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Fractality in coffee bean surface for roasting process

Author

Listed:
  • Gabriel-Guzmán, Mauricio
  • Rivera, Victor M.
  • Cocotle-Ronzón, Yolanda
  • García-Díaz, Samuel
  • Hernandez-Martinez, Eliseo

Abstract

The roasting is the stage where the coffee bean undergoes physiochemical changes that provide their typical sensory characteristics (i.e., aroma and flavor). Despite the importance, the roasting process is performed based on the operator experience, which makes difficult the homogenization between batches of roasted coffee. In that sense, this paper proposes a methodology to analyze changes in the coffee bean during roasting; this can be used as an indicator of the roasting degree. The proposal is based on R/S fractal analysis of coffee bean surface images taken during the roasting process. The results indicate that the Hurst exponent exhibits dynamic changes that can be correlated with the physical changes of the coffee bean, such as fractures and color changes, suggesting that the fractal index could be used for indirect monitoring of the roasting degree.

Suggested Citation

  • Gabriel-Guzmán, Mauricio & Rivera, Victor M. & Cocotle-Ronzón, Yolanda & García-Díaz, Samuel & Hernandez-Martinez, Eliseo, 2017. "Fractality in coffee bean surface for roasting process," Chaos, Solitons & Fractals, Elsevier, vol. 99(C), pages 79-84.
    • Handle: RePEc:eee:chsofr:v:99:y:2017:i:c:p:79-84
    DOI: 10.1016/j.chaos.2017.03.056
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    References listed on IDEAS

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    1. Alvarez-Ramirez, Jose & Echeverria, Juan C. & Rodriguez, Eduardo, 2008. "Performance of a high-dimensional R/S method for Hurst exponent estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(26), pages 6452-6462.
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    Cited by:

    1. Ramírez-Platas, Mariana & Morales-Cabrera, Miguel A. & Rivera, Victor M. & Morales-Zarate, Epifanio & Hernandez-Martinez, Eliseo, 2021. "Fractal and multifractal analysis of electrochemical noise to corrosion evaluation in A36 steel and AISI 304 stainless steel exposed to MEA-CO2 aqueous solutions," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    2. Martsepp, Merike & Laas, Tõnu & Laas, Katrin & Priimets, Jaanis & Tõkke, Siim & Mikli, Valdek, 2022. "Dependence of multifractal analysis parameters on the darkness of a processed image," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    3. Eugenio Ivorra & Juan Camilo Sarria-González & Joel Girón-Hernández, 2020. "Computer vision techniques for modelling the roasting process of coffee (Coffea arabica L.) var. Castillo," Czech Journal of Food Sciences, Czech Academy of Agricultural Sciences, vol. 38(6), pages 388-396.
    4. Zenteno-Catemaxca, Rolando & Moguel-Castañeda, Jazael G. & Rivera, Victor M. & Puebla, Hector & Hernandez-Martinez, Eliseo, 2021. "Monitoring a chemical reaction using pH measurements: An approach based on multiscale fractal analysis," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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