A New NIR Calibration Transfer Method Based on Parameter Correction

Model transfer plays an important role in solving the problem of the difference between near infrared (NIR) spectroscopic instruments and the prediction difficulty of models. The spectral differences between the same samples taken on different NIR instruments were identified using the principal component-Mahalanobis distance method. Based on the constrain conditions of Tikhonov regularization (TR) and model parameter correction, a new algorithm (called new Tikhonov regularization-based calibration transfer, NTRCT) was proposed for calibration transfer between NIR instruments, so as to facilitate the share and use of the calibration models. The spectra of a set of standard samples were first utilized to establish a specific function that could minimize the prediction errors obtained from the master and slave instrumental models. By constraining the difference of the model parameters, the parameters of the slave instrument model were then determined, to achieve the purpose of model transfer from the master instrument to the slave one. This method was applied to analyze the content of the active pharmaceutical ingredient (API) of tablets and quantify the contents of total alkaloids and total sugars in tobacco leaves respectively, by means of their NIR spectra acquired on different instruments. The results showed that the root means square error of prediction (RMSEP) of samples taken on the salve instrument was reduced from 8. 3 mg, 0. 49% and 1. 91% to 3. 9 mg, 0. 09% and 0. 83% respectively; when 15 standard samples were employed for modelling. As the calibration transferred all the resulting RPD values were larger than 3. 0, and the sample predictions from the salve instrumental spectra were thus significantly improved. The method was explicit and intuitive in theory, and had good accuracy in sample prediction in practical applications. It provided a new idea for calibration transfer method with standard samples.