Effects of a zero exchange biofloc system on the growth performance and health of Nile tilapia at different stocking densities

Journal Pre-proof Effects of a zero exchange biofloc system on the growth performance and health of Nile tilapia at different stocking densities

Ludson Guimarães Manduca, Marcos Antônio da Silva, Érika Ramos de Alvarenga, Gabriel Francisco de Oliveira Alves, Arthur Francisco de Araújo Fernandes, Anna Facchetti Assumpção, Ana Carolina Cardoso, Suellen Cristina Moreira de Sales, Edgar de Alencar Teixeira, Martinho de Almeida e Silva, Eduardo Maldonado Turra PII:

S0044-8486(19)30167-X

DOI:

https://doi.org/10.1016/j.aquaculture.2020.735064

Reference:

AQUA 735064

To appear in:

aquaculture

Received date:

18 February 2019

Revised date:

31 December 2019

Accepted date:

2 February 2020

Please cite this article as: L.G. Manduca, M.A. da Silva, É.R. de Alvarenga, et al., Effects of a zero exchange biofloc system on the growth performance and health of Nile tilapia at different stocking densities, aquaculture (2019), https://doi.org/10.1016/ j.aquaculture.2020.735064

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© 2019 Published by Elsevier.

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Title: Effects of a zero exchange biofloc system on the growth performance and health of Nile tilapia at different stocking densities

Ludson Guimarães Manduca(1), Marcos Antônio da Silva(1), Érika Ramos de Alvarenga(1), Gabriel Francisco de Oliveira Alves(1), Arthur Francisco de Araújo

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Fernandes(2), Anna Facchetti Assumpção(3), Ana Carolina Cardoso(1), Suellen Cristina Moreira de Sales(1), Edgar de Alencar Teixeira(1), Martinho de Almeida e Silva(1),

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Laboratório de Aquacultura (LAQUA). Escola de Veterinária da Universidade

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(1)

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Eduardo Maldonado Turra(1)

Federal de Minas Gerais. Av. Antônio Carlos. nº 6627. Caixa Postal 567. Campus da

University of Wisconsin – Madison, 470 Animal Science Building 1675,

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(2)

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UFMG. CEP 30123-970. Belo Horizonte. MG – Brazil.

Observatory Dr., Madison, WI 53706, USA.

(3)

University of Wisconsin – Madison, 4345 Veterinary Medicine Building 2015,

Linden Dr., Madison, WI 53706, USA.

* Corresponding author: Phone: 55 31 3409 2190; E-mail: [email protected] Keywords: Oreochromis niloticus, density.

biofloc technology, zero exchange, stocking

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Abstract Biofloc technology (BFT) has recently gained

attention as an environmentally

sustainable production system. In this system, bacteria convert fish waste into microbial biomass (biofloc), improving the water quality in the tank and subsequently resulting in less water use. Information on the stocking density of Nile tilapia using this technology

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remains scarce. This work evaluated the growth performance, survival, gill lesions, body composition, nutritional value of the floc and clinical biochemistry variables of

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Nile tilapia (Oreochromis niloticus) during the grow-out phase (initial body weight

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approximately 100 g) with different stocking densities (20, 40, 60 and 80 fish m-3 ) in zero exchange BFT. The growth performance at stocking densities of 20 and 40

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individuals m-3 was better than that of 60 and 80 individuals m-3 , especially for daily

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weight gain and the survival rate. The best growth performance values were 1.69 g day-1

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for daily weight gain and 1.70 for the feed conversion rate for the 20 and 40 fish m-3 treatments, respectively. The quadratic regression model to stocking density (y = -

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0.0074x² + 0.7665x - 6.8512) revealed 51.79 fish m-3 (13 Kg m-3 ) as the maximum for a zero exchange biofloc.

During the

grow-out phase of Nile tilapia,

there were high levels of settleable solids (≥74 mL L-1 ) and nitrate (≥1.09 g L-1 ) that could explain the low growth performance and changes in the clinical biochemistry variables. Reduction of crude protein in carcasses was observed at the highest densities. However, all of the stocking densities evaluated showed degenerative effects to the gill structure. In conclusion, cultivation of tilapia in zero exchange BFT is optimum at stocking densities close to 13 Kg m-3 .

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1. Introduction For aquatic species production, the biofloc technology (BFT) has recently gained attention as an economic and environmentally sustainable production system. In this system, bacteria convert the fish waste into microbial biomass (biofloc) improving water quality in the tank, resulting in less water use (De Schryver et al., 2008; Avnimelech, 2009; Crab et al., 2012; Luo et al., 2014; Ekasari et al., 2015a, 2015b, 2016; Long et al., 2015; Ahmad et al., 2017, Alvarenga et al., 2018). The produced

tilapia (Azim and Little, 2008; Avnimelech and

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biofloc is rich in nutrients that can be utilized as a food source by filter feeders like Nile Kochba, 2009; Ekasari et al, 2014;

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Silva et al, 2018, 2019). Moreover, the BFT also may act as a source of bioactive

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compounds that improve the defense mechanisms of aquatic animals (Ekasari et al.,

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2015a; Long et al., 2015, Menaga et al, 2019). Although substantial advances have been achieved, BFT is far from being fully developed for tilapia culture, and many questions

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about the better management of this system need to be answered. Especially for the

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grow-out phase, basic information has not been defined to date, such as the suitable

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stocking density and the need for water exchange for the BFT. Stocking density is a key factor in determining the productivity and profitability of commercial fish farms. The definition of a suitable stocking density is essential to judge the economic sustainability of a production system (Rafatnezhad et al., 2008). In general, stocking densities above the optimum for a given system cause water quality reduction, low growth performance and physiological changes (Abdeltawwab et al., 2014; Ni et al., 2014; Qiang et al., 2017; Liu et al., 2018). In BFT, the following question remains: Which stocking density of Nile tilapia could be used in commercial fish farms based on BFT without causing negative effects? According our knowledge, this information is not clear in the literature. Limited studies have evaluated

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different densities in BFT (Widanarni et al., 2012, Lima et al., 2015), especially for the grow-out phase in the zero exchange system. Since the grow-out phase is long, solids and nitrate levels could reach high values that are harmful for the fish. This situation can compromise animal growth, thus zero water exchange in BFT may be impracticable for this production phase. However, this hypothesis has not been tested to date. Therefore, the focus of this study was to evaluate the effects of different stocking densities on water quality, growth performance, body composition, gill morphometry and clinical

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biochemistry of Nile tilapia (Oreochromis niloticus) in a zero exchange biofloc system.

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2. Materials and Methods

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2.1 Location

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The experiment was conducted in a greenhouse at the Aquaculture Laboratory of the Veterinary School of the Federal University of Minas Gerais (Universidade

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Federal de Minas Gerais - UFMG), Brazil. All procedures used in the present study

Fish and experimental conditions

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2.2

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complied with local and/or national animal welfare laws, guidelines and policies.

We used 400 masculinized Nile tilapia (O. niloticus) juveniles with a mean initial weight of 96.8 ± 4.2 g. The study lasted 112 days and followed a completely randomized design with four treatments and four replications for a total of 16 experimental units. Each unit consisted of a 1,000-liter polypropylene tank with a useful volume of 500 liters. The evaluated treatments comprised four different stocking density (20, 40, 60 and 80 animals m-3 ) in the zero exchange biofloc systems, and the salinity was adjusted in the beginning of the trial to 4 g L-1 using NaCl and any adjustment was applied during the trial. Only the water lost by evaporation was replenished weekly. Feed was offered to apparent satiety three times per day (at 8:00

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am, 12:00 pm and 4:00 pm), and leftovers were collected after 15 minutes for evaluation of feed conversion (the leftover feed was collected and stored in a freezer at -18 °C. Subsequently, the leftovers were dried in a ventilated oven at 55 °C and weighed). Commercially extruded feed for tilapia was used with 36% crude protein content (FRIRIBE Nutreco, Brazil). 2.3 Water quality Assessment of dissolved oxygen, pH, temperature and salinity was conducted

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twice a day (at 8:00 am and 4:00 pm) using the multiparameter probe YSI Model 6920 V2® (Yellow Springs Incorporated – YSI, OH, USA). Total ammonia nitrogen (TAN) nitric

nitrogen

(N-NO 2 -) concentrations were measured

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and

trice weekly by

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spectrophotometry according to the methodology generated by UNESCO (1983) and

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Bendschneider and Robinson (1952), respectively. Nitrogen nitrate (N-NO3 -) was quantified at the end of the experiment by the methodology described by Monteiro et al.

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(2003). Alkalinity (CaCO 3 ) and settleable solids (SS) were measured once a week.

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Alkalinity was quantified according to the Standard Method for the Examination of

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water and wastewater (APHA, 1998). SS was measured with 1 L Imhoff cone after sedimentation for 15 minutes.

Dried molasses (50% carbon) was used as an additional source of carbon because it mainly consists of sugars. The amount of molasses added to the system was calculated based on the carbon content of this compound required by the biofloc to neutralize TAN. The carbon input was determined according to Ebeling et al. (2006), employing a C:N ratio of 6:1 based on TAN. For pH maintenance, calcium hydroxide (Ca(OH)2 ) was added when the values were less than 6.0. 2.4 Animal performance and survival

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The performance was evaluated based on the following growth indices: 1) final biomass weight (Kg), calculated using the final number of animals per tank multiplied by the mean weight (Kg); 2) final stocking density (Kg m-³), obtained by dividing the final biomass (Kg) per volume of the tanks in cubic meter (m³); 3) daily weight gain (g), obtained by dividing the individual weight increment (mean final weight - mean initial weight) by the number of days the animals remained in the experiment; 4) feed conversion ratio (FC), obtained using the following formula: FC = Feed intake / ((final

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biomass + weight of dead fish) – initial biomass); Feed intake = weight of feed given weight of uneaten feed; 5) survival, defined as the percentage of number of animals at

Carcass composition

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2.5

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the end of the experiment divided by the initial number of animals.

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At the end of the experiment, two animals from each experimental unit were collected, euthanized, processed and frozen in a freezer at -18 °C for analysis of carcass

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composition. Next, the carcasses were frozen at -40 °C for 48 hours and lyophilized for

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72 hours to eliminate moisture from the samples. After lyophilization, the samples were

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disintegrated in a food processor until the entire sample could pass through a 1-mm sieve.

The carcass composition (dry matter, crude protein, and ether extract) was determined according to the standard methodology of AOAC (2005). The energy content was determined using a PARR 6200 bomb calorimeter (Parr Instrument Company, IL, USA). Analyses were performed at the Animal Nutrition Laboratory of the Veterinary School of UFMG. 2.6

Biofloc Composition

At the end of the experiment, samples of settleable solids (1 L) from each experimental unit were collected. The samples were filtrated to evaluate the biofloc

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nutritional composition. These samples were dried and processed following the same methodology described for carcass composition. 2.7

Gill histology Four animals from each experimental unit (16 per treatment) were euthanized,

and their gills were collected for morphometric analysis. However, due to the mortality and losses in the processing, the following samples were analyzed: 14 individuals from the stocking of 20 fish m-3 , 15 individuals from the stocking of 40 and 60 fish m-3 and

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12 individuals from the stocking of 80 fish m-3 . A central fragment of the second gill arch was immersed in Bouin's fixative for 24 h and then subjected to routine

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histological techniques (i.e., dehydration through a graded series of ethanol, cleaning in

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xylol, paraffin embedding, tissue sectioning at 5 µm and staining with hematoxylin-

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eosin).

The processed gill slides were analyzed using a binocular microscope at 400x

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magnification for the presence of three types of gill lesion: aneurysm, lamellar fusion

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and epithelial lifting. To classify these lesions, we followed the definitions of Mallatt

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(1985), and 30 fields of vision were necessary for accurate counting per animal. Thus, 1,680 fields were analyzed. The number of each type of lesion in each treatment was determined as the number of lesions per field. In addition, we obtained the number of fish with lesions as a proportion of the number of fish from each treatment. 2.8

Clinical biochemistry

At the end of the experiment, blood samples of four animals from each experimental unit were collected. One to two ml of blood were collected via direct puncture of the caudal vein. At the moment of collection, glucose was measured with the aid of a portable digital blood glucose meter ACCU-CHEK ® Active (Roche Diagnostic Systems, Herts, UK). Then, the blood samples were conditioned in a 2-mL

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Eppendorf tube and centrifuged at 3,000 rpm for 10 minutes to obtain serum. Serum samples were frozen at -20 °C for further analysis. Serum was used to determine the serum levels of albumin, aminotransferase),

total protein,

triglycerides,

AST (aspartate aminotransferase),

cholesterol,

ALT (alanine

total CK (creatine kinase),

chloride, magnesium, phosphorus and calcium using automated biochemical analyzer COBAS MIRA® Plus (Roche Diagnostic Systems, Herts, UK). Serum levels of sodium and potassium were analyzed by flame spectrophotometry technique (Celm FC-280, SP,

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Brazil). 2.9 Statistical analysis

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Multiple linear regression analysis was used to generate equations to describe

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the statistical relationship between stocking densities and response variables. Data

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normality and homogeneity of variances were tested by Shapiro-Wilk and Bartlett tests, respectively. When the data met the assumptions of the parametric test (normality and

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homogeneity of variances), they were subjected to an analysis of variance (ANOVA),

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followed by Tukey test (CV < 10%), Student-Newman-Keuls (SNK) test (CV from 10%

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to 15%) and Duncan test (CV > 15%). Differences were considered significant at p<0.05. For data that did not follow a normal distribution, such as the survival and gill lesion data, we used the Kruskal-Wallis non-parametric test (p<0.05). Fisher Exact test was used to compare the percentage of animals with lesions among the treatments (p<0.05). Statistical analyses were performed using the InfoStat program (Di Rienzo et al., 2015) and R software (R Core Team, 2016). 3. RESULTS 3.1 Water quality With the exception of alkalinity and setteable solids, water quality parameters, such as temperature, dissolved oxygen (DO), pH, salinity, TAN and nitrite, were within

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the recommended range for the tilapia growth phase in all treatments evaluated (Table 1). As expected, DO, pH and alkalinity values decreased at higher densities, while nitrate, nitrite, salinity, settleable solids and TAN exhibited an opposite pattern. An increase in salinity was noted over the experimental period at higher densities, an expected result since the salinity accumulated came from the feed imputed in each tank of each treatment, mainly. Temperature did not differ among densities. Higher densities

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caused a marked increase in nitrate and settleable solid values.

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3.2 Growth performance

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The values and models for the animal performance are presented in Table 2. The fitted models for final individual weight and daily weight gain were linear, while

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biomass and stocking density were quadratic. The maximum points were noted at

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densities of 51.57 and 51.79 fish m-3 , respectively, which corresponds to 13 kg m-3 for fish with average body weight of 250 g. The survival rates of animals in treatments with

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higher densities were lower, especially in densities of 80 fish m-3 , where the survival

Body composition

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3.3

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rate was only 33.75% (p<0.05).

In the present work, the stocking densities partially altered the body composition (Table 3). The crude protein levels of animals reared in 20 fish m-3 were different from those in 40 and 60 fish m-3 but were similar to those reared in 80 fish m-3 . However, the different stocking densities did not alter (p>0.05) dry matter, ether extract or ashes of the fish body composition.

3.4

Biofloc nutritional composition

In general, the nutritional quality of biofloc was very similar among the treatments (Table 4). Dry matter, crude protein and gross energy did not differ among

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the densities. Nevertheless, the biofloc ash percentage at the stocking density of 20 fish m-3 was higher than those from densities of 60 fish m-3 .

3.5

Gill histology

The results of the gill morphometry analysis are shown in Table 5. No differences were noted among the treatments for total or specific lesions (p>0.05). In

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addition, the number of animals with lesions did not differ among treatments (p>0.05).

Clinical biochemistry

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The data and models for the clinical biochemistry are presented in Table 6. In

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general, R-squared values (R2 ) of the regression models were low. The blood serum

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parameters of fish at the stocking density of 20 fish m-3 showed lower levels of glucose, albumin, total protein, triglycerides and cholesterol, suggesting that these animals at this

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time point showed worst nutritional indexes than the other three groups. In addition, the

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60 and 80 fish m-3 groups presented higher albumin and total protein compared with 40 fish m-3 . However, 40 and 60 fish m-3 groups presented higher triglycerides and

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cholesterol levels than the 80 fish m-3 group, taken together these results suggest that the 60 fish m-3 group (corresponding 13.12 kg m-3 ) presented better blood levels of nutritional markers of the four groups. All four groups present normal hepatic function as demonstrated by normal levels of hepatic enzymes (ALT and AST) in addition to normal serum magnesium, phosphorus and potassium levels. The 20 fish m-3 group presented serum chloride and sodium levels within the reference levels but decreased calcium serum. The 40 fish m-3 group presented decreased serum chloride, calcium and sodium levels compared with reference levels. The 60 and 80 fish m-3 also presented reductions in all three electrolytes compared with reference levels, but the calcium levels were higher than the other two groups. The four groups presented lower levels of

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CK compared with reference values. H++owever, the 60 and 80 fish m-3 groups presented increased CK levels compared with the other two groups, suggesting higher muscle metabolism in these two groups than the lower density groups at the end of the experiment. Discussion BFT is an intensive production system with less environmental impact compared

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with other production systems, such as ponds and cages. The main factor for this claim is that water exchange in BFT is minimal or zero, while the stocking densities can be

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higher than those used in the pond system. In the present study, no water exchange was

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applied; thus, only water lost by evaporation was replenished, representing a typical zero exchange system. As expected, the constant input of nutrients (provided by diet,

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molasses and calcium hydroxide) resulted in high proliferation of microorganisms, as

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also described by Ray et al. (2010a), and accumulation of settleable solids.

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Excess solids increased the demand for oxygen, reduced feed consumption, and consumed calcium carbonate, which consequently reduced alkalinity. Some authors also

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described the relation between the high solid levels and the clogging of gills (Rakocy et al., 2004; Hargreaves, 2013). Before this scenario, some control strategies of floc concentration are necessary during the production (Ray et al., 2010b). This work used organic carbon source exclusively when the TAN was greater than or equal to 1 mg L-1 . Preventive addition of carbon to stimulate heterotrophic bacteria has been practiced in BFT (Azim and Little, 2008; Pérez-Fuentes et al., 2016; Liu et al., 2018). Although this strategy promotes lower levels of nitrite and nitrate (Pérez-Fuentes et al., 2016), this practice increases the costs of solid management (Ray and Lotz, 2014; Liu et al., 2018). In the current study, to keep the cost as lower as possible and to prevent hyperstimulation of microorganism proliferation, molasses was added only when the

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ammonia levels were greater than the critical value of 1 mg L-1 . Even with this management, solid accumulation over time was observed, with mean values ranging between 74 mL L-1 to 166 mL L-1 (depending on stocking density), a volume of solids above of those recommended (25-50 mL L-1 ) for tilapia in BFT (Hargreaves, 2013). Thus, our results indicated the need of some additional intervention to control the increase of solids in all stocking densities evaluated in this study with zero water exchange BFT. Other studies with fish and shrimp in BFT also showed the need for

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intervention to control the increase of solids (Azim and Little, 2008; Ray and Lotz, 2014; Luo et al., 2014; Long et al., 2015, Pérez-Fuentes et al. al., 2016). Moreover, in

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studies conducted by Ray et al. (2010a) and Rakocy et al. (2004), the removal of solids

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did not impair the removal of ammonia and nitrite by BFT.

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In this study, we observed an increase in TAN levels at the highest densities, but the concentration of un-ionized ammonia did not exceed 0.1 mg L-1 , which is the level

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considered harmful to tilapia (El-Sayed, 2006). Regarding nitrite, we used salinized

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water (4 g L-1 ) since the beginning of the assay to avoid toxic effects of possible peaks

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of this parameter (Alvarenga et al., 2018). Chloride ions from NaCl reduce the toxicity of nitrite possibly because chloride inhibits nitrite absorption across the gills (Atwood et al., 2001, Yanbo et al., 2006).

It was used a matured biofloc in this assay, which had probably an initial amount of nitrate. A matured biofloc was used to reduce stress and its hard consequences to fish survival and growth caused by the process of biofloc maturation itself (spikes of ammonia and nitrite) (Alves et al., 2017; Alvarenga et al., 2018). In this assay we did not measure this initial amount, but we have already conducted other trials where it was measured. For example, in Silva et al (2019), a recent published paper from our research group, we measured the initial amount of nitrate from matured biofloc used in the assay

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and we obtained approximately 300 mg/L of nitrate concentration. Once there was any water exchange, this amount of initial nitrate probably contributed to the final high nitrate concentration results. The high nitrate values observed in this work reinforce an important role of nitrification in the reduction of TAN in BFT. Corroborating this study, Rakocy et al. (2004), Ebeling et al (2006) and Azim and Little (2008) found that nitrification was dominant in studies using the same system. Liu et al. (2018) compared BFT with and

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without extra addition of organic carbon, and found higher nitrate concentration when the extra addition was not used. In addition, the reduction of alkalinity and dissolved

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oxygen at densities greater than 20 fish per m3 coincided with the higher nitrate

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concentration due to high inorganic carbon and oxygen consumption by nitrifying

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bacteria (Hargreaves, 2006). Besides nitrification, a possible source of N contributing to the high nitrate concentrations is the nitrogen fixation from the atmosphere by

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cyanobacteria (Hargreaves, 1998), a common microorganism in BFT composition (Wei

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et al., 2020; Wei et al., 2016; Luo et al., in press). The nitrate concentration was greater

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than that recommended for tilapia, which may have caused lower growth performance, especially at higher densities. The high nitrate concentrations in the final of grow-out phase of Nile tilapia reared in BFT may have affected feed intake, which is similar to the results reported by Rakocy et al. (2004). According to Monsees et al. (2017), nitrate concentrations greater than 500 mg L-1 result in reduced growth and worse feed conversion and promote the conversion of hemoglobin to meta-hemoglobin in Nile tilapia. A lower growth performance with increased nitrate has also been reported in turbot juveniles (Psetta maxima) (Van Bussel et al., 2012) and zebrafish (Danio rerio) (Pereira et al., 2017).

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In our study, the growth performance was probably affected by the lack of solid removal and high nitrate concentrations. We obtained high mortality and reduction in weight gain and final weight at the highest stocking densities. Corroborating these results, the study conducted by Ray et al. (2010b) showed that the lack of solid removal also reduced the growth performance of Pacific shrimp (Litopenaeus vannamei). In general, our results suggest a stocking density of tilapia in zero exchange BFT of 13 kg m-3 at most for fish with average body weight of 250 g.

Rakocy et al. (2004)

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evaluated two essays of 25 and 29 weeks in 200-m³ tanks with 20 and 25 tilapia m-³ for fish with average body weight of 700 to 900 g and obtained 14.4 and 13.7 kg m-³,

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respectively. The authors described problems to maintain the water quality mainly due

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the accumulation of solids and nitrate even with the daily removal of solids. On the

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other hand, other recent studies in BFT with some intervention to remove solids, as Rakocy et al (2004) have also applied, indicated better final densities between 16.28 and

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26.04 kg m-³ with 70 to 100 individuals per m-³ (Pérez-Fuentes et al., 2016; Liu et al.,

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2018; Pasco et al., 2018). Literature data indicated that high densities (40 kg m³, for

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example) were reached only for Nile tilapia at intermediate growth stages (average body weight approximately 150 g), far from higher harvest weights (> 700g, close to 1 kg of body weight), products expected by many demanding and remunerative tilapia markets like USA and Europe (Rutten et al., 2005), raising the question of whether high densities could be used in the final stage of growth. Regarding floc composition, protein levels (mean = 24.36%) and energy (mean = 12.03 KJ g-1 ) were below the nutritional requirements for tilapia (NRC, 2011). However, wide variation in the composition of the floc is reported by different studies, ranging from 13.20% to 53.5% and 5.85 KJ g-1 to 19.04 KJ g-1 for crude protein and crude energy, respectively (Azim and Little, 2008; Azim et al., 2008; Martins et al.,

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2017; Silva et al., 2018). In this study, we observed a high ash content for all densities (mean = 35.52%). Although the ashes were lower at high densities, this did not reflect changes in the floc protein and energy composition. The high content of ash in BFT has also been noted by other researchers (Martins et al., 2017; Widanarni et al., 2012; Silva et al., 2018). During the stress period, cortisol levels increase and promote changes in the metabolism of proteins, carbohydrates and lipids (Mommsen et al., 1999). As described,

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a reduction in crude protein in the carcass at the highest densities was observed, and the animals were likely mobilizing protein reserves due to the stress conditions (Abdel-

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tawwab et al., 2014; El-Saidy and Hussein, 2015). The regulation of lipid metabolism

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by cortisol is still not well defined in tilapia (Mommses et al., 1999). Some studies have

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shown a reduction in lipid levels with increasing stocking density (Abdel-tawwab et al., 2014; Qi et al., 2016; Refaey et al., 2018), while another showed increasing lipid levels

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as density increases (El-Saidy and Hussein , 2015). In our study, no significant

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stocking densities.

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difference was detected for the lipid content of the Nile tilapia carcass at different

The average of nutritional composition of Nile tilapia reared in biofloc is relatively stable under different conditions. Variations water salinity levels (Alvarenga et al., 2018), crude protein in the diet (Azim and Little, 2008) and oscillation of water quality during the beginning of biofloc formation (Alves et al., 2017) did not affect the body or fillet composition of this species. However, our results indicated that the effect of prolonged exposure to nitrate and solids at high levels possibly caused chronic stress, which was capable of promoting these changes. In the present work, we did not find a significant difference in gill lesions caused by the stocking densities evaluated despite the high levels of mortality, solids and

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nitrate. Corroborating this result, other studies also did not present anomalies in gill structure related to in Nile tilapias reared in biofloc (Azim and Little, 2008; Alvarenga et al., 2018) under different salinities (Alvarenga et al., 2018) and even in high levels of nitrate (Monsees et al., 2017). Due to the low permeability of nitrate by the gills, it is likely that the route of nitrate intoxication occurs in the gastrointestinal tract through the conversion of nitrate to nitrite (Monsees et al., 2017). In the present study, the clinical biochemistry data corroborated this possible

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nitrate intoxication. According Monsees et al. (2017), nitrate intoxication occurs due to a reduction of nitrate to nitrite within the body of tilapia. In its turn, nitrite may cause

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anoxia in fish because it changes hemoglobin to methemoglobin (which does not carry

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oxygen). In fact, the clinical biochemistry parameters showed a tendency to change

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from the lowest density to the others, and a similar pattern was observed for the nitrate concentration. The nitrate concentration at the lowest density was approximately half of

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the concentration obtained for the other densities. Therefore, this result is at least partly

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attributed to a possible imbalance in the blood variables in response to the toxic effects

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of nitrate (possibly converted in nitrite). Corroborating this hypothesis, Jia et al. (2015) showed changes in the variables ionic, glucose and triglycerides in juveniles of turbot (Scophthalmus maximus) exposed to high levels of nitrite. Interestingly, our results of blood mineral concentration also are consistent with hypoxia and nitrite toxicity. In higher densities, we observed higher nitrate concentration, the increase of potassium and calcium and the decrease of chloride blood concentrations. Similar to our results, nitrite toxicity results in hyperkalemia in common carp (Groff and Zinkl, 1999) and trout (Stormer et al., 1996), with a concomitant hypochloremia in carp (Groff and Zinkl, 1999). In addition, hypoxic conditions probably caused by methaemoglobinaemia may explain the hyperkalemia and hypercalcemia caused by a reduction in glomerular

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It is worth noting, the brown-

coloured blood was observed in tilapias, especially in higher densiiy groups, confirming methaemoglobinaemia in these fish. In addition to nitrate intoxication, the changes in blood parameters could be related to chronic stress. Changes in metabolic and hydromineral factors have been indicators of stress in fish (Barton and Iwama, 1991). Upon long-term exposure to extreme conditions, animals lose the ability to maintain homeostasis necessary for

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maintenance and growth (Schreck, 1982). As expected, increased glucose levels were observed when the stocking density increased (El-khaldi, 2010; Kpundeh et al., 2013;

pr

Aketch et al., 2014; Zhang et al., 2017; Refaey et al., 2018). Similarly, others authors

e-

also found increases in triglycerides, cholesterol (Qi et al., 2016; Refaey et al., 2018),

Pr

ALT and AST at higher densities (Kpundeh et al., 2013, Refaey et al., 2018; Wu et al. 2018). These responses have been associated with the increased demand for

al

mobilization of energy reserves by stressed animals (Barton and Iwama, 1991; Abdel-

rn

tawwab, 2012; Qi et al., 2016, Wu et al., 2018). In addition, the increase in total protein

Jo u

levels observed at higher densities might be related to increased activation of the immune response (Hrubec et al., 2000). In conclusion, the production of tilapia in zero exchange BFT is only viable at stocking densities of less than 13 kg m-3 for fish with an average body weight of 250 g. The performance of the animals under this condition was relatively low, probably due to the high solids content and nitrate level. Therefore, systematic management of the solids and nitrate is necessary for the grow-out phase of Nile tilapia reared in BFT. Systematic solid management could involve minimum drainage or clarification. Although the clarification could solve the high solid concentration, it will not reduce the nitrate levels because this nitrogenous waste is highly soluble in water. Strategies to control nitrate

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18

concentrations could include minimum drainage, denitrification and phytoremediation. Thus, more studies should be performed to evaluate the applicability and efficiency of these strategies for the removal of solids and nitrate in different stocking densities of Nile tilapia in the grow-out phase reared in BFT and its impact on the growth performance of this species.

Acknowledgments

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f

This research received support from FAPEMIG (Fundação de Amparo à Pesquisa do Estado de Minas Gerais), CAPES (Coordenação de Aperfeiçoamento de

pr

Pessoal de Nível Superior) and CNPq (Conselho Nacional de Desenvolvimento

Pr

e-

Científico e Tecnológico).

al

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Table 1: Water quality parameters in a zero exchange biofloc system with different densities. Density (fish m-3 )

Variables

20

40

60

80

CV

27.59

28.16

27.68

27.66

1.58

T (8 am)

25.06

25.40

25.02

25.11

1.31

T (4 pm)

30.13

30.92

30.34

30.22

1.86

Dissolved oxygen (mg L-1 )*

5.49a

4.97ab

4.93b

4.88b

5.00

DO (8 am)*

5.87a

5.42ab

5.38b

5.34b

3.92

DO (4 pm)*

5.12a

4.51ab

4.47b

4.42b

6.29

a

b

b

c

1.27

5.93d

1.18

6.58

pH (8 am)*

6.81a

6.44b

pH (4 pm)*

7.05a

6.71b

Alkalinity (mg of CaCO3 L-1 )**

61.95a

43.09b

oo

6.93

6.43

6.28c

6.13

pr

pH*

f

Temperature (°C)

References 27-32I

>4II

6-9II

6.33c

1.40

40.55b

38.50b

13.56

>50III

Settleable solids (mL L-1 )*

74.02c 100.71b 166.31a 153.85a

8.11

25-50IV

Salinity (g L-1 )*

3.94c

Total ammonia nitrogen (mg L-1 )**

0.20c

Pr 4.38b

4.87a

5.17a

3.99

4-8V

0.21c

0.31b

0.58a

12.18

<1I

0.24b

0.25b

0.17b

--

<100I

al

rn 0.55a

Jo u

Un-ionized ammonia (µg L-1 )****

e-

6.58b

Nitrite (mg L-1 )***

0.25b

0.32ab

0.40ab

0.45a

27.90

<8I

Nitrate (g L-1 )***

1.09b

1.86a

1.97a

2.03a

24.20

<0.5VI

* Means with different letters in the same line differ according to ANOVA and Tukey test (p<0.05). ** Means with different letters in the same line differ according to ANOVA and Student-Newman-Keuls tests (p<0.05). *** Means with different letters in the same line differ according to ANOVA and Duncan´s multiple range test (p<0.05). ****Medians with different letters in the same line differ according to the KruskalWallis test (p<0.05). I

El-Sayed (2006). Wedemeyer (1996). III Avnimelech (2009). IV Hargreaves (2013). V Alvarenga et al. (2018). II

Journal Pre-proof

30

VI

Monsees et al. (2017). Table 2: Growth performance of Nile tilapia reared in a zero exchange biofloc system with different densities.

Density (fish m-3 )

Variables 20

40

60

80

CV

97.94

95.40

99.36

94.73

4.58

Final body weight (g)* (1)

287.61a

283.19a

245.70a

201.08b

8.34

Daily weight gain (g)** (2)

1.69a

1.68a

1.31b

0.95c

13.43

Initial body weight (g)*

2,876.13c 5,590.82b 6,561.34a 3,330.53c

Feed intake (g)*(5)

11.18b

2791.39a

Feed conversion ratio(6)

6.66c

12.37

5367.83b

7327.59c

8975.69d

9.20

1.50

1.68

1.70

10.63

100.00a

88.33ab

33.75b

--

e-

1.52

100.00a

Survival rate (%)***

12.36

13.12a

f

5.75c

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Final stocking density (kg m³)**(4)

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Final biomass (g)** (3)

(1)

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*Means with different letters in the same line differ according to ANOVA and Tukey test (p<0.05). **Means with different letters in the same line differ according to ANOVA and StudentNewman-Keuls tests (p<0.05). *** Medians with different letters in the same line differ according to the Kruskal-Wallis test (p<0.05).

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Final body weight = -1.49x + 328.66 R²= 0.71 Daily weight gain = -0.01x + 2.06 R²= 0.70 (3) Final biomass = -3.72x² + 383.26x-3,425.60 R²= 0.88 (4) Final stocking density = -0.01x²+0.77x-6.85 R²=0.88 (5) Feed intake = 102.56x + 987.46 R²=0.94 (6) Feed conversion ratio: The regression model was not significant (p>0.05). (2)

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Table 3: Body composition of Nile tilapia reared in a zero exchange biofloc system with different densities. Density (fish m-3 )

Variables

20

Dry matter (%)

40

92.96

60

93.08

80

93.31

b

93.51

0.59

Crude protein (%)*

51.89

a

48.95

Ether extract (%)

20.59

21.83

24.14

24.52

7.90

Ash (%)

15.04

14.43

15.40

14.69

9.54

47.16

b

CV

49.19

ab

3.36

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*Means with different letters in the same line differ according to ANOVA and Tukey test (p<0.05).

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Table 4: Biofloc’s nutritional value based on dry matter samples in a zero exchange biofloc system with different densities. Density (fish m-3 )

20

40

60

80

CV

e-

Variables

94.46

94.16

94.10

94.00

0.96

Crude protein (%)

22.52

22.24

26.35

26.34

12.73

37.28a

36.60ab

33.62b

34.59ab

4.88

11.41

11.77

12.52

12.43

5.90

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Dry matter (%)

Ash (%)*

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Gross energy (KJ g-1 )

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*Means with different letters in the same line differ according to ANOVA and Tukey tests (p<0.05).

Variables

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Table 5: Proportion lesion gill of Nile tilapia cultivated in a zero exchange biofloc system with different stocking densities. Density (fish m-3 ) 20

40

60

80

Number of animals

14

15

15

12

Fields analyzed

420

450

450

360

Total of animals with lesion (%)**

50.00

46.67

53.33

50.00

Number of total of lesion/field*

0.02

0.00

0.07

0.05

Number of epithelium lifting/field*

0.00

0.00

0.00

0.00

Number of fusing of gill lamellae/field*

0.00

0.00

0.00

0.00

Number of gill aneurysm/field*

0.00

0.00

0.00

0.00

* Medians did not differ according to Kruskal-Wallis test (p>0.05). **Frequencies did not differ according to Fisher Exact test (p>0.05).

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Table 6: Biochemical variables of tilapias cultivated in a zero exchange biofloc system with different densities. Density (fish m-3 ) Variables 20 40 60 80 CV 40.69a

52.94b

59.06b

73.00c

12.68

Albumin (g dL-1 )*(2)

0.64b

0.80a

0.91a

0.86a

8.33

Total protein (g dL-1 )*(3)

3.54b

4.08ab

4.52a

4.41a

7.78

Triglyceride (mg dL-1 )***

197.66a

284.39a

318.49a

219.00a

42.81

Cholesterol (mg dL-1 )***(4)

175.80b

302.26a

290.78a

283.20a

22.38

Magnesium (mg dL-1 )***(5)

4.23a

4.05a

3.62ab

2.54b

21.21

Phosphorus (mg dL-1 )**

10.06a

8.55a

8.70a

19.42

9.88

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Calcium (mg dL )**

(6)

b

9.92

166.04a

Chloride (mEq L-1 )*(7)

115.39a 1.79b

ALT (U L-1 )****

6.34a

12.50

a

12.19

a

10.90

98.57a

127.19a

45.05

93.36b

77.36c

74.66c

7.91

3.39a

3.66a

3.92a

32.13

20.81a

19.93a

14.03a

59.63

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Potassium (mEq L-1 )***(8)

9.56a

73.91a

e-

Sodium (mEq L-1 )****

b

pr

-1

f

Glucose (mg dL-1 )**(1)

33.62a

32.78a

39.62a

60.65a

47.09

CK (U L-1 )***(9)

76.01b

91.15ab

150.42a

232.58a

54.89

al

AST (U L-1 ) *****

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*Means with different letters in the same line differ according to ANOVA and Tukey tests (p<0.05). **Means with different letters in the same line differ according to ANOVA and Student-NewmanKeuls tests (p<0.05). ***Means with different letters in the same line differ according to ANOVA and Duncan tests (p<0.05). **** Means with the same letters in the same line did not differ according to ANOVA (p<0.05). ***** Medians with different letters in the same line differ according to the KruskalWallis test (p<0.05). (1)

ln(Glucose) = 0.01x + 3.55 R²= 0.45 (Natural logarithm transformation of Glucose data was used to address the problem of lack of normality in error terms) (2)

Albumin = - 0.00013x² + 0.02x + 0.35 R²= 0.70

(3)

Total protein = 0.02x + 3.37 R²= 0.49

(4)

Cholesterol = - 0.08x² + 9.93x R²= 0.37

(5)

Magnesium = - 0.03x + 4.98 R²= 0.39

(6)

Calcium = 0.05x + 8.75 R²= 0.39

(7)

Chloride = 0.01x² - 1.90x + 148.91 R²= 0.85

(8)

Potassium = 0.03x + 1.53 R²= 0.33

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al

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CK= 5.83x R²= 0.42

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(9)

33

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Ludson Manduca – data analysis, interpretation of data and article preparation Eduardo Maldonado Turra — experimental interpretation of data and article preparation.

design,

data

collection,

Érika Ramos de Alvarenga — data collection, interpratation of data and article preparation. Gabriel Francisco de Oliveira Alves – data collection and article preparation Arthur Francisco Araújo Fernandes - data collection and article preparation Ana Carolina Cardoso – data collection and article preparation Marcos Antonio da Silva - data collection, interpratation of data and article preparation.

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Anna Facchetti Assumpção - data collection and article preparation Suellen Cristina Moreira de Sales - data collection and article preparation

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Edgar de Alencar Teixeira - data collection and article preparation.

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rn

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Pr

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Martinho de Almeida e Silva - data collection and article preparation.

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Federal University of Minas Gerais, December 29 th , 2019.

CONFLICT OF INTEREST STATEMENT

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Dear Dr. Jian Qin,

Manuscript title: “Effects of a zero exchange biofloc system on the growth

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performance and health of Nile tilapia at different stocking densities”

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Sincerely yours,

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My co-authors and I certify that we have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Eduardo Maldonado Turra

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Highlights of the manuscript 1) High densities of Nile tilapia in BFT with zero water exchange are not recommended for the grow-out phase. 2) Nitrate and solid accumulation in BFT with zero water exchange reduce the growth performance of Nile tilapia in the grow-out phase. 3) Blood biochemistry variables and crude protein in carcasses were changed in Nile tilapia

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e-

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reared at higher densities in BFT with zero water exchange.