Special Issue "Application of Multivariate Data Analysis in Food Quality"

Dear Colleagues,

Nowadays, in the era of globalization of the food market, increase in consumers' awareness and their demands, as well as the influence of the food industry on the environment, economic and social aspects of food production, there is a great interest of consumers, public opinion, as well as politicians in production methods, safety, and quality of food products. This leads to the necessity of having effective tools for monitoring, optimization, characterization, specification, authenticity and adulteration of raw materials, intermediates, and final products. A full spectrum of analytical methods is now available to collect multivariate and complex datasets on widely perceived food quality.  Although multivariate measurements provide much more information and often allow a better understanding of complex systems, they can also make it difficult to analyse data and extract the maximum amount of information. Correct and valuable interpretation of multivariate data sets requires the use of appropriate mathematical and statistical methods (multivariate analysis). Therefore, we are initiating this special issue to discuss the latest developments in application of multivariate analysis in food quality. In this Special Issue, original research articles and reviews are welcome. Research areas may include the following: supervised and unsupervised multivariate exploratory analyses (such as principal component analysis, cluster analysis, linear and partial least squares discriminant analysis, classification and regression trees,  support vector machine and others) design-of-experiment methodology, multivariate regression modelling, multivariate calibration, multivariate process control, artificial neural networks and others.

Dr. Anna Kaczmarek
Guest Editor

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• multivariate data analysis
• food quality
• multivariate modeling
• multivariate classification
• artificial neural networks
• multivariate calibration
• multivariate process control