Fuzzy-logic-based feeder system for intensive tilapia production (Oreochromis niloticus)

In high-fish-density aquaculture systems, tilapia producers are compelled to provide 100% of food required to obtain profitable growth rates. It is well known that fish have a low food conversion rate and feeding represents the most important expenditure, approximately 40% of total production cost. Therefore, precise quantities of food should be provided to avoid water pollution and economic losses due to food waste when water conditions are inadequate for fish feeding. A way to control food provisions in this work was determined by the conditions of temperature, dissolved oxygen, fish age, and body weight, since these variables have a direct effect on fish metabolism and growth. Thus, a change in metabolism is reflected in a modification of energy requirements and, as a consequence, in variations of food consumption. In this work, a new feeder with fuzzy-logic control algorithms is proposed for fish feeding; this technique allows farmer knowledge to be taken into account in a series of if–then-type rules. To define these rules the temperature and dissolve oxygen were considered in order to provide precise food quantities. The results show minimal differences in growth (P > 0.05) between treatments, important food saving of 29.12% (equivalent to 105.3 kg), and lower water pollution (reduced water dissolved solids and ammonium components) compared with timed feeders. This system provides an important contribution to sustainability of intensive aquaculture systems, increasing productivity and profitability, and optimizing water use.

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