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Email the author (Login required) A fuzzy logic approach for preliminary biological suitability assessment for aquaculture of two spiny lobster species
Submited: 2026-01-29 16:21:15 | Published: 2026-08-04 18:53:50
DOI: https://doi.org/10.3856/vol54-issue4-fulltext-3623
Abstract
Selecting suitable species is a critical and complex decision in aquaculture development, requiring the integration of uncertain biological and economic variables. This study demonstrates the application of a Mamdani-type fuzzy inference system as a generalizable decision-support tool, using the farming suitability of two lobster species (Panulirus inflatus and P. gracilis) as a case study. The parameters considered were the growth performance index (phi prime), the abdominal-to-total weight ratio, the natural mortality rate (M), and mean fecundity. Gaussian membership functions were used for inputs and triangular for outputs, with 15 fuzzy rules. A Monte Carlo simulation estimated 95% uncertainty intervals. Based on the selected biological criteria, membership functions, and fuzzy rule base, P. gracilis obtained a higher preliminary suitability score than P. inflatus. The model proved robust to uncertainty, supporting its use as a flexible, adaptable framework for species selection in diverse aquaculture contexts under data-limited conditions. However, further validation under farming conditions is required before making definitive recommendations for aquaculture.
