Improving feeding strategies for shrimp farming using fuzzy logic, based on water quality parameters
2018
Bórquez-Lopez, R.A. | Casillas-Hernandez, R. | Lopez-Elias, J.A. | Barraza-Guardado, R.H. | Martinez-Cordova, L.R.
In intensive shrimp farming systems, formulated feed represents the main nutrition source and its adequate management significantly influences the economic feasibility of the farm. Based on that, the present study evaluated two dynamic feeding strategies: fuzzy logic (FL) and mathematical functions (MF). For both strategies, the temperature and dissolved oxygen were modified in a controlled way. A conventional feeding table was the control treatment. The results showed that DO was the parameter that mostly influences the feeding rate (74%) while the temperature also did it, but in a lower grade (26%). The results showed that feed conversion rate (FCR) was significantly better when the FL strategy was used, saving around 35% of feed when compared to the control. An expert system based on FL may replace the traditional feeding strategies with no significant adverse effects on growth, survival and FCR, and may easily be adapted to some other culture systems.
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