Digital control system based on Machine Learning for the monitoring of in vitro propagation processes: comparative study of institutional cases
Keywords:
machine learning, propagación in vitro, sistemas inteligentes, control digital, análisis comparativoAbstract
The present study comparatively analyzes the management of experimental data in in vitro propagation processes based on three institutional investigations developed at the Universidad Técnica de Cotopaxi, corresponding to banana (Musa × paradisiaca L.), heliconias (Heliconia sp.), and blueberry (Vaccinium corymbosum L.). In these studies, a predominantly manual management of experimental information is evidenced, which limits traceability, integration of variables, and capacity for advanced analysis. Based on this analysis, a digital control system based on Machine Learning is proposed, aimed at automating the recording, storage, and analysis of experimental variables. The methodology adopted a comparative and descriptive approach, contrasting traditional data management mechanisms with the technological proposal. The results show potential improvements in information organization, reduction of human errors, and enabling of predictive analysis. The study demonstrates the contribution of systems engineering to the digitalization of biotechnological processes through the use of intelligent systems.
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Copyright (c) 2026 Danny Manuel Diaz Puruncaja, Dayana Noemi Cedeño Zambrano, Mauricio Nabor Loor Cepeda
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