Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report
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 senso...
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| Format: | Article |
| Language: | English |
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Czech Academy of Agricultural Sciences
2022-04-01
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| Series: | Research in Agricultural Engineering |
| Subjects: | |
| Online Access: | https://rae.agriculturejournals.cz/artkey/rae-202204-0007_prediction-of-the-rhodinol-content-in-java-citronella-oil-using-nir-spectroscopy-in-the-initial-stage-developin.php |
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| author | Dedi Wahyudi Erliza Noor Dwi Setyaningsih Taufik Djatna Irmansyah Irmansyah |
| author_facet | Dedi Wahyudi Erliza Noor Dwi Setyaningsih Taufik Djatna Irmansyah Irmansyah |
| author_sort | Dedi Wahyudi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T08:04:48Z |
| format | Article |
| id | doaj.art-0bc29266c98b4fe998c19c1cca49fcbb |
| institution | Directory Open Access Journal |
| issn | 1212-9151 1805-9376 |
| language | English |
| last_indexed | 2024-04-10T08:04:48Z |
| publishDate | 2022-04-01 |
| publisher | Czech Academy of Agricultural Sciences |
| record_format | Article |
| series | Research in Agricultural Engineering |
| spelling | doaj.art-0bc29266c98b4fe998c19c1cca49fcbb2023-02-23T03:48:02ZengCzech Academy of Agricultural SciencesResearch in Agricultural Engineering1212-91511805-93762022-04-0168421622210.17221/87/2021-RAErae-202204-0007Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case reportDedi Wahyudi0Erliza Noor1Dwi Setyaningsih2Taufik Djatna3Irmansyah Irmansyah4Department of Agro-industrial Technology, IPB University, Bogor, IndonesiaDepartment of Agro-industrial Technology, IPB University, Bogor, IndonesiaDepartment of Agro-industrial Technology, IPB University, Bogor, IndonesiaDepartment of Physics, IPB University, Bogor, IndonesiaDepartment of Physics, IPB University, Bogor, IndonesiaThe 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.https://rae.agriculturejournals.cz/artkey/rae-202204-0007_prediction-of-the-rhodinol-content-in-java-citronella-oil-using-nir-spectroscopy-in-the-initial-stage-developin.phpcalibrationfractional distillationpartial least squareprocess controlspectra |
| spellingShingle | Dedi Wahyudi Erliza Noor Dwi Setyaningsih Taufik Djatna Irmansyah Irmansyah Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report Research in Agricultural Engineering calibration fractional distillation partial least square process control spectra |
| title | Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report |
| title_full | Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report |
| title_fullStr | Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report |
| title_full_unstemmed | Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report |
| title_short | Prediction of the rhodinol content in Java citronella oil using NIR spectroscopy in the initial stage developing a spectral smart sensor system - Case report |
| title_sort | prediction of the rhodinol content in java citronella oil using nir spectroscopy in the initial stage developing a spectral smart sensor system case report |
| topic | calibration fractional distillation partial least square process control spectra |
| url | https://rae.agriculturejournals.cz/artkey/rae-202204-0007_prediction-of-the-rhodinol-content-in-java-citronella-oil-using-nir-spectroscopy-in-the-initial-stage-developin.php |
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