[Research on the robustness improvement of calibration model for measuring the contents of components in milk by multidimensional calibration in near-infrared spectroscopy]

Abstract

A new hybrid algorithm (NOSC-NPLS), the combination of multi-way orthogonal signal correction (N-OSC) algorithm and multi-way partial least squares (N-PLS) algorithm, is proposed. In NOSC-NPLS algorithm, the 3-D spectral matrix was firstly constructed, which is composed of the temperature information and the NIR spectrum. Secondly, the N-OSC algorithm was used as a pretreatment algorithm to remove the interference information irrelevant to analyte in 3-D spectral matrix. Finally, the N-PLS algorithm was applied to develop the calibration model based on the pretreated 3-D transmission spectral matrix and content matrix of major components in milk. In order to evaluate the performances of conventional algorithms and multidimensional calibration algorithms on suppressing the effects of temperature variation, a batch of milk samples at temperature of 25, 30, 35 and 40 degrees C were measured in the wavelength range from 1,100 to 1,700 nm and the experimental results were investigated. It was found that the conventional algorithms, which could not suppress the effects caused by temperature variation, failed to obtain satisfactory results. However, compared with these algorithms, the experimental results showed that the NOSC-NPLS algorithm can effectively eliminate the effects of temperature variation and also can help achieve the analytic models with better prediction ability and robustness.