Rapid and nondestructive quantification of trimethylamine by FT-NIR coupled with chemometric techniques

Abstract

This paper focused on the quick and nondestructive evaluation of trimethylamine (TMA-N) in fish storage which is sequent to its freshness, the key for controlling the quality and safety of fish products by combining Fourier transform near-infrared (FT-NIR) and chemometric techniques. Calibration models of fish freshness were established using three multivariate chemometric methods—partial least square (PLS), synergy interval PLS (Si-PLS), and genetic algorithm PLS (GA-PLS) for quantitative prediction of TMA-N in fish. Results of the developed model were estimated using the correlation coefficients of the prediction (Rp) and calibration (Rc); root mean square error of prediction (RMSEP) and the ratio of sample standard deviation to RMSEP (RPD). The established model’s performance achieved 0.943 ≤ Rp ≤ 0.977 and 4.25 ≤ RPD ≤ 4.30. The model’s prediction strength improved in the order PLS < Si-PLS < GA-PLS. GA-PLS significantly improved the prediction of TMA-N prediction with RMSEC = 5.08 and Rc = 98.28 for the calibration data whereas the prediction set gave an RMSEP = 5.10 and Rp = 97.70. FT-NIR spectroscopy combined with GA-PLS technique may be employed for rapid and non-invasive quantification of TMA-N in fish for monitoring safety and quality.