Global and Specific NIR Models for Oxidative Stability Prediction and Cultivar Discrimination in Extra Virgin Olive Oil
Yılmaz-Düzyaman, Hande | Rosa Navarro, Raúl de la | Núñez-Sánchez, Nieves | León, Lorenzo
The Oxidative Stability Index (OSI) is crucial for evaluating the commercial, nutritional, and sensory properties of extra virgin olive oils (EVOO). Near-infrared spectroscopy (NIRS) offers a rapid and cost-effective alternative to evaluate OSI with respect to traditional methods like Rancimat. This study aimed to develop a robust global NIRS model for predicting OSI in EVOO and compare it with specific models for key Spanish cultivars such as ‘Picual’, ‘Arbequina’, and ‘Sikitita’ (a new, recently released cultivar for commercial hedgerow planting systems). Using NIRS spectra from 1100 to 2500 nm, we analyzed 939 samples globally and developed cultivar-specific models based on 59 ‘Picual’, 84 ‘Arbequina’, and 48 ‘Sikitita’ samples. Partial Least Squares (PLS) regression models demonstrated promising results in all sample sets tested, with the global model outperforming individual yearly models, highlighting the importance of incorporating variability to enhance predictive performance. Log-transformed OSI data improved accuracy across all models. Additionally, discriminant analysis (LDA) was performed on NIRS spectra from five cultivars (‘Arbequina,’ ‘Picual,’ ‘Koroneiki,’ ‘Sikitita,’ and ‘Arbosana’), a total of 254 samples, achieving 96% accuracy in differentiating monovarietal EVOO samples. These findings demonstrate the versatility of NIRS for OSI modeling and cultivar discrimination, making it a valuable tool for breeding programs and quality assessment.
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Эту запись предоставил Universidad de Córdoba