Controle do estágio de torrefação de café através de técnicas de visão artificial

Juan Camilo Sarria-González; Eugenio Ivorra-Martínez; Joel Girón-Hernández

doi:10.25186/cs.v14i1.1517

Controle do estágio de torrefação de café através de técnicas de visão artificial

Translated title of the contribution: Control of the coffee roasting stage usingsi-gnzáz1artificial j vision techniques

Juan Camilo Sarria-González, Eugenio Ivorra-Martínez, Joel Girón-Hernández

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Artificial vision techniques were used to evaluate its application in the control of the coffee roasting stage. Coffee samples of Colombia and Castillo varieties were obtained and analyzed by comparing images during the roasting stage. A one-way ANOVA analysis exhibited 94.28% of similarity of the coffee varieties studied; a multivariate analysis showed significant differences (p<0.05) for the time factor and its interaction with the variety factor, no differences were observed (p>0.05) for the coffee varieties. Additionally, a Principal Component, with two components demonstrated 90.77% of the variance by differentiating the samples in the different roasting times. Therefore, the proposed technique could be used in the control of the coffee roasting stage.

Translated title of the contribution	Control of the coffee roasting stage usingsi-gnzáz1artificial j vision techniques
Original language	Portuguese
Pages (from-to)	33-37
Number of pages	5
Journal	Coffee Science
Volume	14
Issue number	1
DOIs	https://doi.org/10.25186/cs.v14i1.1517
Publication status	Published - 2019
Externally published	Yes

Keywords

Index terms: Variety Colombia
Variety Castillo
Visible spectrum

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10.25186/cs.v14i1.1517

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title = "Controle do est{\'a}gio de torrefa{\c c}{\~a}o de caf{\'e} atrav{\'e}s de t{\'e}cnicas de vis{\~a}o artificial",

abstract = "Artificial vision techniques were used to evaluate its application in the control of the coffee roasting stage. Coffee samples of Colombia and Castillo varieties were obtained and analyzed by comparing images during the roasting stage. A one-way ANOVA analysis exhibited 94.28% of similarity of the coffee varieties studied; a multivariate analysis showed significant differences (p<0.05) for the time factor and its interaction with the variety factor, no differences were observed (p>0.05) for the coffee varieties. Additionally, a Principal Component, with two components demonstrated 90.77% of the variance by differentiating the samples in the different roasting times. Therefore, the proposed technique could be used in the control of the coffee roasting stage.",

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author = "Sarria-Gonz{\'a}lez, {Juan Camilo} and Eugenio Ivorra-Mart{\'i}nez and Joel Gir{\'o}n-Hern{\'a}ndez",

year = "2019",

doi = "10.25186/cs.v14i1.1517",

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AU - Sarria-González, Juan Camilo

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AU - Girón-Hernández, Joel

PY - 2019

Y1 - 2019

N2 - Artificial vision techniques were used to evaluate its application in the control of the coffee roasting stage. Coffee samples of Colombia and Castillo varieties were obtained and analyzed by comparing images during the roasting stage. A one-way ANOVA analysis exhibited 94.28% of similarity of the coffee varieties studied; a multivariate analysis showed significant differences (p<0.05) for the time factor and its interaction with the variety factor, no differences were observed (p>0.05) for the coffee varieties. Additionally, a Principal Component, with two components demonstrated 90.77% of the variance by differentiating the samples in the different roasting times. Therefore, the proposed technique could be used in the control of the coffee roasting stage.

AB - Artificial vision techniques were used to evaluate its application in the control of the coffee roasting stage. Coffee samples of Colombia and Castillo varieties were obtained and analyzed by comparing images during the roasting stage. A one-way ANOVA analysis exhibited 94.28% of similarity of the coffee varieties studied; a multivariate analysis showed significant differences (p<0.05) for the time factor and its interaction with the variety factor, no differences were observed (p>0.05) for the coffee varieties. Additionally, a Principal Component, with two components demonstrated 90.77% of the variance by differentiating the samples in the different roasting times. Therefore, the proposed technique could be used in the control of the coffee roasting stage.

KW - Index terms: Variety Colombia

KW - Variety Castillo

KW - Visible spectrum

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EP - 37

JO - Coffee Science

JF - Coffee Science

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Controle do estágio de torrefação de café através de técnicas de visão artificial

Abstract

Keywords

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