Soluble Coffee Classification through Rapid Scanning Methodologies

Foods

The Specialty Coffee Association (SCA) sensory analysis protocol is the methodology that is used to classify specialty coffees. However, because the sensory analysis is sensitive to the taster’s training, cognitive psychology, and physiology, among other parameters, the feasibility of instrumental approaches has been recently studied for complementing such analyses. Spectroscopic methods, mainly near infrared (NIR) and mid infrared (FTIR—Fourier Transform Infrared), have been extensively employed for food quality authentication. In view of the aforementioned, we compared NIR and FTIR to distinguish different qualities and sensory characteristics of specialty coffee samples in the present study. Twenty-eight green coffee beans samples were roasted (in duplicate), with roasting conditions following the SCA protocol for sensory analysis. FTIR and NIR were used to analyze the ground and roasted coffee samples, and the data then submitted to statistical analysis to build up PLS models in...

Food Research International, 2014

During the last two decades, near and mid-infrared spectral analyses have emerged as a reliable and promising analytical tool for objective assessment of coffee quality attributes. The literature presented in this review clearly reveals that near and mid-infrared approaches have a huge potential for gaining rapid information about the chemical composition and related properties of coffee. In addition to its ability for effectively quantifying and characterizing quality attributes of some important features of coffee such as moisture, lipids and caffeine content, classification into quality grades and determination of sensory attributes, it is able to measure multiple chemical constituents simultaneously avoiding extensive sample preparation. Developing a quality evaluation system based on infrared spectral information to assess the coffee quality parameters and to ensure its authentication would bring economical benefits to the coffee industry by increasing consumer confidence in the quality of products. This paper provides an overview of the recently developed approaches and latest research carried out in near and mid-infrared spectral technology for evaluating the quality and composition of coffee and the possibility of its widespread deployment.

ETP International Journal of Food Engineering, 2016

Given the successful application of spectroscopic methods in the field of coffee analysis as fast and reliable routine techniques, the objective of this work was to evaluate the feasibility of employing Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) for discrimination between roasted coffees that presented distinct sensory characteristics and were submitted to a range of roasting conditions. Samples consisted of coffees obtained from Nespresso type capsules of intensity levels ranging from 2 to 12. Principal Component Analysis (PCA) of the processed spectra provided separation of the samples into three groups: low (positive PC1), medium (scattered) and high (negative PC1) intensity. Group separation was related to both roasting intensity and sensory parameters, with a clear separation between samples described as low roasted with fruity and floral flavors in comparison to samples described as being intense and very roasted. PLS-DA models were constructed and provided satisfactory discrimination according to sensory characteristics. Samples were classified according to flavor as sugar browning, enzymatic, or dry distillation. Such results confirm the potential of DRIFTS in the discrimination and classification of roasted and ground coffees.

Journal of Food Science, 2011

The objective of this work was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) in the characterization and discrimination between immature and mature or ripe coffee beans. Arabica coffee beans were submitted to FTIR analysis by reflectance readings employing attenuated total reflectance (ATR) and diffuse reflectance (DR) accessories. The obtained spectra were similar, but in general higher absorbance values were observed for nondefective beans in comparison to immature ones. Multivariate statistical analysis (principal component analysis, PCA, and agglomerative hierarchical clustering, AHC) was performed in order to verify the possibility of discrimination between immature and mature coffee samples. A clear separation between immature and mature coffees was observed based on AHC and PCA analyses of the normalized spectra obtained by employing both ATR and DR accessories. Linear discriminant analysis was employed for developing classification models, with recognition and prediction abilities of 100%. Such results showed that FTIR analysis presents potential for the development of a simple routine methodology for separation of immature and mature coffee beans.

Journal of Agricultural and Food Chemistry, 1996

Two species of coffee bean have acquired worldwide economic importance: these are, Coffea Arabica and Coffea Canephora variant Robusta. Arabica beans are valued most highly by the trade, as they are considered to have a finer flavor than Robusta. In this work, Fourier ...

UV–Vis spectrometry and chemometric techniques were used to classify aqueous extracts of Brazilian ground roast coffee with respect to type (caffeinated/decaffeinated) and conservation state (expired and non-expired shelf-life). Two classification methods were compared: soft independent modelling of class analogy (SIMCA) and linear discriminant analysis (LDA) with wavelength selection by the successive projections algorithm (SPA). The best results were obtained by SPA–LDA, which correctly classified all test samples. The classification accuracy of this model remained high (96%) even after the introduction of artificial spectral noise. These results suggest that UV–Vis spectrometry and SPA–LDA modelling provide a promising alternative for assessment of conservation state and decaffeination condition of coffee samples.

Journal of Food Science, 2009

Kona coffee, the variety of "Kona typica" grown in the north and south districts of Kona-Island, carries a unique stamp of the region of Big Island of Hawaii, U.S.A. The excellent quality of Kona coffee makes it among the best coffee products in the world. Fourier transform infrared (FTIR) spectroscopy integrated with an attenuated total reflectance (ATR) accessory and multivariate analysis was used for qualitative and quantitative analysis of ground and brewed Kona coffee and blends made with Kona coffee. The calibration set of Kona coffee consisted of 10 different blends of Kona-grown original coffee mixture from 14 different farms in Hawaii and a non-Kona-grown original coffee mixture from 3 different sampling sites in Hawaii. Derivative transformations , mathematical enhancements such as mean centering and variance scaling, multivariate regressions by partial least square (PLS), and principal components regression (PCR) were implemented to develop and enhance the calibration model. The calibration model was successfully validated using 9 synthetic blend sets of 100% Kona coffee mixture and its adulterant, 100% non-Kona coffee mixture. There were distinct peak variations of ground and brewed coffee blends in the spectral "fingerprint" region between 800 and 1900 cm −1 . The PLS-2nd derivative calibration model based on brewed Kona coffee with mean centering data processing showed the highest degree of accuracy with the lowest standard error of calibration value of 0.81 and the highest R 2 value of 0.999. The model was further validated by quantitative analysis of commercial Kona coffee blends. Results demonstrate that FTIR can be a rapid alternative to authenticate Kona coffee, which only needs very quick and simple sample preparations.

Molecules, 2022

Coffee is both a vastly consumed beverage and a chemically complex matrix. For a long time, an arduous chemical analysis was necessary to resolve coffee authentication issues. Despite their demonstrated efficacy, such techniques tend to rely on reference methods or resort to elaborate extraction steps. Near infrared spectroscopy (NIRS) and the aquaphotomics approach, on the other hand, reportedly offer a rapid, reliable, and holistic compositional overview of varying analytes but with little focus on low concentration mixtures of Robusta-to-Arabica coffee. Our study aimed for a comparative assessment of ground coffee adulteration using NIRS and liquid coffee adulteration using the aquaphotomics approach. The aim was to demonstrate the potential of monitoring ground and liquid coffee quality as they are commercially the most available coffee forms. Chemometrics spectra analysis proved capable of distinguishing between the studied samples and efficiently estimating the added Robusta c...

Food Chemistry, 2012

The objective of this work was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) for the discrimination of defective and non-defective coffee beans. Defective (black, immature and sour) and non-defective Arabica coffee beans were submitted to FTIR analysis by transmittance readings employing KBr discs and reflectance readings employing attenuated total reflectance (ATR) and diffuse reflectance (DR) accessories. Multivariate statistical analysis (PCA, clusters) was performed in order to verify the possibility of discrimination between defective and non-defective coffee samples. A clear separation between defective and non-defective coffee beans was observed, based on both PCA and cluster analysis of the reflectance spectra (ATR and DR accessories) and of the first derivatives of the transmittance spectra (KBr discs). Such results indicate that FTIR analysis has the potential for the development of a fast and reliable analytical methodology for the discrimination between defective and non-defective coffee beans.

Food Chemistry, 2011

We have applied visible micro Raman spectroscopy combined with principal component analysis (PCA) as a powerful technique for the fast discrimination between the two coffee species, Arabica and Robusta, based on their chlorogenic acid (CGA) and lipid contents. The Raman spectra reveal different CGA and lipid compositions when comparing Arabica and Robusta green coffee. Analysing the whole Raman spectrum, the PCA yielded a clear separation between Arabica and Robusta with 93% of the total spectral variation. Here, the most significant spectral range lies between 1000 and 1750 cm À1 and is dominated by the Raman bands of CGA. Also, by restricting the PCA analysis to the spectral range from 2700 to 3050 cm À1 , which is dominated by lipid bands, a reliable discrimination between the two coffee species could be achieved. In this case, the first two principal components of the PCA accounted for 85% of the explained total spectral variation.