Usefulness of Near-Infrared Reflectance (NIR) Spectroscopy and Chemometrics To Discriminate Fishmeal Batches Made with Different Fish Species

Abstract

Near-infrared reflectance (NIR) spectroscopy combined with chemometrics was used to identify and authenticate fishmeal batches made with different fish species. Samples from a commercial fishmeal factory (n = 60) were scanned in the NIR region (1100-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), dummy partial least-squares regression (DPLS), and linear discriminant analysis (LDA) based on PCA scores were used to identify the origin of fishmeal produced using different fish species. Cross-validation was used as validation method when classification models were developed. DPLS correctly classified 80 and 82% of the fishmeal samples. LDA calibration models correctly classified >80% of fishmeal samples according to fish species The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method for the authentication and identification of fish species used to manufacture the fishmeal.