The need to consider variability due to raw materials, seasonality, agricultural practices, and food processing, that are aspects which all play a role in authenticity tasks, justifies the need for chemometrics methods. This chapter presents a few basic chemometrics methods, such as exploratory data analysis, multiway data analysis, and data fusion. New chemometrics methods are continuously being updated and improved upon, two main distinctive characteristics are required: data exploration and graphical representation; and deep model validation through all steps of data processing. This also explains why chemometrics tools based on latent variables, for example, principal component analysis (PCA), soft independent modeling of class analogies (SIMCA), partial least squares (PLS), and PLS discriminant analysis (PLSDA), are still so popular and powerful. Nowadays, there is an established set of chemometric multiway methods and algorithms. The chapter mentions those that can serve the purposes of exploratory data analysis and classification, the tasks most frequently encountered in food authentication.

Chemometrics, Bioinformatics / Durante, Caterina; LI VIGNI, Mario; Cocchi, Marina. - (2017), pp. 481-518. [10.1002/9781118810224.ch17]

Chemometrics, Bioinformatics

DURANTE, Caterina;LI VIGNI, Mario;COCCHI, Marina
2017

Abstract

The need to consider variability due to raw materials, seasonality, agricultural practices, and food processing, that are aspects which all play a role in authenticity tasks, justifies the need for chemometrics methods. This chapter presents a few basic chemometrics methods, such as exploratory data analysis, multiway data analysis, and data fusion. New chemometrics methods are continuously being updated and improved upon, two main distinctive characteristics are required: data exploration and graphical representation; and deep model validation through all steps of data processing. This also explains why chemometrics tools based on latent variables, for example, principal component analysis (PCA), soft independent modeling of class analogies (SIMCA), partial least squares (PLS), and PLS discriminant analysis (PLSDA), are still so popular and powerful. Nowadays, there is an established set of chemometric multiway methods and algorithms. The chapter mentions those that can serve the purposes of exploratory data analysis and classification, the tasks most frequently encountered in food authentication.
2017
3-mar-2017
Food Authentication: Management, Analysis and Regulation
Constantinos A. Georgiou; Georgios P. Danezis
9781118810224
John Wiley & Sons, Ltd
Chemometrics, Bioinformatics / Durante, Caterina; LI VIGNI, Mario; Cocchi, Marina. - (2017), pp. 481-518. [10.1002/9781118810224.ch17]
Durante, Caterina; LI VIGNI, Mario; Cocchi, Marina
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1132272
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 5
social impact