Title: Development of direct orthogonalization method in NIR spectral analysis
Abstract: In this paper, methods of adopting NIR spectra to measure milk constituents and Direct Orthogonalization (DO) pre-processing are studied. Based on the spectra of representative solutions, the DO method was employed to filter the signal noise that is irrelevant to the concentration being measured. The predictions of the Partial Least Squares (PLS) Regression models with and without the DO pre-processing are evaluated. During the experiments, the transmitted spectra of a water solution with glucose and NaCl mixture and the scattered reflection spectra of milk are acquired respectively in the near infrared region of 1000~1700nm using a homemade NIR Spectral System for measuring milk constituents. With the DO pre-processing of the spectroscopic data, the number of the optimal Principal Component (PC) of the PLS model is reduced. It should be noted that the sum of this PC number and the PC number corresponding to the DO preprocessing is equal to the optimal PC number of the PLS model without DO pre-processing. After the DO pre-processing, the Root Mean Square Error of Cross Validation (RMSECV) of PLS model is slightly reduced whereas the Root Mean Square Error of Prediction (RMSEP) is reduced significantly.
Publication Year: 2005
Publication Date: 2005-01-10
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 2
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot