Predicting the growth of gilthead sea bream (Sparus aurata L.) farmed in marine cages under real production conditions using temperature- and time-dependent models (original) (raw)
Related papers
Aquaculture Research, 2013
Modelling growth as a function of feeding rate (FR) could be one of the most important tools for fish farms, because this knowledge allows growth to be maximized, or the feed conversion ratio (FCR) to be minimized, thereby improving profits. All growth models should include the three principal variables involved in growth: initial body weight, temperature and feeding rate. The thermal-unit growth coefficient (TGC) already includes water temperature variation and initial body weight. Studying variation in TGC for fish fed the same diet, but at several feeding rates provides interesting information for modelling. Six different trials were conducted where gilthead sea bream of several different initial weights (24, 38, 50, 110, 220 or 289 g) were fed increasing amounts, and growth and the conversion index response were measured. The TGC response was modelled as a function of FR, and both asymptotic and quadratic responses were examined. The asymptotic model, TGC 9 1000 = 2.037* (1Àe (À0.8*(FRÀ0.22) ), had an adjusted R 2 value of 96.18, whereas the quadratic model, TGC 9 1000 = À0.381 + 1,715 9 FRÀ0,382 9 FR 2 , had an adjusted R 2 value of 96.42. Simulations of the FCR and the economical profitability index (EPI) were conducted to provide tools for maximizing efficiency and profitability, and the results suggest that these tools will be useful for future investigations.
A growth model for gilthead seabream ( Sparus aurata
Ecological Modelling, 2003
This paper presents a growth model for gilthead seabream (Sparus aurata), which is one of the most culture species in the Mediterranean area. The model is designed by means of stochastic differential equations, and is based on previous research for other species [Modélisation de la Croissance des Poissons en Élevage, 1990]. Fish growth is assumed to be influenced by three fundamental factors: fish weight, water temperature, and ration size. The formulation incorporates fish physiology theory, requiring fewer specific parameters than other bionenergetic models. Empirical data were obtained from culture in the Canary Islands waters for a 30-month period. Some simulations were run to validate the model. Although the influence of water temperature on fish growth might need to be refined, satisfactory results are obtained. Two environmental scenarios are also examined, the "Atlantic" and "Mediterranean," which vary in the annual cycles of water temperature. The results produce significant differences in the growth patterns between both areas, suggesting potential economic implications for the cultivation of larger commercial sizes.
GJIJE , 2024
Marine fish farming is an important activity to reduce fishing pressure on natural resources. This study sought to examine the effect of season of fingerlings introduction and initial stocking density on the growth performances of gilthead seabream (Sparus aurata) raised in offshore floating cages in Dakhla Bay The experiment was carried out at the offshore pilot farm of INRH located in Dakhla bay, for a period of 45 months. The total number of S. aurata fingerlings used during this study was 450,000, with an initial average weight of 3.95±0.47 g, and an initial mean length of 5.96±0.39 cm. The physicochemical parameters (temperature, dissolved oxygen, salinity and pH) recorded during the study period were within the optimal ranges for obtaining the expected growth and survival of gilthead seabream. Regarding the effect of rearing season on growth performance, no significant effect was observed (p>0.05). The harvest weight per fish for the entire rearing season reached over 500 g in 15 condition factor and survival rate values ranged from 1.12±0.21 to 1.09±0.19 (g day-1), 1.08±0.15 to 1.05±0.12 (%), 1.33±0.09 to 1.31±0.05, 1.90±0.05 to 1.75±0.06 and 88.73±0.37 to 86.93±0.47 (%), respectively. A significant difference was observed between the initial stocking density 1: 25 fish m-3 and initial stocking density 2: 35 fish m-3 with regard to their influence on growth performance. The period of rearing, weight gain, specific growth rate and survival rate increased with a decrease in stocking density. The results indicate that low stocking density led to better growth and gross benefit compared to high stocking density in gilthead seabreams. The findings of the present study provide information in terms of the year-round growth performance, as the effect of rearing season and stocking density.
Aquaculture Research
In this work, a seasonal quantile regression growth model for the gilthead sea bream (Sparus aurata L) based on an aggregation of the quantile TGC models with exponent 1/3 and 2/3, named the "Quantile TGC-Mixed Model", is presented. This model generalizes the proposal of Mayer et al. (2012) in the sense that the new model is able to describe the evolution of weight distribution throughout an entire production cycle, which could be a powerful tool for fish farm management. The information provided by the model simulations enables us to estimate total fish production and final fish size distribution, and helps to design and simulate production and sales plan strategies considering the market price of different fish sizes, in order to increase economic profits. The most interesting alternative in the studied case results in sending all production when 0.25 quantile fish reach 600 g, although on each fish farm it would be necessary to evaluate optimum strategy depending on its own quantile regression model, the production cost and the market price.
2022
The aim of the present investigation is to assess the growth performance of giltheadseabream fingerlings (Sparus aurata) farmed in marine cages at Boutalha site inDakhla Bay in Morocco for a period of fifteen months (March 2018 - July 2019). Fingerlings were imported from a European hatchery (50.000 individuals), with an average initial weight of 3.68 ± 0.16g and an average initial length of 6.23 ± 0.53cm. Specimens were placed in fish nurseries and treatments were duplicated in two batches, with 25.000 individuals/ batch. The physicochemical parameters, recorded during the study period, were within the optimal ranges for obtaining the appropriate growth and the survival of gilthead sea bream. In terms of growth performance, average weight (AW), daily growth rate (DGR), and the specific growth rate (SGR) were estimated to fall within the range of 512 ± 19.71g, 1.13 ± 0.08 g/day, and 1.09 ± 0.12 %/day, respectively for the first batch, and 520.29 ± 22.40g, 1.15 ± 0.06 g/day and 1.10 ± 0.15 %/day for the second batch. The relationship between the total body weight (TBW) of gilthead sea bream and total body length (TBL) could be expressed as: TBW1 = 0.039 TBL 2.892 (n =315, R² = 0.91) for batch 1 and TBW2 = 0.0035 TBL 2.935 (n =318, R² = 0.90) for batch 2. The final equation of the length-weight relationship of the two gilthead sea bream batches has an allometry coefficient close to 3, which represents isometric growth. Concurrently, the recorded final biomass values, as well as the feed conversion rate, amounted to 11.58 T and 1.18 ± 0.31, respectively for batch 1 and 11.65 T and 1.19 ± 0.34 for batch 2. These trials also demonstrate, for the first time, that the growth of gilthead sea bream is technically feasible, and indicates a potential for improvement through the implementation of a model project which is technically feasible at Dakhla bay.
Growth Rate of Gilthead Bream Sparus Aurata L
1990
In this study, growth rates of the gilthead bream Sparus aurata L. in their natural habitat (Egyptian Mediterranean waters) were determined. Absolute growth, annual increment and percentage annual gain (in length and weight) were estimated from scale reading. Regression equation representing fish length/scale radius relationship is given. The rate of increase in weight (W) with length (L) is described by the formula: Log W =-2.1724 + 3.2216 Log. L. Maximum expected length (Lx = 62.44 cm) and weight (W x = 4091.3 g) were computed using von Bertalanffy's growth equation.
Aquaculture International, 2011
In experimental culture conditions in tanks, the effect of weight (W: 11-452 g) and temperature (T: 14-29°C) on the growth rate (SGR, % bw day -1 ) and maximum daily food intake (SFR, % bw day -1 ) in sharpsnout sea bream (Diplodus puntazzo) was studied. The possible combined effect of both independent variables (W and T) was also analyzed by multiple regression analysis, fitting the data to the equation Ln Y = Ln a ? b Ln W ? cT ? dT 2 ? eT Ln W. Both SGR and SFR, and therefore feed efficiency (FE = SGR/SFR), were significantly influenced by the interaction between temperature and weight and may be expressed by means of the following equations: Ln SGR = -6.1705 ? 0.5809T -0.0087T 2 -0.0249T Ln W (R 2 adj = 0.949; ANOVA P \ 0.0001); Ln SFR = -4.8257 ? 0.4425T -0.0063T 2 -0.0163T Ln W (R 2 adj = 0.964; ANOVA P \ 0.0001).The results suggest that the optimum temperature for SGR and FE (T SGRopt and T FEopt ), and the temperature at which the maximum SFR (T SFRmax ) is reached, decreases with body weight, in accordance with the equations: T SGRopt = 33.297 -1.435 Ln W; T FEopt = 29.332 -1.890 Ln W; and T SFRmax = 34.
Aquaculture International, 2002
Sea bream (Sparus aurata) production is growing in the Mediterranean and the evaluation of its quality concerns both producers and consumers alike. In this area, most of the sea bream culture is carried out in cages but there is also production in land-based facilities. The culture system, and specifically its degree of intensity, greatly influences final product quality, through management during production, harvest and marketing processes. In this respect, land-based technology is more likely to affect final quality, both in a positive and in a negative way. In the present work the effects on sea bream (Sparus aurata) of three inland culture systems are studied. The quality of wild fish is also studied and taken as standard because it is the quality better known to the consumers. Different aspects related to biometry, sensorial evaluation, degree of freshness (pH and water holding capacity) and chemical composition of muscle are assessed. The influence of post-harvest management on the sensorial quality of cultured and fishery caught fish is also studied when they arrive at the market. According to the results all parameters, i.e. sensorial, freshness and biometric measures, show some significant differences according to the culture system. A super-intensive culture system significantly affects the appearance of the fish, producing more compact fish without the characteristic colour pattern of the species. The fish cultured in two different semi-intensive systems show more similarities with the wild fish, both in colour and appearance. Some differences in the freshness indices are also found, with the super-intensive cultured fish the ones showing the lowest results. When evaluating the influence of post-harvest management on semi-intensive cultured fish and wild fish, all freshness indices except gills are affected, but both groups of fish tolerate the process in a similar way.
2018
The available forecasting models for growth pattern in fish are based on either classical approach or a particular growth model. In the present study, reparamerisation methodologies were attempted for forecasting growth of fish cultured in cemented ponds of plain areas. Forecasting methodology is not readily available for any other types of ponds for uplands of India. So, other appropriate growth curves (Logistic, Gompertz and von-Bertalanffy) were considered while developing the most suitable model for forecasting fish (common carp Cyprinus carpio var communis and silver carp Hypophthalmichthys molitrix) production from cemented ponds. Gompertz-1 and Logistic-1 models gave the best fit as well as fish yield forecasting, two months ahead from various ponds
Heterogeneous Growth Prediction in Farmed Tilapia
Turkish Journal of Fisheries and Aquatic Sciences
This study displays the application of the quantile regression theory to predict the size heterogeneity of cultured organisms. The analysis was applied to empirical data of the tilapia cultured in freshwater. Tilapia was cultured at four diets (50%, 80%, 100%, and Satiation). The quantile regression (QR) demonstrated to successfully model the size heterogeneity in tilapia (p<0,05; u<0,20), due to the feeding strategies effect. These results indicate tilapia fed an 80% ration size simulated a maximum biomass of 2,345.17 and 2,853.38kg at the harvest size of 200-300g (at 180 days) and 300-400g (at 210 days). The simulation of the quantile curves at a higher production scale allowed an estimate of the biomass distribution according to different market sizes, this strengthens management decision making in tilapia aquaculture. Implications of quantile regression and size heterogeneity in aquaculture are presented here.