Real-time spectrophotometric determination of coffee roast degree

One of the most pivotal stages of coffee production is the roasting process, as it determines the quality of the beverage. The final measure of the degree of roast is determined by the color of the bean. Visual inspection of the bean color using the naked eye can be a source of inconsistency since m...

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Main Authors: Andres, Jerome Moises L., Araño, Angelo C., Diwara, Don Levi Andre V., Sazon, Cedric Paul M.
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Language:English
Published: Animo Repository 2022
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Online Access:https://animorepository.dlsu.edu.ph/etdb_ece/22
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1017&context=etdb_ece
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etdb_ece-10172022-12-20T03:02:04Z Real-time spectrophotometric determination of coffee roast degree Andres, Jerome Moises L. Araño, Angelo C. Diwara, Don Levi Andre V. Sazon, Cedric Paul M. One of the most pivotal stages of coffee production is the roasting process, as it determines the quality of the beverage. The final measure of the degree of roast is determined by the color of the bean. Visual inspection of the bean color using the naked eye can be a source of inconsistency since many factors are involved. For instance, the human visual system (HVS) exhibits chromatic adaptation where the perceived color of an object is affected by the color of the ambient light, and assessment of color is a subjective task that may cause inconsistencies. Professional roasters use an Agtron Process Analyzer to objectively measure the degree of roast, but measurement can only be done after the coffee beans are cooled. Thus, no changes can be made if the roast level is under or over the desired degree. Hence, this study proposes to create a device made of an LED module, microcontroller, and a camera that will measure the degree of roast in real-time by quantifying the amount of light reflected at different wavelengths by the coffee beans during the roasting process. The process involves using a Convolutional Neural Network (CNN) that extracts features from the images in the dataset and generates a reflectance output and Regression that will manipulate the data and will yield an Agtron number that is used in the determination of the coffee Roast degree. The Real-time measurement of the Agtron number aims to lessen the human subjectivity in the determination of the coffee roast degree and set a gauge of measurement of the doneness of the coffee beans during the roasting process. 2022-12-01T08:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdb_ece/22 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1017&context=etdb_ece Electronics And Communications Engineering Bachelor's Theses English Animo Repository Image processing Coffee—Processing Coffee—Imaging Electrical and Computer Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Image processing
Coffee—Processing
Coffee—Imaging
Electrical and Computer Engineering
spellingShingle Image processing
Coffee—Processing
Coffee—Imaging
Electrical and Computer Engineering
Andres, Jerome Moises L.
Araño, Angelo C.
Diwara, Don Levi Andre V.
Sazon, Cedric Paul M.
Real-time spectrophotometric determination of coffee roast degree
description One of the most pivotal stages of coffee production is the roasting process, as it determines the quality of the beverage. The final measure of the degree of roast is determined by the color of the bean. Visual inspection of the bean color using the naked eye can be a source of inconsistency since many factors are involved. For instance, the human visual system (HVS) exhibits chromatic adaptation where the perceived color of an object is affected by the color of the ambient light, and assessment of color is a subjective task that may cause inconsistencies. Professional roasters use an Agtron Process Analyzer to objectively measure the degree of roast, but measurement can only be done after the coffee beans are cooled. Thus, no changes can be made if the roast level is under or over the desired degree. Hence, this study proposes to create a device made of an LED module, microcontroller, and a camera that will measure the degree of roast in real-time by quantifying the amount of light reflected at different wavelengths by the coffee beans during the roasting process. The process involves using a Convolutional Neural Network (CNN) that extracts features from the images in the dataset and generates a reflectance output and Regression that will manipulate the data and will yield an Agtron number that is used in the determination of the coffee Roast degree. The Real-time measurement of the Agtron number aims to lessen the human subjectivity in the determination of the coffee roast degree and set a gauge of measurement of the doneness of the coffee beans during the roasting process.
format text
author Andres, Jerome Moises L.
Araño, Angelo C.
Diwara, Don Levi Andre V.
Sazon, Cedric Paul M.
author_facet Andres, Jerome Moises L.
Araño, Angelo C.
Diwara, Don Levi Andre V.
Sazon, Cedric Paul M.
author_sort Andres, Jerome Moises L.
title Real-time spectrophotometric determination of coffee roast degree
title_short Real-time spectrophotometric determination of coffee roast degree
title_full Real-time spectrophotometric determination of coffee roast degree
title_fullStr Real-time spectrophotometric determination of coffee roast degree
title_full_unstemmed Real-time spectrophotometric determination of coffee roast degree
title_sort real-time spectrophotometric determination of coffee roast degree
publisher Animo Repository
publishDate 2022
url https://animorepository.dlsu.edu.ph/etdb_ece/22
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1017&context=etdb_ece
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