Final Activity Report Summary - FOOD INFORMATICS (A New Integrated Systems Science)
The objectives of this project in terms of targeted and focussed secondments of experienced researchers from the University of Copenhagen to the industrial partners' laboratories were achieved, and two-way transfers of knowledge proceeded primarily through the advancement of the two major topics for chemometric applications during and beyond the periods of the visits. The two major areas of scientific focus in the project plan were followed together with contributions to other scientific themes and the development in parallel of algorithms and methodologies which have the potential to be applied widely to other industrial research systems.
Detailed experimental design methodology knowledge was transferred from the University of Copenhagen experts to the industrial partner. These methodologies were implemented in the two major project themes, to produce materials for analysis from which high quality experimental data were obtained (NMR spectroscopy, LC-MS, GC-MS and sensory). These data were used in the development of novel pre-processing methods prior to multivariate statistical analyses for characterisation of variability within sample populations and for defining links to external variables. Technique developments included the creation and implementation of a new method for alignment of NMR data prior to PCA (and other chemometric) analyses. The latter methodology has been published in a major NMR journal and has been extended to other analytical data types.
Detailed experimental design methodology knowledge was transferred from the University of Copenhagen experts to the industrial partner. These methodologies were implemented in the two major project themes, to produce materials for analysis from which high quality experimental data were obtained (NMR spectroscopy, LC-MS, GC-MS and sensory). These data were used in the development of novel pre-processing methods prior to multivariate statistical analyses for characterisation of variability within sample populations and for defining links to external variables. Technique developments included the creation and implementation of a new method for alignment of NMR data prior to PCA (and other chemometric) analyses. The latter methodology has been published in a major NMR journal and has been extended to other analytical data types.