Vibrational Spectroscopy Applications in Biomedical, Pharmaceutical and Food Sciences

Description

Vibrational Spectroscopy Applications in Biomedical, Pharmaceutical and Food Sciences synthesizes the latest research on the applications of vibrational spectroscopy in biomedical, pharmaceutical and food analysis. Suitable for graduate-level students as well as experienced researchers in academia and industry, this book is organized into five distinct sections. The first deals with the fundamentals of vibrational spectroscopy, with the second presenting the most important sampling methodology used for infrared and Raman spectroscopy in various fields of interest. Since spectroscopy is the study of the interaction of electromagnetic radiation with matter, this section deals with the characteristics, properties and absorption of electromagnetic radiation. Final sections describe the analytical studies performed all over the world in biomedical, pharmaceutical and in the food sciences. Cover Vibrational Spectroscopy Applications in Biomedical, Pharmaceutical and Food Sciences Copyright Preface Introduction Brief history of vibrational spectroscopy References Further reading Part I: Fundamental aspects of vibrational spectroscopy Basic theory, sampling techniques, and instrumentation Basic theory Sampling techniques and instrumentation References Part II: Biomedical analysis applications Body fluid analysis References Tissues analysis References Part III: Pharmaceutical analysis applications Chemical drug analysis Drug quantification and formulation characterization Polymorphic analysis Counterfeiting drug analysis References Herbal drug analysis References Part IV: Food analysis applications Edible oil analysis References Milk analysis References Alcoholic drink analysis References Some concluding remarks Appendix. Chemometric processing of spectroscopic data Introduction: From the spectra to the data Exploratory data analysis PCA Explorative multiblock approaches Regression Partial least squares Estimation of a response vector y by PLS Estimation of a response matrix Y by PLS (PLS2) Estimation of the goodness of a fit Multiblock regression approaches Classification Discriminant analysis PLS-DA Class modeling SIMCA Multiblock approaches for classification Validation References Index A B C D E F G H I J K L M N O P Q R S T V W Back Cover