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Hematological analysis and relative condition factor in naturally parasitized Nile tilapia.

INTRODUCTION

Aquaculture currently accounts for half of all fish for human consumption in the world, reaching a record in 2014, with per capita consumption of 20 kg/inhabitant/year (FAO, 2016). The preference for fish comes from several factors such as nutritional quality (rich in proteins and polyunsaturated fatty acids), sensory (pleasant and mild flavor), economic and convenience, presenting the potential for the market (MPA, 2015). In this context, Nile tilapia (Oreochromis niloticus) has characteristics favorable for culture and consumption (Khaw et al., 2012) and is widely marketed worldwide (Fitzsimmons et al., 2011). Nevertheless, it is the second most widely cultivated fish species in the world and the first in Brazil (Vicente et al., 2014).

With the intensification of culture system, a favorable environment for epizootic outbreaks is created, due to several factors that contribute to the onset of diseases (Tavares-Dias et al., 2009). Parasitic diseases are a limiting factor in fish production. Also, lesions caused by parasites serve as gateways for secondary infections (Takemoto et al., 2013; Valladao et al., 2014). Some studies suggest that parasites are also vectors of other pathogens, which can lead to acute mortality of fish (Xu et al., 2012; Pilloux et al., 2015). Ectoparasites are common in tilapia culture and have been reported by several authors (Ghiraldelli et al., 2006a; Jeronimo et al., 2011; Tavares-Dias et al., 2013; Nunes et al., 2016) and according to Moraes & Martins (2004) are directly related to water quality and animal management.

Hematological analysis is a diagnostic tool that has been used in fish studies and shows normal and pathological equilibrium conditions (Azevedo et al., 2006). Blood parameters can be used as indicators to monitor the degree of fish health, effectively identifying responses to breeding challenges, such as the stress that the environment and pathogens cause to fish (Tavares-Dias et al., 2009; Ranzani-Paiva et al., 2013). Tavares-Dias et al. (2002) evaluating Nile tilapia from a fishery located in southeastern Brazil have observed that the parasitism by Ichthyophthirius multifiliis Fouquet, 1876 (Protozoa: Ciliophora) and Saprolegnia sp. caused anemia and an increase in the percentage of neutrophils and monocytes in fish. On the other hand, Ranzani-Paiva et al. (2005) and Ghiraldelli et al. (2006b) in parasitological studies with Nile tilapia originating respectively from cultures and dam, did not observe significant changes in hematological variables, a fact attributed to low parasite intensity. The authors concluded that the fish were in good health.

Another commonly used parameter to determine fish welfare is the relative condition factor (Kn), measured by the relationship between the observed weight and the expected weight for a given length (Guidelli et al., 2009). It is expected that, under normal conditions, Kn is equal to 1, but it is known that it can be influenced by numerous factors such as nutrition, contamination and parasites (Yamada et al., 2008). Analyzing the relative condition factor (Kn), Ranzani-Paiva et al. (2000) and Tavares-Dias et al. (2002) have reported that the parasites did not significantly affect the health condition of the hosts. In contrast, Singhal et al. (1990) found that high infestation by Argulus indicus Weber, 1892 (Crustacea: Branchyura) and infection by Saprolegnia sp. significantly suppressed the growth of Cyprinus carpio. Tavares-Dias et al. (2000) reported that high parasite infection reduced welfare in O. niloticus, Leporinus macrocephalus and Piaractus mesopotamicus, which may retard fish growth and cause damage to the producer in different culture systems.

Although Nile tilapia is one of the most cultured and studied fish in the world, there are few parasitological studies associated with hematological characteristics and relative condition factor in this species. Thus, this study aimed to evaluate the health status through the hematological profile and the relative condition factor in Nile tilapia naturally parasitized in fish farms from southern Brazil.

MATERIALS AND METHODS

Ethics statement

The procedures adopted for this study were approved by the Committee on Ethics in the Use of Animals of the Federal University of Santa Catarina-CEUA N PP00928.

Study area

Adult tilapia from 12 fish farms were collected, covering four regions of the State of Santa Catarina: north, south, Itajai valley and west, with three fish farms per region. In each, 20 specimens were studied, totaling 240 fish.

During the year 2015, punctual collections were carried out in each of the 12 fish farms, located in the cities of Braco do Norte (28[degrees]16'30"S, 49[degrees]09'57"W) in the south of the state, Joinville (26[degrees]18'14"S, 48[degrees]50' 45"W) in the northern region, Gaspar (26[degrees]55'51"S, 48[degrees]57'32"W) in the Itajai Valley, and three other fish farms west of Santa Catarina, in the cities of Caxambu do Sul (27[degrees]09'39"S, 52[degrees]52'44"W), Pinhalzinho (26[degrees]0'52"S, 52[degrees]59'31"W) and Barra Bonita (26[degrees]39'14"S, 53[degrees]26'24"W).

Physical and chemical parameters of water

During the sampling, the following water quality parameters were evaluated: transparency with Secchi disk, temperature, pH and dissolved oxygen with the aid of multiparameter (model HI 9828 - Hanna instruments), and ammonia with commercial Hanna[R] kit.

Hematological analysis

After fish capture with the aid of net, they were anesthetized with Eugenol Vetec[R] (75 mg [L.sup.-1]) during one minute of exposition and the blood (1 mL) was collected by puncturing the caudal vessel, using a syringe with a 20x0.55 mm (24 G x 3/4") needle containing a drop of 10% EDTA. Blood smears were performed in duplicates, later stained with May-Grunwald/Giemsa/Wright, for total thrombocyte and leukocyte counts and differential leukocyte count. The counts of these cells were calculated by the indirect method, from the blood extensions (Ishikawa et al., 2008). An aliquot of the blood was used to determine the percentage of hematocrit (Ranzani-Paiva et al., 2013). The total erythrocyte count was performed in a Neubauer chamber, after dilution (1:200) in Dacie solution (Blaxhall & Daisley, 1973).

Parasitological analysis

After blood sampling, the animals were euthanized by a rapid cerebral concussion, followed by a detailed macroscopic examination and biometry. The body surface mucus was scraped to make two slides each in duplicates that were later stained with silver nitrate and Giemsa to identify the protozoans. The remainder of the mucus was conditioned in flasks and fixed in 5% formalin for further parasite counting. The eyes, gills and gastrointestinal tract were collected separately and fixed, according to Jeronimo et al. (2011).

For protozoan quantification, the body surface and gill contents were homogenized and subsequently three 1 mL aliquots were taken for counting in the Sedgewick-Rafter chamber to estimate the volume of the fixed, as proposed by Martins et al. (2011). Monogeneans were quantified under a stereomicroscope in a labeled Petri dish and later mounted on slides with Hoyer's medium for identification.

Prevalence rate, mean intensity and mean parasite abundance were calculated according to Bush et al. (1997) for each parasite species. The identification of Trichodina sp. was performed according to Ghiraldelli et al. (2006c) and Martins & Ghiraldelli (2008), and Monogenea according to Paperna & Thurston (1969) and Pariselle & Euzet (1995).

Relative condition factor (Kn)

Kn values were calculated according to the method described by Le Cren (1951). Thus, with the logarithms of the total length (Lt) and total individual weight (Wt) values, the curve of the Wt/Lt relationship was adjusted, and the values of the regression coefficients a and b were estimated. The values of these coefficients were used to estimate the theoretically expected values of body weight (We), using the equation We = a [Lt.sup.b]. Then Kn was calculated, corresponding to the ratio between the observed weight and the theoretically expected weight for a given length (Kn = Wt/We).

Statistical analysis

Statistical analyses were performed using Statistica 10.0[R] software. Since normality and homoscedasticity were not reached, the non-parametric Kruskal-Wallis test was used to compare the means. The possible correlations were verified with Spearman's correlation coefficient. The level of significance was P [less than or equal to] 0.05.

RESULTS

The fish farms in this study were generally characterized by monocultures of tilapia, polyculture and catch and fee fishing systems (Table 1), and no mortalities were found.

The water quality values, measured only on the collection day, showed variations among the fish farms (Table 2). The mean weight of the animals ranged from 250.2 to 868.7 g, while the mean maximum and minimum total lengths were 22.2 and 35.6 cm, respectively.

The condition factor presented an average of one (Kn = 1) in all fish farms in the present study, except for one in which the mean was 0.99 (Table 3).

The parasitological analysis revealed the presence of Trichodina magna Van as & Basson, 1989 and Trichodina compacta Van as & Basson, 1989 on the fish body surface of all fish farms, with a maximum prevalence of 95% and a minimum of 35%, with a relatively low average intensity. Already the parasitism by Trichodina sp. Ehrenberg, 1830 on the gills, was reported in fish from all fish farms in the north, Itajai valley and west, with prevalences of 40 to 100% and the high mean intensity of infestation (Table 4).

Ichthyophthirius multifiliis was observed in tilapia gills of all fish farms in the south and west regions, and only one of the northern regions of the state. The prevalence of I. multifiliis ranged from 5 to 100%, and the mean intensity followed the variation, being more intense in fish farms with higher prevalences (Table 5).

Only two species of Monogenea were observed on the gills, Ciclidogyrus sclerosus Paperna & Thurston, 1969 and Ciclidogyrus halli Price & Kirk, 1967, well as Trichodina sp. were present in all fish farms in the north, valley and west region, and absent in fish farms in the south. The lowest prevalence observed was 15%, where the lowest values for intensity and average infection abundance were also observed (Table 6). Prevalence of 100% was observed in fishery 3 of the Itajai valley. However, the highest mean infestation intensity by Ciclidogyrus sp. was in the northern fish farm with 100.42 [+ or -] 65.32 parasites per fish.

The hematological parameters (Table 7) revealed variations in the red blood cells that presented minimum and maximum values of 1.4x [10.sup.6] and 2.4x [10.sup.6] [micro][L-.sup.1], respectively, as well as the hematocrit, which ranged from 25.1 to 36.5%, remaining within the reference values for the species (Azevedo et al, 2006; Ghiraldelli et al., 2006b).

Thrombocytes presented low values in all fish farms, characterizing thrombocytopenia. The total white blood cells count showed variations among the fish farms, with the most abundant leucocytes being lymphocytes, followed by monocytes and neutrophils. The monocytes presented marked values in all fish farms, which were consistent with a monocytosis. However, the lymphocytes and neutrophils, despite a wide variation, were within the reference values for the species (Azevedo et al, 2006; Ghiraldelli et al, 2006b).

When all the parasites were compared with each hemogram parameter, no correlation was observed between the hematological variables and the parasitism. However, monocytes were positively correlated with protozoan I. multifiliis ([rho] = 0.19) and neutrophils showed positive correlations with I. multifiliis ([rho] = 0.25), Trichodina sp. on the gills ([rho] = 0.18) and Monogenea ([rho] = 0.15). The relative condition factor (Kn) when related to hematological indices and parasitism presented only negative correlation ([rho] = -15) with Trichodina sp. in the mucus.

DISCUSSION

Nile tilapia is a rustic fish capable of supporting lowquality water environments (Zaniboni-Filho, 2004). However, dissolved oxygen was relatively low in fish farms 1 and 2 in the south region and fish farming 2 in the west region. Likewise, the water temperature in most fish farms was below the ideal limit for their cultivation (Kubitza, 2000). In general, changes in water quality, high stocking density, inadequate management or unbalanced nutrition are factors capable of producing stress in the fish, predisposing them to various infestations and parasitic infections (Zanolo & Yamamura, 2006).

The parasites reported in this study are common to tilapia culture, especially Monogenea and Trichodina sp. (Azevedo et al., 2006; Ghiraldelli et al., 2006a; Jeronimo et al., 2011; Zago et al., 2014; Nunes et al., 2016) and the protozoans have been shown to be the most prevalent group in Santa Catarina. Ranzani-Paiva et al. (2005), in a study with Nile tilapia from a reservoir in Sao Paulo, observed among other parasites, Trichodina sp., Ichthyophthirius multifiliis and Monogenea on gills and Trichodina sp. on the fish skin, corroborating the parasitic fauna found in the present study. On the other hand, previous studies did not report the presence of I. multifiliis in fish from Santa Catarina while other ectoparasites such as Piscinoodinium pillulare (Schaperclaus 1954) Lom 1981 were found to be recurrent (Azevedo et al., 2006; Ghiraldelli et al., 2006a; Jeronimo et al., 2011; Nunes et al., 2016). The above suggests a possible variation of the parasitological fauna of Oreochromis niloticus among the fish farms and along with culture cycles in the same region.

The highest values of prevalence and the average intensity of Trichodina magna and Trichodina compacta on the body surface of fish from fish farms 3 in the southern region may be associated with the fact that drying and treatment of tanks between harvests were not performed. These management practices contribute to an environment conducive to the proliferation of these protozoa, since they are indicators of water quality, and are directly related to the concentration of organic matter in the environment (Jeronimo et al., 2011). In addition to poor water quality, its proliferation is also associated with the total number of bacteria and the ecological aspects of the host (Martins et al., 2015). Similar fact occurs in fish farming 2 of the northern region, which is the only one of the fish farms in this study that uses manure for fertilization of the tanks, contributing to a higher average intensity of Trichodina sp. in the gills of the fish at that site.

Ichthyophthirius multifiliis was the parasite that affected the fish of the west region with higher intensity. It is known to be a widespread infestation in times of lower temperatures in the southern and southeastern regions of Brazil as well as in stressful situations (Martins & Romero, 1996; Tavares-Dias et al., 2001). The temperature is a factor that influences the duration of the cycle of this parasite. In colder climates it can last several months, thus explaining the fact that, in apparently unaffected populations, massive infestations may develop suddenly as a consequence of the increase in water temperature, which demonstrates the need for constant surveillance in fish during the summer months (Eiras, 1994). The indexes reported in this study are higher than observed by Zago et al. (2014) that reported the maximum prevalence of 38% and meant intensity of 100 parasites per fish in Nile tilapia parasitized by I. multifiliis. According to Lemos et al. (2007), this shows that, in Brazil, the same host may present a different pattern of this infestation, depending on the region in which it is being cultivated.

Monogenea helminths had higher average infestation intensity in fish culture 3 in the north region, which was characterized by a storage tank, in which several species of fish were allocated, that stocking density was unknown. The fact of not controlling the amount of fish in a nursery contributes to the dissemination of this parasite, which has a direct life cycle and has its proliferation and dissemination facilitated in high storage densities and poor water quality (Moraes & Martins, 2004). The above mentioned may justify the results of the present study, mainly associated with poor sanitary management and mechanisms of parasite permanence in fish (Buchmann & Lindenstrom, 2002).

In a study with Mugil platanus from an estuarinelagoon region in the state of Sao Paulo (Brazil), Ranzani-Paiva & Silva-Souza (2004) observed that parasitism of the gills by Monogenea affects the weight of fish, especially when co-infected with Trichodina sp. and copepods, demonstrating the negative correlation of parasitism with the condition factor (Kn). Contrary to what was observed in this study, in which Kn showed an only negative correlation ([rho] = -15) with Trichodina sp. in mucus and when associated with all parasites, there was no correlation. However, all fish farms analyzed in this study showed a Kn equal to or very close to 1, which indicates indirectly that the observed parasitism did not affect the growth and well-being of the fish, a fact that was also reported by Ranzani-Paiva et al. (2000) and Tavares-Dias et al. (2002).

In the present study, the number of monocytes exceeded the number of neutrophils, contrary to that observed in other studies (Hrubec et al., 2000; Tavares-Dias & Moraes, 2003; Ghiraldelli et al., 2006b). However, the same situation was reported by Azevedo et al. (2006) in O. niloticus in fish-pay. On the other hand, the higher lymphocyte rates in relation to monocytes and neutrophils suggest that the fish were not submitted to stressors before blood withdrawal, since several studies have indicated lymphopenia and neutrophilia in fish under stress (Martins et al., 2002, 2004, 2006).

In O. niloticus highly infested by I. multifiliis and Saprolegnia sp, the neutrophil and monocyte percentages were significantly higher in the parasitized group, but the number of thrombocytes was equivalent between the two groups (Tavares-Dias et al., 2002). On the other hand, Tavares-Dias et al. (1999) reported the occurrence of thrombocytopenia and monocytosis in P. mesopotamicus parasitized with Argulus sp., corroborating the results of the present study, in which the same changes in the hematological profile of Nile tilapias parasitized with Trichodina sp., Monogenea and I. multifiliis were observed.

The values of thrombocytes in the present study were lower than those reported in several studies with tilapias (Hrubec et al., 2000; Tavares-Dias et al., 2002; Tavares-Dias & Moraes, 2003; Azevedo et al., 2006; Ghiraldelli et al., 2006a). Thrombocytes are responsible for blood coagulation and play an essential role in phagocytosis, especially of cellular debris (Ranzani-Paiva et al., 2013). According to Nagasawa et al. (2015), in their study with carp, thrombocytes require activation factors secreted by other activated leukocytes to perform phagocytosis. Possibly thrombocytes have been activated and recruited from their reserve compartments to contribute to the mechanisms of organic defense (Tavares-Dias et al., 1999), justifying the thrombocytopenia observed in the present study. On the other hand, monocytes, which are the principal fish phagocytes (Tavares-Dias & Moraes, 2004), in cases of infectious processes, migrate from the blood vessels to the inflammatory focus (Martins et al., 2009 and Santos et al., 2009), increased production in the bloodstream in order to supply the requirements for organic defenses, unlike thrombocytes that possibly were only sequestered for the focus of inflammation.

The correlations observed in the present study suggest that neutrophils and monocytes are involved in the organic defense of fish against the parasites found. Studies with P. mesopotamicus related the increase in the number of circulating monocytes against parasite infection (Tavares-Dias et al., 1999, 2008). However, monocytosis observed in this study refers in particular to I. multifiliis parasitism, given the positive correlation observed between the two.

Tavares-Dias et al. (1999), when studying the hematology and relative condition factor (Kn) of parasitized L. macrocephalus and P. mesopotamicus, observed that despite the high level of Monogenea infestation, Trichodina sp., Lernaea cyprinacea Linnaeus, 1758 (Crustacea: Copepoda), P. pillulare and I. multifiliis, there were no changes in the studied parameters, possibly having a balance between parasites and hosts. In contrast to the report mentioned above, in the present study, the high infestations did not influence the relative condition factor, but the alterations observed in the blood count suggest a direct relationship with the parasitic infestation.

Even without apparent losses in production, such as inadequate growth and/or mortality, the parasites of this study had a direct influence on fish health, as could be observed through changes in the blood count. The hematological profile of the tilapias showed the sequestration and use of cellular components of organic defense, possibly as a function of parasitism. Thus, parasites can divert the immune response of the fish, compromising them against any future adverse events.

CONCLUSIONS

The tilapia organic defense system was effective against the observed parasitism, so as not to affect the physiological state of animals and growth. Thus, the monocytosis and thrombocytopenia conditions were possibly due to the high parasitic intensities caused by Trichodina spp., I. multifiliis, and Monogenea. The correlations observed in the present study suggest that neutrophils and monocytes are directly involved in the organic defense of fish against parasites, and monocytes are primarily related to I. multifiliis infection.

ACKNOWLEDGMENTS

The authors are grateful to Luiz Rodrigo Motta Vicenti (Epagri), Ofelia Maria Campigotto (Gaspar fish farmers' association), Susane Pahl-Klipp (Municipal Rural Development Foundation July 25) and Marcelo Tonial and Alexander Hilata (Nicolluzi) for assistance in collecting and to the fish farms of the state of Santa Catarina that donated the fish. The authors thank Dr. Evoy Zaniboni Filho, Dra. Natalia Costa Marchiori and Dr. Eduardo Cargnin for critical review of the manuscript prior to submission. We thank National Council for Scientific and Technological Development (CNPq) for their financial support (CNPq 446072/2014-1) and grant to M.L. Martins (CNPq 305869/2014-0), the Improvement Coordination Higher Level Personnel (CAPES-EMBRAPA n. 15/2014) for award of the Master's scholarship to L.D. Steckert, Post-Doctoral scholarship to G.T. Jeronimo (CNPq 402434/2016-1) and CAPES Finance code 001.

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Lilian Dordete Steckert (1), William Eduardo Furtado (1), Gabriela Tomas Jeronimo (1,2) Karen Roberta Tancredo (1), Gabriela Sayuri de Oliveira Hashimoto (1) Scheila Anelise Pereira (1) & Mauricio Laterca Martins (1)

(1) AQUOS-Aquatic Animal Health Laboratory, Aquaculture Department

(2) Federal University of Santa Catarina, Florianopolis, SC, Brazil

Corresponding author: Mauricio Laterca Martins (mauricio.martins@ufsc.br)

Corresponding editor: Mariel Gullian

Received: 27 September 2018; Accepted: 22 March 2019

DOI: 10.3856/vol47-issue3-fulltext-12
Table 1. Management characteristics in the different regions and fish
farms in the state of Santa Catarina. (*) One year ago, was consortium
with pigs. (**) In the winter the animals were not receiving feed,
which coincided with the date of collection.

                           South
Characteristics            Fish farming 1

System                     Fish-pay
Density (fish [m.sup.-3])  2
Feeding                    2 times daily (**)
Complementary Aeration     No
Water Quality Monitoring   No
Prophylaxis                No
Treatment of tanks         Disinfection between crops
Characteristics            Fish farming 1
System                     Polyculture
Density (fish [m.sup.-3])  4
Feeding                    2 times daily
Complementary Aeration     Yes
Water Quality Monitoring   Monthly
Prophylaxis                Salt
Treatment of tanks         Fertilization
                           It
Characteristics            Fish farming 1
System                     Polyculture
Density (fish [m.sup.-3])  3
Feeding                    3 times daily
Complementary aeration     2 times daily
Water Quality Monitoring   2 times per week
Prophylaxis                Salt
Treatment of tanks         Disinfection and fertilization
                           between crops
Characteristics            Fish farming 1
System                     Polyculture
Density (fish [m.sup.-3])  3.6
Feeding                    -
Complementary aeration     Yes
Water Quality Monitoring   Monthly
Prophylaxis                No
Treatment of tanks         Drying, disinfection, and
                           fertilization between crops

                           South
Characteristics            Fish farming 2

System                     Monoculture (*)
Density (fish [m.sup.-3])  -
Feeding                    3 times daily (**)
Complementary Aeration     Yes
Water Quality Monitoring   Monthly
Prophylaxis                No
Treatment of tanks         Disinfection between crops
                           North
Characteristics            Fish farming 2
System                     Polyculture
Density (fish [m.sup.-3])  2
Feeding                    2 times daily
Complementary Aeration     Yes
Water Quality Monitoring   1 time per week
Prophylaxis                Salt
Treatment of tanks         Disinfection and fertilization
                           (uses manure)
                           ajai Valley
Characteristics            Fish farming 2
System                     Fish-pay
Density (fish [m.sup.-3])  8-10
Feeding                    1 time daily
Complementary aeration     2 times daily
Water Quality Monitoring   Nao
Prophylaxis                Salt
Treatment of tanks         Disinfection between crops
                           West
Characteristics            Fish farming 2
System                     Fish-pay
Density (fish [m.sup.-3])  4
Feeding                    2 times daily
Complementary aeration     No
Water Quality Monitoring   No
Prophylaxis                Salt e and syrup with pine
Treatment of tanks         Drying, disinfection, and
                           fertilization between crops

                           South
Characteristics            Fish farming 3

System                     Monoculture
Density (fish [m.sup.-3])  4-5
Feeding                    5 times daily (**)
Complementary Aeration     Yes
Water Quality Monitoring   No
Prophylaxis                No
Treatment of tanks         No
Characteristics            Fish farming 3
System                     Tank tank
Density (fish [m.sup.-3])  -
Feeding                    1 time daily
Complementary Aeration     Yes
Water Quality Monitoring   No
Prophylaxis                Salt
Treatment of tanks         No
Characteristics            Fish farming 3
System                     Polyculture
Density (fish [m.sup.-3])  5
Feeding                    5 times daily
Complementary aeration     2 times daily
Water Quality Monitoring   Monthly
Prophylaxis                Salt
Treatment of tanks         Disinfection between crops and
                           fertilization sometimes
Characteristics            Fish farming 3
System                     Polyculture
Density (fish [m.sup.-3])  2.5
Feeding                    8 times daily - automatic
Complementary aeration     Yes
Water Quality Monitoring   Monthly
Prophylaxis                No
Treatment of tanks         Drying, disinfection, and
                           fertilization between crops

Table 2. Physical and chemical parameters of water quality in the
nurseries of the different fish farms studied. P: fish farming, DO:
dissolved oxygen.

                          South              North
Parameters                  P1    P2     P3    P1    P2     P3

DO (mg [L.sup.-1])           1.8   1.4    8.3   7.3   6.6    6.1
Transparency (cm)           21    20     19    11    13     41
pH                           6.1   7.0    7.0   6.6   6.8    7.0
Ammonia (mg [L.sup.-1])      1     0.5    0.2   0.1   0      0.1
Temperature ([degrees]C)    20.7  23.6   22.0  22.8  23.7   20.9
                          Itajai Valley                     West
Parameters                P1             P2     P3    P1    P2     P3
DO (mg [L.sup.-1])         2.2            7.8    3.3   7.6   0.6    3.1
Transparency (cm)         14              6     20    21    19     20
pH                         6.4            7.0    6.0   6.7   5.9    5.8
Ammonia (mg [L.sup.-1])    1.5            0.1    1.0   1.6   0.2    0.6
Temperature ([degrees]C)  28.7           22.4   22.9  29.2  25.3   30.9

Table 3. Biometric indices (mean [+ or -] standard deviation) and
relative condition factor (Kn) of Nile tilapia. Different letters
indicate a significant difference in the columns by the Kruskal-Wallis
test (P < 0.05). P: fish farming.

Fish farming  Weight (g)                   Length (cm)        Kn

P1 south      362.3 [+ or -] 124.3 (abc)   25.4 [+ or -] 3.1  1.0 (a)
P2 south      347.0 [+ or -] 76.1 (abc)    24.2 [+ or -] 1.6  1.0 (b)
P3 south      250.2 [+ or -] 52.0 (a)      23.3 [+ or -] 1.6  0.9 (c)
P1 north      407.5 [+ or -] 86.9 (bcd)    26.4 [+ or -] 1.8  1.0 (a)
P2 north      488.7 [+ or -] 170.7 (cd)    28.3 [+ or -] 3.3  1.0 (a)
P3 north      422.8 [+ or -] 166.3 (abcd)  28.4 [+ or -] 3.7  1.0 (a)
P1 valley     261.5 [+ or -] 50.6 (ab)     22.2 [+ or -] 1.6  1.0 (ab)
P2 valley     868.7 [+ or -] 123.7 (e)     35.6 [+ or -] 1.5  1.0 (a)
P3 valley     372.9 [+ or -] 71.9 (abc)    26.7 [+ or -] 1.6  1.0 (ab)
P1 west       815.3 [+ or -] 113.8 (e)     33.6 [+ or -] 1.8  1.0 (a)
P2 west       588.1 [+ or -] 116.6 (de)    31.2 [+ or -] 2.7  1.0 (ab)
P3 west       511.0 [+ or -] 7.7 (cde)     29.4 [+ or -] 1.5  1.0 (ab)

Table 4. Parasitological indices of Trichodina sp. in Nile tilapia.
Different letters indicate a significant difference in the lines by the
Kruskal-Wallis test (P < 0.05). P%: prevalence, MI: mean intensity and
MA: mean abundance (mean [+ or -] standard deviation), SII: site of
infestation/infection, G: gills, M: mucus of body surface, P: fish
farming.

Fish farming  SII   P (%)    MI

P1 south      G      0         0 (a)
              M     65        12.3 [+ or -] 15.2 (abc)
P2 south      G      0         0 (a)
              M     70         8.1 [+ or -] 6.9 (abc)
P3 south      G      0         0 (a)
              M     95        97.2 [+ or -] 144.7 (d)
P1 north      G     75       486.6 [+ or -] 533.4 (bcd)
              M     65         4.3 [+ or -] 3.6 (abc)
P2 north      G     40     11250.0 [+ or -] 29540.3 (ab)
              M     60         2.7 [+ or -] 3.4 (abc)
P3 north      G     90       983.3 [+ or -] 1001.3 (bcd)
              M     35         2.5 [+ or -] 4.1 (a)
P1 valley     G     70      1004.7 [+ or -] 3033.8 (ab)
              M     40         2.2 [+ or -] 3.1 (ab)
P2 valley     G     80       283.3 [+ or -] 189.3 (bcd)
              M     80         6.8 [+ or -] 5.6 (abcd)
P3 valley     G     75       275.5 [+ or -] 260.4 (abc)
              M     45         6.4 [+ or -] 8.8 (abc)
P1 west       G    100      4956.4 [+ or -] 11594.9 (b)
              M     55         4.6 [+ or -] 5.9 (abc)
P2 west       G    100      4136.3 [+ or -] 8661.8 (cd)
              M     90        15.1 [+ or -] 25.2 (cd)
P3 west       G    100       566.3 [+ or -] 375.6 (bcd)
              M     45         4.3 [+ or -] 6.5 (abc)

Fish farming       MA

P1 south          0
                  8.0 [+ or -] 13.5
P2 south          0
                  5.7 [+ or -] 6.8
P3 south          0
                 92.3 [+ or -] 142.5
P1 north        365.0 [+ or -] 505.1
                  2.8 [+ or -] 3.2
P2 north       4500.0 [+ or -] 18800.8
                  1.6 [+ or -] 2.9
P3 north        885.0 [+ or -] 994.3
                  0.9 [+ or -] 2.6
P1 valley       703.3 [+ or -] 2553.5
                  0.9 [+ or -] 2.2
P2 valley       226.6 [+ or -] 204.4
                  5.5 [+ or -] 5.7
P3 valley       206.6 [+ or -] 254.8
                  2.9 [+ or -] 6.3
P1 west        4956.4 [+ or -] 11594.9
                  2.5 [+ or -] 4.8
P2 west       136,3 [+ or -] 8661.8
                 13.6 [+ or -] 24.3
P3 west         566.3 [+ or -] 375.6
                  1.9 [+ or -] 4.7

Table 5. Parasitological indices of Ichthyophthirius multifiliis in
gills of Nile tilapia. Different letters indicate a significant
difference in the lines by the Kruskal-Wallis test (P < 0.05). P: fish
farming, P%: prevalence, MI: mean intensity and MA: mean abundance
(mean [+ or -] standard deviation).

Fish farming   P (%)   MI                          MA

P1 south       45      377.7 [+ or -] 210.8 (ab)   170 [+ or -] 236.4
P2 south       50      330.0 [+ or -] 231.1 (ab)   165 [+ or -] 232.3
P3 south       30      116.6 [+ or -] 40.8 (a)      35 [+ or -] 58.7
P1 north        0        0 (b)                       0
P2 north        5      100 [+ or -] 0 (b)          5 [+ or -] 22.3
P3 north        0        0 (b)                       0
P1 valley       0        0 (b)                       0
P2 valley       0        0 (b)                       0
P3 valley       0        0 (b)                       0
P1 west        95     1564.5 [+ or -] 988.9 (a)   1486.3 [+ or -] 1024.1
P2 west        95      571.6 [+ or -] 554.4 (a)    543.0 [+ or -] 554.5
P3 west       100     2419.6 [+ or -] 1515.1 (a)  2419.6 [+ or -] 1515.1

Table 6. Parasitological indices of Monogenea in gills of Nile tilapia.
Different letters indicate a significant difference in the lines by the
Kruskal-Wallis test (P < 0.05). P: fish farming, P%: prevalence, MI:
mean intensity, MA: mean abundance (mean [+ or -] standard deviation).

Fish farming  P(%)  IM                         AM

P1 south       0      0 (ab)                     0
P2 south       0      0(ab)                      0
P3 south       0      0(ab)                      0
P1 north      15      1 [+ or -] 0 (ab)          0.1 [+ or -] 0.3
P2 north      25      2 [+ or -] 1.7 (ab)        0.5 [+ or -] 1.1
P3 north      95    100.4 [+ or -] 65.3 (e)     95.4 [+ or -] 67.4
P1 valley     70      3.3 [+ or -] 3.5 (bcd)     2.3 [+ or -] 3.3
P2 valley     60      5.2 [+ or -] 6.7 (bcd)     3.1 [+ or -] 5.8
P3 valley    100      9.1 [+ or -] 9.1 (de)      9.1 [+ or -] 9.1
P1 west       15      1.3 [+ or -] 1.1 (b)       0.2 [+ or -] 0.7
P2 west       40      3.2 [+ or -] 4.8 (bc)      1.3 [+ or -] 3.3
P3 west       80     13.9 [+ or -] 22.3 (cde)   13.1 [+ or -] 20.6

Table 7. Hematological characteristics (mean [+ or -] standard
deviation) of Nile tilapia cultivated in fish farms in the state of
Santa Catarina. Different letters indicate a significant difference
between the columns by the Kruskal-Wallis test (P < 0.05). RBC: red
blood cells, WBC: white blood cells, P: fish farming.

                                              South
Parameters                                    P1

Hematocrit (%)                                34.3 [+ or -] 4.9 (ab)
RBC (x[10.sup.6] [micro][L.sup.-1])            2.3 [+ or -] 5.2 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])           63.8 [+ or -] 2.5
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   99.4 [+ or -] 2.4 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])    4.4 [+ or -] 3.0 (ab)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      9.9 [+ or -] 4.2 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])   4.3 [+ or -] 3.9 (bc)

Parameters                                    P1
Hematocrit (%)                                 28.1 [+ or -] 4.3 (cde)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.2 [+ or -] 4.9 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])           104.0 [+ or -] 3.0
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])    99.8 [+ or -] 2.6 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     1.3 [+ or -] 1.7 (cd)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      15.7 [+ or -] 8.1 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])   13.8 [+ or -] 10.2 (ab)

                                               South
Parameters                                     P2

Hematocrit (%)                                 32.7 [+ or -] 3.6 (abc)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.3 [+ or -] 2.6 (a)
WBC (x[10.sup.3] [micro][L.sup.-1])           112.0 [+ or -] 2.9
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   103.0 [+ or -] 2.4 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     1.4 [+ or -] 1.6 (bcd)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      17.8 [+ or -] 13.2 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])    6.6 [+ or -] 5.4 (abcd)
                                               Itajai Valley
Parameters                                     P2
Hematocrit (%)                                30.3 [+ or -] 3.4 (abcde)
RBC (x[10.sup.6] [micro][L.sup.-1])            2.0 [+ or -] 3.6 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])           78.6 [+ or -] 3.4
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   94.1 [+ or -] 1.9 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])    3.0 [+ or -] 3.3 (abc)
Monocytes (x[10.sup.3] [micro][L.sup.-1])     10.4 [+ or -] 6.5 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])  11.6 [+ or -] 11.4 (abc)

                                              South
Parameters                                    P3

Hematocrit (%)                                 27.2 [+ or -] 3.3 (e)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.4 [+ or -] 3.91 (a)
WBC (x[10.sup.3] [micro][L.sup.-1])            88.6 [+ or -] 2.9
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   108.0 [+ or -] 1.6 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     1.2 [+ or -] 1.5 (cd)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      12.2 [+ or -] 6.4 (ab)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])    2.0 [+ or -] 3.7 (d)

Parameters                                     P3
Hematocrit (%)                                 25.1 [+ or -] 7.1 (de)
RBC (x[10.sup.6] [micro][L.sup.-1])             1.9 [+ or -] 4.5 (abc)
WBC (x[10.sup.3] [micro][L.sup.-1])            47.4 [+ or -] 2.2
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])    83.8 [+ or -] 2.0 (abc)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])    6.9 [+ or -] 4.8 (a)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      7.8 [+ or -] 4.5 (ab)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])  13.2 [+ or -] 8.6 (ab)

                                                North
Parameters                                      P1

Hematocrit (%)                                34.1 [+ or -] 3.1 (a)
RBC (x[10.sup.6] [micro][L.sup.-1])            2.0 [+ or -] 5.6 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])           70.9 [+ or -] 3.1
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   98.5 [+ or -] 2.8 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])    1.6 [+ or -] 2.5 (cd)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      1.2 [+ or -] 1.2 (c)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])  13.2 [+ or -] 8.8 (ab)

Parameters                                     P1
Hematocrit (%)                                 36.5 [+ or -] 2.5 (ab)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.3 [+ or -] 5.1 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])            69.9 [+ or -] 1.9
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   104.0 [+ or -] 2.4 (a)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     6.3 [+ or -] 6.1 (abc)
Monocytes (x[10.sup.3] [micro][L.sup.-1])       2.8 [+ or -] 3.4 (bc)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])   22.7 [+ or -] 9.9 (a)

                                              North
Parameters                                    P2

Hematocrit (%)                                35.2 [+ or -] 4.2 (a)
RBC (x[10.sup.6] [micro][L.sup.-1])            1.8 [+ or -] 6.0 (bc)
WBC (x[10.sup.3] [micro][L.sup.-1])           53.0 [+ or -] 2.3
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])   88.4 [+ or -] 3.1 (abc)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])    0.1 [+ or -] 0.2 (d)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      2.5 [+ or -] 4.5 (bc)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])   9.6 [+ or -] 8.1 (abcd)
                                              West
Parameters                                    P2
Hematocrit (%)                                 32.7 [+ or -] 2.9 (abc)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.1 [+ or -] 3.5 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])            60.4 [+ or -] 1.8
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])    87.6 [+ or -] 1.7 (abc)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     3.6 [+ or -] 3.5 (abc)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      12.3 [+ or -] 5.4 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])    8.9 [+ or -] 6.6 (abcd)

                                              North
Parameters                                    P3

Hematocrit (%)                                 32.3 [+ or -] 3.3 (abcd)
RBC (x[10.sup.6] [micro][L.sup.-1])             1.4 [+ or -] 2.8 (c)
WBC (x[10.sup.3] [micro][L.sup.-1])            37.3 [+ or -] 1.5

Lymphocytes (x[10.sup.3] [micro][L.sup.-1])    63.6 [+ or -] 1.9 (c)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     1.7 [+ or -] 2.2 (bcd)
Monocytes (x[10.sup.3] [micro][L.sup.-1])       1.8 [+ or -] 2.3 (bc)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])    2.4 [+ or -] 4.1 (cd)
Parameters                                    P3
Hematocrit (%)                                 29.1 [+ or -] 3.9 (bcde)
RBC (x[10.sup.6] [micro][L.sup.-1])             2.1 [+ or -] 3.1 (ab)
WBC (x[10.sup.3] [micro][L.sup.-1])            83.0 [+ or -] 1.9
Lymphocytes (x[10.sup.3] [micro][L.sup.-1])    85.4 [+ or -] 1.1 (abc)
Neutrophils (x[10.sup.3] [micro][L.sup.-1])     4.1 [+ or -] 3.6 (abc)
Monocytes (x[10.sup.3] [micro][L.sup.-1])      14.9 [+ or -] 6.1 (a)
Thrombocytes (x[10.sup.3] [micro][L.sup.-1])   12.5 [+ or -] 9.7 (ab)
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Title Annotation:Research Articles
Author:Steckert, Lilian Dordete; Furtado, William Eduardo; Jeronimo, Gabriela Tomas; Tancredo, Karen Robert
Publication:Latin American Journal of Aquatic Research
Date:Jul 1, 2019
Words:8299
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