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Mateo M J, OвЂ™Callaghan D J, Everard C D, et al. Journal of Food Composition and Analysis, 2003, 16: 507. Kamizake N K K, Goncalves M M, Zaia C T B V, et al. SHAN Yang, ZHU Xiang-rong, XU Qing-song, et al(еЌ• жќЁ, жњ±еђ‘иЌЈ, и®ёйќ’жќѕ, з‰). Arlington: Association of Official Analytical Chemists Inc., 1990. Official Methods of Analysis of the Association of Official Chemists (15th ed.). Miniature Near-Infrared Fibre Optic Spectrometer for the Quantitative Detection of Protein and Fat in Milk Powder. ZHANG Zhong-wei,WEN Zhi-yu,ZENG Tian-ling, et al. Near-infrared spectroscopy/NIR Fiber optic spectrometer Milk powder Partial least squares The results indicate that these correction models have prediction capability with unknown samples and meet the on line requirements. Using these correction models to predict the protein and fat contents with 30 sets of forecast sample data, the prediction standard deviation is SEP Protein=0.751 for protein, and is SEP Fat=1.109 for fat. The determination coefficients R 2 of the correction modes are 0.987 and 0.986 for protein and fat respectively, and the root mean square errors RMSEC are 0.385 and 0.419 respectively. By selecting the appropriate spectral bands, the correction models of protein and fat were established with partial least squares algorithm using Unscrambler 9.7 Chemometrics software. Abstract The method based on miniature near-infrared spectrometer combined with Y fiber optic probe to detect the protein and fat in milk powder by diffuse reflectance spectroscopy in the wavelength range of 900пЅћ1 700 nm was proposed.

Unscrambler software 9.7