title: Multivariate calibration on NIR data: development of a model for the rapid evaluation of ethanol content in bakery products.
abstract: A new NIR method based on multivariate calibration for determination of ethanol in industrially packed wholemeal bread was developed and validated. GC-FID was used as reference method for the determination of actual ethanol concentration of different samples of wholemeal bread with proper content of added ethanol, ranging from 0 to 3.5% (w/w). Stepwise discriminant analysis was carried out on the NIR dataset, in order to reduce the number of original variables by selecting those that were able to discriminate between the samples of different ethanol concentrations. With the so selected variables a multivariate calibration model was then obtained by multiple linear regression. The prediction power of the linear model was optimized by a new "leave one out" method, so that the number of original variables resulted further reduced.
authors.affiliation: Dipartimento di Chimica Generale ed Inorganica, Chimica Analitica, Chimica Fisica, Università degli Studi di Parma, Viale G.P. Usberti 17/A, Campus Universitario, 43100 Parma, Italy.
authors.forename: Alessandra
authors.initials: A
authors.lastname: Bello
authors.forename: Federica
authors.initials: F
authors.lastname: Bianchi
authors.forename: Maria
authors.initials: M
authors.lastname: Careri
authors.forename: Marco
authors.initials: M
authors.lastname: Giannetto
authors.forename: Giovanni
authors.initials: G
authors.lastname: Mori
authors.forename: Marilena
authors.initials: M
authors.lastname: Musci