Variable selection in the chemometric treatment of food data: A tutorial review

DE ARAÚJO GOMES, ADRIANO; AZCARATE, SILVANA M.; DINIZ, PAULO HENRIQUE GONÇALVES DIAS; DE SOUSA FERNANDES, DAVID DOUGLAS; VERAS, GERMANO

FOOD CHEMISTRY

ELSEVIER SCI LTD

Año: 2022 vol. 370

0308-8146

Food analysis covers aspects of quality and detection of possible frauds to ensure the integrity of the food. The arsenal of analytical instruments available for food analysis is broad and allows the generation of a large volume of information per sample. But this instrumental information may not yet give the desired answer; it must be processed to provide a final answer for decision making. The possibility of discarding non-informative and/or redundant signals can lead to models of better accuracy, robustness, and chemical interpretability, in line with the principle of parsimony. Thus, in this tutorial review, we cover aspects of variable selection in food analysis, including definitions, theoretical aspects of variable selection, and case studies showing the advantages of variable selection-based models concerning the use of a wide range of non-informative and redundant instrumental information in the analysis of food matrices.