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Multi-way Analysis in the Food Industry Models, Algorithms, and Applications

There is a need to improve current practices in Asia with regard to selection of cattle for breeding purposes, for both dairy and beef production. For many years, most of the countries in the region have been importing cows, bulls, and semen, largely from the temperate regions of the world, and using them to ‘upgrade’ the genetics of their existing herds of indigenous cattle for producing ability. However, and based on current evaluation of production levels and the productivity of cattle and buffalo, some doubts exist regarding the need and wisdom to continue this practice. Because the importation has been. | Multi-way Analysis in the Food Industry Models Algorithms and Applications This monograph was originally written as a Ph. D. thesis see end of file for original Dutch information printed in the thesis at this page i MULTI-WAY ANALYSIS IN THE FOOD INDUSTRY Models Algorithms Applications Rasmus Bro Chemometrics Group Food Technology Department of Dairy and Food Science Royal Veterinary and Agricultural University Denmark Abstract This thesis describes some of the recent developments in multi-way analysis in the field of chemometrics. Originally the primary purpose of this work was to test the adequacy of multi-way models in areas related to the food industry. However during the course of this work it became obvious that basic research is still called for. Hence a fair part of the thesis describes methodological developments related to multi-way analysis. A multi-way calibration model inspired by partial least squares regression is described and applied N-PLS . Different methods for speeding up algorithms for constrained and unconstrained multi-way models are developed compression fast non-negativity constrained least squares regression . Several new constrained least squares regression methods of practical importance are developed unimodality constrained regression smoothness constrained regression the concept of approximate constrained regression . Several models developed in psychometrics that have never been applied to real-world problems are shown to be suitable in different chemical settings. The PARAFAC2 model is suitable for modeling data with factors that shift. This is relevant for example for handling retention time shifts in chromatography. The PARATUCK2 model is shown to be a suitable model for many types of data subject to rank-deficiency. A multiplicative model for experimentally designed data is presented which extends the work of Mandel Gollob and Hegemann for two-factor experiments to an arbitrary number of factors. A matrix product is introduced .