Feasibility of using a cylindrical resonator sensor for adulteration detection in sesame oil

Document Type : Research Article

Authors

1 Associate Professors, Department of Mechanical Engineering of Biosystems, Shahrekord University

2 B.Sc. Student, Department of Mechanical Engineering of Biosystems, Shahrekord University

3 Ph.D., Young Researchers Club, Islamic Azad University of Shahrekord

Abstract

One of the important concerns regarding the food safety is widespread adulteration in food production which necessitates the development of precise and rapid diagnostic instruments more than ever. In this study, a cylindrical resonator sensor, developed in previous studies and examined for quality detection of some food materials, was applied for detection of adulteration in sesame oil mixed with corn, canola and sunflower oils. To measure the dielectric response of oil in 0-150 MHz frequency range, a new sensor with 400 mm long cylinder was fabricated. Adulteration samples were prepared with mixing pure sesame oil with the above mentioned oils at 15, 30 and 45% by weight and each sample was measured with three replications using the dielectric sensor. Statistical methods of principal component analysis (PCA), linear discriminant analysis (LDA) and support vector machine (SVM) were evaluated for detection of adulteration type and level from the dielectric spectral data. The biplot of the first two principal components showed excellent discrimination of adulteration type and level with 96% of variation explanation. As the best result, LDA classifier showed 96.7% accuracy for adulteration detection.

Graphical Abstract

Feasibility of using a cylindrical resonator sensor for adulteration detection in sesame oil

Highlights

  • Adulteration detection in sesame oil was studies with dielectric properties.

 

  • A cylindrical dielectric sensor (resonator) was evaluated.

 

  • Adulteration in sesame oil was made with sunflower, corn and canola oils.

 

  • As the best result, classification with LDA showed 96.7% accuracy in differentiation of adulteration in sesame oil.

Keywords

Main Subjects

References

 [1] فهیم دانش، م،؛ بهرامی، م. ع. (1395) بررسی تقلب در روغن کنجد با روش آنالیز گرماسنجی افتراقی. فصلنامه علوم و صنایع غذایی، جلد 13، شماره 55، ص 81-89.
 [2] Dong-Sun, L., Bong-Soo, N., Sun-Yong, B., Kun, K. (1998). Characterization of fatty acids composition in vegetable oils by gas chromatography and chemometrics. Analytica Chimica Acta., 358, 163–175.
[3] Dong-Sun, L., Eun-Sung, L., Hyun-Jung, K., Shin-Ok, K., Kun, K. (2001). Reversed phase liquid chromatographic determination of triacylglycerol composition in sesame oils and the chemometric detection of adulteration. Analytica Chimica Acta., 429, 321–330.
[4] Seo, H.Y., Ha, J., Shin, D.B., Shim, S.L., No, K.M., Kim, K.S., Lee, K.B., Han, S.B. (2010). Detection of corn oil in adulterated sesame oil by chromatography and carbon isotope analysis. J. Am. Oil Chemis. Soc., 87, 621–626.
[5] Aued-Pimentel, S., Takemoto, E., Antoniassi, R., Badolato, E.S.G. (2006). Composition of tocophercols in sesame oil: An indicative of adulteration. Grasas Y Aceites., 57, 205–210.
[6] Ok, S. (2017). Detection of olive oil adulteration by low-field NMR relaxometry and UV-Vis spectroscopy upon mixing olive oil with various edible oils. Grasas Y Aceites., 68 (1), doi: http://dx.doi.org/10.3989/gya.0678161
[7] Torrecilla, J.S., Rojo, E., Domínguez, J.C., Rodríguez, F. (2010). A novel method to quantify the adulteration of extra virgin olive oil with low-grade olive oils by UV−VIS. J. Agric. Food Chemis., 58 (3), 1679–1684.
[8] Tay, A., Singh, R.K., Krishnan, S.S. Gore, J.P. (2002). Authentication of olive oil adulterated with vegetable oils using Fourier transform infrared spectroscopy. LWT - Food Sci. Tech., 35(1), 99-103.
[9] Rizki, H., Terouzi, W., Kzaiber, F., Hanine, H. Oussama, A. (2016). Quantification of adulterations in sesame oil with inferior edible oils by using ATR-FTIR coupled to chemometrics. IOSR J. Environ. Sci. Toxicol. Food Technol., 10(8), 138-145.
[10] Zhao, X., Dong, D., Zheng, W., Jiao, L. Lang Y. (2014). Discrimination of adulterated sesame oil using mid-infrared spectroscopy and chemometrics. Food Anal. Meth.., DOI 10.1007/s12161-015-0125-7
[11] Baeten, V. Aparicio, R. (2000). Edible oils and fats authentication by Fourier transform Raman spectroscopy. Biotech. Agron. Soc. Environ., 4, 196–203.
[12] Sega, A., Zanardi, I., Chiasserini, L., Gabbrielli, A., Bocci, V. Travagli, V. (2010). Properties of sesame oil by detailed H and C NMR assignments before and after ozonation and their correlation with iodine value, peroxide value, and viscosity measurement. Chemis. Phys. Lipids., 163, 148–156.
[13] Martin, Y.G., Pavon, J.L., Perez, C., Bernardo, M., Pinto, C.G. (1999). Classification of vegetable oils by linear discriminant analysis of electronic nose data. Analytica Chimica Acta, 384, 83-94.
[14] Haddi, Z., Alami, H., Bari, N.El., Tounsiet, M., Barhoumi, H., Maaref, A., Jaffrezic-Renault, N. Bouchikhi, B. (2013). Electronic nose and electronic tongue combination for improved classification of Moroccan virgin olive oil profile. Food Res. Int., 54(2), 1488-1498.
[15] Skierucha, W., Wilczek, A. Szypowska, A. (2012). Dielectric spectroscopy in agrophysics. Int. Agrophys., 26, 187-197.
[16] Lizhi, H., Toyoda, K. Ihara, I. (2008). Dielectric properties of edible oils and fatty acids as a function of frequency, temperature, moisture and composition. J. Food Eng., 88, 151-158.
[17] Cataldo, A., Piuzzi, E., Cannazza, G., De Benedetto, E. Tarricone, L. (2010). Quality and anti-adulteration control of vegetable oils through microwave dielectric spectroscopy. Measurement, 43, 1031–1039.
[18] Corach, J., Sorichetti, P.A. Romano, S.D. (2014). Electrical properties of vegetable oils between 20 Hz and 2 MHz. Int. J. Hydrogen Energy., 39, 8754-8758.
[19] Rashvand, M., Omid, M., Mobli, H. Soltani Firouz, M. (2016). Adulteration detection in olive oil using dielectric technique and data mining. Sens Biosensing Res., 11, 33–36.
[20] Ghasemi-Varnamkhasti, M., Mohtasebi, S.S., Siadat, M., Ahmadi, H. Razavi, S.H. (2015). From simple classification methods to machine learning for the binary discrimination of beers using electronic nose data. Eng.Agric. Environ. Food., 8, 44-51.
[21] Naderi-Boldaji, M., Mishra, P., Ahmadpour-Samani, M., Ghasemi-Varnamkhasti, M., Ghanbarian, D. Izadi, Z. (2018). Potential of two dielectric spectroscopy techniques and chemometric analyses for detection of adulteration in grape syrup. Measurement, 127, 518–524.
[22] Rao, R.C. (1948). The utilization of multiple measurements in problems of biological classification, J. Roy. Statis. Soc. Series B., 10 (2), 159–203.
 [23] صفری امیری، ز، ؛ قاسمی ورنامخواستی، م، ؛ توحیدی، م، ؛ محتسبی، س.س، ؛ دولتی، م. (1396) استفاده از سامانه ماشین بویایی به­منظور تشخیص تقلب در زیره کوهی. فصلنامه فناوری­های نوین غذایی. پذیرش شده. doi: 10.22104/JIFT.2017.2487.1579
[24] Amari, A. El., Bari, N., Bouchikhi, B. (2007). Electronic nose for anchovy freshness monitoring based on sensor array and pattern recognition methods: principal components analysis, linear discriminant analysis and support vector machine. Int. J. Found. Comput. Sci., 6, 61–67.
 [25] توحیدی، م، ؛ قاسمی ورنامخواستی، م، ؛ غفاری نیا، و، ؛ محتسبی، س.س، ؛ بنیادیان، م. (1395) ساخت و توسعه یک سامانه ماشین بویایی در ترکیب با روش‌های شناسایی الگو برای تشخیص تقلب فرمالین در شیر خام. مهندسی بیوسیستم ایران. جلد 47، شماره 4، ص 1-10.
[26] Sanaeifar, A., Mohtasebi, S., Ghasemi-Varnamkhasti, M., Ahmadi, H., Lozano Rogado, J.S. (2014). Development and application of a new low cost electronic nose for the ripeness monitoring of banana using computational techniques (PCA, LDA, SIMCA, and SVM). Czech J. Food Sci., 32 (6), 538-548
 [27] خلیلیان، ح، ؛ قاسمی ورنامخواستی، م، ؛ نادری-بلداجی، م، ؛ رستمی، س. (1396) توسعه و آزمون حسگر دی الکتریک استوانه ای برای اندازه گیری غلظت قند شربت چغندر قند. مهندسی بیوسیستم ایران، جلد 48، شماره 1، ص 137-144.
[28] Ghasemi-Varnamkhasti, M., Ghatreh-Samani, N., Naderi-Boldaji, M., Forina, M. Bonyadian, M. (2017). Development of two dielectric sensors coupled with computational techniques for detecting milk adulteration. Comput. Electron. Agric., 140, 266–278.
 [29] خلیلیان، ح، ؛ نادری بلداجی، م، ؛ قاسمی ورنامخواستی، ؛ رستمی، س. (1396) آزمون در حال جریان یک حسگر دی الکتریک استوانه ای برای اندازه گیری غلظت قند شربت چغندر قند. فصلنامه فناوری های نوین غذایی. جلد 4، ص 131-140.
 [30] Hoog, N. A., Olthuis, W., Mayer, M. J. J., Yntema, D., Miedema, H. van-den-Berg, A. (2012). On-line fingerprinting of fluids using coaxial stub resonator technology. Sens. Actuators B: Chem., 163, 90-96.
Innovative Food Technologies
Volume 6, Issue 3
May 2019
Pages 409-420

Files

History

  • Receive Date: 16 October 2018
  • Revise Date: 26 January 2019
  • Accept Date: 17 February 2019

Share

How to cite

Statistics