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Genetic Algorithm–Artificial Neural Network Modeling of Capsaicin and Capsorubin Content of Chinese Chili Oil

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Abstract

Chili oil, which contains large amounts of capsaicin and capsorubin, is one of the most consumed seasonings in China. These compounds significantly affect the quality, antioxidant activity, pungency, and color of chili oil. This study aimed to investigate the effect of stewing temperature, stewing time, and amount of oil on the capsaicin and capsorubin contents of Chinese chili oil. The partial least squares (PLS) regression and genetic algorithm–artificial neural network models were established and used to predict capsaicin and capsorubin contents. The genetic algorithm was applied to optimize the parameters of the network. The developed genetic algorithm–artificial neural network, which included ten hidden neurons, predicted capsaicin and capsorubin contents with correlation coefficients of 0.995 and 0.986, respectively. The neural network exhibited more accurate prediction and practicability compared with the PLS regression model.

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Acknowledgments

This study was financially supported by the National Key Technology R&D Program (2012BAD31B08) and National science and technology program (2012BAD27B00). The authors gratefully acknowledge the members of the Hubei Food and Fermentation Engineering Technology Research Centre.

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Authors and Affiliations

  1. Hubei Collaborative Innovation Center of Industrial Fermentation, Research Center of Food Fermentation Engineering and Technology of Hubei, Key Laboratory of Fermentation Engineering (Ministry of Education), Hubei University of Technology, Lizhi Road 1st, Wuhan City, Hubei Province, 430068, China

    Cheng Ding, Libin Xu, Na Zhou, Yang Chen, Dongsheng Li, Ning Xu, Yong Hu & Chao Wang

  2. Hubei Shunxi Biological Food Co., Ltd, Wuhan, China

    Yueze Cao

Authors
  1. Cheng Ding
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  2. Libin Xu
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  3. Na Zhou
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  4. Yang Chen
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  5. Dongsheng Li
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  6. Ning Xu
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  7. Yong Hu
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  8. Yueze Cao
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  9. Chao Wang
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Corresponding author

Correspondence to Chao Wang.

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Funding

We have received research grants from National Key Technology R&D Program (2012BAD31B08) and National science and technology program (2012BAD27B00).

Conflict of Interest

Cheng Ding declares that there is no conflict of interest. Libin Xu declares that there is no conflict of interest. Na Zhou declares that there is no conflict of interest. Yang Chen declares that there is no conflict of interest. Dongsheng Li declares that there is no conflict of interest. Ning Xu declares that there is no conflict of interest. Yong Hu declares that there is no conflict of interest. Yueze Cao declares that there is no conflict of interest. Chao Wang declares that there is no conflict of interest.

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This article does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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Ding, C., Xu, L., Zhou, N. et al. Genetic Algorithm–Artificial Neural Network Modeling of Capsaicin and Capsorubin Content of Chinese Chili Oil. Food Anal. Methods 9, 2076–2086 (2016). https://doi.org/10.1007/s12161-015-0392-3

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  • DOI: https://doi.org/10.1007/s12161-015-0392-3

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