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Soil nutrient depletion and other forms of soil degradation threaten future soil productivity, especially in sub-Saharan Africa (SSA). Even under optimistic assumptions, data from SSA show that 8–12 years of fallow are needed to replenish the nitrogen pool after 2–3 years of cropping. This implies that for sustainable soil management at the current level of fertilizer and manure inputs, it would only be possible to cultivate annually about 20% of the arable land. This situation rarely exists today in SSA where, through population pressure, the average percentage of land cultivated is about 60%. The data illustrate that soil conservation and improved nutrient management are crucial but can only reduce the speed of nutrient depletion. Availability and efficient use of farm external inputs will be required to make a broad impact. Data from 37 countries in SSA show a significant relationship between nutrient depletion and land pressure indicators and thus illustrate the unsustainable population–agriculture–environment nexus on the continent. Nutrient depletion accounts for about 7% of the agricultural share of the average gross domestic product of SSA, indicating nutrient mining is a significant factor in current economic development.

Red soils cover 21% of China's surface: some 2.10 6 km 2 . Much of the area is hilly. Rice grows mainly in the lowlands. Only a fraction of the uplands in the red soil area is cropped, but yields are low due to inadequate topsoil as a result of erosion and nutrient mining. The remainder is wasteland that is not used for cropping and a little for grazing. But these areas have a high agricultural production potential if some constraints are removed. The World Bank has set up a major project named “China Red Soil II”. It comprises a total area of over 9.10 4 ha for development or rehabilitation, with 215 small watersheds including one named Qingshishan. Techniques of system analysis and optimization are applied to this watershed, and a watershed development planning model (QINGS) has been created. QINGS includes seven objectives, 32 activities and some constraints, two scenarios; three land use forms and two irrigation systems are available to the model for selection. This complexity provides a web of possibilities and there can be many solutions for suitable development. By running QINGS a number of times for successively more specific goals, a window of opportunities is established where land use practice is the key factor to development and where all goals are met to a certain degree. Feasible solutions can then be identified in which reduction of soil erosion, increased income and sustainability in land use are combined. Local farmers and technical officers can identify and accept the best compromise. QINGS is a tool for watershed developers that allows them to quantify opportunities and constraints, and set specific targets for developments with the local population. Results of QINGS can empower local farmers in negotiations with watershed developers. After 5 years of red soil development supported by the World Bank Project, various activities were initiated, including new crops (e.g. bamboo), trees (e.g. mulberry), livestock, fish and pearl production, and an ecological and social benefit forest. Infrastructure was improved (such as irrigation system, traffic conduction, biogas ponds and so on). The year 2000 total net income is 870,000 yuan, compared with 265,000 in 1994 before the project. Before the project, the forest cover rate was 9%, now it is up to 50%; soil erosion is at low level, and water supply has increased the length of the secure growing season by more than 50 days. The social employment conduction is also improved, especially the employment of rural women. The whole structure of agro-ecology system is optimized.

The world population is expected to grow to 10 billion people in 2040, requiring food production at least to triple, as a combined result of population growth and dietary changes. In this study scenarios for food security are developed for 15 major regions of the world. Food production is calculated on a 1°x1° grid basis, using inputs from a digital data base containing soil, climatic, agronomic and demographic data. This allows us to study impacts of different production scenarios and their environmental side effects. Soil area data are derived from the digitized FAO soil map, considered to be representative for soil units on a 1°x1° grid; weather variables of 978 stations are allocated to the grid cells. Food production estimations are made with a simple crop growth module, a soil water balance and a soil nitrogen balance. Calculations are done on a grid basis, each grid cell being characterized by its suitability for arable farming or grassland, soil and climatic conditions and the availability of irrigation water. Results of Yield Oriented Agriculture (YOA) and Environment Oriented Agriculture (EOA) production scenarios on food self-sufficiency are presented. If we assume that there is no limit to transport of food across the globe, YOA allows the entire globe an affluent diet, while EOA allows only a moderate diet. For this scenario, regional self sufficiency indices vary widely: most regions can produce food required for an affluent diet, but not East, South and West Asia that account for 48% of the expected global population in 2040. Also Southeast Asia (9% of expected global population in 2040) and West and North Africa (10%) come close to the lower limit for food self-sufficiency. With EOA, only the former USSR, North and South America, Central and Southern Africa and Oceania can offer their future populations an affluent diet. Southern Asia will experience food shortages even under minimum food demand, and less affluent diets do not provide a solution. In this paper, attention is given to the methodology regarding soils, and to the uncertainty regarding soil and water in input data. Particularly soil suitability for agriculture for each of the grid cells has a large effect on model calculations, as it is a rather rough approximation. Knowledge of soils across the world shows important weaknesses with respect to the extent of coverage, extrapolation of point observations to grid cells, definition of soil characteristics compatible with crop models, and handling of preferential flow in soil profiles. We emphasize the need for digitized, reliable and readily available natural resource information in the fields of soil surveys, climatology, irrigation water availability, land use and land cover. The ultimate goal of the approach is not to predict the future of global agriculture, but to allow decision makers to compare various scenarios for food self-sufficiency, and to raise awareness regarding issues related to food security. In spite of the above-mentioned shortcomings in basic data, it is demonstrated that it is possible to develop the required scenarios now, instead of having to wait on more reliable soil information.

Percolation ponds are constructed in many parts of the tropics to augment fast-depleting groundwater resources. Increased agricultural productivity due to additional well irrigation water is the direct benefit from the pond schemes. Usually, location-specific empirical relationships are adopted for hydrologic and economic design of ponds. In this paper, an approach is presented to evaluate hydrologic pond design, by combining watershed, aquifer and crop simulation models of the pond system. A watershed model (CAPSIM) was developed based on the ‘state variable approach’ describing the dynamic catchment-pond hydrologic processes such as runoff, runoff due to interflow, evapotranspiration, direct percolation, pumping and irrigation. CAPSIM operates on a daily basis, using rainfall and pan evaporation data. Based on the Alternating Direction Implicit Algorithm (ADIA), a finite difference Aquifer Simulation model (ASIM) was developed to simulate two-dimensional recharge mounds beneath the pond. Predictability of CAPSIM and ASIM was verified with observed field data from one pond site, from which the models were improved. The models were further validated separately for three pond locations and for different years of weather data, by comparing observed pond and well water levels. The crop model, SAHEL, was adapted to the rice-growing environments of pond command areas, by representing water stress, runoff and well irrigation. Total Additional well Irrigation made possible Due to recharge (AID-recharge) in two space dimensions during a crop season was predicted by linking CAPSIM and ASIM. AID-recharge thus computed was input to the crop model for predicting the spatial distribution of crop response to different well irrigation scenarios. A series of ‘distance-capacity-yield’ curves were developed, which quantify the benefits associated with a modification in the pond structure. The batch of models thus linked could serve as a decision support tool for pond designers for evaluating desired hydrologic economic strategy.

To cope with estimated population growth in Asia, attainable rice yield potential must increase in the irrigated lowlands. At odds with this goal is the fact that yield potential of released high yielding rice varieties has remained constant since the release of IR8 in the late 1960s, although yield per day increased as a result of shorter growth duration and host plant resistance was improved. For example, highest rice yields of IR72 (released in 1987) were 6 and 9.5tha-1, in the 1991 wet season and the 1992 dry season, respectively, in a tropical environment with good agronomic management. These yields are comparable but no higher, than the highest yields attained by IR8 in the same environment more than 20 years ago. Detailed growth analysis from these recent studies allowed us to improve an eco-physiological model for rice growth. Subsequent simulations demonstrated accurate prediction of wet and dry season rice yield. The model was then used to evaluate the effects of global climate change as expected by the year 2020. Changes in temperature and atmospheric CO2 had relatively small effects on simulated rice growth and yield compared with (1) the impact of crop management practices in high-yielding environments and (2) genetic improvement that could further increase yield potential. Varieties with a longer grain filling duration will be needed to increase the yield plateau and to reverse negative effects of increased temperature.

There is potential in cultivating cowpeas (Vigna unguiculata (L.) Walp.) in rice-based cropping systems in the humid tropics as a source of proteins for humans, forage for ruminants, and for improvement of soil fertility. Seasonal and yearly variability is, however, a major constraint. A statistical stability model and a mechanistic simulation model were used to quantify yield variability of early and medium maturity groups of cowpea cultivars in pre- and post-rice environments at Los Banos, Philippines. Four field experiments, with 24 cultivars in each experiment, were conducted in pre- and post-rice environments, to determine the response of the cultivars to varying moisture and to water table depth regimes, and a stability analysis was performed across the regimes using a statistical model. In the post-rice environment, irrespective of moisture and water table depth regimes, the medium maturing cultivars tended to outyield early maturing cultivars, whereas in the pre-rice environment, early maturity demonstrated a distinct yield advantage. The statistical stability model indicated that medium maturing cultivars performed well in high-yielding environments, whereas in low-yielding environments their yields were comparable with those of early maturing types. However, results of the statistical stability model are limited because of the short time series of basic data. To broaden the analysis, a simulation model of the cowpea crop was calibrated and validated for its performance. Measured and simulated dry weights of crop parts (leaves, stems and pods) and soil moisture contents at 10-cm soil depths throughout the growing season indicated satisfactory performance of the simulation model. Long-term simulation results using the validated model indicate that TVX1948-012F (medium maturity) performs betters (800–2250 kg ha−1) than IT82D-889 (early maturity) (430–1620 kg ha−1) with a fluctuating shallow water table in the post-rice environment, whereas IT82D-889 is superior (80–1150 kg ha−1) to TV1948-012F (30–1150 kg ha−1) in the pre-rice environment. Yields are highest and least variable for the 15 January planting in the post-rice environment, and for the 15 April planting in the pre-rice environment.

A simulation model of the population dynamics of Scirpophaga incertulas (Walker) was developed for ultimate use in pest management programs. The processes of development, mortality, migration, and oviposition are modeled. Information from literature and field data were used to set the model's parameters. The model satisfactorily simulated the timing of egg, larval, and pupal population density peaks in farmers' fields for both the 1987 wet and 1988 dry seasons in the Philippines. Most population peak numbers lie within ±2 SD of the field means. Sensitivity analyses indicated that the most important factors in the system were egg, larval, and pupal developmental rate; egg mortality rate due to predation and parasitism; larval mortality rate related to plant age; immigration rate; and oviposition rate. Effects of growing resistant varieties, releasing egg parasites, and applying insecticides on larval populations in the 1987 wet season were evaluated with the model and discussed in regard to their implications for pest management.

Growing prosperity in the South is accompanied by human diets that will claim more natural resources per capita. This reality, combined with growing populations, may raise the global demand for food crops two– to four–fold within two generations. Considering the large volume of natural resources and potential crop yields, it seems that this demand can be met smoothly. However, this is a fallacy for the following reasons. (i) Geographic regions differ widely in their potential food security: policy choices for agricultural use of natural resources are limited in Asia. For example, to ensure national self–sufficiency and food security, most of the suitable land (China) and nearly all of the surface water (India) are needed. Degradation restricts options further. (ii) The attainable level of agricultural production depends also on socio–economic conditions. Extensive poverty keeps the attainable food production too low to achieve food security, even when the yield gap is wide, as in Africa. (iii) Bio–energy, non–food crops and nature ‘compete’ with food crops for natural resources. Global and regional food security are attainable, but only with major efforts. Strategies to achieve alternative aims will be discussed.

As the result of a recent BBSRC-funded workshop between soil scientists, modellers, statisticians and others to discuss issues relating to the derivation of complex environmental models, a set of modelling guidelines is presented and the required associated research areas are discussed.

Food demand for the year 2040 is estimated for 15 major regions of the world. It is compared with potential food production in these regions, which is computed from the area with soils suitable for cropping and grazing, the amount of irrigation water available, and the farming system used. Application of the best known techniques for sustainable farming is assumed, but two alternatives are explored: integrated agriculture, with intensive use of chemical inputs and energy to produce maximum yields for minimum prices, and ecological agriculture, in which legumes provide all N, intensity is lower, agriculture is more diverse, but hectare yields are lower. Comparing future scenarios of demand and supply of food shows that most regions can avoid serious food security problems but that in Asia, situations may arise where a moderate or affluent diet is out of reach of its population, even when maximum use is made of all natural resources. Implications for soil science are (i) more accurate global soil data bases are required, containing more characteristics (e.g., soil depth); (ii) more knowledge is required as to how to scale up field data bases and models to national or regional levels; and (iii) more knowledge is needed at field and regional scale about leaching of nutrients, particularly from organic manure. Future challenges are to (i) increase P availability, (ii) reduce loss of nutrients under high and low input systems, and (iii) increase water-use efficiency in irrigation systems.

Food demand is estimated for the 15 major regions of the world for the year 2040. It is compared with the potential food production in these regions, which is derived from the area with soils suitable for cropping and grazing, the amount of irrigation water available, and the farming system used. All farmers are assumed to employ the best known techniques for sustainable farming. Two alternative production systems are explored: optimum productivity per unit of land, with intensive use of chemical inputs and energy to produce top yields (‘HEI’), and agriculture in which environmental damage per unit area is minimised (‘LEI’). In the latter system, legumes provide all nitrogen, agriculture is more diverse, and hectare yields are lower. Farming could occur at a smaller scale than in HEI-f arming, with strong integration of arable farming and animal husbandry, but these aspects play no role in this study.

In this chapter, the authors develop the concept of the endophyte as a unique candidate for genetic engineering for the purpose of conferring resistance. Endophytes should be viewed as an important genome for crop protection. Genetic engineering of well-chosen endophytes offers several advantages over other means of imparting insect and disease resistance to crops: the freedom of interspecific gene movement expands possibilities beyond that of traditional breeding. Scientists at Crop Genetics International (CGI) have chosen the bacterium Clavibacter xyli subsp. cynodontis (Cxc) for commercial development to produce and deliver biopesticides in planta. Since Cxc is the only endophyte being engineered for commercial development, it will serve as the chapter's primary example of potential benefits of the endophyte approach to crop improvement. CGI is continuing product development research to identify appropriate market opportunities for endophyte-based crop protection products.

A long series of pre-testing trials of promising cultures at many locations is a prerequisite for the selection and release of a new rice variety. This involves considerable time and effort. To reduce time and expense, we sought to employ a crop growth simulation model that explains the interaction of environment and genotype.

There is a growing interest in cultivating wheat in Southeast Asia for reduction of the drain of foreign exchange and for crop diversification. A crop growth model was used to establish potential and rainfed yields of wheat following rice in different parts of this region. A comparison of measured and simulated yields indicated satisfactory performance of the model. The results indicate that the yield potential of irrigated wheat is between 3·0 and 5·0 t ha−1 between 10 S and 23 N latitude at sea level, but it is higher at altitudes between 500–2000 m. Such yields are stable and relatively insensitive to sowing date. Rainfed yields are lower, and have a high year-to-year variability. The gap between potential and water-limited grain yields is small if wheat is sown towards the end of the rainy season on a deep and well-drained soil.

A strictly linear relation was established between the carbon and ash contents of plant biomass and the relative amount of substrate required to produce this biomass. Data concerned storage organs of crops of widely different biochemical composition. Amounts of substrate required were calculated by an analysis of the metabolic pathways for the synthesis of the principal components of biomass. Carbon contents were derived from the biomass composition. A linear relation was also established between biomass carbon and ash contents and the CO 2 loss during biosynthesis. The linearity of both relations and the ease with which the carbon and ash contents of new biomass samples can be determined accurately imply that the previous procedure for determining the conversion efficiency for plant biomass and growth respiration can be simplified substantially with a gain in accuracy.

For the simulation of organ formation and assimilate partitioning, information is required on the current level of activities like CO2 assimilation and the growth of various organs, as well as state variables such as leaf and root wt., N content and carbohydrate reserves and exogenous variables like radiation and temp. This information may be retained in auxiliary state variables by considering the dynamic equilibrium between growth of roots and shoots. Auxiliary state variables are not tangible quantities but mathematical artefacts of the simulation program; it is speculated that in real plants similar information may be retained and transferred by the hormonal system. A hormonal system is a communication system and such systems may be analysed either in terms of means (of the hardware used) or in terms of purpose (of the messages transferred). In dynamic models of crop growth, interest should be focused on the latter. Wheat, maize and ryegrass are used as examples. (Abstract retrieved from CAB Abstracts by CABI’s permission)

Summary Maize plants hydroponically grown on nutrient solution were used to study the effect of alterations in N supply on N concentrations in the organs as related to the ability of biomass production. Omission of nitrate from the nutrient solution induced in the vegetative organs a breakdown of nitrogenous compounds which were partly redistributed towards the ears. These processes took place more at the expense of membrane proteins than of the buffer-soluble proteins and resulted in N concentrations lower than the theoretical minimum; then the biomass production stopped. Re-supply of nitrate to young N-starved plants induced an increase of N concentrations in all plant parts and the resumption of biomass production. The newly produced amount of membrane proteins was larger than that of buffer-soluble proteins. However, the ratio of buffer-soluble to membrane protein concentrations in mature leaves did not return to the original value. It was concluded that re-supply of nitrate resulted in a recuperation of N-starved plants to a restricted extent.

Systems analysis and simulation have developed into advanced tools in agriculture. They are used in research, extension and education. The recent availability of powerful inexpensive microcomputers now allows the use of these techniques in developing countries. A training programme was developed and conducted to enable the implementation of systems analysis and simulation in several national research institutes in South and Southeast Asia. Eight teams of four researchers from different disciplines participated in the training programme, which included a case study, involving both experimentation and computer simulation at their home institutes. The evaluation indicated that this approach to training was effective. It is expected to be applicable on a wider scale. The interactions between team members from different disciplines were strengthened by the course experiences. Simulation provided a means and a reason for communication. However, reaching the ultimate goal of systems analysis and modelling at these national research institutes, i.e. to use these tools to contribute toward increased national agricultural production, is expected to require several years.

Prediction may be envisaged as organized thinking about the possible. For this purpose, dynamic models of the state-variable approach are important tools because they combine basic knowledge on the physical, chemical and physiological processes that underlie crop growth and agricultural production. At one extreme are comprehensive models that claim to integrate all aspects of growth and to focus attention on the main gaps in present operational knowledge. As such, they are research tools. At the other extreme are summarizing models that are especially geared to answer ‘w hat-if’ questions and are used for evaluating regional production potentials and constraints, for irrigation management and integrated control of pests, diseases and weeds. Examples of these types of models are given and their usefulness for predictive purposes is discussed.

A workshop on evaluation of simulation models was held in Wageningen. The object of the meeting was to discuss problems and points of view concerning evaluation of complex models. Most of the workshop was devoted to discussions. At the end, there was a considerable consensus on many points. This paper summarises the major conclusions.

1 tables 11 graph. Proceedings of a seminar series 1996/1997*INRA, Centre de Versailles-Grignon (FRA)

Quantitative Approaches in Systems Analysis No. 10 chap. 15

*INRA, Centre de Toulouse chap. 8; International audience

The general objective of this thesis is to formulate a general model for fish production in integrated ponds and ricefields as a means of obtaining a better understanding of these production systems. Integrated culture systems produce fish without large industrial energy inputs and have positive effects on the whole farm system. A main characteristic is their environmental variability, notably dissolved oxygen concentration and temperature. A systems approach using mathematical models is advocated because it can lead to insights that have universal applicability while avoiding the pitfalls of site- and species-specific, expensive experimental work. Two modelling approaches are distinguished: descriptive models, generally the result of statistical analysis of datasets; and explanatory models, based on knowledge of the biological processes underlying fish production.Multiple regression analysis (a descriptive modelling technique) was used for the analysis of data from 15 integrated rice-fish production experiments with the Nile tilapia (Oreochromis niloticus L.) in the Philippines. Results showed that this technique led to insights that had not been obtained through separate analysis of the experiments. Main drawback of this method was that the models were not applicable to other production environments.An explanatory model (called Fish Growth Simulator, or FGS) for growth of O.niloticus was developed on the basis of an existing simulation model for the African catfish Clarias gariepinus Burchell (1822). After parameterization and calibration, the model gave good predictions of fish growth in independent datasets. Parameterization and calibration of the same model for the rainbow trout Onchorhynchus mykiss (Walbaum) demonstrated the generality of the model and it was concluded that, provided that enough data are available, the model may be used to predict growth in a wide range of fish species. Food amount and composition, and temperature were the environmental variables upon which the model based its predictions.FGS was expanded with a dissolved oxygen module to accomodate oxygen as an environmental variable. The module was based on the hypothesis that oxygen is needed in sufficient amounts for aerobic metabolism, and that gill surface area limits the supply of oxygen to fish. The resulting model allowed the simulation of fish growth under low dissolved oxygen concentration and also provided an explanation for differences in the final weight of fishes, both within and between species.FGS was used for simulation of food and oxygen limitations in waste-fed fish ponds in Honduras, Thailand and Rwanda. The model simulated fish growth for various combinations of environmental conditions: temperature, food availability and dissolved oxygen concentration. Validation, using data from Indonesia and Panama, was not successful because estimates of the food consumption rate in these countries were not reliable.In the last chapter methodology, the role of oxygen in fish metabolism and growth, model implications for the management of integrated agriculture-aquaculture systems and implications for further work are discussed.

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. Clariasgariepinus (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 C . gariepinus 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 C . gariepinus 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 C . gariepinus 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 C . gariepinus , fed with differently formulated diets. The output of the model was compared with the results of an experiment were C . gariepinus 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 C . gariepinus . 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.