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FT NIR assisted Machine and Deep learning for determination of Acteoside, Aucubin and Catalpol contents of Plantago lanceolata

Author

Listed:
  • Cedric Camps
  • Xavier Simonnet

    (Agroscope, Institute for Plant Production Sciences IPS, Switzerland)

  • Valérie Bardot
  • Michel Dubourdeaux

    (Pileje Industrie, Naturopôle Nutrition Santé, Les Tiolans, F-03800 Saint-Bonnet-de-Rochefort, France)

Abstract

Aucubin, acteoside and catalpol are important compounds present in this plant but their determination is time consuming, costly and necessitate the use of chemicals. In the present study we developed a method based on FT-NIR spectroscopy to determine aucubin, acteoside and catalpol from dry powders of Plantago lanceolata. FT-NIR spectra were processed in PLS and deep learning methods and the accuracies of models were calculated and compared. Aucubin, acteoside and catalpol contents were predicted with a root mean square error of 0.56, 0.25 and 0.18%, respectively by using PLS method. Deep learning did not allow to improve the accuracies but allowed obtaining similar accuracies. FT-NIR based method showed interesting results and is promising to develop a fully usable method for selection programs of plantain with high level contents of bioactive compounds.

Suggested Citation

  • Cedric Camps & Xavier Simonnet & Valérie Bardot & Michel Dubourdeaux, 2020. "FT NIR assisted Machine and Deep learning for determination of Acteoside, Aucubin and Catalpol contents of Plantago lanceolata," Agricultural Research & Technology: Open Access Journal, Juniper Publishers Inc., vol. 25(2), pages 64-68, October.
    • Handle: RePEc:adp:artoaj:v:25:y:2020:i:2:p:64-68
    DOI: 10.19080/ARTOAJ.2020.25.556296
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    References listed on IDEAS

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    1. Editorial Article, 0. "Contents," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    2. Editorial Article, 0. "Contents," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 3.
    3. Editorial Article, 0. "Contents," Economics of Contemporary Russia, Regional Public Organization for Assistance to the Development of Institutions of the Department of Economics of the Russian Academy of Sciences, issue 2.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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