Res. Agr. Eng., 2022, 68(4):216-222 | DOI: 10.17221/87/2021-RAE

Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case reportShort Communication

Dedi Wahyudi1,3, Erliza Noor1, Dwi Setyaningsih ORCID...*,1,4, Taufik Djatna2, Irmansyah Irmansyah2
1 Department of Agro-industrial Technology, IPB University, Bogor, Indonesia
2 Department of Physics, IPB University, Bogor, Indonesia
3 Polbangtan Medan, Ministry of Agriculture Republic Indonesia, Medan, Indonesia
4 Surfactant and Bioenergy Research Center, IPB University, Bogor, Indonesia

The rhodinol content is an essential component in determining the citronella oil qualities. This study aimed to develop a model calibrated to predict the rhodinol content in citronella oil using near-infrared (NIR) spectroscopy. This research is the initial stage in developing a spectral smart sensor system that predicts the rhodinol content of citronella oil in the distillation and fractionating process. Citronella oil samples were scanned by NIRFlex liquid N-500 with a wavelength of 1 000-2 500 nm having an absorbance value (log 1/T). The accuracy of the prediction was achieved using the partial least square (PLS) model. Based on the NIR spectrum at a peak of around 1 620 nm, the rhodinol content in the citronella oil was estimated. The finest model to predict the rhodinol content was y = 0.9874x + 15.6439 with a standard error of the calibration set (SEC) = 2.78%, a standard error of the prediction set (SEP) = 2.88%, a ratio of the performance to the deviation (RPD) = 9.23, a coefficient of variation (CV) = 16.81%, and the correlation coefficient (r) = 0.99. The NIR and PLS models are possible to use for the initial stage in developing a spectral smart sensor system to determine the rhodinol content of citronella oils.

Keywords: calibration; fractional distillation; partial least square; process control; spectra

Published: April 15, 2022  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Wahyudi D, Noor E, Setyaningsih D, Djatna T, Irmansyah I. Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report. Res. Agr. Eng. 2022;68(4):216-222. doi: 10.17221/87/2021-RAE.
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Agustian E., Sulaswatty A., Tasrif, Laksmono J.A., Adilina I.B. (2007): Isolation of citronellal from citronella oil using bench scale fractionation unit. Journal of Agroindustrial Technology, 17: 49-53.
    2. Almeida R.N., Soares R.P., Cassel E. (2018): Fractionation process of essential oils by batch distillation. Brazilian Journal of Chemical Engineering, 35: 1129-1140. Go to original source...
    3. Avizienis A. (2019): Essential Oils. San Diego, Thunder Bay Press.
    4. Bec K.B., Grabska J., Huck C.W. (2020): Near-infrared spectroscopy in bio-applications. Molecules, 25: 2948. Go to original source... Go to PubMed...
    5. Beneti S.C., Rosset E., Corazza M.L., Frizzo C.D., Luccio M.D., Oliveira J.V. (2011): Fractionation of citronella (Cymbopogon winterianus) essential oil and concentrated orange oil phase by batch vacuum distillation. Journal of Food Engineering, 102: 348-354. Go to original source...
    6. Bota W., Martosupono M., Rondonuwu F.S. (2015): Characterization of citronella oil products using near infrared spectroscopy (NIRs). Journal Faculty of Engineering Muhammadiyah University of Jakarta, 2: 1-7.
    7. Cen H., He Y. (2007): Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science and Technology, 18: 72-83. Go to original source...
    8. Chandra S., Krishanthi M., Octavian P.J., Postolache A. (2019): Smart Sensors, Measurement and Instrumentation: Modern Sensing Technologies. Sidney, Springer.
    9. Eden W.T., Alighiri D., Cahyono E., Supardi K.I., Wijayati N. (2018): Fractionation of Java citronella oil and citronellal purification by batch vacuum fractional distillation. IOP Conference Series: Materials Science and Engineering, 349: 012067. Go to original source...
    10. Hutchins D.A. (1997): Data Acquisition for Sensor Systems. London, Springer Science + Business Media. Go to original source...
    11. Iqbal Z., Herodian S., Widodo S. (2019): Development of partial least square (PLS) prediction model to measure the ripeness of oil palm fresh fruit bunch (FFB) by using NIR Spectroscopy. IOP Conference Series: Earth and Environmental Science, 347: 012079. Go to original source...
    12. Jumaah A.M.S., Xue J. (2019): Developing intelligent machines with smart sensors for a smart factory. International Journal of Scientific and Research Publications, 9: 221-230. Go to original source...
    13. Kurniawan F., Budiastra I.W., Sutrisno, Widyotomo S. (2019): Classification of arabica Java coffee beans based on their origin using nir spectroscopy. IOP Conference Series: Earth and Environmental Science, 309: 012006. Go to original source...
    14. Novianty I., Seminar K.B., Irzaman, Budiastra I.W. (2020): Improving the accuracy of near-infrared (NIR) spectroscopy method to predict the oil content of oil palm fresh fruits. IOP Conference Series: Earth and Environmental Science, 460: 012004. Go to original source...
    15. Pfeffer S., Schulz H., Kruger H. (2001): Potential of near infrared spectroscopy (NIRS) for rapid quality evaluation of essential oils. ISEO Journal, 32: 93-94.
    16. Popescu D., Gharbi A., Stefanoiu D., Borne P. (2017): Process Control Design for Industrial Applications. Hoboken, John Wiley & Sons, Inc. Go to original source...
    17. Purwanto Y.A., Zainal P.W., Ahmad U., Sutrisno M., Makino Y., Oshita S., Kawagoe Y., Kuroki S. (2013): Non destructive prediction of pH in mango fruit cv. Gedong Gincu using NIR spectroscopy. International Journal of Engineering and Technology, 13: 70-73.
    18. Rondonuwu F.S., Setiawan A. (2020): Determination of glucose content with a concentration within the physiological range by FT-NIR spectroscopy in a trans-reflectance mode. AIP Conference Proceedings, 2237: 020013. Go to original source...
    19. Setyaningsih D., Roselly F., Muna N. (2020): Formulation of essential oils as mosquito repellent. Journal of Tropical Pharmacy and Chemistry, 5: 71-79. Go to original source...
    20. Singh C.B., Jayas D.S. (2012): 5 - Optical sensors and online spectroscopy for automated quality and safety inspection of food products. Robotics and Automation in the Food Industry: Current and Future Technologies, 2013: 111-129. Go to original source...
    21. Sulaswatty A., Rusli M.S., Abimanyu H., Tursiloadi S. (2019): Quo Vadis Citronella Oil and Its Derivative Products. Jakarta, LIPI Press.
    22. Tisserand R., Young R. (2014): Essential Oil Composition. In: Williamson E.M. (ed.): Essential Oil Safety. London, Elsevier: 5-22. Go to original source...
    23. Tsimogiannis D., Oreopoulou V. (2018): A kinetic study of essential oil components distillation for the recovery of carvacrol rich fractions. Journal of Applied Research on Medicinal and Aromatic Plants, 9: 117-123. Go to original source...
    24. Verma R.S., Verma S.K., Tandon S., Padalia R.C., Darokar M.P. (2020): Chemical composition and antimicrobial activity of Java citronella (Cymbopogon winterianus Jowitt ex Bor) essential oil extracted by different methods. Journal of Essential Oil Research, 32: 449-455. Go to original source...
    25. Wany A., Kumar A., Nallapeta S., Jha S., Nigam V.K., Pandey D.M. (2014): Extraction and characterization of essential oil components based on geraniol and citronellol from Java citronella (Cymbopogon winterianus Jowitt). Plant Growth Regulation, 73: 133-145. Go to original source...
    26. Windawati V., Purwanto Y.A., Budiastra I.W., Widodo S., Kuroki S. (2019): Prediction of chemical content in patchouli oil (Pogostemon cablin Benth) by portable NIR spectroscopy. IOP Conference Series: Materials Science and Engineering, 557: 012087. Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY NC 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content