Real-time monitoring of a coffee roasting process with near infrared spectroscopy using multivariate statistical analysis: A feasibility study

Abstract

This work proposes the use of near infrared (NIR) spectroscopy in diffuse reflectance mode and multivariate statistical process control (MSPC) based on principal component analysis (PCA) for real-time monitoring of the coffee roasting process. The main objective was the development of a MSPC methodology able to early detect disturbances to the roasting process resourcing to real-time acquisition of NIR spectra. A total of fifteen roasting batches were defined according to an experimental design to develop the MSPC models. This methodology was tested on a set of five batches where disturbances of different nature were imposed to simulate real faulty situations. Some of these batches were used to optimize the model while the remaining was used to test the methodology. A modelling strategy based on a time sliding window provided the best results in terms of distinguishing batches with and without disturbances, resourcing to typical MSPC charts: Hotelling's T and squared predicted error statistics. A PCA model encompassing a time window of four minutes with three principal components was able to efficiently detect all disturbances assayed. NIR spectroscopy combined with the MSPC approach proved to be an adequate auxiliary tool for coffee roasters to detect faults in a conventional roasting process in real-time.

Monitoring coffee roasting cracks and predicting with in situ near‐infrared spectroscopy

“…Two 50 W halogen bulbs placed at a 45° angle from the fiber probe illuminated the chamber, and the spectrometer captured a new NIR spectrum every 10 s during roasting. This differs from the setup used in previous in situ NIR studies, which have placed the probe at a distance of 2 mm from the roasting window (Catelani et al, ; Catelani et al, ; Santos, Lopo, et al, ; Santos, Viegas, et al, ). The increased distance allows a larger area of the sample (~6 cm 2 ) to be captured by the probe, resulting in improved averaging of inconsistencies in the coffee, but also requiring a more intense light source.…”

“…Only one study (Santos et al), measured color in situ with a correlation coefficient of 0.89. Several recent studies have measured other aspects of coffee with in situ NIR, including acidity, sucrose, roasting disturbances, and antioxidant properties (Catelani et al, ; Catelani et al, ; Santos, Lopo, Rangel, & Lopes, ; Santos, Viegas, et al, ). Roast degree has also been measured based on color with NIR hyperspectral imaging (Chu, Yu, Zhao, & He, ).…”

Evaluation of chemical properties of intact green coffee beans using near‐infrared spectroscopy

“…14 In quantitative analyses, signal strength in certain spectrum bands is related to analyte concentration. 15 Near-infrared spectroscopy has been successfully applied to coffee analysis, including estimation of its chemical properties, 16,17 roasting process monitoring, [18][19][20] adulteration detection, 15,21,22 determination of geographical origin 23 and sensory analysis. 3 Most of these studies evaluated NIR spectra measured from intact or ground roasted coffee bean.…”

Identification of markers of thermal processing (“roasting”) in aqueous extracts of Coffea arabica L. seeds through NMR fingerprinting and chemometrics

“…Using high‐performance liquid chromatography approaches, the formation of lactones by chlorogenic acids during roasting and the characterisation of coffee odourants or compounds responsible for bitter taste in the finished product have also been investigated . More recently, Catelani et al used near‐infrared spectroscopy and principal component analysis (PCA) for real‐time monitoring of the roasting process . Gloess et al resorted to ion mobility spectrometry–mass spectrometry with corona discharge ionisation to monitor online the formation of volatile organic compounds during coffee roasting …”