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Analysis of Computer Vision Algorithms to Determine the Quality of Fermented Cocoa (Theobroma Cacao): Systematic Literature Review

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ICT for Agriculture and Environment (CITAMA2019 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 901))

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Abstract

Computer vision techniques have been used for the automation of processes in the agricultural sector due to the benefits obtained such as effectiveness and quality. A clear example is the analysis of cocoa beans quality. The increasing interest of computer vision in this area calls for a clear, systematic overview. In this sense, we present a systematic literature review (SLR) of computer vision algorithms to determine the quality of fermented cocoa in a six-year period: from 2013–2018. The aim of this review is to identify the techniques or computer vision algorithms used to assess fermentation index of cocoa beans for quality control, as well, the main physical and chemical characteristics of the cocoa beans identified through the computer vision algorithms. The results show that the PLS (Partial Least-Squares) algorithm is the most used for the classification of images in a statistical approach. Also, color is the physical parameter that is commonly identified through artificial vision algorithms. Meanwhile, Fat and pH are the chemical parameters most identified by FT-NIR (Fourier transform near-infrared) technology in conjunction with the chemometric technique.

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Acknowledgments

We thank the researchers of the Agrarian University of Ecuador for their contribution in the search of the opportune information for the literature review

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Authors and Affiliations

  1. Faculty of Agricultural Sciences, Computer Science Department, Agrarian University of Ecuador, Av. 25 de Julio y Pio Jaramillo, P.O. BOX 09-04-100, Guayaquil, Ecuador

    Karen Mite-Baidal, Evelyn Solís-Avilés, Tayron Martínez-Carriel, Augusto Marcillo-Plaza, Elicia Cruz-Ibarra & Wilmer Baque-Bustamante

Authors
  1. Karen Mite-Baidal
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  2. Evelyn Solís-Avilés
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  3. Tayron Martínez-Carriel
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  4. Augusto Marcillo-Plaza
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  5. Elicia Cruz-Ibarra
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  6. Wilmer Baque-Bustamante
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Corresponding author

Correspondence to Karen Mite-Baidal .

Editor information

Editors and Affiliations

  1. Facultad de Informática, Universidad de Murcia, Murcia, Spain

    Rafael Valencia-García

  2. Departamento de Filología Moderna, Universidad de Castilla-La Mancha, Toledo, Spain

    Gema Alcaraz-Mármol

  3. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Javier del Cioppo-Morstadt

  4. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Néstor Vera-Lucio

  5. Universidad Agraria del Ecuador, Guayaquil, Ecuador

    Martha Bucaram-Leverone

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Mite-Baidal, K., Solís-Avilés, E., Martínez-Carriel, T., Marcillo-Plaza, A., Cruz-Ibarra, E., Baque-Bustamante, W. (2019). Analysis of Computer Vision Algorithms to Determine the Quality of Fermented Cocoa (Theobroma Cacao): Systematic Literature Review. In: Valencia-García, R., Alcaraz-Mármol, G., Cioppo-Morstadt, J., Vera-Lucio, N., Bucaram-Leverone, M. (eds) ICT for Agriculture and Environment. CITAMA2019 2019. Advances in Intelligent Systems and Computing, vol 901. Springer, Cham. https://doi.org/10.1007/978-3-030-10728-4_9

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