Multivariate determination of free fatty acids and moisture in fish oils by partial least-squares regression and near-infrared spectroscopy

• Published in: Food science & technology 2005-12, Vol.38 (8), p.821-828
• Main Authors: Cozzolino, D., Murray, I., Chree, A., Scaife, J.R.
• Format: Article
• Language: English
• Subjects: anisidine value; Biological and medical sciences; chemical analysis; Fat industries; fatty acid composition; Fish oil; fish oils; food analysis; Food industries; Free fatty acids; Fundamental and applied biological sciences. Psychology; least squares; Lipid oxidation; lipid peroxidation; lipids; model validation; Moisture; multivariate analysis; Near-infrared spectroscopy; NIR; oxidation; Partial least squares; peroxide value; Peroxides; Pisces; rancidity; water content
• ISSN: 0023-6438; 1096-1127
• DOI: 10.1016/j.lwt.2004.10.007

The oxidative and hydrolytic degradation of lipids in fish oil was monitored using partial least-squares (PLS) regression and near-infrared reflectance (NIR) spectroscopy. One hundred and sixty ( n=160) fish oil samples from a fishmeal factory were scanned in transflectance by an NIR monochromator instrument (1100–2500 nm). Calibration models were performed for free fatty acids (FFA), moisture (M), peroxide value (PV) and anisidine value (AV). Coefficients of determination in calibration ( R 2) and standard errors of cross validation (SECV) were 0.96 (SECV: 0.59) and 0.94 (SECV: 0.03) for FFA and M in g/kg, respectively. The accuracy of the NIR calibration models were tested using a validation set, yielding coefficients of correlation ( r) and standard errors of prediction (SEP) of 0.98 (SEP: 0.50) and 0.80 (SEP: 0.05) for FFA and M in g/kg, respectively. Poor accuracy ( R 2