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《Infrared Technology》 2008-09
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Direct Orthogonal Correction in Near-infrared Spectral Analysis of Milk

WANG Li-jie1,CAI Li-juan1,ZHOU Zhen1,QIN Yong1,SU Zi-mei1,XU Ke-xin2,GUO Jian-ying1 (1.College of Measurement-Control Technology and Communications Engineering, Harbin University of Science and Technology, Harbin Heilongjiang 150080, China; 2.State Key Laboratory of Precision Measuring Technology and Instruments, College of Precision Instruments of Opt-electronics Engineering, Tianjin University, Tianjin 300072, China)  
The basic principles of the near infrared spectra (NIR) of milk measurement were introduced and basic methods of direct orthogonal correction (DO) were studied. The near infrared(NIR) of milk measurement system was used to collect two home-made components (glucose, albumin) samples’ and milk’s near infrared spectra, to preprocess spectral data and to establish the calibration model by partial least squares (PLS). This indicated that the major information in milk spectrum could be reserved while part noise was removed by DO method. The number of optimal factors of PLS model used to predict the main components fat and protein content against milk spectra would be reduced in accordance with DO factors reduction. In this study, the optimum PLS calibration model was obtained when 3 and 4 DO factors were respectively filtered from fat and protein, to have obtained the standard error of calibration(SEC) of 0.3204 and 0.2727 and the standard error of prediction (SEP) of 0.7316 and 0.4460 and when 1 DO factors were respectively filtered from albumin and glucose, to have obtained the standard error of calibration(SEC) of 0.2513 and 0.2780 and the standard error of prediction (SEP) of 0.5169 and 0.7870. Although this model could not improve precise to a great extent, but in comparison on with the model before DO pretreatment,less reduction factors would be necessary and the model would be simpler.
【Fund】: 黑龙江省教育厅科学技术项目资助(编号:11531056)
【CateGory Index】: TS252.7
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