rapid and nondestructive quantification of trimethylamine by ft-nir coupled with chemometric techniques

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 be employed for rapid and non-invasive quantification of tma-n in fish for monitoring safety and quality.