El. knyga: Mathematical and Statistical Methods in Food Science and Technology

Food scientists and engineers explain to their non-statistician colleagues how to use some recently developed mathematical modeling techniques to develop and evaluate food products. Their topics include a case study of optimizing the enzyme-aided extraction of polyphenols from unripe apples by response surface methodology, principal component regression and partial least squares regression, statistical approaches to developing and validating microbiological analytic methods, infrared spectroscopy detection coupled with chemometrics to characterize food-borne pathogens at a subspecies level, and translating randomly fluctuating quality control records into the probabilities of future mishaps. Annotation ©2014 Ringgold, Inc., Portland, OR (protoview.com)

Mathematical and Statistical Approaches in Food Science and Technology offers an accessible guide to applying statistical and mathematical technologies in the food science field whilst also addressing the theoretical foundations. Using clear examples and case-studies by way of practical illustration, the book is more than just a theoretical guide for non-statisticians, and may therefore be used by scientists, students and food industry professionals at different levels and with varying degrees of statistical skill.