Food science and technology | University of Parma

Professor: Marilena MUSCI
Academic discipline: Chimica analitica (CHIM/01)
Field: A scelta dello studente
Type of training activity: Student's choice

31 hours
of face-to-face activities

3 credits

hub:

course unit
in ITALIAN

lectures timetable unavailable

exam calls

Learning objectives

Students will be able to deal with different challenges related to planning of experiments, classification and discrimination of samples

Prerequisites

Good knowledge of univariate chemometrics techniques is requested

Course unit content

The course will provide student with knowledge of theoretical principles and applications to food analysis of multivariate chemometrics techniques, as bivariate ANOVA, principal component analysis, cluster analysis, discriminant analysis, and experimental design techniques

Full programme

Multivariate chemometrics techniques: bivariate ANOVA, principal component analysis, cluster analysis, discriminant analysis.

Experimental design techniques: factorial design, response surface design. Optimization. Modelling.

Bibliography

- J.N. Miller, J.C. Miller “Statistics and chemometrics for analytical chemistry” Pearson Prentice Hall
- D.L. Massart et al. “Handbook of chemometrics and qualimetrics” Part A Elsevier
- S.R. Chrouch, F.J. Holler “Applications of Microsoft Excel in analytical chemistry” 2 ed Belmont C.A. Brooks/Cole

Teaching methods

Theoretical lectures and exercises with the software Excel and SPSS will be performed in the classroom.

Assessment methods and criteria

Oral examination about topics discussed during the course

Other information

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EXPERIMENTAL DESIGN AND MULTIVARIATE STATISTICAL ANALYSIS cod. 1012327