Comparative assessment of ensemble machine learning models for detecting water dynamics in freeze-dried mushrooms using Vis-NIR spectroscopy

Key Points

• Efficient detection of water dynamics was achieved using machine learning models, enhancing food quality assessment.
• Final model reached an accuracy of 89% in identifying water levels in freeze-dried mushrooms based on vis-NIR spectroscopy.
• Assessment focused on the application of ensemble machine learning techniques to analyze spectral data for water content detection.
• Findings may enable more accurate monitoring of food preservation techniques, though further validation is needed.