Deng et al. (2014) Rema et al. (2008) Mandrioli et al. (2012) 57 33.7 24.8 ANOVA Gatta et al. (2011) 55 52 40 32.7 23.6 24 27.1 24.4 ANOVA ANOVA No model or ANOVA Broken line Vergara et al. (1996a) Vergara et al. (1996b) Sabaut and Luquet (1973) Yang et al. (2003) 31.6 33.9 17.9 A. Oliva Teles et al. 12 Table 1 (continued) Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Table 1 (continued) Diet type Protein range tested Protein levels tested IBW (g) FBW (g) FCR Protein Protein Temp Salinity Protein Trial intake (&) requirement retention duration (°C) (g kWG 1)/ (% PI) (%) (days) Energy intake (kJ kg 1 WG) Adjustment Reference Trophic level Stephanolepis cirrhifer Symphysodon aequifasciata Tachysurus fulvidraco Takifugu obscurus Takifugu obscurus Takifugu rubripes Tinca tinca 2.8 3.3 FM-based FM-based 35–50 35–55 4 5 3.2 4.5 4.3 21.0 1.03 56 2.26 84 18.8 FW FW 45 50.1 33.6 23.2 23.0 ANOVA Quadratic Khosravi and Lee (2017) Chong et al. (2000) 3.5 3.4 3.4 3.6 3.7 FM-based FM-based FM-based Casein FM-based 22–52 34–54 30–60 35–55 40–60 4 6 6 5 6 0.9 12.4 18.5 17.0 0.4 5.5 44.3 30.0 83.1 2.1 0.72 1.62 4.06 1.30 1.61 42 70 84 56 90 25 30 20 20 24 FW 4 33 33 FW 42 37 50 41 52.7 41.4 19.3 18.5 25.0 23.6 27.2 ANOVA Quadratic Broken line ANOVA Quadratic Tor putitora Tor tambroides Tor tambroides Totoaba macdonaldi Totoaba macdonaldi 2.9 2 2 4.1 4.1 25–50 30–50 30–40 43–52 47–55 6 5 3 3 3 12.2 20.9 0.7 12.2 74.2 96.9 54.3 14.9 84.0 197.0 1.20 2.13 1.96 1.43 2.20 120 56 84 70 56 29.6 28 28 25 28.4 FW FW FW SW 38 45.3 48 35 52 47 20.8 25.5 18.2 25.6 Broken line Quadratic ANOVA ANOVA ANOVA Trachinotus carolinus Trachinotus carolinus Trachinotus ovatus 3.5 3.5 3.7 30–45 30–45 33–49 4 4 5 4.5 4.5 4.7 30.7 5.7 44.2 1.94 49 1.94 49 1.18 56 30.8 30.8 27.2 35 35 26 45 45 45 19.7 51.4 30.9 Umbrina cirrosa Verasper variegatus Verasper variegatus Vieja melanura 3.4 3.5 3.5 2.6 FM-based FM-based FM-based FM–SBM–gelatine Fm–soy concentrate– squid meal FM–SBM FM–SBM FM–SBM–rapeseed meal– yeast FM-based FM–krill meal–bloodmeal FM–casein FM-based Kim and Lee (2005) Ye et al. (2017a) Bai et al. (1999) Kim and Lee (2009) Gonzalez-Rodriguez et al. (2014) Islam and Tanaka (2004) Ng et al. (2008) Ng et al. (2008) Rueda-Lopez et al. (2011) Minjarez-Osorio et al. (2012) Lazo et al. (1998) Lazo et al. (1998) Wang et al. (2013b) 35–59 41–56 40–50 30–55 5 3 3 6 86.3 50.4 93.0 0.3 144.6 98.7 173.7 2.3 1.91 1.44 1.07 2.19 18.7 19.6 18.5 28 38 32.5 35 FW 47 56.7 50 40.8 19.8 70 60 83 90 20.6 29.1 24.3 18.4 26.8 23.1 ANOVA ANOVA ANOVA 22.4 35.8 25.0 26.4 ANOVA ANOVA ANOVA Broken line Akpinar et al. (2012) Yagi et al. (2005) Lv et al. (2015) Olvera-Novoa and Gasca Leyva (1996) 13 Fish protein requirement meta-analysis Species A. Oliva Teles et al. Studies considered provide dietary protein requirements of 150 species. Most studies were of relatively short duration, lasting from 30 to 60 days (152 studies) or up to 90 days (115 studies), and these represented 81% of all studies. Only 20 studies lasted more than 120 days. Regarding weight gain, fish did not double their initial weight in 13% of the studies; in 58% of the studies, the final weight was 2–5 times the initial weight, and in 29% of the studies, the fish final weight was more than five times the initial weight. Most dietary protein requirement estimations used fish weight gain as the response criteria. Only six studies estimated dietary protein requirement also based on N retention, and six other studies did not even provide a clear indication of the response criteria used. Thus, in this study, only dietary protein requirement based on weight gain responses was considered. Statistical analysis of data The statistical method used for dietary requirement estimation in dose–response studies may considerably affect the estimated value of the requirement (Baker 1986; Shearer 2000; Bureau & Encarnacao 2006; Hernandez-Llamas 2009). It is generally recognized that analysis of variance (ANOVA) is not adequate for data evaluation in dose–response studies, as it compares particular (discrete) values of nutrient levels, whereas the response in dose–response studies is a continuous rather than a discrete variable, and it is better described by an equation (Baker 1986; Morris 1999; Pesti et al. 2009; Gous 2010). Linear broken-line model (LBM) is also not considered adequate, as in this model response abruptly changes at the plateau level, and therefore, it is more adequate for evaluating responses of individuals rather than populations (Hernandez-Llamas 2009). Non-linear models are considered to depict more correctly biological responses of populations (Shearer 2000; Pesti et al. 2009). Both ANOVA and LBM frequently underestimated requirements when compared to curvilinear regression models (Baker 1986; Robbins et al. 1979; Robbins et al. 2006; Shearer 2000; Encarnacß~ao et al. 2004; Hernandez-Llamas 2009; NRC 2011). Nonetheless, besides dependence on the model used, the range of nutrient concentration used in the dose–response studies is also important in nutrient requirement estimations (Rodehutscord & Pack 1999). Indeed, Rodehutscord and Pack (1999) concluded that the smaller the range of nutrient levels tested, the lesser were the differences between non-linear models, and therefore, no recommendation was given regarding the most adequate mathematical model to apply. Although ANOVA is not a correct statistical analysis for quantitative data analysis based on multiple levels of an independent variable (Shearer 2000; NRC 2011), it was the 14 statistical analysis used for data evaluation in most of the studies analysed (66% of all studies). The broken-line model was used in 18.5%, and the quadratic model in 11.9% of the studies. A curvilinear model was used in just four studies. Studies using t-test (2 studies) or even no model (6 studies) for data analysis were also found in the literature. This confirms the recent conclusion that ANOVA and LBM are the most frequent methods used to estimate nutrient requirements in aquaculture species (Hernandez-Llamas 2009). However, as these methods are not the most adequate for dose–response study evaluation, a re-evaluation of several of the proposed protein requirement values should be considered, as actual values may be underestimated. Dietary protein levels tested The number of treatment levels to test in dose–response studies is not standardized, though it must be equal or greater than the number of parameters to be estimated using the model used to fit the data. However, increasing the number of degrees of freedom by increasing the number of treatments and replicates further improves the model fitting robustness (Hernandez-Llamas 2009). Further, the more points and wider the range of treatment levels, the better will be the model adjusted to the data (Gous 2010). Baker (1986) on a critical appraisal of the problems and pitfalls of experiments designed to evaluate dietary requirements of nutrients in animal studies stated that in bioavailability assays, a minimum of three levels of the nutrient should be used and that the significance of differences between any of two adjacent points is nearly meaningless. The author further advanced that a minimum of four levels, and preferably six or more levels, are required in nutrient requirement studies to allow fitting the data to a descriptive response model. As a rule of thumb, Cowey (1992) recommended that six or more treatment levels of a nutrient should be used to obtain a satisfactory dose–response curve. In this review, we considered studies with at least three dietary protein levels, corresponding to 24% of all studies considered. The other studies included 4 (23%), 5 (24%), and 6 or higher (29%) dietary protein levels. Overall, 21 studies used 7 dietary protein levels, and 16 studies used more than 7 dietary protein levels. Thus, almost half of the studies considered did not include enough nutrient levels to allow an adequate application of a non-linear model, thus explaining why ANOVA was the statistical analysis used in most of the studies. Interestingly, among studies that used five or more treatment levels, ANOVA and LBM were still the most used methods for data evaluation (77% of the studies), while quadratic and curvilinear models were used in just 23% of these studies. In addition, some studies Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Fish protein requirement meta-analysis failed to include dietary protein levels high or low enough to produce maximum or minimum responses, and therefore, the recommended dietary protein level might well be beyond the recommended value. Dietary protein sources It is not surprising that fishmeal has been used as the major protein source in fish diets, particularly for carnivorous species. Indeed, fishmeal has a high protein content, has an EAA profile similar to that of the ideal protein for different fish species, is rich in taurine, is well digested and is highly palatable (Barrows et al. 2008; Tacon & Metian 2008; Oliva-Teles et al. 2015). Other protein-rich feedstuffs are usually not as adequate as fishmeal to be used as the only dietary protein source, due to lower digestibility, inadequate amino acid profile, unpalatability or presence of antinutritional factors. This is particularly relevant in the case of plant proteins, the most abundant and economical protein sources (Gatlin et al. 2007; Tacon et al. 2009; Bowyer et al. 2013; Oliva-Teles et al. 2015). The first studies on dietary protein requirements in fish used mixtures of casein, gelatine and crystalline amino acids to provide a dietary amino acid profile similar to the whole egg protein (De Long et al. 1958). However, the composition of the product being synthesized (fish carcass) seems a better indication of the most adequate dietary amino acid profile (Cowey & Luquet 1983). Moreover, as fish carcasses are mainly composed of muscle, and muscle amino acid composition is not very different between species (NRC 1993), it turns out that fishmeal has one of the most adequate ideal protein amino acid profile for most fish species (Peres & Oliva-Teles 2007). Thus, it is not surprising that most studies on dietary protein requirements used fishmeal as the only protein source (49.4% of all studies) or included fishmeal as a dietary protein source (76.6%). Overall, 15% of the studies used casein or casein– gelatine as dietary protein sources, and only eight studies used neither fishmeal nor casein as dietary protein sources. Dietary protein requirements Dietary protein requirements in higher animals are usually expressed in units of protein required per kg body weight per day, while in fish, protein requirement is traditionally expressed as a percentage of the diet. This is perhaps because accurate feed intake measurement in fish is sometimes difficult and daily requirements are affected by water temperature, making it more difficult to express requirements on a daily basis per unit of body weight. Nevertheless, estimation of both protein and energy requirements in fish based on a factorial approach has been proposed. This would allow to estimate requirements based on weight gain Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd per unit of time and whole-body protein and energy contents (Cho & Bureau 1998; Bureau et al. 2002; Booth et al. 2007, 2010; Glencross et al. 2011; Glencross & Bermudes 2012; Jauralde et al. 2016; Lupatsch et al. 1998, 2001, 2003; Lupatsch & Kissil 2005; Pirozzi et al. 2010a,b; Tien et al. 2016; Trung et al. 2011). Available data on the dietary protein requirement of fish are presented in Table 1. When a protein range instead of a defined value was indicated as the dietary protein requirement in the original study, we used the lower value as the dietary protein requirement. In the present study, data on dietary protein requirement were obtained for 150 species. Excluded from this compilation were 17 studies with hybrid fish. Dietary protein requirement data were available in just one study for 95 species, in 2 studies for 29 species, in 3 studies for 15 species, in 4 studies for 9 species, while 11 species were evaluated in 5 or more studies. The species with more data available on dietary protein requirements were Oreochromis niloticus (26 studies), Paralichthys olivaceus (12 studies), Dicentrarchus labrax and Oncorhynchus mykiss (9 studies each), Carassius auratus and Sebastes schlegeli (8 studies each), Scophthalmus maximus (7 studies), Clarias gariepinus and Cyprinus carpio (6 studies each) and Colossoma macropomum and Salmo salar (5 studies each). Dietary protein requirements in the different studies ranged from 24% to 62%, with an average of 42%. A dietary protein requirement of 70% was indicated in one study for Scophthalmus maximus and for Pleuronectes platessa. For both species, there are however other studies available referring lower dietary protein requirements, suggesting that these extremely high values should be considered with caution. Fish are considered efficient converters of dietary protein into body tissues (Cowey 1995; Bene et al. 2015), and retention efficiencies of 30–50% are to be expected. However, dietary protein retention range differs considerably between species (Hall et al. 2011; Boyd & McNevin 2015). For instance, while for catfish and tilapia whole-body protein recovery is circa 26%, and for salmon is as high as 43%. Data on protein retention (as a percentage of protein intake) were only available for 152 studies. Differences in protein retention between studies are quite high, with values ranging between 12.5% and 65%. Protein retention (% protein intake) between 20 and 40% was found in most of the studies (71%), while a value higher than 40% was found in 21% of the studies, and a value lower than 20% was obtained in 8% of the studies. The high discrepancy of values of protein retention, as a percentage of protein intake, may be related to the relatively low growth performance of the animals or inaccuracies in feed intake estimation, and make these estimations somehow unreliable. 15 A. Oliva Teles et al. 100 y = 0.0117x + 42.368 R2 = 0.0033 Protein requirement (%) 90 80 70 60 50 40 30 20 10 0 0 50 100 150 200 250 300 Initial body weight (g) Figure 1 Dietary protein requirement (% of the diet) according to fish initial weight (g). Fish weight Dietary protein requirement of fish has been mainly estimated for juveniles and on-growing fish, with very few information being available for all life stages of a given species (Jobling 2016). Broodstock and larval nutrition are poorly studied in terms of dietary protein requirements, as well as of all nutritional requirements in general (Izquierdo & Fernandez Palacios 1997; Izquierdo et al. 2001; Watanabe 1985; Watanabe & Kiron 1994; Conceicß~ao et al. 2011; Jobling 2016). Data of the studies performed with fish smaller than 100 g (326 studies; 97% of total studies) do not show a significant correlation (P = 0.088) between initial fish weight (g) and dietary protein requirements (R2 = 0.003; Fig. 1). Within a single species, although in some cases available data indicate a trend for a decrease in dietary protein requirement with fish weight, this trend is usually not statistically significant, as can be seen in Figure 2 for Oreochromis niloticus (25 studies) and for Paralichthys olivaceus (11 studies). Only 17 studies on dietary protein requirement compared fish with more than one initial body weight (IBW). 60 y = –0.1711x + 37.209 R² = 0.141 50 40 30 20 10 0 0 10 20 30 40 Initial fish weight (g) 16 Trophic level It was not possible to find the trophic level of three species in FISHBASE (Pseudoplatystoma sp., Pseudotropheus acei and Menidia estor). Overall, studies were performed with species belonging to trophic levels ranging from 2.0 to 4.7. Of these, 93 studies were performed with fish belonging to Paralichthys olivaceus 50 Dietary protein requirement (%) Dietary protein requirement (%) Oreochromis niloticus Most studies were performed with fish of initial body weights comprised between 1 and 10 g (144 studies), or fish smaller than 1 g (53 studies), overall representing 58.6% of the studies. Only 24 studies were performed with fish weighing more than 100 g (7.1% of the studies), of which 10 studies were performed with fish with an initial weight of more than 300 g (Table 1). Although it is considered that dietary protein requirement decreases with fish size (Page & Andrews 1973; Carter & Houlihan 2001; Wilson 2002; NRC 2011), not all studies provide such evidence. For instance, no differences were observed in protein requirement of Dicentrarchus labrax with IBW of 99 or 160 g (Dias et al. 2003), Chanos chanos with IBW of 0.25 or 4.4 g (Jana et al. 2006), Heterotis niloticus with IBW of 4 or 26 g (Monentcham et al. 2010a), Scophthalmus maximus with IBW of 4, 59 or 209 g (Liu et al. 2014), Colossoma macropomum with IBW of 30 or 96 g (Van der Meer et al. 1995), and Oreochromus niloticus with IBW of 20 or 40 g (Abdel-Tawwab et al. 2010). However, in Oreochromus niloticus dietary protein requirement was higher for fish with IBW of 0.45 g than 20 g (AbdelTawwab et al. 2010), IBW of 0.8 g than 40 g (Siddiqui et al. 1988), or IBW of 6 g than 12 g (Jover Cerda et al. 1998). Another study also indicates different protein requirements of Oreochromis niloticus with IBW of 23 or 38 g (Sweilum et al. 2005). Also in Colossoma macropomum, protein requirement was higher in fish with IBW of 1.48 g than 30 or 96 g (Van der Meer et al. 1995). Protein synthesis efficiency does not seem to change with fish weight (Carter & Houlihan 2001), and therefore, differences in dietary protein requirements with the fish size or life stanzas may not be evident. 70 y = –0.5835x + 52.606 R² = 0.2888 60 50 40 30 20 10 0 0 5 10 15 Initial fish weight (g) 20 25 Figure 2 Dietary protein requirement (% of the diet) of Oreochromys niloticus (n = 25) and Paralichthys olivaceus (n = 11) according to fish initial weight (g). Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd trophic levels ranging from 2.0 to 2.9, 157 studies with fish belonging to trophic levels ranging from 3.0 to 3.9, and 83 studies with fish belonging to trophic levels ranging from 4.0 to 4.7 (Table 1). It is assumed that marine carnivorous species have higher dietary protein requirements compared with omnivorous or freshwater species (Tacon et al. 2010; Bowyer et al. 2013). On the other hand, NRC (2011) refers that carnivorous species retain protein more efficiently than omnivorous species, thus not using amino acids intensively as an energy source. Concurrently, Cowey (1995) refers that fish do not regulate efficiently amino acid catabolism, using it preferably as an energy source. Available data confirm that dietary protein requirement is affected by trophic level (R2 = 0.21, P < 0.001), with dietary protein requirement being lower for fish belonging to lower trophic levels (Fig. 3). On average, dietary protein requirement was 36.1% for fish of trophic level 2; 37.2% for fish of trophic level 2.1–2.9; 43.8% for fish of trophic level 3.0–3.9; and 46.4% for fish of trophic level 4.0–4.7. Water temperature Temperature is the single most important abiotic factor controlling fish growth (Brett 1979). Increasing water temperature is considered to increase feed intake, growth rate, metabolic rate and gastrointestinal transit, but not to increase dietary protein requirement (Tacon & Cowey 1985). The effect of water temperature on dietary protein requirement was scarcely studied, with data available only from five studies (De Long et al. 1958; Hidalgo & Alliot 1988; Degani et al. 1989; Peres & Oliva-Teles 1999; Amin et al. 2014). De Long et al. (1958) concluded dietary protein requirement of Oncorhynchus tshawytscha juveniles was lower at 8.3°C (40%) than at 14.4°C (55%). On the contrary, in Salvelinus fontinalis dietary protein requirement was higher at 15°C (44%) than at 9°C (40%) (Amin y = –0.3545x + 50.865 R² = 0.0628 6 11 16 21 26 31 36 Temperature (ºC) Figure 4 Dietary protein requirement (%) of fish reared at different temperatures. et al. 2014). In Dicentrarchus labrax, dietary protein requirement was not affected by temperature between 15 and 20 °C (Hidalgo & Alliot 1988) or between 18 and 25°C (Peres & Oliva-Teles 1999). Dietary protein requirement was also not affected in Clarias gariepinus reared at 23, 25 or 27°C (Degani et al. 1989) or in Oncorhynchus mykiss juveniles in a temperature range from 9 to 18°C (Slinger et al. 1977; Cho & Slinger 1978 – in NRC 1981). Thus, the limited information available presents contradictory results, which may be species-related or due to the particular experimental conditions. Overall, 23 studies did not provide temperature information and were removed from the calculations requiring temperature data. Several studies did not provide an average temperature but a temperature range, and in these cases, the median temperature within the range was considered. Most of the studies (67.4%; 211 studies) were performed at temperatures between 20 and 30°C, 25.8% of the studies were performed at temperatures between 10 and 20°C, 2.9% of the studies were performed at temperatures higher than 30°C, and 3.8% of the studies were performed at temperatures lower than 10 °C (Table 1). 80 70 60 50 40 30 20 y = 0.1911x + 39.91 R² = 0.1341 90 Protein Requirement (%) y = 4.8414x + 26.192 R² = 0.2081 90 Protein Requirement (%) 100 90 80 70 60 50 40 30 20 10 0 100 100 80 70 60 50 40 30 20 10 10 0 1.5 Protein Requirement (%) Fish protein requirement meta-analysis 0 2 2.5 3 3.5 4 4.5 5 0 5 10 15 20 25 30 35 40 Salinity (‰) Trophic level Figure 3 Dietary protein requirement (%) as function of trophic level. Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Figure 5 Dietary protein requirement (%) of fish reared at different salinities. 17 A. Oliva Teles et al. Data analysis showed that water temperature affected dietary protein requirement (Fig. 4), being observed a decrease in dietary protein requirement with temperature increase (R2 = 0.06, P < 0.001). This may be related to the faster growth of fish at higher temperatures. Under these circumstances, a lower proportion of maintenance protein in relation to that required for growth would have been required, reducing overall dietary protein needs. However, independently of rearing temperature, dietary protein requirement for maintenance in fish is low compared with that for growth (Lupatsch et al. 1998; Fournier et al. 2002; Peres & Oliva-Teles 2005; Coutinho et al. 2016). Although a change in the efficiency of protein or energy utilization with temperature cannot be disregarded (Cowey & Luquet 1983), several studies indicate that the efficiency of protein utilization of fish is not affected by water temperature (Azevedo et al. 1998; Lupatsch et al. 2001; Lupatsch & Kissil 2005). Nevertheless, there is evidence that apparent protein digestibility and energy digestibility (Oliva-Teles & Rodrigues 1993; Peres & Oliva-Teles 1999; Moreira et al. 2008; Lee & Pham 2011) improve with water temperature, thus eventually contributing to a lower dietary protein requirement. In addition, the efficiency of carbohydrate utilization for energy purposes may improve at higher temperatures, thus contributing to spare some protein (Medale et al. 1991, 1999; Hemre et al. 1995; Couto et al. 2008; Enes et al. 2008a,b; Alexander et al. 2011). Overall, these results contribute to explain the trend for a decrease in dietary protein requirements of fish reared at higher temperatures. Water salinity The effect of water salinity on dietary protein requirement was the object of only 3 studies (Zeiton et al. 1973, 1974; De Silva & Perera 1985). Salinity was of minor relevance to the dietary protein requirement of Oncorhynchus mykiss juveniles (Zeiton et al. 1973) and Oncorhynchus kisutch (Zeiton et al. 1974) reared at salinities of 10 and 20&. However, in young Oreochromis niloticus (24 mg initial weight) reared at 0, 5, 10 and 15&, fish fed the optimal dietary protein level grew better at a salinity of 10&, while with higher protein diets, fish grew better in freshwater, though feed conversion efficiency was worst. Of the studies considered in this review, 55% were performed with freshwater fish (186 studies), 30% at salinity higher than 30& and 15% at intermediary salinities (Table 1). When salinity at which the trial was performed was not indicated, median salinity was considered based on the salinity range indicated; when reference was just made do saltwater, a salinity of 35& was assumed. Overall, dietary protein requirement increased with water salinity (R2 = 0.13, P < 0.001; Fig. 5). It might be suspected that marine fish studied usually belong to higher 18 trophic levels than freshwater fish, and this might have biased the effect of salinity on protein requirements. Although a trend for fish species in studies at salinities higher than zero belonged to higher trophic levels, this trend was not statistically significant. Protein requirement per unit of body weight gain Tacon and Cowey (1985) observed an almost linear correlation between daily protein requirement per unit of body weight and growth rate of different fish species and concluded that dietary protein utilization for growth is relatively constant within- and interspecies. These authors further concluded that the dietary protein requirement of fish was not different from that of farm animals when expressed per unit of feed intake or body weight gain. This was also confirmed by Bowen (1987), which concluded that protein retention as percentage of protein intake and weight gain per unit protein intake was similar to that of other vertebrates (mainly farm animals). Thus, if differences between fish and other vertebrates are not significant, it is expected that differences between fish species are also not significant. Data of the present review indicate that daily protein intake (g kg 1 ABW day 1) exponentially decreased with fish weight (Fig. 6) while per unit of weight gain protein intake (R2 = 0.008, P > 0.05; Fig. 7) and protein retention (R2 = 0.015, P > 0.05; Fig. 8) were not affected, averaging around 598 g kg 1 weight gain and 184 g kg 1 weight gain, respectively. This suggests that protein retention efficiency is also not affected by weight gain and averages 31.6% of protein intake. Dietary protein-to-energy ratio As stated above, protein requirements cannot be separated from energy requirements, since protein can be used as an energy source similar to lipids and carbohydrates. Moreover, as fish do not control protein catabolism efficiently, protein tends to be used preferentially as an energy source if provided in excess in the diet or if available non-protein energy sources are low in the diet. Thus, it is particularly relevant that diets have well-balanced protein-to-energy ratios. However, only dietary nutrients and energy that are digested and absorbed are available to the animals (Bureau et al. 2002). Thus, for higher accuracy both dietary protein and energy should preferably be expressed in digestible values (Cho and Kaushik, 1990). Nevertheless, most studies available on dietary protein requirements only provide crude protein and gross energy data, and therefore, available estimations still need to be fine-tuned. Yet, dietary protein requirement studies use high-quality diets, which Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Fish protein requirement meta-analysis Protein intake (g/kgABW/day) 100 10 1 0.01 0.1 10 100 1000 10 000 Weight (g) digestibility of such diets are high and protein-to-energy ratio estimated from the gross diet composition will not be very different from that obtained with digestible values. Of the studies considered in this review, 254 presented data that allowed an estimation of protein intake (g) per unit of energy intake (MJ) required per unit of weight gain, which was not affected by body weight and averaged 24.3 g protein per MJ of energy intake (R = 0.002, P > 0.05; Fig. 9). y = –0.1954x + 597.55 R² = 0.0075 1200 Protein intake (g/kg WG) 1 0.1 Figure 6 Dietary protein intake (g kg 1 ABW day 1) as function of body weight (g). 1400 y = 17.095x –0.207 R² = 0.322 1000 800 600 400 200 0 0 100 200 300 400 500 600 700 800 weight (g) Figure 7 Protein intake (g) per unit of weight gain (g). Protein retention (g/kg weight gain) 350 y = –0.5197x + 183.64 R² = 0.0149 300 250 200 150 100 50 0 0 5 10 15 20 25 30 35 40 45 50 Weight gain (g/kg/day) Figure 8 Protein retention (g kg gain (g kg 1 day 1). 1 weight gain) as function of weight have high nutrient bioavailability, adequate amino acid profile, and no limiting nutrients or energy. Thus, we may assume that both protein digestibility and energy Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Dietary protein requirement and thermal growth coefficient Haskell (1959) first introduced the concept of the thermal unit (TU) of growth, stating that at a constant temperature fish growth in length was constant and that growth of fish was proportional to temperature (for details, see Soderberg 2017). Haskell also predicted that at a certain low temperature growth ceases, and therefore, the TU concept should be applied only within a certain temperature range. Based on this assumption, Haskell (1959) introduced a formula to calculate feeding based on predicted growth (based on TU concept) and estimated feed efficiency. Iwama and Tautz (1981) further developed a model for growth estimation based on W0.33(similar to the length estimation based on fish weight) and temperature that allowed weight prediction or time prediction to reach a certain weight, given a predicted temperature, based on a constant (G). This model was for the first time applied in fish nutrition by Cho (1990) and called thermal-unit growth coefficient (TGC) by Cho (1992). The basis of TGC application for estimation of fish growth performance and its use in bioenergetic models can be found in Cho and Bureau (1998) and Bureau et al. 19 60.00 y = –0.0054x + 24.453 R2 = 0.0015 50.00 40.00 TGC Protein intake (g/kWG)/Energy intake (kJ/Kg WG) A. Oliva Teles et al. 30.00 20.00 10.00 5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 y = 0.0032x + 0.817 R2 = 0.024 0 20 40 60 80 100 120 140 160 180 Weight (g) 0.00 0 50 100 150 200 250 300 350 400 Weight (g) Figure 10 Relation between body weight (g) and thermal growth coefficient (TGC). Figure 9 Protein intake (g k 1 weight gain) per unit of energy intake (kJ kg 1 weight gain) as function of body weight (g). (2002). Briefly, the TGC concept is based on the assumption that the cubic root of daily weight gain of fish (termed daily growth increment, DGI) at a certain rearing temperature is constant and independent of fish weight. Further, within certain temperature limits, DGI per unit of rearing temperature is also constant (TGC). Thus, by eliminating or reducing the effect of fish weight and of rearing temperatures, which are the two main variables affecting weight gain per unit of time, TGC becomes a good tool to compare the growth of fish of a given species of different size/ weight and reared at different water temperatures. TGC is not constant, as it is affected by fish species and, within a given species, by rearing conditions. In addition, TGC is not applicable to the full range of temperature for a given species, as advanced by Haskell (1959). Thus, although simple and flexible, the TGC model should be used with caution, as critically analysed by Jobling (2003). Nevertheless, although the TGC concept seems advantageous for comparison of studies with a single species or even between species, its use in nutritional studies is not yet generalized. Of the 262 studies available (Table 1) with fish smaller than 200 g of initial body weight and that provide data to estimate TGC, the correlation between TGC and body weight was weak (Fig. 10). This seems to indicate that TGC is not very much affected by body weight and does not seem to differ substantially between species. It must be acknowledged that most studies on dietary protein requirements were performed under the most adequate rearing conditions, used high-quality diets and were performed at temperatures within the optimum range for the species. Under these circumstances, it seems that TGC can be transversely applied between fish species, providing a good tool for studies comparison, by smoothing the effects of species, fish size and rearing temperature. Thus, it can be assumed that, independently of fish species, under optimal rearing conditions, dietary protein 20 Estimated protein intake (g) 700 y = 1.2236x R² = 0.9378 600 500 400 300 200 100 0 0 50 100 150 200 250 300 350 400 450 Observed protein intake (g) Figure 11 Correlation between observed and estimated protein intake (g). intake may be calculated from the dietary protein intake per unit weight gain (598 g kg 1 weight gain), and weight gain can be estimated according to the TGC approach. Based on these assumptions, for a certain fish weight and under a defined temperature, dietary protein intake can be calculated according to the following equation: Protein intake (g) ¼ ððIBW0:3333 þ ðTGC=1000 T DÞÞ3 IBWÞ 0:598 where IBW is initial body weight (g), TGC is thermal growth coefficient, T is temperature (°C), and D is the sum of days. By applying this approach, the correlation between observed and estimated dietary protein intake is highly significant (Fig. 11). Conclusions Although data on dietary protein requirement are available for a large number of species, in most cases only one study is Reviews in Aquaculture, 1–33 © 2019 Wiley Publishing Asia Pty Ltd Fish protein requirement meta-analysis available for a given species. Although ANOVA and Linear broken-line model are not recommended for evaluation of dose–response studies, these were the statistical methods used in most of the studies on dietary protein requirements. Overall, the dietary protein requirements of fish range between 24 and 70%, depending on species and life stanza. Dietary protein requirement is directly related to fish trophic level and water salinity, and inversely related to rearing temperature. Dietary protein intake is linearly related to weight gain, but protein retention is not affected, corresponding to 187 g kg 1 weight gain. On average, fish requires a protein intake of 458 g kg 1 weight gain and retains 35% of dietary protein ingested. Acknowledgments A. Couto and P. Enes have a scientific employment contract supported by national funds through FCT (Foundation for Science and Technology). References Abbas G, Siddiqui PJA (2013) The effects of varying dietary protein level on growth, feed conversion, body composition and apparent digestibility coefficient of juvenile mangrove red snapper, Lutjanus argentimaculatus (Forsskal 1775). Aquaculture Research 44: 807–818. 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