A dynamic simulation model for growth of the African catfish, Clarias gariepinus (Burchell 1822).

In the early '70 it was tried to identify new fish species for aquaculture in Africa. Amongst the most promising candidates was the African catfish. <u>Clarias</u><u>gariepinus</u> (Burchell 1822). It is an omnivorous fish. which means a wide feeding spectrum. The fish is a partial air breather, so the oxygen concentration in the water is no strongly limiting factor, which facilitates high density culture.To provide the basis for a production programme of any species the various phases of its culture process must be elaborated. First of all methods for reproduction have to be established to ensure a reliable supply of fingerlings. Secondly raising of fingerlings to fish of marketable size is a field of major importance.An important question in fattening of fish is what to feed how much. The amount and the composition of the fish diet have a pronounced effect on growth rate and feed conversion. The conversion process of feed nutrients into fish biomass is influenced by a number of biotic and a-biotic factors like for instance body weight, maturity, water temperature and water quality. Many experiments are required to perform dose-respond relationships for the amount of feed and the weight gain at different temperatures, different weight classes and various diet compositions. To reduce these efforts developing a growth model may be helpful.In this study an explanatory growth model is developed to gain knowledge about the influence of various factors on the growth process. The quantitative equations of the model describe the processes at the underlying levels of growth, the intermediate metabolism and biochemistry. These equations reflect our understanding and knowledge of the relationship in the real system.To carry out the simulation the state variable approach is used. All rates of change between small time lags are calculated from the conditions of the system at time of start and if necessary from data in the past. The state of the system can be calculated by semi-parallel integration over the small time interval. From these new circumstances the calculations are repeated.The model calculations start with the amount of various digested nutrients. The digestion rate of the various nutrients depends on the eating rate, the diet composition and the digestion efficiency. The resulting amino acids. fatty acids and mono sacharides (glucose) are the building blocks for biosynthesis of new biomass. Apart from the composition of digested nutrient the conversion process of feed nutrients into fish biomass also depends on the composition of the biomass. Because the glycogen content in fish is very low it is assumed that glucose and fatty acids are converted to fat. The amino acids are used for the biosynthesis of protein. Since fish has to maintain its body composition within certain limits, more or less amino acids are used for other purposes via gluconeogenesis, depending the diet composition.Using the biochemical pathways, as given in the literature. of biosynthesis and other metabolic processes a molecular reaction equation can be made, giving the substrate required for any particular end product. The reaction equations generally include ATP and other recycling intermediates for energy transformations. The final equations for the most complex substrate and end products represent the efficient conversion possible, given the biochemical "machinery". The conversion process is easily expressed in terms of weight of substrate and end products formed. The reactions also include the gas exchange.The new fish biomass formed by biosynthesis is not all weight gain, because part of the biomass is broken down for respiration purposes. Respiration is determined by the total metabolic rate. The total metabolic rate is the sum of the routine metabolic rate at fasting conditions, the metabolic rate due to feed intake and assimilation and the metabolic rate for the biosynthesis of biomass. The ratio at which body fat and protein are oxidized for respiration is set to depend on the body composition in order to avoid unrealistic body compositions.The change in the amounts of different body constituents is calculated as the difference between biosynthesis and breakdown for respiration. When the protein gain is known, fresh weight gain is calculated with a relation between body weight and protein content. The fat gain is considered to affect the body composition only. The fat and the water content of fish biomass show a strong negative correlation.Feed consumption by the fish is determined by the daily feed ration. Since at high feeding levels a difference between amount of feed consumed and amount of feed provided may occur, a relation between maximum consumption and fish weight at different temperatures is incorporated in the model in order to limit the weight gain in such circumstances. In the model, the maximum feed intake by the fish is also controlled by the composition of both the fish biomass and the diet. Fat fish can consume less feed than a leaner fish of the same weight. A fish will also eat less in case of a carbohydrate rich diet.The input needed for the calculations are body weight and fat content of the fish. amount and composition of the feed and the water temperature. The output of the model includes fresh weight gain. protein gain. fat gain, oxygen consumption, carbon dioxide production and ammonia production.,During its development the model was tested by comparing the model output with experimental results which were not used during the calibration procedure.Firstly a comparison was made with results of an experiment were a diet with a fixed composition was offered to different weight classes of <u>C</u> . <u>gariepinus</u> at 3 temperatures and 5 feeding levels. A second comparison was made with result of an experiment were diets with different composition were fed to the fish. The model estimates the effects of feeding level, feed composition (in particular protein and fat content) and temperature on growth and growth composition reasonably well. The test results indicate that <u>C</u> . <u>gariepinus</u> utilises the feed nutrients at maximum biochemical efficiency. It became also apparent that the fish regulates its maximum feed intake by the fat content of the biomass. Because there were no data available to support this hypothesis. an experiment was carried out to determine the effects of body composition on growth and feed intake. In this experiment it was shown that feeding a diet to lean or fat fish, resulted in a higher maximum gain for lean fish due to a higher maximum feed intake level. Below the maximum gain, fat fish showed a slightly better feed conversion. It is likely, that <u>C</u> . <u>gariepinus</u> regulates its maximum feed intake. besides by lipostatic mechanisms. also by glucostatic mechanisms, because the maximum feed intake levels of a carbohydrate rich diet (54 %) were lower than the maximum intake levels of a low carbohydrate diet. The implications of these finding are of great practical value. The production results can be influenced by changing the biomass composition of the fish through different feeding strategies or diet compositions.Finally, the model was used to calculate the performance of <u>C</u> . <u>gariepinus</u> , fed with differently formulated diets. The output of the model was compared with the results of an experiment were <u>C</u> . <u>gariepinus</u> was fed with diets containing different protein sources of plant and animal origin. The model is suited to predict the effect of nutrient supply on growth and growth composition of <u>C</u> . <u>gariepinus</u> . For feed formulation purposes it seems possible to calculate a ranking order of different protein ingredients to be included in the fish diet.Limitations of the model are found for the prediction of growth at high feed intake levels. Emphasis must be given to find adequate relations for feed intake regulation at the upper limits of growth and/or feed intake, because the model is very sensitive for changes in the maximum feed Intake level.The model can be easily adopted for simulating growth of other fish species. Other possible applications are research and teaching on the principles of fish growth and nutrition, development and evaluation of new diets for various production methods and. in combination with a model of the physical culture system, economic analysis of real farm results