Dados do Trabalho

Título

Near and mid-infrared spectra characterization of the main coffee compounds for chemical interpretation of multivariate models

Introdução

Infrared spectroscopy is an analytical technique that has improved the efficiency, safety and quality of food analysis. Both the mid-infrared (MIR) and near-infrared (NIR) regions have been important in this context. However, the chemical interpretation of multivariate models often lags behind in these applications. This interpretation provides the knowledge base for understanding the cause and effect of molecular structure with respect to specific types of absorption in the NIR and MIR to gain an analytical understanding of these measurements. One of the most commonly analyzed products using NIR and MIR spectroscopy is coffee, which has several compounds that interact with energy in this spectral region.

Material e Métodos

To support new studies using infrared analysis in coffee, this work directly analyzed the pure compounds or analytical standards of chlorogenic acids, caffeine, theobromine, caffeic acid, p-coumaric acid, theobromine, ferulic acid, gallic acid, cellulose, quercetin, catechin, sucrose, glucose, casein, and lipids using NIR and MIR instruments.

Resultados e Discussão

Most of these compounds are present in coffee and it was found that each of them has a different spectral behavior related to their absorption bands. This indicates that in order to obtain the important signals of a multivariate model, interpretation using pure spectra in parallel can be useful. However, there are variations that must be taken into account for a more reliable interpretation, such as the way the spectra of the samples are obtained in the laboratory, which must meet the same conditions as the analysis of the pure compounds.

Conclusão

In addition, these pure compound spectra can be used in multivariate models that use the pure signal as input. This can help models resolve mixtures of signals. In addition to being useful for coffee analysis applications with NIR and MIR, these results and interpreted pure spectra serve as a basis for working with other food matrices that share characteristics with coffee.