BASES VISUAIS E MATEMÁTICAS PARA O USO DE INTELIGÊNCIA ARTIFICIAL NA IDENTIFICAÇÃO DE QUATRO ESPÉCIES DO GÊNERO MUGIL
DOI:
https://doi.org/10.18817/repesca.v17i1.4426Palabras clave:
Inovação, Recursos pesqueiros, Pesca, Análise de imagem, Gestão pesqueiraResumen
A identificação correta de espécies de peixes é fundamental para a gestão pesqueira sustentável, a conservação da biodiversidade aquática e a produção de dados científicos confiáveis, especialmente em ambientes costeiros e estuarinos onde a pesca artesanal desempenha papel central. No entanto, grupos taxonômicos com elevada similaridade morfológica, como o gênero Mugil (Mugilidae), apresentam elevados índices de erro quando a identificação se baseia exclusivamente em observação visual. Diante das limitações de métodos moleculares, que demandam alto custo e infraestrutura especializada, este estudo teve como objetivo desenvolver e apresentar uma abordagem integrada, acessível e não invasiva para auxiliar na identificação de espécies do gênero Mugil comuns na costa maranhense, utilizando imagens digitais e modelagem matemática explicativa. Foram analisadas imagens de Mugil brevirostris, Mugil curema, Mugil incilis e Mugil liza, a partir das quais foram extraídas medidas morfométricas básicas (área corporal, comprimento e altura máximos) e índices proporcionais, como Índice de Área, Razão de Aspecto e um índice de regularidade das escamas baseado em variação de brilho. A integração desses descritores permitiu a construção de um modelo matemático interpretável capaz de diferenciar logicamente as espécies analisadas, mesmo em um grupo morfologicamente críptico. Os resultados demonstraram que características visualmente perceptíveis podem ser traduzidas em métricas quantitativas objetivas, reduzindo a subjetividade da identificação tradicional. A metodologia mostrou-se promissora para aplicações em educação ambiental, monitoramento participativo, ciência cidadã e gestão pesqueira, além de estabelecer bases conceituais para futuras aplicações em inteligência artificial. Conclui-se que a combinação entre análise visual, morfometria digital e modelos matemáticos simples constitui uma ferramenta eficaz, compreensível e de baixo custo para a identificação de espécies de peixes costeiros.
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