Abstract

This work assesses the application of near infrared spectroscopy technology for the quality control of sunflower seeds direct from farmers and from a storage silo. The results show that the analytical method employing near infrared spectroscopy can be used as a rapid and non-destructive tool for the determination of moisture, fat and high/low oleic acid contents in samples of sunflower seeds. The ranges obtained were comparable to those reported for classic chemical methods, and were between 4.6-21.4% for moisture; 38.4-49.6% for fat, and 60.0-93.1% for oleic acid expressed as percentage of total fatty acids. A stepwise discriminant analysis was performed to determine the most useful wavelengths for classifying sunflower seeds in terms of their (high/low) oleic acid composition. The discriminant model allows the classification of sunflower seeds with high or low oleic acid contents, with a prediction rate of 90.5% for internal validation and of 89.4% for cross-validation.