FTIR–Machine Learning Tandem for Predicting Antioxidant Bioactives in Fig Seed Oil: A Pathway to High-Throughput Screening

Key Points

• Predictive models identify antioxidant bioactives effectively using machine learning techniques and FTIR analysis.
• The study demonstrates notable accuracy with a correlation coefficient of 0.85 in antioxidant prediction.
• Methodology involves combining FTIR spectroscopy with machine learning algorithms for analysis.
• Findings may enable rapid screening of antioxidants in various natural oils, encouraging further exploration.