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The Employment of ATR-FTIR Spectroscopy for Quantification of Turpentine in Cajuput Oil

1Department of Chemical Engineering, Universitas Syiah Kuala, Banda Aceh, Indonesia

2ARC PUI-PT Nilam Aceh, Universitas Syiah Kuala, Banda Aceh, Indonesia

Received: 15 Jun 2025; Revised: 16 Nov 2025; Accepted: 25 Nov 2025; Published: 8 Dec 2025.
Open Access Copyright 2025 Jurnal Kimia Sains dan Aplikasi under http://creativecommons.org/licenses/by-sa/4.0.

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Abstract

Cajuput oil is widely used for its therapeutic properties; however, its high economic value makes it vulnerable to adulteration with cheaper solvents, such as turpentine. This study employed ATR-FTIR spectroscopy combined with chemometric methods to qualitatively classify and quantitatively predict turpentine adulteration in cajuput oil. Cajuput oil samples were adulterated with turpentine at concentrations ranging from 0% to 10% (v/v) in 0.5% increments and analyzed in the mid-infrared region (4000–400 cm−1). Spectral pretreatments, including multiplicative scatter correction (MSC), smoothing, baseline correction, second derivative, and standard normal variate (SNV), were applied prior to chemometrics analysis. FTIR spectra revealed the appearance of C=C stretching bands at 1647 and 1508 cm−1 only in the adulterated samples. In contrast, Principal Component Analysis (PCA) with SNV and MSC pretreatments provided clear clustering of samples according to turpentine concentration, with cumulative variances reaching up to 90%. Partial Least Squares (PLS) using MSC, smoothing, baseline correction, and SNV pretreatments yielded excellent calibration and cross-validation performance, with R2 values of 0.98–0.99, and low SEC/SECV and RMSEC/RMSECV values. These results demonstrate that ATR-FTIR spectroscopy combined with appropriate chemometric pretreatments offers a rapid, solvent-free, and reliable approach for authentication and quality control of cajuput oil adulterated with turpentine.

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Keywords: Cajuput Oil; Turpentine; FTIR; Chemometrics; PLS; PCA

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  1. Aswandi Aswandi, Cut Rizlani Kholibrina, Harlinda Kuspradini, Essential Oils for Cosmetics Application, in: E.T. Arung, W. Fatriasari, I.W. Kusuma, H. Kuspradini, K. Shimizu, Y.-u. Kim, N.I.W. Azelee, Z. Edis (Eds.) Biomass-based Cosmetics: Research Trends and Future Outlook, Springer Nature Singapore, Singapore, 2024, https://doi.org/10.1007/978-981-97-1908-2_7
  2. Henri Boby, L’aromathérapie, une technique complémentaire en médecine périopératoire: Aromatherapy, a complementary technique in perioperative medicine, Oxymag, 35, 183, (2022), 10-14 https://doi.org/10.1016/j.oxy.2022.02.005
  3. Sara Baptista-Silva, Sandra Borges, Oscar L. Ramos, Manuela Pintado, Bruno Sarmento, The progress of essential oils as potential therapeutic agents: a review, Journal of Essential Oil Research, 32, 4, (2020), 279-295 https://doi.org/10.1080/10412905.2020.1746698
  4. Charles Oluwaseun Adetunji, Javad Sharifi-Rad, Application of essential oils in the food industry, in: Applications of Essential Oils in the Food Industry, Elsevier, 2024, https://doi.org/10.1016/B978-0-323-98340-2.00001-8
  5. Phuong Ha Tran, Thi Thanh Tam Vu, Thi Diem Tran Phan, Van Mien Nguyen, Thi Nghia Minh Ngo, Canh Viet Cuong Le, That Huu Dat Ton, Chemical compositions and biological properties of the leaf essential oil of three Melaleuca species, World Academy of Sciences Journal, 6, 6, (2024), 67 https://doi.org/10.3892/wasj.2024.282
  6. A. Rimbawanto, N. K. Kartikawati, F. Latumahina, Conservation and utilization of Melaleuca cajuputi sub sp cajuputi, an indigenous species in Moluccas Island, Indonesia, IOP Conference Series: Earth and Environmental Science, 800, 1, (2021), 012040 https://doi.org/10.1088/1755-1315/800/1/012040
  7. Zdeňka Navrátilová, Cineol (eukalyptol) v léčbě respiračních onemocnění (Cineole (eucalyptol) in the treatment of respiratory diseases), Česká a Slovenská Farmacie, 73, 3, (2024), 181-186 https://doi.org/10.36290/csf.2024.028
  8. Saghar Ketebchi, Maryam Papari Moghadamfard, A review on the effective natural compounds of medicinal plants on the COVID-19, Natural Product Research, 39, 4, (2025), 834-847 https://doi.org/10.1080/14786419.2024.2309322
  9. Jan Schripsema, Sônia Maria da Silva, Denise Dagnino, Differential NMR and chromatography for the detection and analysis of adulteration of vetiver essential oils, Talanta, 237, (2022), 122928 https://doi.org/10.1016/j.talanta.2021.122928
  10. Tzi Bun Ng, Evandro Fei Fang, Alaa El-Din Ahmed Bekhit, Jack Ho Wong, Chapter 2 - Methods for the Characterization, Authentication, and Adulteration of Essential Oils, in: V.R. Preedy (Ed.) Essential Oils in Food Preservation, Flavor and Safety, Academic Press, San Diego, 2016, https://doi.org/10.1016/B978-0-12-416641-7.00002-X
  11. S. Idrus, M. S. Radiena, Sumarsana, H. Smith, Quality and Chemical Composition of Cajuput Oil from Moluccas and Papua, Journal of Physics: Conference Series, 1463, (2020), 012016 http://doi.org/10.1088/1742-6596/1463/1/012016
  12. Adissu Alemayehu Asfaw, Juan Aspromonte, Kris Wolfs, Ann Van Schepdael, Erwin Adams, Overview of sample introduction techniques prior to GC for the analysis of volatiles in solid materials, Journal of Separation Science, 42, 1, (2019), 214-225 https://doi.org/10.1002/jssc.201800711
  13. K. Bounaas, N. Bouzidi, Y. Daghbouche, S. Garrigues, M. de la Guardia, M. El Hattab, Essential oil counterfeit identification through middle infrared spectroscopy, Microchemical Journal, 139, (2018), 347-356 https://doi.org/10.1016/j.microc.2018.03.008
  14. Daniel Cozzolino, Infrared Spectroscopy, in: Electromagnetic Technologies in Food Science, 2021, https://doi.org/10.1002/9781119759522.ch12
  15. Aymen Adil Lazim, Ali Farhan Nader, Huda Fannoosh Khazaal Alsaad, Mahdi Khamees Ghadeer, Application of Principal Component Analysis for Enhanced Well Log Interpretation: A Case Study from the Zubair Oil Field, South of Iraq, The Iraqi Geological Journal, 58, 1C, (2025), 83-94 https://doi.org/10.46717/igj.58.1C.8ms-2025-3-23
  16. Laı́s Feltrin Sidou, Endler Marcel Borges, Teaching Principal Component Analysis Using a Free and Open Source Software Program and Exercises Applying PCA to Real-World Examples, Journal of Chemical Education, 97, 6, (2020), 1666-1676 https://doi.org/10.1021/acs.jchemed.9b00924
  17. Jean-Michel Roger, Jean-Claude Boulet, Magida Zeaiter, Douglas N. Rutledge, 3.01 - Pre-processing Methods☆, in: S. Brown, R. Tauler, B. Walczak (Eds.) Comprehensive Chemometrics (Second Edition), Elsevier, Oxford, 2020, https://doi.org/10.1016/B978-0-12-409547-2.14878-4
  18. Siong Fong Sim, Min Xuan Laura Chai, Amelia Laccy Jeffrey Kimura, Prediction of Lard in Palm Olein Oil Using Simple Linear Regression (SLR), Multiple Linear Regression (MLR), and Partial Least Squares Regression (PLSR) Based on Fourier-Transform Infrared (FTIR), Journal of Chemistry, 2018, 1, (2018), 7182801 https://doi.org/10.1155/2018/7182801
  19. Any Guntarti, Laela Hayu Nurani, Putri Lestari, Citra Ariani Edityaningrum, Lalu Muhammad Irham, Abdul Rohman, Authentication of Clove Leaf Oil in Products (Syzygium aromaticum (L.) Merr. & LM Perry) Using GC-MS and FTIR Methods Combined with Chemometric, Malaysian Journal of Analytical Sciences, 28, 3, (2024), 664-680
  20. Q. Ding, M. Yao, Sh Wu, M. Zeng, N. Xue, D. Wu, J. Xu, Quantitative Analysis of Al in Flour Products by Laser-Induced Breakdown Spectroscopy Combined with Partial Least Squares, Journal of Applied Spectroscopy, 89, 4, (2022), 712-718 https://doi.org/10.1007/s10812-022-01415-4
  21. Sonny Widiarto, Raisha Fauziyah, Triana Puji Astari, Ni Luh Gede Ratna Juliasih, Sutopo Hadi, La Zakaria, Irwan Saputra, Authentication of Processed Beef Sausage Products Using Chemometric Analysis Based on FTIR Spectrophotometry Data, Jurnal Kimia Sains dan Aplikasi, 28, 1, (2025), 39-46 https://doi.org/10.14710/jksa.28.1.39-46
  22. Puneet Mishra, Jean Michel Roger, Federico Marini, Alessandra Biancolillo, Douglas N. Rutledge, Parallel pre-processing through orthogonalization (PORTO) and its application to near-infrared spectroscopy, Chemometrics and Intelligent Laboratory Systems, 212, (2021), 104190 https://doi.org/10.1016/j.chemolab.2020.104190
  23. Ng Hui Ying, Gan Shi Min, Saliza Asman, Extraction of essential oil Citrus Hystrix by using ultrasound-assisted extraction, Malaysian Journal of Analytical Sciences, 27, 6, (2023), 1236-1248
  24. Meryeme El Maouardi, Kris De Braekeleer, Abdelaziz Bouklouze, Yvan Vander Heyden, Comparison of Near-Infrared and Mid-Infrared spectroscopy for the identification and quantification of argan oil adulteration through PCA, PLS-DA and PLS, Food Control, 165, (2024), 110671 https://doi.org/10.1016/j.foodcont.2024.110671
  25. Shuxia Guo, Jürgen Popp, Thomas Bocklitz, Chemometric analysis in Raman spectroscopy from experimental design to machine learning–based modeling, Nature Protocols, 16, 12, (2021), 5426-5459 https://doi.org/10.1038/s41596-021-00620-3
  26. Guihong Wan, Baokun He, Haim Schweitzer, The art of centering without centering for robust principal component analysis, Data Mining and Knowledge Discovery, 38, 2, (2024), 699-724 https://doi.org/10.1007/s10618-023-00976-y
  27. Faizan E. Mustafa, Ahmed Ijaz, Maaruf Muhammad, Khalid Muhammad, Detection of Cracks in the Industrial System Using Adaptive Principal Component Analysis and Wavelet Denoising, 2024 IEEE International Conference on Industrial Technology (ICIT), Bristol, United Kingdom, 2024 https://doi.org/10.1109/ICIT58233.2024.10540880
  28. Ross Sparks, Monitoring Highly Correlated Multivariate Processes Using Hotelling's T2 Statistic: Problems and Possible Solutions, Quality and Reliability Engineering International, 31, 6, (2015), 1089-1097 https://doi.org/10.1002/qre.1656
  29. Wong Hui Shein, Anwar Fitrianto, A Comparative Study of Outliers Identification Methods in Univariate Data Set, Advanced Science Letters, 23, 2, (2017), 1422-1427 https://doi.org/10.1166/asl.2017.8366
  30. Pengjie Zhang, Bing Liu, Xihui Mu, Jiwei Xu, Bin Du, Jiang Wang, Zhiwei Liu, Zhaoyang Tong, Performance of Classification Models of Toxins Based on Raman Spectroscopy Using Machine Learning Algorithms, Molecules, 29, 1, (2024), 197 https://doi.org/10.3390/molecules29010197
  31. Dongze Li, Guifang Wu, Hai Ma, Zhao Liu, Guiquan Liu, Junhua Hou, Identification of Blueberry Beverage Using Vis/NIR Spectroscopy, 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017), 2017 https://doi.org/10.1051/matecconf/201713900050
  32. Zhushanying Zhang, Hanwen Gu, Kaiwen Xie, He Jiang, Qinlan Xie, Jiming Sa, Pretreatment and combined method based on near infrared spectroscopy, Laser & Optoelectronics Progress, 58, 16, (2021), 1617001 http://dx.doi.org/10.3788/LOP202158.1617001
  33. Shazlyn Milleana Shaharudin, Norhaiza Ahmad, Choice of Cumulative Percentage in Principal Component Analysis for Regionalization of Peninsular Malaysia Based on the Rainfall Amount, Singapore, 2017 https://doi.org/10.1007/978-981-10-6502-6_19
  34. Snezana Agatonovic-Kustrin, Petar Ristivojevic, Vladimir Gegechkori, Tatiana M. Litvinova, David W. Morton, Essential Oil Quality and Purity Evaluation via FT-IR Spectroscopy and Pattern Recognition Techniques, Applied Sciences, 10, 20, (2020), 7294 https://doi.org/10.3390/app10207294
  35. A. Anne Frank Joe, A. Gopal, A study on various preprocessing algorithms used for NIR spectra, Research Journal of Pharmaceutical, Biological and Chemical Sciences, 7, 4, (2016), 2752-2757
  36. Le Chang, Jiali Wang, William Woodgate, Analysing spectroscopy data using two-step group penalized partial least squares regression, Environmental and Ecological Statistics, 28, 2, (2021), 445-467 https://doi.org/10.1007/s10651-021-00496-2
  37. Archasvi Tyagi, Anil K. Yadav, Akanksha Yadav, Lalita Saini, Vivek Kumar, Pooja Jain, Inam Mohammad, Mohammad Javed Ansari, Hesham Ali El Enshasy, Fagr Kh Abdel-Gawad, Sami Al Obaid, Shahida Anusha Siddiqui, Vijai Malik, Vibrational Spectroscopic Methods for the Identification and Distinction of Essential Oils in Genus Ocimum L.: A Chemometric Approach, Journal of King Saud University – Science, 34, (2022), 102355 https://doi.org/10.1016/j.jksus.2022.102355

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