Acceso usuarios
Hilton Prado de Castro Junior, Cleydson Breno Rodrigues dos Santos, Victor Hugo Gomes Sales, Elisa Maria de Oliveira, Lauana Natasha da Gama Pantoja, Prisna Jamile Santos Leder
The search for alternative sources of energy and biocompounds has driven the development of technologies focused on the use of microalgae as productive platforms. However, the cultivation stage still faces technical challenges related to the variability of environmental parameters and the difficulty of large-scale optimization. This study aims to conduct a systematic review of the scientific literature on the use of mathematical tools and artificial intelligence (AI) techniques applied to the optimization of microalgae cultivation for biotechnological purposes. The methodology involved a structured analysis of scientific and technological databases, using defined inclusion criteria and bibliometric and exploratory approaches. The results indicate a growing application of computational models, with emphasis on artificial neural networks and genetic algorithms, although their use during the cultivation phase remains incipient. The analysis also reveals gaps in experimental validation and in the integration of these tools into automated systems. Despite the conceptual advances, there is significant room for the consolidation of AI-based solutions, especially those aimed at the operational optimization of cultivation in real contexts. This study contributes to mapping trends, identifying limitations, and guiding future research focused on innovation in the microalgal biotechnology sector.
