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. 2023 Nov 8;18(11):e0294064. doi: 10.1371/journal.pone.0294064

Impact of duck stocking density on growth performance, digestive enzymes, blood biochemistry, and antioxidant capacity of the Labeo rohita reared in an integrated ponds system

Iqra Anwer 1,*, Muhammad Hafeez-ur-Rehman 1, Farzana Abbas 1, Shagufta Saeed 2
Editor: Amel Mohamed El Asely3
PMCID: PMC10631685  PMID: 37939144

Abstract

This study investigated the effects of duck stocking density (SD) on growth performance, meat quality, hematology, serum metabolites, and antioxidant status of L. rohita reared in an integrated pond system. A total of 9000 fingerlings of L. rohita average weighing 150.5±1 grams were reared in nine ponds (n = 1000/pond) and randomly allotted one of three SDs under a completely randomized design. The stocking densities were 100 (SD-100), 150 (SD-150), and 200 (SD-200) ducks/pond and each group had three replicates. The final body weight, weight gain, and specific growth rates were greater (p<0.05) in SD-200 than in the rest of the treatments. The activities of proteases and amylase were also greater (p<0.05) for SD-200 than for the rest of the SD. However, hematological parameters like red blood cells, white blood cells, hematocrit, met hematocrit, and hemoglobin contents were not influenced (p>0.05) by SD in ponds. The serum total protein, albumin, globulin, creatinine, and glucose contents were also similar (p>0.05) across the ponds. However, blood urea nitrogen was higher (p<0.05) in SD-200 than in the rest of the SD. Moreover, alanine transaminase, aspartate transaminase, and alkaline phosphatase activities were linearly decreased (p<0.05) with increasing SD across the ponds. The changes in catalases and superoxide dismutase were non-significant (p>0.05) among the groups. However, glutathione peroxidase was greater for SD-200 than for the rest of the SD. The carcass compositional characteristics such as dry matter, protein, fat, and ash contents were not changed (p>0.05) by varying SD. In conclusion, SD over 200 birds/pond improved growth performance, digestive enzyme functions, and oxidative capacity without any negative impact on the hematology and carcass composition of L. rohita.

Introduction

Aquaculture is rapidly emerging as an industry that plays a crucial role in ensuring global food security by providing a reliable supply of high-quality protein for human consumption [1]. Aquaculture production systems in developing countries such as Pakistan range from extensive polyculture farming systems to intensive commercial rearing practices [2, 3]. Intensive aquaculture has demonstrated the ability to achieve remarkable growth performance within a relatively short timeframe [3]. However, the sustainability of such production systems is being called into question because of increasing environmental challenges [4] and resource constraints such as higher feeding costs (70–80% of total production cost), availability of feed ingredients, and their quality [5]. Integrated aquaculture farming systems evolve fish rearing alongside other livestock or crop species. Such operations cut production costs by utilizing animal excreta nutrients to boost pond productivity and, ultimately, fish growth [6]. Efficient use of energy, water, land, and feed resources, as well as reduced commercial fertilizer inputs, could be key to long-term healthy aquatic food production [7]. Ecological intensification is proposed to achieve the long-term goals of food production systems by integrating anthropogenic inputs with ecosystem services [8]. Sustainable intensification is important in adapting to global climate change [9].

Fish blood parameters and stress levels are linked to growth regulation [10]. Stocking density has also been shown to influence blood hematology, a critical parameter in determining fish physiological performance [11, 12]. Furthermore, stress caused by stocking density affects fish physiological performance, influencing growth, survival, body proximate composition, and health in farm-raised catfish [11, 13]. The fish stocking density in a pond is well optimized in several studies with varying success [14–16]. To the best of the authors’ knowledge, no studies have assessed the influence of the ducks stocking density on the growth performance and physiological responses of L. rohita reared in an integrated pond system was limited. Moreover, pond integration with livestock species manure such as duck dropping is a common practice in the developing world, and information regarding stocking optimization is also scarce. L. rohita, is one of the major species that have been widely subjected to pond culturing in developing countries such as Pakistan because of good meat quality and higher consumer preference [17]. Rohu is typically subjected to higher stocking due to the larger feeding niche that extends from column to bottom [18]. Keeping all in view, the current study aimed to evaluate the influence of SD on growth performance, digestive enzyme activities, blood biochemistry, meat quality, and antioxidant capacity of the L. rohita reared in an integrated pond system.

Materials and methods

Ethical approval, experimental design, and husbandry practices

The current research was carried out at the aquaculture research station, C block Ravi Campus Pattoki, UVAS Lahore. A total of 9000 fingerlings of L. rohita average weighing 150.5±1 grams were reared in nine ponds (n = 1000/pond) and randomly allotted one of three SDs under a completely randomized design. The stocking densities were 100 (SD-100), 150 (SD-150), and 200 (SD-200) ducks/pond and each group had three replicates. The ponds were rectangular with dimensions 24 feet in length, and 9 feet in width of each pond. Ducks were housed and reared in a group form after randomization. Each pond was specified for respective ducks’ stock throughout the experimental duration (110 days). Stocks were discharged in the respective ponds at 0:900 h after the morning feeding and collected back to cages at 17:00 h of the day. The ducks were fed on a commercial feed throughout the experiment and daily feed was offered at 7:00 and 18:00 h of the day. The ponds were fenced with wire to ensure the separation of the groups in their respective ponds. The water of each pond was drained biweekly and refilled with fresh clean water. The physical parameters were measured every day between 9:00 and 10:00 hours of the day by using a multi-parameter probe (HI 9829 Hanna). The recorded water temperature, pH, dissolved oxygen, conductivity, and total dissolved oxygen levels ranged between 17–19°C, 8.5–8.7, 6.3–6.4 mg L−1, 1225–1230, and 686–688 mg L−1 respectively. Fish harvesting was performed by the net method at the end of the experiment.

Growth performance

The body weights were measured before the start of the feeding trial, and biweekly fishes from each pond were randomly sampled (200 fish/pond) on the day of termination of the experiment to calculate the body weight changes. The following Eqs 1–2 were used to calculate the growth performance.

Bodyweightgain(g)=Finalweight(g)−Initialweight(g) (1)
Specificgrowthrate=[(Finalweight−Initialweight)/growthtrialduration]×100 (2)

Sample collection and laboratory analysis

At the end of the experiment, twenty fish from each pond were selected and anesthetized by using a 150 mg/L concentration of tricane methanesulphate (MS-222) according to Mushtaq et al. [3]. Blood samples from ten fishes/ponds were collected in plain tuberculin syringes by puncturing the caudal vasculature, centrifugated immediately at 3000 x g for 15 minutes, and harvested serum was stored at -20°C for further analysis. Furthermore, the caudal vein was punctured using EDTA-coated tuberculin syringes, and collected blood samples were immediately analyzed for hematological parameters using an automated hematology analyzer (MEK6550). The blood glucose level was measured through commercial kits (21503, Biosystems, Barcelona, Spain). Five fishes from each pond were dissected for organ collection (intestine, kidney, liver, gills, and pancreas) and biological indices, and the rest five were homogenized in a meat mincer (ANEX, AG 3060) to evaluate the meat quality. The collected organs and meat samples were stored at -20°C in labeled plastic airtight zipper bags until further analysis. To calculate the dry matter contents, the meat samples were dried for 48 h at 55°C in a forced-air oven. Using a Foss grinder, dried meat samples were ground and passed through a 1 mm sieve (CT 293 Cyclotec, Denmark). The crude protein (Method 976.06) and fat contents of meat samples were determined using the AOAC, (1990) standard procedures (Soxtec procedure, Tecator, Hoganas, Sweden; method 920.29). To determine the ash content of ground meat and feed samples, they were ignited in a muffle furnace at 620°C for 3 hours.

Antioxidant assay

The 2 g muscle and liver samples of each fish were homogenized with 6 ml phosphate buffer (pH 7.4), filtered (Whatman filter paper no. 1), and centrifuged at 10,000 g for 15 min. All the steps to measure the enzymatic activities were carried out at 4°C. The superoxide dismutase (SOD) activity to restrain nitroblue tetrazole was estimated according to the method described by Giannopolitis and Ries [19]. The activities of catalase (CAT) and glutathione peroxidase (GPx) were estimated by measuring the concentration of decomposed hydrogen peroxide at 240 nm and 470 nm respectively, as described by Mushtaq, Fatima [20]. The activities of ALT, AST, and ALP in serum samples were estimated by using commercial kits (AL1205, AS3804, AP9764; Randox Laboratories Ltd).

Digestive enzyme activity

The collected intestinal samples were homogenized immediately after mixing with sodium phosphate buffer (0.05 M, pH 7.0; wt: vol = 1:9), centrifuged at 6000 ×g for 10 min at 4°C, and the supernatant was harvested to test the intestinal digestive enzymes activities. Amylase activity was determined using the 3,5-dinitro salicylic acid method as described by Thongprajukaew, Kovitvadhi [21]. Briefly, 0.5 mL of the supernatant was incubated with 1% starch solution (0.5 mL) at 37°C for 30 min. Approximately 1 mL of 3,5-dinitro salicylic acid reagent was added to the mixture, incubated in boiling water, soaked for 5 min, and cooled to ambient temperature. After the solution was diluted with an appropriate amount of double-distilled water, the absorbance was measured at a 540 nm spectrophotometer. One unit of amylase activity shows the presence of an enzyme that released 1 μg of reducing sugar per minute. The protease enzyme activity was estimated according to the method by Cupp-Enyard [22] by using bovine serum albumin as the substrate. The absorbance values were recorded at 680 nm.

Statistical analysis

Data were analyzed using ANOVA techniques of SAS (Online version 2023) with stocking densities as a fixed factor/independent variable. Means were compared and separated by the Tukey test with a significant level of p<0.05.

Results

Growth performance

According to Table 1, the duck’s SD influenced (p<0.05) the fish survival rates and growth performance. The survival rates for the SD-200, SD-150, and SD-100 groups were recorded as 97.75%, 96.75%, and 95.25%, respectively. The growth parameters like final body weight, body weight gain, and specific growth rate were linearly increased (p<0.05) with increasing ducks SD in ponds.

Table 1. Growth performance of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
Initial body weight (g) 150.43 150.51 150.86 0.368 0.532
Final body weight (g) 565.71a 608.50b 654.91c 0.582 0.000
Body weight gain (g) 415.27a 457.92b 504.01c 0.853 <0.0001
Weight gain (%) 73.41a 75.26b 76.96c 0.814 0.000
Specific growth rate (g) 3.77a 4.16b 4.58c 0.007 0.000
Survival rate (%) 95.25a 96.75b 97.75c 0.250 0.013
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200); and

2SEM = standard error of means.

Digestive enzyme activities

The means along with pooled stander error of means of digestive enzyme activities of L. rohita reared under different SD of ducks are given in Table 2. The activities of proteases and amylase were significantly greater (p<0.05) for SD-200 than the rest of the SD of the ducks in ponds.

Table 2. Digestive enzyme activities of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
Protease Activity (μg/min) 130.45a 143.8b 141.25c 0.745 0.002
Amylase activity (μg /min) 8.71a 10.73b 11.76c 0.437 0.016
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200); and

2SEM = standard error of means.

Hematology and serum metabolites

The hematological analysis and serum metabolites of L. rohita reared under different ducks SD are given in Tables 3 & 4 respectively. The means of RBCs, WBCs, HCT, MCHC, and Hb were similar (p>0.05) among the groups. Similarly, serum total protein, albumin, globulin, creatinine, and glucose contents were also similar (p>0.05) across the groups. The blood urea nitrogen contents were greater (p<0.05) in the SD-200 group across the treatments. Moreover, ALT, AST, and ALP activities were linearly decreased (p<0.05) with increasing SD across the groups.

Table 3. Hematology of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
WBC (106/μl)3 26.10 27.55 28.00 0.582 0.113
RBC (106/μl)4 2.83 2.95 2.94 0.032 0.130
Hb (g/dl)5 8.23 8.95 8.32 0.017 0.125
HCT (%)6 43.19 44.05 43.25 1.023 0.407
MCHC (g/dl)7 26.12 25.24 26.98 0.655 0.141
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200)

2SEM = standard error of means

3WBC = White blood cells

4RBC = Red blood cells

5Hb = Hemoglobin

6HCT = Hematocrit; and

7MCHC = Met hematocrit.

Table 4. Serum metabolites of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
Total protein (g/dl) 5.53 5.83 6.02 0.235 0.551
Albumin (g/dl) 2.92 3.12 2.95 0.143 0.250
Globulin (g/dl) 3.21 3.42 3.34 0.537 0.228
Creatinine (g/dl) 3.32 3.31 3.41 0.042 0.390
Blood urea nitrogen (mg/dl) 4.21a 5.43b 5.97c 0.120 0.011
Glucose (mg/dl) 80.01 81.51 80.99 0.822 0.251
ALP (IU/ml)3 29.94c 27.24b 26.12b 0.962 0.021
ALT (IU/ml)4 50.68c 48.76b 46.75b 1.586 0.014
AST (IU/ml)5 97.25c 95.23b 93.57b 1.651 0.023
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200)

2SEM = standard error of means

3ALP = Alanine phosphatase

4ALT = Alanine transaminase; and

5AST = Aspartate transaminase.

Oxidative stress-associated biomarkers

The results of the antioxidant enzymes of L. rohita are given in Table 5. The changes in catalases and SOD in both liver and muscle were non-significant (p>0.05) among the groups. However, means of glutathione peroxidase were influenced (p<0.05) by SD for both muscle and liver. The glutathione peroxidase was greater for SD-200 than for the rest of SD.

Table 5. Oxidative stress-associated biomarkers of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
Liver
Superoxide dismutase (μ/mg) 5.98 5.87 6.32 0.054 0.159
Catalases (μ/mg) 77.23 76.89 76.84 0.234 0.153
Glutathione peroxidase (μ/mg) 228.89a 236.02b 243.63c 2.865 0.026
Muscle
Superoxide dismutase (μ/mg) 6.23 6.01 6.13 0.003 0.167
Catalases (μ/mg) 71.42 71.84 72.48 0.432 0.132
Glutathione peroxidase (μ/mg) 221.6a 228.03b 251.34c 1.593 0.017
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200); and

2SEM = standard error of means.

Meat chemical composition

According to Table 6, the carcass compositional characteristics such as dry matter, protein, fat, and ash contents of fish were not changed (p>0.05) by varying SD of the ducks in ponds.

Table 6. Carcass composition of L.rohita reared in integrated ponds containing different duck stocking densities.

Parameters Stocking Densities1 SEM2 p-linear
SD-100 SD-150 SD-200
Dry matter (%) 75.75 75.24 74.25 0.251 0.162
Crude protein (%) 16.43 16.52 16.51 0.027 0.081
Crude fat (%) 5.55 4.97 5.32 0.422 0.269
Ash (%) 4.32 5.27 5.55 0.193 0.235
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1Stocking densities = ponds containing stocking density of ducks @ 100 ducks/pond (SD-100), 150 ducks/pond (SD-150), and 200 ducks/pond (SD-200)

2SEM = standard error of means.

Discussion

To our knowledge, this is the first study describing responses of L. rohita to different SD in an integrated pond-rearing system and to show how SD could affect fish growth performance, carcass composition, and health parameters. In integrated aquaculture systems, the co-cultivation of ducks and fish in the same pond is performed. Ducks not only provide an additional source of income but also contribute to the nutrient dynamics of the pond [23]. Moreover, such farming practices are commonly practiced by smallholders, particularly in developing countries [24]. However, the stocking density of ducks can significantly affect the growth performance of fish. Therefore, the current experiment hypothesized that greater SD can improve the growth performance of L. rohita by increasing pond productivity. This discussion aims to explore the impact of duck stocking density in ponds on fish performance and health. As expected, high SD (SD-200) improved body weight gain and specific growth rates in the current experiment. These results can be associated with a greater number of ducks in ponds serving as a source of organic matter and nutrients through their droppings, which contain protein, phosphorus, and other essential elements. Adequate nutrient availability can enhance primary productivity, leading to an abundant food source for fish. Several studies reported that higher dietary protein intake improved the growth performance of the fish [25–27]. It is well established that higher availability of the protein enhances the performance of the fish [28]. The improved digestive enzyme activities of the current study are augmenting the finding regarding growth performance as these are established indicators of nutrient digestibility, utilization, and assimilation in different fish species [29, 30]. Greater nutrient availability is presumably due to the enrichment of the pond water with floating nutrients from ducks’ droppings resulting in better growth performance with better digestion indicators [29, 31]. The increased protease and amylase activities for the SD-200 group in our experiment, support the above points. Thus, we can infer that increasing SD resulting more nutrient availability to improve the growth performance of the L. rohita. Blood metabolites serve as biomarkers to investigate health and disease conditions. Several factors including fluctuations in environments factors cause changes in the normal physiological levels of these metabolites [32]. Moreover, it is well established that the digested nutrients and metabolic products are directly absorbed in the blood through portal circulation and changed the blood’s biochemical properties [3]. Although the means of RBCs, WBCs, HCT, MCHC, and Hb were similar across different groups in the current experiment. The results also showed that levels of the serum metabolites such as serum total protein, albumin, globulin, creatinine, and glucose were also not changed across the groups. However, blood urea nitrogen was greater in SD-200 than in the rest of the groups. In the current research, we hypothesized that SD might affect the blood cells and serum metabolites of L. rohita. As results show that SD had no effects on hematological items and blood metabolites (except blood urea nitrogen) of growing fish. In addition, all of the measured parameters were in the normal range for L. rohita [33]. There are no data regarding the impacts of SD on blood hematology and metabolites of fish. Blood glucose is well-known stress-associated biomarker in fishes [34], and serum total protein has a connection with nutrient metabolism, and the immune system of fish [35]. The concentration of WBCs reflects the lysozyme activities and health status of the fish [20]. In the current experiment, increasing SD linearly decreased ALT, AST, and ALP activities suggesting healthy fish with better liver function and antioxidant capacity [3].

Oxidative stress is a pathophysiological condition that triggers irreversible tissue damage by reactive oxygen species [36]. The fish redox system basing upon certain enzymes such as SOD, CAT, and GPx which play a scavenging role to detoxify the reactive oxygen species [3]. In our experiment, the activities of SOD, and CAT for both muscle and liver were not changed across the groups. However, the level of GPx was significantly greater in SD-200 than in the rest of the groups suggesting that increasing SD produced stronger L. rohita. Studies in different fish species reported improved GPx activities meaning stronger fish with better antioxidant status [37, 38]. Several studies documented stocking density affects the antioxidative status of aquatic animals [39, 40]. The proximate analysis showed that fish meat protein, dry matter, fat, and ash contents were similar across the groups in the current experiment suggesting that the muscle composition of L. rohita has no sensitivity to SD.

Conclusion

Based on the results, the higher stocking density of the ducks in an integrated pond improved the growth performance, and digestive enzyme functions of L. rohita. In addition, strengthens the oxidative burst by increasing the concentrations of GPX which is a key enzyme to activate the redox defense system. The liver health indicators (ALT, AST, and ALP) were improved by increasing the ducks stocking density in the pond. However, the hematological parameters and carcass chemical composition of the fish were not influenced by varying duck stocking densities. Further studies are warranted to explore the higher duck stocking density and their influence on the growth performance of different carbs in an integrated pond-rearing setup.

Data Availability

All relevant data are within the manuscript.

Funding Statement

This research received funding from the Punjab Agricultural Research Board funded project no 674. The funders had no role in study design, data collection, and analysis, the decision to publish, or the preparation of the manuscript.

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