REMPI-TOFMS for on-line monitoring and controlling the coffee roasting process

2001 ◽  
Author(s):  
Ralph Dorfner
Keyword(s):  
Roasting Process ◽  
On Line ◽  
Coffee Roasting

scholarly journals From the green bean to the cup of coffee: investigating coffee roasting by on-line monitoring of volatiles

2002 ◽  
Vol 214 (2) ◽  
pp. 92-104 ◽  
Author(s):  
Chahan Yeretzian ◽  
Alfons Jordan ◽  
Raphael Badoud ◽  
Werner Lindinger
Keyword(s):  
Green Bean ◽  
On Line ◽  
Coffee Roasting

scholarly journals Computer vision techniques for modelling the roasting process of coffee (Coffea arabica L.) var. Castillo

2020 ◽  
Vol 38 (No. 6) ◽  
pp. 388-396
Author(s):  
Eugenio Ivorra ◽  
Juan Camilo Sarria-González ◽  
Joel Girón-Hernández
Keyword(s):  
Robust Regression ◽  
Low Cost ◽  
Principal Component ◽  
Titratable Acidity ◽  
Artificial Vision ◽  
Physico Chemical ◽  
Coffee Beans ◽  
Roasting Process ◽  
Roasting Time ◽  
Coffee Roasting

Artificial vision has wide-ranging applications in the food sector; it is easy to use, relatively low cost and allows to conduct rapid non-destructive analyses. The aim of this study was to use artificial vision techniques to control and model the coffee roasting process. Samples of Castillo variety coffee were used to construct the roasting curve, with captured images at different times. Physico-chemical determinations, such as colour, titratable acidity, pH, humidity and chlorogenic acids, and caffeine content, were investigated on the coffee beans. Data were processed by (i) Principal component analysis (PCA) to observe the aggrupation depending on the roasting time, and (ii) partial least squares (PLS) regression to correlate the values of the analytical determinations with the image information. The results allowed to construct robust regression models, where the colour coordinates (L*, a*), pH and titratable acidity presented excellent values in prediction (R2Pred 0.95, 0.91, 0.94 and 0.92). The proposed algorithms were capable to correlate the chemical composition of the beans at each roasting time with changes in the images, showing promising results in the modelling of the coffee roasting process.

Numerical modeling of heat and mass transfer during coffee roasting process

2011 ◽  
Vol 105 (2) ◽  
pp. 264-269 ◽  
Author(s):  
Angelo Fabbri ◽  
Chiara Cevoli ◽  
Laura Alessandrini ◽  
Santina Romani
Keyword(s):  
Mass Transfer ◽  
Numerical Modeling ◽  
Heat And Mass Transfer ◽  
Roasting Process ◽  
Coffee Roasting

scholarly journals Temperature coverage simulation of horizontal cylinder type coffee roasting machine

2021 ◽  
Vol 922 (1) ◽  
pp. 012031
Author(s):  
F Fachruddin ◽  
S Syafriandi ◽  
R Fadhil
Keyword(s):  
Bulk Density ◽  
Horizontal Cylinder ◽  
Roasted Coffee ◽  
Actual Temperature ◽  
Coffee Beans ◽  
Roasting Process ◽  
Study Results ◽  
Roasting Temperature ◽  
Roasted Coffee Beans ◽  
Coffee Roasting

Abstract This study aims to simulate the temperature distribution of coffee roasting machines and study the profile of coffee beans roasted using a horizontal cylinder-type roaster. The coffee used in this study is arabica. The simulation method for the temperature estimation in the coffee roasting process uses the Solidworks Flow Simulation 2016 software, while the actual temperature measurement using a thermocouple is simulated with the Surfer software version 16. Furthermore, each stage of the coffee roasting process has been carried out, including the weight of the material, the roasting temperature, and the bulk density. The final step is to observe the profile of the roasted coffee beans at every minute of treatment. The study results indicate a difference between the approximate temperature simulation (top 176.85°C, bottom 191.97°C) and the actual temperature measured results (upper 214°C, bottom 220°C). The weight of the material (coffee green bean), the roasting temperature, and the bulk density during the test experienced regular movements from the beginning to the end of the treatment. The profile of roasted coffee beans shows a darker color movement along with the longer roasting time used. The profile of the roasted coffee beans will be beneficial in determining at which level of roasting you want (light, medium, medium-dark, dark).

scholarly journals Perbaikan Tingkat Risiko Musculoskeletal Disorders Berdasarkan Pendekatan Nordic Body Map dan Rapid Upper Limb Assessment Pada Hasil Rancang Bangun Mesin Roasting Kopi Digital Otomatis

2021 ◽  
Vol 10 (2) ◽  
pp. 191-200
Author(s):  
Ratih Rahmahwati
Keyword(s):  
Upper Limb ◽  
Musculoskeletal Complaints ◽  
West Kalimantan ◽  
Roasting Machine ◽  
Work Posture ◽  
Working Posture ◽  
Coffee Beans ◽  
Roasting Process ◽  
Body Map ◽  
Coffee Roasting

The roasting process of coffee beans in West Kalimantan, especially Pontianak city, is still done traditionally. The coffee roasting process is done manually by using a fire stove as a heater. Workers with standing posture stir the coffee beans continuously, and it can take 4 hours for 20 kilos of coffee beans. Standing work posture is required for stirring the coffee beans but can cause fatigue in workers due to long-standing times and high heating temperatures. This situation causes the roasting process to be less efficient and can cause the roasting process to be uneven. The purpose of this study was to identify musculoskeletal complaints of standing work posture in the manual coffee roasting process and provide an evaluation of corrective work posture when using the design results of an automatic digital roasting machine. The methods used in this study were the Nordic Body Map (NBM) and the Rapid Upper Limb Assessment (RULA) to assess the level of risk of posture for musculoskeletal complaints. The results of the identification of body points that experience fatigue were carried out by distributing NBM questionnaires and evaluating the worker's posture using RULA on CATIA V5R20. Based on the existing NBM, the risk score is 78, and the final RULA score is 6, which means that immediate corrective action is needed because the work posture is categorized as dangerous and does not meet ergonomic principles. Improvement of working posture is made by designing a roasting machine that is digital and automatic. So the workers do not need to mix the coffee beans manually. Based on roasting machine implementation results, there was a significant change in the NBM score and the final RULA score. The NBM results obtained a score of 55 which means that the risk is moderate with the risk of fatigue in the neck, right leg and, left leg. Meanwhile, evaluation of work posture based on RULA on CATIA obtained a final score of 3, which means that the work posture is not dangerous and does not require immediate improvement.  

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