In-line monitoring of the coffee roasting process with near infrared spectroscopy: Measurement of sucrose and colour

A Non-invasive Real-Time Methodology for the Quantification of Antioxidant Properties in Coffee During the Roasting Process Based on Near-Infrared Spectroscopy

“…NIRS has been used successfully for quantification of chemical compounds in coffee samples (Pizarro et al 2004(Pizarro et al , 2007, discrimination between Arabica and Robusta species (Esteban-Díez et al 2007), and prediction of sensory properties and degree of roast (Esteban-Díez et al 2004;Ribeiro et al 2011). Recently, in a pioneering approach, NIRS was employed for in situ prediction of titratable acidity (Santos et al 2016a) and sucrose concentration (Santos et al 2016b) during coffee roasting processes. The potential to accompany chemical reactions during coffee roasting enables more efficient implementation of corrective procedures, better understanding of the roasting process, and, most importantly, improvement of the general quality of the coffee product.…”

Determination of the complex permittivity of cherry, pulped, green, and roasted coffee using a planar dielectric platform and a coaxial probe between 0.3 and 6 GHz

“…[22] As an alternative analytical approach, the dielectric spectroscopy approach losses the resonant nature of other approaches that have proven to be effective for this type of coffee studies. [30][31][32][33][34] One of the most notable advantages of this approach is that the samples do not require of any sort of previous handling and that the wide frequency range offers the possibility of exploring several behaviors. Consequently, this technology offers an intermediate alternative between data availability and easiness of analysis and use.…”

Farm to Consumer: Factors Affecting the Organoleptic Characteristics of Coffee. II: Postharvest Processing Factors

“…Color measurements have been successfully applied to predict the optimal temperature and period of roasting (Mendes, De Menezes, Aparecida, & Da Silva, ), acrylamide level (Gökmen & Şenyuva, ), and to discriminate between raw and roasted Arabica and Robusta beans (Mendonca, Franca, & Oliveira, ). Fine color correlations with sucrose content (Santos, Viegas, & Pascoa, ), acidity (Santos, Lopo, Rangel, & Lopes, ), moisture, density (Alessandrini, Romani, Pinnavaia, & Rosa, ), and caffeine content (Pizarro, Esteban‐Diez, Gonzalez‐Sáiz, & Forina, ) have also been established. Online roasting control systems via online image monitoring also work on the principle of evaluating variation in surface color/brightness and surface area of coffee beans (Hernandez, Heyd, & Trystram, ).…”

“… Note : Data were compiled from Akiyama et al., , 2003; Baggenstoss et al., ,b; Craig et al., ; Czerny et al., , 2008; Czerny & Grosch, ; Dawidowicz & Typek, ; Dorfner et al., ; Gloess et al., ; Gonzalez‐Rios et al., ,b; Grosch et al., , 2001a,b; Hertz‐Schünemann et al. , ; Lee et al., ,b; Mayer & Grosch, ; Moon and Shibamoto et al., ; Nebesny et al., ; Pramudita et al., ; Ribeiro et al., 2010; Rousi et al., 2012; Santos et al., ; Schenker et al., 2002; Steen et al., 2017; Toledo et al., ; Wang & Lim, .…”