Quantitative assessment of specific defects in roasted ground coffee via infrared-photoacoustic spectroscopy

•Spectroscopic and chemometric studies for quality control of processed coffees.•Panel of 154 blends of healthy and defective beans of Arabica and Robusta coffees.•Infrared spectroscopy with photoacoustic detection assesses coffee composition.•Multivariate analysis applied for discrimination of roas...

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Veröffentlicht in:Food chemistry 2018-07, Vol.255, p.132-138
Hauptverfasser: Dias, Rafael Carlos Eloy, Valderrama, Patrícia, Março, Paulo Henrique, dos Santos Scholz, Maria Brigida, Edelmann, Michael, Yeretzian, Chahan
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Sprache:eng
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Zusammenfassung:•Spectroscopic and chemometric studies for quality control of processed coffees.•Panel of 154 blends of healthy and defective beans of Arabica and Robusta coffees.•Infrared spectroscopy with photoacoustic detection assesses coffee composition.•Multivariate analysis applied for discrimination of roasted coffee samples.•Simple and high sample throughput analytical technique for coffee quality monitoring. Chemical analyses and sensory evaluation are the most applied methods for quality control of roasted and ground coffee (RG). However, faster alternatives would be highly valuable. Here, we applied infrared-photoacoustic spectroscopy (FTIR-PAS) on RG powder. Mixtures of specific defective beans were blended with healthy (defect-free) Coffea arabica and Coffea canephora bases in specific ratios, forming different classes of blends. Principal Component Analysis allowed predicting the amount/fraction and nature of the defects in blends while partial Least Squares Discriminant Analysis revealed similarities between blends (=samples). A successful predictive model was obtained using six classes of blends. The model could classify 100% of the samples into four classes. The specificities were higher than 0.9. Application of FTIR-PAS on RG coffee to characterize and classify blends has shown to be an accurate, easy, quick and “green” alternative to current methods.
ISSN:0308-8146
1873-7072
DOI:10.1016/j.foodchem.2018.02.076