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Estimation of Anthocyanins in Homogeneous Bean Landraces Using Neuroevolution

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Advances in Computational Intelligence. MICAI 2023 International Workshops (MICAI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14502))

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Abstract

A pigment of great interest is the anthocyanins. It is due to the nutritional benefits discovered in various foods, such as common beans. In this work, we report the estimation of anthocyanins in homogeneous colored bean landraces using neuroevolution. Two neuroevolution techniques, NEAT and DeepGA, were implemented to find this task’s suitable neural network structure. Both techniques were compared against a Convolutional Neural Network (CNN) experimentally developed called AnthEst-Net architecture, which found competitive results in anthocyanin estimation. The input data of the network architectures were two-color characterizations, two-dimensional histograms, and data vectors. The accuracies obtained on the test set in HSI color space were 85.38 ± 11.77 and 87.89 ± 9.67 for DeepGA and AnthEstNet architecture, respectively. Regarding CIE L*a*b* color space, DeepGA obtained an accuracy of 86.85 ± 11.08, while AnthEstNet got 87.08 ± 14.19. Results suggest that the architecture reported by DeepGA is suitable for anthocyanins estimation.

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Acknowledgements

The first author acknowledges the National Council of Humanities, Sciences and Technologies (CONAHCyT) of Mexico for granting support for the realization of this investigation through scholarship 712056 awarded for postdoctoral studies at the Centre for Food Research and Development in the University of Veracruz.

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Authors and Affiliations

  1. Centre for Food Research and Development, University of Veracruz, Xalapa, Veracruz, Mexico

    José-Luis Morales-Reyes & Elia-Nora Aquino-Bolaños

  2. Artificial Intelligence Research Institute, University of Veracruz, Xalapa, Veracruz, Mexico

    Héctor-Gabriel Acosta-Mesa & Aldo Márquez-Grajales

Authors
  1. José-Luis Morales-Reyes
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  2. Elia-Nora Aquino-Bolaños
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  3. Héctor-Gabriel Acosta-Mesa
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  4. Aldo Márquez-Grajales
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Corresponding author

Correspondence to José-Luis Morales-Reyes .

Editor information

Editors and Affiliations

  1. Instituto Politecnico Nacional, Center for Computing Research, Mexico, Distrito Federal, Mexico

    Hiram Calvo

  2. Panamerican University, Ciudad de México, Distrito Federal, Mexico

    Lourdes Martínez-Villaseñor

  3. Universidad Panamericana, Mexico City, Distrito Federal, Mexico

    Hiram Ponce

  4. Instituto Tecnologico de Culiacan, Culiacán, Sinaloa, Mexico

    Ramón Zatarain Cabada

  5. Universidad Politécnica de Aguascalient, Aguascalientes, Mexico

    Martín Montes Rivera

  6. Universidad Veracruzana, Veracruz, Mexico

    Efrén Mezura-Montes

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Morales-Reyes, JL., Aquino-Bolaños, EN., Acosta-Mesa, HG., Márquez-Grajales, A. (2024). Estimation of Anthocyanins in Homogeneous Bean Landraces Using Neuroevolution. In: Calvo, H., Martínez-Villaseñor, L., Ponce, H., Zatarain Cabada, R., Montes Rivera, M., Mezura-Montes, E. (eds) Advances in Computational Intelligence. MICAI 2023 International Workshops. MICAI 2023. Lecture Notes in Computer Science(), vol 14502. Springer, Cham. https://doi.org/10.1007/978-3-031-51940-6_28

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  • DOI: https://doi.org/10.1007/978-3-031-51940-6_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-51939-0

  • Online ISBN: 978-3-031-51940-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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