Published 2008

Read in Norwegian

Publication details

Journal : Chemometrics and Intelligent Laboratory Systems , vol. 93 , p. 11–19–9 , 2008

Publisher : Elsevier

International Standard Numbers :
Printed : 0169-7439
Electronic : 1873-3239

Publication type : Academic article

Contributors : Jørgensen, Kjetil; Næs, Tormod

Issue : 1

If you have questions about the publication, you may contact Nofima’s Chief Librarian.

Kjetil Aune
Chief Librarian


In this paper we demonstrate both a design strategy and a set of analysis techniques for a designed experiment from an industrial process (cheese making) with multivariate responses (sensory data). The design strategy uses two-level factorial design for the factors that can be controlled, and blocking on the raw material to cover other non-designed variation in the raw material. We measure both the raw materials and on several points during the process with FT-IR spectroscopy. The methods of analysis complement each other to give more understanding and better modelling. The 50-50 MANOVA method provides multivariate analysis of variance to test for significance of effects for the design variables. Ordinary PLS2 analysis gives an overview of the data and generates hypotheses about relations. Finally, the orthogonal LS-PLS method is extended to multivariate responses and used to identify the source of the observed block effect and to build models that can be used for statistical process control at several points in the process. In these models, the information at one point is corrected for information that has already been described elsewhere. (C) 2008 Elsevier B.V. All rights reserved.