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Near-Infrared Spectroscopy in Food Science and Technology
This reference gives food science professionals a working understanding of near-infrared spectroscopy (NIRS) and its role in maximizing food potential. It explains the technical aspects of NIRS, including: basic principles; characteristics of the NIR spectra; instrumentation; sampling techniques; and chemometrics. The book details applications of NIRS in agricultural and marine products, foodstuffs and processed foods, engineering and process monitoring, and food safety and disease diagnosis.
Jet
The weekly source of African American political and entertainment news.
The Handbook of Organic Compounds, Three-Volume Set
The Handbook of Organic Compounds: NIR, IR, Raman, and UV-Vis Spectra Featuring Polymers and Surfactants represents a compendium of practical spectroscopic methodology, comprehensive reviews, and basic information for organic materials, surfactants, and polymer spectra covering the Ultraviolet, Visible, Near Infrared, Infrared, Raman and Dielectric measurement techniques. This set represents a complementary organic compound handbook to the Nyquist inorganic handbook, published in 1996. This set comprises the first comprehensive multi-volume handbook to provide basic coverage for UV-Vis, 4th overtone NIR, 3rd overtone NIR, NIR, Infrared, Raman spectra, and Dielectric data for common organic c...
Handbook of Near-Infrared Analysis, Second Edition
With contributions from over 40 experts in the field, this reference presents comprehensive, single-source coverage of the instrumentation, computerization, calibration, and methods development of NIR spectroscopy. It provides novel applications for accurate time- and cost-effective analyses of pharmaceuticals, polymers, textiles, agricultural products, dairy products, foods, and beverages. Emphasizing trends in sample preparation, the book covers historical development, calibration transfer, biomedical applications, plastics, and counterfeiting; on-line, in-line, and at-line analyses for process control, multilinear regression and principal component analysis, and more.
George Bush
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