In addition to the conventional methods of the calibration model construction, such as PCR (principal components regression) and PLS (partial least-squares), a MPM (mathematical programming method) is developed ...In addition to the conventional methods of the calibration model construction, such as PCR (principal components regression) and PLS (partial least-squares), a MPM (mathematical programming method) is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk (for fat), corn (for protein) and rye flour (for moisture). The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.展开更多
文摘In addition to the conventional methods of the calibration model construction, such as PCR (principal components regression) and PLS (partial least-squares), a MPM (mathematical programming method) is developed and proposed for practical use in NIR analyses of agricultural and food products. The proposed method involves the mathematical programming techniques to seek the regression coefficients for the calibration model calculation. It is based on the optimization theory used for finding the extremum of the objective function in the given domain of a vector space and employs the method of the complementarity problems solving. The MPM algorithm is described in detail. The MPM was tested on an InfraLUM FT-10 NIR analyzer of Lumex company with samples of dry milk (for fat), corn (for protein) and rye flour (for moisture). The obtained results show that the MPM can be used for constructing multivariate calibrations with the qualitative characteristics superior over those of the classical PCR and PLS methods of analysis.