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Article

Impact of Stocking Density on Growth, Feeding Behavior, and Flesh Quality of Largemouth bass (Micropterus salmoides) in Coupled Aquaponic Systems

by
Marco Birolo
*,
Veronica Trabacchin
,
Paolo Sambo
,
Stefano Triolone
and
Carlo Nicoletto
Department of Agronomy, Food, Natural Resources, Animal and Environment (DAFNAE), University of Padova, Viale dell’Università 16, 35020 Legnaro, Italy
*
Author to whom correspondence should be addressed.
Fishes 2025, 10(11), 552; https://doi.org/10.3390/fishes10110552 (registering DOI)
Submission received: 2 October 2025 / Revised: 24 October 2025 / Accepted: 28 October 2025 / Published: 2 November 2025
(This article belongs to the Special Issue Fish Health and Welfare in Aquaculture and Research Settings)
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Abstract

Stocking density is a key driver of performance in aquaponics, affecting both fish welfare and crop yield. This study evaluated the impact of three initial stocking densities (3.1, 4.1, and 6.2 kg/m3) on survival, growth, feeding behavior, carcass and filet quality of largemouth bass (Micropterus salmoides), as well as on the yield of lettuce (Lactuca sativa), sweet basil (Ocimum basilicum), and Swiss chard (Beta vulgaris var. cicla) cultivated in vertical coupled aquaponic units. A total of 184 fish (109 ± 28 g) were reared for 176 days in nine independent recirculating systems. Fish reared at the lowest density achieved the highest final live weight and specific growth rate, with a better feed conversion ratio, whereas performance declined at higher densities despite similar survival rates. Feeding behavior was generally consistent across groups, although feed intake rate was reduced at the highest density. Carcass and filet quality traits were unaffected by stocking density. Vegetable yield was enhanced by higher fish biomass, with significant increases in lettuce production and a positive trend for basil. These findings indicate that intermediate stocking densities may represent the most sustainable compromise, ensuring fish welfare and acceptable growth while supporting efficient plant production in largemouth bass–based aquaponics.
Keywords:
aquaponics; fish behavior; fish growth performance; fish survival; fish welfare
Key Contribution: Stocking density emerged as a central factor in shaping the overall performance of coupled aquaponic systems. Higher fish biomass increased nutrient availability and improved lettuce yield, but negatively affected largemouth bass growth and feed efficiency, even when water parameters remained within acceptable ranges. Balancing fish welfare and plant production suggests that intermediate stocking densities may represent the most sustainable compromise for largemouth bass–based aquaponics.

1. Introduction

Aquaponics is an innovative and sustainable food production technology that integrates fish farming (aquaculture) with soilless crop cultivation (hydroponics) in recirculating systems, where animals, plants, and microorganisms interact in mutualistic symbiosis. In these systems, nutrient-rich aquaculture effluents are biologically converted and subsequently used to meet most of the nutritional requirements of plants [1]. Aquaponics offers multiple potential benefits that address the challenges of a growing global population, including environmentally friendly production of both fish and vegetables, reduced nutrient losses, and lower demands for water and land resources [2].
In aquaponic systems, defining the appropriate fish stocking density is crucial, as it represents the primary factor influencing water quality in terms of dissolved solids, nutrient concentrations, and metabolic waste production [3]. Both excessively high and excessively low stocking densities may have detrimental effects on fish performance, system profitability, and ecological sustainability [4]. A recent review further highlighted that the “golden stocking density” must balance economic viability with the avoidance of long-term physiological stress that ultimately reduces productivity and product quality [5]. Indeed, high stocking density is a major chronic stressor in farmed fish, impairing both fish welfare and plant growth [6,7]. Excessive fish biomass can increase oxygen consumption and waste production, leading to the accumulation of ammonia and nitrite. The accumulation of these compounds may induce chronic stress, reduce feed efficiency, and suppress growth in fish by affecting endocrine and immune functions [5]. At the same time, changes in nutrient availability and water chemistry can markedly influence plant performance. Elevated ammonium and nitrate concentrations may initially stimulate vegetative growth, but excessive levels or unbalanced N:P ratios can induce nutrient antagonisms, osmotic stress, and morphological alterations in roots and leaves. Moreover, suboptimal pH conditions, often resulting from the biological activity of fish and nitrifying bacteria, can reduce the solubility and uptake of key micronutrients thereby limiting photosynthetic activity and plant yield [3]. High stocking density has also been associated with a decline in fish quality, including reduced skin lightness, altered muscle pH, and lower water-holding capacity [8]. The physiological response to crowding stress is mediated by increased secretion of corticosteroids and catecholamines, which in turn alters behavior, immune competence, and overall disease resistance [9]. Conversely, low stocking density may underutilize the available culture space and thereby limit the economic efficiency of the system [5].
The largemouth bass (Micropterus salmoides) is an important freshwater carnivorous species of high economic relevance [9]. Its production has expanded considerably over the past decade, reaching about 800,000 tons in 2022, with China contributing over 95% of the global volume [10]. Due to its fast growth, high market value, and flesh quality, it represents a key species for intensive aquaculture and an attractive candidate for integration into aquaponic systems. A recent study by Fischer et al. [11], found that juvenile largemouth bass reared in aquaponic systems displayed no significant differences in survival, growth, feeding efficiency, or condition when compared with individuals reared in an equivalent intensive recirculating aquaculture system (RAS). Originally introduced worldwide for its rapid growth, desirable flesh quality, and high market value [12], this species has also proven suitable for intensive aquaculture. In commercial-scale in-pond raceway systems, largemouth bass have been successfully reared at densities up to 114 fish/m3, corresponding to an initial biomass of approximately 4.0 kg/m3, without negative effects on growth performance or evidence of chronic stress [13].
To date, however, limited information is available on the performance of largemouth bass reared in recirculating aquaponic systems [11,14]. Bordignon et al. [15] tested this species in a low-tech aquaponic setup at two initial stocking densities (4.23 kg/m3 and 8.05 kg/m3), reporting limited growth performance and no significant differences among groups in morphometric indices, slaughter traits, or filet quality. In the same system, Birolo et al. [7] observed that rainbow trout reared at high initial density (7.26 kg/m3) did not experience stressful conditions during a 117-day growth period and produced high-quality flesh. Conversely, Maucieri et al. [3] showed that a low initial stocking density (2.5 kg/m3) improved both carp production and leafy vegetable yield compared to a higher density (4.6 kg/m3), by contributing to more stable water quality. In tilapia-based aquaponics, Al-Zahrani et al. [16] reported that high stocking density improved vegetable yield but compromised fish survival and feed conversion efficiency. Taken together, these findings indicate that the effects of stocking density in aquaponics are highly species- and system-dependent, underscoring the need for further research to clarify the suitability of largemouth bass for recirculating aquaponic systems. Furthermore, few information is still available on fish behavior especially in alternative production systems.
In this context, the present study investigated the effects of three stocking densities on fish survival, growth, and feeding behavior, as well as on the yield of three leafy vegetables: lettuce (Lactuca sativa L.), sweet basil (Ocimum basilicum L.), and Swiss chard (Beta vulgaris var. cicla), cultivated in a vertical recirculating aquaponic system.

2. Materials and Methods

2.1. Experimental Conditions

The trial was carried out at the experimental farm of the University of Padua, North-East Italy (45°2′ N, 11°57′ E, 6 m a.s.l.), inside a plastic greenhouse to ensure protection from external climatic variability. The system comprised nine independent experimental units, each designed to operate as a closed recirculating aquaponic module (Figure 1). Each unit consisted of: one insulated fish tank (500 L, height 0.80 m, diameter 1.00 m) with a central drain; one decanter (20 L, height 0.41 m, diameter 0.25 m) for the sedimentation of feed residues and feces; one biofilter tank (100 L, height 0.63 m, diameter 0.45 m) filled with plastic carriers (Bio-balls aquatecno, SCUBLA S.r.l., Remanzacco, Italy; specific surface 340 m2/m3) to support nitrifying bacterial colonization; one settling tank (50 L, height 0.32 m, diameter 0.45 m) for filtered water collection; nine vertical cultivation towers (height 1.70 m, width 105 mm, depth 90 mm) filled with felt and plastic material to sustain plant growth; and one storage tank (275 L, height 0.35 m, diameter 1.00 m) for water collection prior to recirculation into the fish tank.
Water recirculation was maintained by an immersion pump (NEWA Jet 1700, 33 W, 1700 L/h, TecnoIndustria Srl, Loreggia, Italy) ensuring continuous flow between components. An additional pump (NEWA Jet 4500, 33 W, 4500 L/h, TecnoIndustria Srl, Loreggia, Italy) conveyed filtered water to the top of the cultivation towers, where it was distributed through a drip irrigation system equipped with 4 L/h drippers at the head of each tower. Water inflow into the fish tanks was regulated by a tap set at 8 L/min, and tanks were covered with fitted lids to prevent fish escape.
Aeration was guaranteed by two diaphragm aerators (SCUBLA D100, 106 W, Scubla Srl, Remanzacco, Italy), each with a nominal capacity of 102 L/min. Air was supplied to both the fish tank and the biofilter via porous stones (4 cm × 4 cm × 15 cm, 14 L/min; Sweetwater® AS15S, Pentair, Cary, NC, USA). Establishment of a mature bacterial population in the biofilter was verified through routine monitoring of nitrate and nitrite concentrations.
The experimental design followed a randomized complete block structure with three treatments and three replicates per treatment, each replicate consisting of one independent aquaponic unit. Treatments were defined by initial fish stocking density: very low (D3, 3.1 kg fish/m3), low (D4, 4.1 kg fish/m3), and moderate (D6, 6.2 kg fish/m3). These levels were chosen to represent a gradient of rearing conditions, from extensive to more intensive practices, in order to evaluate the effect of stocking density on both fish performance and system functionality. The three stocking densities (3.1, 4.1, and 6.2 kg/m3) were selected according to the recommendations for small-scale aquaponic systems, which suggest maximum levels of 10–20 kg/m3, and in agreement with previous studies applying similar stocking ranges [3,7,15]. The use of independent units ensured no water exchange among treatments, thereby preventing cross-contamination and guaranteeing true experimental replication. Random allocation of the nine units to treatment groups was adopted to minimize potential bias due to tank location within the greenhouse.

2.2. In Vivo Trial and Recordings

At the beginning of the experiment, each experimental unit was supplemented with 132 g KH2PO4, 197 g K2SO4, 273 g MgSO4·7H2O, 10 g Fe-EDTA, and 5 g of a micronutrient mixture to ensure adequate mineral availability for plant growth.
A total of 184 largemouth bass (Micropterus salmoides, initial body weight 109 ± 28 g) were supplied by a commercial farm (Vicenzi Persici, Finale Emilia, Modena, Italy), transported to the experimental facilities, and randomly distributed among the three experimental groups. Stocking ranged between 15–17 fish per tank in group D3 (very low density, 3.1 kg/m3), 16–20 fish per tank in group D4 (low density, 4.1 kg/m3), and 24–29 fish per tank in group D6 (moderate density, 6.2 kg/m3). Prior to the start of the trial, fish underwent an 18-day acclimation period, during which they were hand-fed to apparent satiety twice daily with a commercial extruded diet (NaturAlleva, Verona, Italy; composition: 92.5% dry matter, 42.5% crude protein, 16.7% crude fat, 0.86% crude fiber).
The experimental trial lasted 176 days (June–November) under natural photoperiod conditions. During the trial, fish were fed manually twice a day (09:00 and 16:00 h) to apparent satiation with the same commercial diet used during acclimation. Feed was administered manually by adding a few pellets at a time, and feeding was stopped when a pellet reached the bottom of the tank without being eaten. This procedure ensured consistent feeding conditions across tanks and minimized feed waste. No antibiotics or other chemotherapeutic treatments were administered through either water or feed.
In parallel with fish rearing, three successive plant crop cycles were conducted in each aquaponic unit: lettuce (Lactuca sativa L., 42 days), sweet basil (Ocimum basilicum L., 74 days; harvested twice, at day 41 and day 33 of the cycle), and Swiss chard (Beta vulgaris var. cicla, 60 days). For each cycle, 72 plants were cultivated per unit (eight plants per tower, arranged at 20 cm intervals). Standard horticultural practices were followed, and no pesticides were used throughout the experiment.

2.3. Water Quality

Throughout the trial, water loss from each unit was recorded daily and manually replenished. Water temperature, dissolved oxygen (DO), and oxygen saturation were measured daily using an optical oximeter (OxyGuard Polaris C, Scubla Srl, Remanzacco, Italy). Three times per week, pH and electrical conductivity (EC) were measured with a portable multi-parameter meter (HQ40d, Hach Lange GmbH, Willstätterstr, Germany). On the same days, chlorophyll content in the water was assessed using a fluorescence detector (HHLD Fluorescence-Chlorophyll, Turner Designs, San Jose, CA, USA). Concentrations of nitrite (NO2−), nitrate (NO3−), and ammonium (NH4+) were determined weekly by ion chromatography, following the protocol described in Maucieri et al. [3].

2.4. In Vivo Recordings on Fish

Fish health, mortality, and feed intake were monitored daily throughout the trial. In detail, fish health was monitored daily by visual inspection to detect potential alterations in swimming activity, feeding response, or external appearance (e.g., skin lesions, fin damage, or discoloration). Dead fish were immediately removed from the tanks, recorded, and promptly transported to the National Reference Centre for Fish, Crustacean and Mollusc Pathology at the Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe, Legnaro, Italy) for diagnostic assessment of the causes of death. Individual body weight was recorded at five time points: the beginning of the trial (day 0), the end of the lettuce cycle (day 41), the end of the basil cycle (day 110), mid-way through the Swiss chard cycle (day 138), and at the end of the experiment (day 176). Weighing was performed using a precision scale (KERN CXB, 1 g accuracy; Kern and Sohn, Albstadt, Ebingen, Germany). During weighing the total length of each fish was also recorded. For these procedures, fish were netted from the rearing tank, transferred into a separate basin, and anesthetized with clove oil (4 mL containing 90% eugenol per 20 L of water). Feeding was suspended for 24 h before each weighing session.
Specific growth rate (SGR), condition factor and feed conversion ratio (FCR) were calculated for each experimental period using the following equations:
SGR (%/d) = [(Loge Final weight (g) − Loge Initial weight (g))/No. of days] × 100
Condition factor = [body weight (g)/(total length (cm))3]
FCR = [weight of dry feed distributed (g)/net wet weight gain of fish (g)]
Feeding behavior was assessed by two trained observers using underwater video recordings. A submerged camera (Exprotrek Action Cam 4K, Willrun Fitness Technology Co., LTD., Denver, CO, USA) was placed in the fish tanks 30 s before feed distribution and removed 30 s after the end of the meal. The camera was positioned 15 cm below the water surface, close to the tank wall, in order to capture the largest possible field of view and include all fish in the feeding area.
Behavioral observations were carried out between days 114 and 144, with recordings taken twice per week during morning meals. To ensure fish acclimation to the recording procedure, the camera was introduced at the beginning and removed at the end of meals for two weeks prior to data collection. Preliminary recordings obtained during the adaptation period were used to train the observers and standardize scoring procedures.
Behavioral variables were extracted from the videos and classified according to the descriptors listed in Table 1. Data were annotated on structured Excel spreadsheets for subsequent analysis. To ensure reliability of scoring, both observers were blinded to treatment allocation during video analysis.

2.5. Recordings at Fish Slaughtering and Vegetable Harvesting

At the end of the rearing period, all fish were slaughtered following fasting for 24 h. Fish were netted from the tanks, transferred to a separate basin, anesthetized with 10 mg/L clove oil, and manually restrained using a plastic knob before percussive stunning was applied to the head. Each fish was weighed, measured for total length, individually tagged, and stored in polystyrene boxes with ice in a cold room (0–2 °C) for 24 h. After chilling, all fish were eviscerated and weighed.
From the total population, 54 fish (six per tank, 18 per experimental group) were randomly selected for detailed carcass and tissue analysis. For these individuals, weights of visceral pack (including heart, gas bladder, and gonads), liver, and filets (with skin) were recorded. The following indices were calculated:
Hepatosomatic index = [liver weight (g)/final weight (g)] × 100
Viscerosomatic index = [visceral pack weight (g)/final weight (g)] × 100
Carcass yield = [eviscerated carcass weight (g)/final weight (g)] × 100
Filets yield = [filets weight (g)/final weight (g)] × 100
After dissection, skin was removed from the filets and color was assessed at three points on the dorsal surface of the right filet using a Minolta CM–508C spectrophotometer (Minolta Corp., Ramsey, NJ, USA) to obtain L*, a*, and b* indices. Muscle pH was measured at three points on the dorsal side of the same filet with a portable pH meter (Basic 20; Crison Instruments SA, Carpi, Italy) equipped with a specific electrode (cat. #5232; Crison Instruments SA).
In parallel with fish harvesting, all aboveground biomass of lettuce, basil (two harvests), and Swiss chard was collected from each unit to determine the fresh weight of leaves and quantify the marketable yield of each crop cycle.

2.6. Statistical Analysis

All data were analyzed with SAS software (v. 9.4; SAS Institute Inc., Cary, NC, USA). Data were tested for normality using the Shapiro–Wilk test and for homogeneity of variances using Levene’s test. Water quality parameters that did not meet the assumption of normality were analyzed by non-parametric tests. Differences among density groups were assessed using the Kruskal–Wallis test (PROC NPAR1WAY, option WILCOXON), followed by pairwise multiple comparisons with the Dwass–Steel–Critchlow–Fligner procedure. Growth performance, slaughter results and flesh quality traits were analyzed by one-way ANOVA using the PROC GLM procedure, with stocking density as fixed effect. Least squares means (LS-means) were compared among groups with Bonferroni adjustment. Daily mortality was expanded to individual records, coding death events as 1 and survivors at the end of the trial as 0. Kaplan–Meier survival curves were estimated with PROC LIFETEST, stratified by stocking density (D3, D4, D6). Survival functions were compared using the log-rank test, and survival curves were plotted with PROC SGPLOT. For behavioral data, inter-observer repeatability was assessed using a linear mixed model (PROC MIXED) including observer as a random effect. The variance attributable to the observer accounted for approximately 2.4% of the total variance, whereas residual variance exceeded 95%, indicating a high level of agreement between observers. Therefore, the observer was excluded from the final statistical models to reduce complexity and improve convergence. For categorical and binary behavioral variables, inter-observer agreement was further evaluated using Cohen’s or Fleiss’ Kappa coefficients. Feeding behavior data were subsequently analyzed using generalized linear mixed models (PROC GLIMMIX). For each behavioral variable, the most appropriate distribution and link function were defined based on preliminary assessment with PROC UNIVARIATE. Fixed effects included stocking density and day of observation, while tank was fitted as a random effect. A compound symmetry structure was specified for the residuals to account for repeated measures within tanks. LS-means were compared among groups using Bonferroni adjustment.

3. Results

3.1. Water Quality

Water quality parameters were generally maintained within the acceptable range for largemouth bass throughout the trial. DO did not change significantly among groups, whereas oxygen saturation was significantly lower in group D6 compared with D3 and D4 (p = 0.003; Figure 2).
Water temperature remained stable across treatments varying from 18 to 27 °C during the trial (Figure 3). Differences were observed in water pH, turbidity, and chlorophyll, with D6 showing lower pH and higher values of turbidity and chlorophyll compared to D3 and D4 (p < 0.05; Figure 3).
Among the nitrogen fractions, ammonium and nitrate concentrations were significantly higher in group D6 compared with D3 and D4, whereas nitrite levels remained unaffected by stocking density (Figure 4). Consistently, overall dissolved nutrient concentration, expressed as electrical conductivity (EC), also differed among groups, with the highest values recorded in D6 (p < 0.05).

3.2. Survival and Growth Performance of Fish

Fish mortality began between days 8 and 10 of the trial and stabilized around day 20 in group D3, whereas sporadic deaths continued in groups D4 and D6 until approximately day 74. A second increase in mortality was observed in all groups during the final phase of the trial (from day 138 onwards), leading to a cumulative loss of 48 fish over the entire trial period. The overall survival rate at day 176 was 73.9%, with no significant differences among treatments (Figure 5). Diagnostic analyses attributed mortality events primarily to infections caused by the protozoan Ichthyophthirius multifiliis and the bacterium Aeromonas salmonicida subsp.
Growth performance was markedly influenced by stocking density. At the beginning of the trial, fish in group D3 had the lowest individual body weight; however, they outperformed the other groups from day 110 onwards, showing the highest body weights at days 110, 138, and at the end of the experiment (p ≤ 0.01; Figure 5).
Fish in group D6 consistently showed the lowest body weights, while intermediate values were recorded in group D4. The highest SGR values were recorded in group D3 during the early (0–41 days), intermediate (41–110 days), and mid (110–138 days) periods of the trial, whereas in the final phase (138–176 days) the best SGR was observed in group D4. Group D6 consistently exhibited the lowest SGR across all experimental periods (p < 0.05; Figure 6).
Throughout the trial, fish in group D3 achieved the highest daily weight gain (0.69 g/day) and SGR (0.43%/day), followed by D4 (0.61 g/day; 0.39%/day), whereas D6 consistently showed the lowest values (0.50 g/day; 0.34%/day) (p < 0.001; Table 2). Feed intake was significantly higher in D3 (0.72% biomass/day) compared with D4 and D6 (0.60–0.61% biomass/day; p = 0.015). Consistently, feed conversion ratio was less efficient in D6 (1.76) than in D3 and D4 (1.43–1.46; p = 0.009). Although both initial and final fish biomass increased with stocking density (p < 0.05), net biomass gain did not differ significantly among treatments (p = 0.839).

3.3. Feeding Behavior

The behavioral observations showed that most feeding descriptors were not significantly affected by stocking density (Table 3). Attack latency was generally short, with mean values ranging between 0.31 and 0.60 s, indicating a prompt reaction of fish to feed distribution. Feeding score averaged around 2 across all groups. Fish consumed feed mainly in the upper and middle layers of the tank (mean level score 1.6–1.9). On average, the number of unsuccessful approaches (attempts) ranged from 2.1 to 3.3 per meal, while the number of successful attacks was markedly higher, between 47 and 65 per meal, confirming an overall high feeding motivation. Feeding duration was relatively short, lasting between 47 and 65 s. Feed intake rate differed significantly among treatments (p = 0.003), being markedly lower in D6 (1.23 g/fish/min) compared with D3 (2.21 g/fish/min) and D4 (1.93 g/fish/min).

3.4. Carcass Characteristics and Filet Quality

Carcass yield, VSI and HSI were not significantly affected by stocking density, with average values around 91.0%, 4.95% and 2.34%, respectively (Table 4).
Filet yield averaged 46.5% without significant differences among groups. Similarly, no significant differences were detected for muscle pH (average 6.46–6.47) or color parameters (L*, a*, b*), which remained consistent across treatments, indicating that flesh quality traits were not negatively influenced by stocking density.

3.5. Vegetables Production

The yields of leafy vegetables cultivated in the aquaponic units are reported in Table 5. Lettuce yield was significantly influenced by fish stocking density (p = 0.007), being higher in D4 and D6 (9.6 kg/m2) compared with D3 (6.1 kg/m2). Sweet basil also tended to show greater productivity in D6 (13.1 kg/m2) than in D3 and D4 (10.6–11.1 kg/m2), although the differences were not statistically significant (p = 0.085). Swiss chard yields were similar across treatments, ranging from 7.5 to 9.8 kg/m2, with no significant effect of stocking density.

4. Discussion

In coupled aquaponic systems, where aquaculture and hydroponic units share the same recirculating water [21,22], maintaining optimal conditions of temperature, dissolved oxygen, pH, and chemical composition is essential for both fish and plants [23,24]. Within this balance, stocking density is a key driver of nutrient concentration, dissolved gases, and waste accumulation, and therefore strongly influences water quality, plant productivity, and fish welfare [6,21,25]. While adequate stocking densities are necessary for system productivity and economic viability, high densities are often linked to chronic stress, impaired growth, reduced feed efficiency, and higher disease susceptibility [5,26,27]. According to Li et al. [28], crowding stress may impair fish growth by interfering with the tricarboxylic acid cycle, the central metabolic pathway that interconnects the utilization of proteins, carbohydrates, and lipids, through modifications in gene expression or alterations in protein and enzyme activities. Moreover, prolonged exposure to high stocking density has been shown to disrupt the intestinal microbiota and impair intestinal cell function in largemouth bass, thereby contributing directly to structural damage of the gut and compromising growth [29]. However, the scientific literature shows conflicting results regarding how largemouth bass respond to different stocking densities. Wang et al. [9] demonstrated that fish growth decreased and stress indicators increased when fish were stocked at 0.4–0.6 kg/m3 compared to 0.2 kg/m3. Wang et al. [30] studied container RAS and found that fish grew better at 50 fish/m3 (≈6.9 kg/m3) than at 75 and 100 fish/m3 (≈10.3 and 13.7 kg/m3, respectively). Xi et al. [31] demonstrated that fish growth performance, condition factor and feed conversion ratio improved at stocking densities of 30 fish/m3 (≈4.7 kg/m3) compared to 40, and 50 fish/m3 (≈6.24, and 7.80 kg/m3). Conversely, other studies found no significant influence of stocking density on performance. Wang et al. [13] reported that largemouth bass reared in in-pond raceway systems at two stocking densities (2.45 vs. 4.10 kg/m3) showed similar growth and feed utilization. Likewise, largemouth bass stocked in RAS at 30, 60, or 120 fish/m3 (≈3.36, 6.72, and 13.44 kg/m3) achieved comparable survival, harvest weight, and FCR, although total biomass density increased proportionally with stocking rate [32]. More recently, Si et al. [33] demonstrated that juvenile largemouth bass stocked at 100 fish/m2 (≈0.069 kg/m3) had improved growth and feed efficiency compared to lower density treatments (90–60 fish/m2; 0.062–0.041 kg/m3). In a 300-day trial with largemouth bass of 8.25 g initial body weight, Ni et al. [34] identified 114 fish/m3 as the optimal stocking density in in-pond raceway systems, as this level resulted in superior growth performance and a more favorable benefit-to-cost ratio compared with 91 fish/m3. These contrasting results suggest that the response of largemouth bass to stocking density is strongly context-dependent. Factors such as production system, fish age and size, feeding strategy, and water quality can modulate the effects of density on growth and welfare [35,36], thereby explaining the variability observed among studies. Differences in fish size and developmental stage also play a key role, since metabolic demand, oxygen consumption, and waste production increase with body weight [9,31]. Feeding strategy further contributes to variability, as feeding frequency and ration size directly affect nutrient load, dissolved oxygen, and the accumulation of metabolic wastes [5,36]. Finally, the dynamic interplay between pH, dissolved oxygen, and nitrogenous compounds modulates both fish welfare and plant nutrient uptake efficiency [3,25]. Collectively, these interacting factors explain the inconsistent patterns reported across studies and highlight the need for density optimization within the specific context of each aquaponic system.
The findings of the present study support the body of evidence showing that high fish density in the system lead to negative outcomes because the weight gain and specific growth rate decreased when the stocking density increased from 3.1 to 6.2 kg/m3. The growth performance in this study fell below the values recorded in pond systems and RAS and industrial aquaponics [11,14,37,38,39], but exceeded the values from low-tech aquaponics [15]. The suboptimal results in this study could have resulted from bacterial (Aeromonas salmonicida) and protozoan (Ichthyophthirius multifiliis) infections that occurred during the trial which led to fish deaths and decreased growth rates.
Although water quality parameters remained within acceptable ranges for largemouth bass [40], increasing stocking density progressively impaired water quality by increasing ammonia, nitrate, turbidity, and chlorophyll. DO levels were unaffected by treatment and consistently suitable for fish welfare [41], nutrient uptake, and nitrifying bacteria activity [25]. However, oxygen saturation declined at higher densities, likely due to elevated respiratory demand from fish and microbial communities [3,42,43]. These results confirm that even within safe ranges, subtle deteriorations in water quality can contribute to reduced growth performance under crowding.
Video recordings provided novel insights into largemouth bass behavior in aquaponics. The recordings were performed during a period of stable health status, as confirmed by the plateau phase of the survival curves, ensuring that the behavioral patterns observed were not biased by morbidity or disease. Fish displayed short attack latencies and high reactivity to feed, consistent with their predatory nature [18]. In the present trial, largemouth bass frequently moved to intercept pellets and then returned to their original position, a pattern that has also been described in L. longirostris [44]. Among behavioral descriptors, only feed intake rate was significantly affected, being lower at the highest density. This likely reflects increased competition and reduced feeding opportunities per fish. Comparable effects of crowding on foraging efficiency and aggression have been reported in other cultured species [36,45]. However, in the present study, no direct aggressive interactions were observed during behavioral recordings. Occasional territorial displays, such as short-distance chases near feeding zones, were noted but were not associated with physical contact or subsequent mortality. Post-mortem analyses did not reveal lesions consistent with physical aggression, as most deaths were attributed to Aeromonas salmonicida and Ichthyophthirius multifiliis infections. Nevertheless, stress induced by intraspecific competition and crowding could have increased disease susceptibility and indirectly contributed to the observed mortality. Overall, the use of video-based monitoring also proved to be a valuable tool for quantifying feeding dynamics, allowing the identification of subtle changes in latency, attack frequency, and intake rate. Previous studies have also emphasized behavioral monitoring as a complementary approach to growth and health indicators [46,47].
Aquaponics has already been recognized as a valuable production system not only for its environmental sustainability but also for the quality of fish and vegetables obtained. Karlik et al. [48] demonstrated that yellow perch (Perca flavescens) reared in a recirculating multitrophic aquaculture system were comparable to wild-caught and farmed counterparts in texture, moisture, total fat, and protein content. Moreover, aquaponic perch were rated as highly as wild-caught perch in consumer sensory tests, and when consumers were informed about the environmental benefits of aquaponics, perceived tastiness, healthiness, and purchase intention significantly increased, in some cases surpassing those for wild-caught fish. Similarly, Atique et al. [2] compared rainbow trout (Oncorhynchus mykiss) raised in RAS versus coupled aquaponics with baby spinach (Spinacia oleracea) and found that the aquaponic setup promoted better fish growth, and lower concentrations of off-flavor compounds (geosmin) in fish flesh. In the case of largemouth bass, the filet quality traits recorded in our aquaponic system were comparable to those reported for pond-reared fish [37,49]. Although high stocking density has been associated with flesh quality alterations such as reduced skin lightness, decreased muscle pH and water-holding capacity [8], as well as increased lipid oxidation and reduced filet firmness [50], no significant differences in filet quality were observed in the present trial. This outcome is consistent with previous aquaponic studies [7,15], and indicates that moderate crowding did not compromise product quality.
In this study, daily water replacement averaged 1.6% of system volume, in line with literature values (0.05–5.0%) [51], thus confirming the high water use efficiency of the aquaponic system. Regarding crops, aquaponics has been shown to equal or surpass hydroponics for lettuce, herbs, and fruiting vegetables [3,52], thanks to continuous nitrogen supply and microbial-assisted nutrient uptake [53]. In the present trial, the vegetable yields exceeded those reported in previous studies [7,54], likely due to the use of vertical farming. Indeed, vertical farming systems are renowned for their high production intensity: for example, a ten-layer vertical farm has been shown to yield up to 76–116 times more crop per unit area than field farming, and 40–80 times more than greenhouse production [55]. In our trial, lettuce yield increased significantly with fish density, and basil showed a similar trend, consistent with higher nutrient inputs from greater fish biomass [56]. However, no density effect was observed for Swiss chard, confirming that nutrient concentration alone does not guarantee higher plant productivity unless supported by favorable water chemistry, particularly pH and mineral balance [57]. Interestingly, feeding to apparent satiation led to relatively higher feed intake at low density, likely due to better water quality and lower competition, which reduced the nutrient gap between groups. This may explain why plant yield differences across treatments were not more pronounced in the later crop cycle.

5. Conclusions

This study shows that fish stocking density exerts a dual influence in coupled aquaponic systems with largemouth bass. On the one hand, higher densities can increase the biomass of fish produced and the nutrient availability in the system while enhancing the vegetables yield. On the other hand, even moderate crowding can impair fish growth, feed efficiency, and overall performance, despite water parameters remaining within acceptable limits. Increasing stoking density from very low to moderate values does not compromise the flesh quality and marketability of aquaponic bass but can affect fish feeding behavior.
These findings highlight the need to identify an optimal balance between fish performance and plant productivity to maximize the efficiency and sustainability of aquaponics while ensuring fish welfare. In practical terms, intermediate stocking densities may represent the most suitable compromise, supporting both animal welfare and vegetable yield. Future research should investigate longer production cycles, multiple species combinations, and strategies to stabilize water quality under high biomass loads in order to refine management guidelines for commercial-scale aquaponics.

Author Contributions

Conceptualization, M.B. and C.N.; methodology, M.B. and C.N.; formal analysis, M.B.; investigation, M.B., V.T. and S.T.; resources, M.B., C.N. and P.S.; data curation, M.B., V.T. and S.T.; writing—original draft preparation, M.B. and V.T.; writing—review and editing, M.B., P.S. and C.N.; visualization, M.B. and C.N.; supervision, M.B. and C.N.; project administration, C.N.; funding acquisition, P.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the Sustainable Vertical Farming (VFarm) project funded by the Italian Ministry of University and Research (MUR) under the National Research Programmes of Significant Interest (PRIN) (Project code: 2020ELWM82; CUP: J33C20002350001).

Institutional Review Board Statement

The study was approved by the Ethical Committee for Animal Experimentation (Organismo Preposto al Benessere degli Animali, OPBA) of the University of Padova (prot. n. 1581/2021; 1 February 2021). All animals were handled according to the principles stated in EC Directive 2010/63/EU (European Commission, 2010).

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
ANOVAAnalysis of Variance
DODissolved oxygen
ECElectrical conductivity
FCRFeed conversion ratio
HISHepatosomatic index
RASLeast square means
RMSERoot mean square error
SASStatistical analysis system (software)
SGRSpecific Growth Rate
VSIViscerosomatic Index

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Figure 1. Schematic representation of the aquaponic unit. A, fish tank (500 L); B, decanter (20 L); C, biofilter tank (100 L); D, settling tank for water collection and pumping to the cultivation towers (50 L); E, vertical cultivation towers; F, storage tank for water collection and pumping to the fish tank (275 L).
Figure 1. Schematic representation of the aquaponic unit. A, fish tank (500 L); B, decanter (20 L); C, biofilter tank (100 L); D, settling tank for water collection and pumping to the cultivation towers (50 L); E, vertical cultivation towers; F, storage tank for water collection and pumping to the fish tank (275 L).
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Figure 2. Boxplots of dissolved oxygen (DO) concentration (a) and oxygen saturation (b) in the water of aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
Figure 2. Boxplots of dissolved oxygen (DO) concentration (a) and oxygen saturation (b) in the water of aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
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Figure 3. Boxplots of water temperature (a), pH (b), turbidity (c), and chlorophyll (d) concentration in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
Figure 3. Boxplots of water temperature (a), pH (b), turbidity (c), and chlorophyll (d) concentration in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
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Figure 4. Boxplots of ammonium (NH4+) (a), nitrite (NO2−) (b), nitrate (NO3−) (c), and electrical conductivity (EC) (d) in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
Figure 4. Boxplots of ammonium (NH4+) (a), nitrite (NO2−) (b), nitrate (NO3−) (c), and electrical conductivity (EC) (d) in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Different letters over the bars indicate significant differences among groups (p < 0.05).
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Figure 5. Kaplan–Meier survival curves of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
Figure 5. Kaplan–Meier survival curves of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
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Figure 6. Live weight (a) and specific growth rate (SGR) (b) of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Values are expressed as LS-means ± 95% confidence limits. Different letters indicate significant differences among groups (p < 0.05).
Figure 6. Live weight (a) and specific growth rate (SGR) (b) of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Values are expressed as LS-means ± 95% confidence limits. Different letters indicate significant differences among groups (p < 0.05).
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Table 1. Descriptors of the feeding behavior of fish.
Table 1. Descriptors of the feeding behavior of fish.
Feeding BehaviorDescription
Attack latency (s)Time elapsed between the entry of the feed (extruded pellet) into the tank and the first successful attack that resulted in ingestion [17,18].
Score (0–3)Feeding activity score: 0, no response to feed; 1, ingestion only of pellets falling directly in front of the fish without active movement; 2, fish move to capture feed but return to the original position; 3, fish move freely between feed items and ingest all presented pellets [19].
Level (1–3)Vertical location in the tank where most feed was consumed: 1, surface; 2, mid-water; 3, bottom [19,20].
Attempts (n)Number of approaches to the feed without ingestion [18].
Attacks (n)Number of approaches to the feed resulting in ingestion [18].
Duration (s)Time elapsed between the first and the last successful attack during a meal.
Feed intake rate (g/fish/min)Feed consumption rate per fish, calculated as the ratio of the total feed consumed to the duration of the meal and the number of fish in the tank.
Table 2. Productive performance of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Data are expressed as LS-means.
Table 2. Productive performance of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Data are expressed as LS-means.
GroupRMSEp-Value
D3D4D6
Tanks, n333
Total length at 176 days (cm)25.224.424.00.87<0.001
Condition factor at 176 days1.441.491.440.110.067
Daily weight gain from 0 to 176 days (g/day)0.69 a0.61 b0.50 c0.08<0.001
Specific growth rate from 0 to 176 days (%/day)0.43 a0.39 b0.34 c0.04<0.001
Feed intake from 0 to 176 days (% biomass/day)0.72 a0.60 b0.61 b0.040.015
Feed conversion ratio from 0 to 176 days1.46 a1.43 a1.76 b0.090.009
Initial biomass (kg/m3)3.112 c4.094 b6.218 a0.168<0.001
Final biomass (kg/m3)5.437 b5.968 ab8.065 a1.0320.045
Biomass growth from 0 to 176 days (kg/m3)2.3251.8741.8471.0920.839
RMSE = Root mean square error. a,b,c Values within a row with different superscript letters differ significantly (p < 0.05).
Table 3. Feeding behavior of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Data are expressed as mean ± standard error.
Table 3. Feeding behavior of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3). Data are expressed as mean ± standard error.
Groupp-Value
D3D4D6
Tanks, n333
Attack latency (s)0.38 ± 0.130.60 ± 0.130.31 ± 0.090.058
Score2.04 ± 0.051.96 ± 0.092.15 ± 0.060.343
Level1.83 ± 0.091.85 ± 0.101.63 ± 0.080.493
Attempts (n)2.10 ± 0.332.83 ± 0.403.31 ± 0.550.200
Attacks (n)47.0 ± 3.649.7 ± 4.365.0 ± 5.00.129
Feeding duration (s)47.4 ± 3.347.2 ± 3.565.4 ± 4.30.314
Feed intake rate (g/fish/min)2.21 ± 0.16 a1.93 ± 0.12 a1.23 ± 0.06 b0.003
a,b Values within a row with different superscript letters differ significantly (p < 0.05).
Table 4. Carcass characteristics and filet quality traits of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
Table 4. Carcass characteristics and filet quality traits of largemouth bass reared in aquaponic units at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
GroupRMSEp-Value
D3D4D6
Carcass characteristics
 Carcass yield (%)91.290.491.34.730.649
 Hepatosomatic index (%)2.382.422.210.510.074
 Viscerosomatic index (%)5.004.874.970.890.808
Filets quality traits
 Filets yield (%)46.646.846.02.050.320
 pH6.476.466.470.090.942
 L*40.340.840.62.820.830
 a*−3.31−3.64−3.660.4820.058
 b*1.421.781.611.300.710
RMSE = Root mean square error.
Table 5. Marketable yield of lettuce (Lactuca sativa L.), sweet basil (Ocimum basilicum L.), and Swiss chard (Beta vulgaris var. cicla) cultivated in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
Table 5. Marketable yield of lettuce (Lactuca sativa L.), sweet basil (Ocimum basilicum L.), and Swiss chard (Beta vulgaris var. cicla) cultivated in aquaponic units with largemouth bass reared at three initial stocking densities: D3 (3.1 kg/m3), D4 (4.1 kg/m3), and D6 (6.2 kg/m3).
GroupRMSEp-Value
D3D4D6
Lettuce yield, kg/m26.126 b9.587 a9.664 a0.9690.007
Sweet basil yield, kg/m211.07710.63613.1061.1670.085
Swiss chard yield, kg/m27.4898.4049.7761.7830.353
RMSE = Root mean square error. a,b Values within a row with different superscript letters differ significantly (p < 0.05).
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Birolo, M.; Trabacchin, V.; Sambo, P.; Triolone, S.; Nicoletto, C. Impact of Stocking Density on Growth, Feeding Behavior, and Flesh Quality of Largemouth bass (Micropterus salmoides) in Coupled Aquaponic Systems. Fishes 2025, 10, 552. https://doi.org/10.3390/fishes10110552

AMA Style

Birolo M, Trabacchin V, Sambo P, Triolone S, Nicoletto C. Impact of Stocking Density on Growth, Feeding Behavior, and Flesh Quality of Largemouth bass (Micropterus salmoides) in Coupled Aquaponic Systems. Fishes. 2025; 10(11):552. https://doi.org/10.3390/fishes10110552

Chicago/Turabian Style

Birolo, Marco, Veronica Trabacchin, Paolo Sambo, Stefano Triolone, and Carlo Nicoletto. 2025. "Impact of Stocking Density on Growth, Feeding Behavior, and Flesh Quality of Largemouth bass (Micropterus salmoides) in Coupled Aquaponic Systems" Fishes 10, no. 11: 552. https://doi.org/10.3390/fishes10110552

APA Style

Birolo, M., Trabacchin, V., Sambo, P., Triolone, S., & Nicoletto, C. (2025). Impact of Stocking Density on Growth, Feeding Behavior, and Flesh Quality of Largemouth bass (Micropterus salmoides) in Coupled Aquaponic Systems. Fishes, 10(11), 552. https://doi.org/10.3390/fishes10110552

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