Discrimination of GMOs Using Terahertz Spectroscopy and CS-SVM.

This paper develops an effective identification method to discriminate genetically modified (GM) and non-GM organisms. The method is proposed based on terahertz (THz) spectroscopy and support vector machines optimized by Cuckoo Search algorithm (CS-SVM). In this study, the THz spectra of three GM and non-GM soya seed samples were obtained by using terahertz time-domain spectroscopy (THz-TDS) system between 0.2 and 1.2 THz. Then, the SVM model is employed to distinguish GM and non-GM soya seeds, in which the two crucial parameters, including the penalty factor and kernel parameter, are optimized by CS algorithm. The experimental results show that THz spectroscopy combined with CS-SVM can provide a rapid, reliable and non-invasive method for GMOs and non-GMOs discrimination.

[Application of interval selection methods in quantitative analysis of multicomponent mixtures by terahertz time-domain spectroscopy].

Interval selection methods combined with terahertz time-domain spectroscopy (THz-TDS) technique were used to perform quantitative analysis of component concentrations in multicomponent mixtures. The THz spectra of 100 quaternary pharmaceutical mixtures composed of lactose monohydrate, acetaminophen, microcrystalline cellulose and soluble starch were measured using THz-TDS system. Four spectral interval selection methods, including iPLS, mwPLS, siPLS and biPLS, were employed to select spectral intervals of THz absorbance spectra of multicomponent mixtures and correlate THz absorbance spectra with the concentrations of lactose monohydrate. The mwPLS method yielded the most accurate result as compared with the other three interval selection methods and full-spectrum PLS. The optimal mwPLS model was obtained with lower root mean square error of cross-validation (RMSECV) of 0.9803, lower root mean square error of prediction (RMSEP) of 1.1141, higher correlation coefficient for calibration (Rc) of 0.9960, and higher correlation coefficient for prediction (Rp) of 0.9951. Experimental results demonstrate that spectral interval selection combined with THz-TDS could be successfully applied as an accurate and rapid method to determine component concentrations in multicomponent mixtures.

[Simultaneous quantitative determination of multicomponents in tablets based on terahertz time-domain spectroscopy].

Terahertz time-domain spectroscopy (THz-TDS) combined with chemometric modeling methods was used to perform quantitative analysis of both active pharmaceutical ingredient (API) and excipient concentrations of multicomponent pharmaceutical mixtures. The THz spectra of ternary mixtures formulated with anhydrous theophylline, lactose monohydrate, magnesium stearate and quaternary mixtures composed of acetaminophen, lactose monohydrate, microcrystalline cellulose and soluble starch were measured using THz-TDS. Two multivariate calibration methods, principal component regression (PCR) and partial least squares (PLS) regression, were employed to correlate THz absorbance spectra with the pharmaceutical tablet concentrations. Both API and excipient concentrations of mixtures were predicted simultaneously, and the PLS method provides better result than PCR method. The correlation coefficients of calibration (Rcal) and validation (Rval) for ternary mixtures' components, anhydrous theophylline and lactose monohydrate, were all more than 0.98. The Rcal and Rval for quaternary mixtures' components, acetaminophen, lactose monohydrate, microcrystalline cellulose and soluble starch, were all more than 0.93, 0.98, 0.63 and 0.86, respectively. Experimental results show that THz-TDS combined with chemometrics is feasible in nondestructive quantitative analysis of multicomponent mixtures, and it can be widely applied in the fields of pharmaceutical analysis and others.