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Chemometric Evaluation of Discrimination of Aromatic Plants by Using NIRS, LIBS

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Abstract

Aromatic plants have different chemical compositions that give them specific properties such as colour, aroma and taste and can be classified based on differentiation of various chemical constituents such as protein, vitamins, minerals, volatile and non-volatile oil, carbohydrates and the presence of adulterants. The aim of the present study was to develop a fast, simple and non-destructive method for discrimination of aromatic plants, juniper (Juniperus communis), rosemary (Rosmarinus officinalis), laurel (Laurus nobilis), sweet basil (Ocimum basilicum), black pepper (Piper nigrum), thyme (Origanum majorana), lavender (Lavandula latifolia), spearmint (Mentha spicata) and ginger (Zingiber officinale), commonly used. In order to discriminate aromatic plants, chemometric methods, namely principal component analysis (PCA), were used together with spectroscopic methods. Analysis of plant samples was carried out using Raman spectroscopy (RS), near-infrared spectroscopy (NIRS) and laser-induced breakdown spectroscopy (LIBS). Although Raman spectra of aromatic plant samples could not be obtained due to problems with sample degradation and fluorescence effect, satisfying classification of aromatic plant samples was accomplished by LIBS and NIRS. PCA models developed using NIRS data showed that the first two principal components explained 82.56% of the total variance. Elemental composition of the aromatic plant samples was investigated using LIBS, and the first two principal components explained 77.97% of the total variance in the PCA model generated by using the LIBS data. The ability to rapidly discriminate various culinary herbs makes these spectroscopic methods available to use by the aromatic plant industry in order to perform a fast quality control of incoming raw materials.

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References

  • ACCC (2016) Australian Competition and Consumer Commission’s activities. Australian Competition and Consumer Commission, Australia

    Google Scholar 

  • AdamsM (1995) Chemometrics in analytical spectroscopy. In: RSC spectroscopy monographs, vol 126. The Royal Society of Chemistry, Letchworth, p 216

  • Alvira FC, Bilmes GM, Flores T, Ponce L (2015) Laser-induced breakdown spectroscopy (LIBS) quality control and origin identification of handmade manufactured cigars. Appl Spectrosc 69(10):1205–1209. https://doi.org/10.1366/15-07935

    Article  CAS  Google Scholar 

  • Anastasaki EG, Kanakis CD, Pappas C, Maggi L, Zalacain A, Carmona M, Alonso GL, Polissiou MG (2010) Quantification of Crocetin esters in saffron (Crocus sativus L.) using Raman spectroscopy and chemometrics. J Agric Food Chem 58(10):6011–6017. https://doi.org/10.1021/jf100143n

    Article  CAS  Google Scholar 

  • AOAC (2005) Adulterants in spices (Method 916.01). Association of official analytical chemists international, Gaithersburg, Maryland, USA

  • ASTA (2004) Spice adulteration. American spice trade association, New York

    Google Scholar 

  • Batten GD (1998) Plant analysis using near infrared reflectance spectroscopy: the potential and the limitations. Aust J Exp Agric 38(7):697–706. https://doi.org/10.1071/EA97146

    Article  Google Scholar 

  • BegemannC, JanderP, WotrubaH, GaastraM (2012) Laser-based online analysis of minerals. Paper presented at the Symposium Sensor Based Sorting, Aachen, Germany

  • Bilge G, Velioglu HM, Sezer B, Eseller KE, Boyaci IH (2016) Identification of meat species by using laser-induced breakdown spectroscopy. Meat Sci 119:118–122. https://doi.org/10.1016/j.meatsci.2016.04.035

    Article  CAS  Google Scholar 

  • Black C, Haughey SA, Chevallier OP, Galvin-King P, Elliott CT (2016) A comprehensive strategy to detect the fraudulent adulteration of herbs: the oregano approach. Food Chem 210:551–557. https://doi.org/10.1016/j.foodchem.2016.05.004

    Article  CAS  Google Scholar 

  • Blanco M, Villarroya I (2002) NIR spectroscopy: a rapid-response analytical tool. TrAC Trends Anal Chem 21(4):240–250. https://doi.org/10.1016/S0165-9936(02)00404-1

    Article  CAS  Google Scholar 

  • Cozzolino D, Dambergs R, Janik L, Cynkar W, Gishen M (2006) Review: analysis of grapes and wine by near infrared spectroscopy. J Near Infrared Spectrosc 14(5):279–289. https://doi.org/10.1255/jnirs.679

    Article  CAS  Google Scholar 

  • Daneshvar A, Tigabu M, Karimidoost A, Odén PC (2015) Single seed Near Infrared Spectroscopy discriminates viable and non-viable seeds of Juniperus polycarpos. Silva Fennica 49(5):14. https://doi.org/10.14214/sf.1334

    Article  Google Scholar 

  • Davies AMC, Grant A (1987) Review: near infra-red analysis of food. Int J Food Sci Technol 22:191–207

    Article  CAS  Google Scholar 

  • Deaville E, Flinn P (2002) Near infrared (NIR) spectroscopy: an alternative approach for the estimation of forage quality and voluntary intake. In: Givens D, Owen E, Axford R, Omedi H (eds) Forage evaluation in ruminant nutrition. CABI Publishing, Wallingford, pp 301–311

    Google Scholar 

  • Dhanya K, Sasikumar B (2010a) Molecular marker based adulteration detection in traded food and agricultural commodities of plant origin with special reference to spices. Curr Trends Biotechnol Pharm 4:454–489

    CAS  Google Scholar 

  • DhanyaK, SasikumarB (2010b) Molecular marker based adulteration detection in traded food and agricultural commodities of plant origin with special reference to spices. Curr Trends Biotechnol Pharm 4:454–489

  • Dhanya K, Syamkumar S, Siju S, Sasikumar B (2011a) SCAR markers for adulterant detection in ground chilli. Br Food J 113(5):656–668. https://doi.org/10.1108/00070701111131755

    Article  Google Scholar 

  • Dhanya K, Syamkumar S, Siju S, Sasikumar B (2011b) Sequence characterized amplified region markers: a reliable tool for adulterant detection in turmeric powder. Food Res Int 44(9):2889–2895. https://doi.org/10.1016/j.foodres.2011.06.040

    Article  CAS  Google Scholar 

  • Eigenvector (2010) Preprocessing methods. In: Solo software user’s guide. Eigenvector Research Inc., Wenatchee, WA

    Google Scholar 

  • Ercioglu E, Velioglu HM, Boyaci IH (2018) Determination of terpenoid contents of aromatic plants using NIRS. Talanta 178:716–721. https://doi.org/10.1016/j.talanta.2017.10.017

    Article  CAS  Google Scholar 

  • Gierlinger N, Schwanninger M (2007) The potential of Raman microscopy and Raman imaging in plant research. Spectroscopy 21(2):69–89. https://doi.org/10.1155/2007/498206

    Article  CAS  Google Scholar 

  • Gudi G, Kraehmer A, Krueger H, Hennig L, Schulz H (2014) Discrimination of fennel chemotypes applying IR and Raman spectroscopy: discovery of a new gamma-asarone chemotype. J Agric Food Chem 62(16):3537–3547. https://doi.org/10.1021/jf405752x

    Article  CAS  Google Scholar 

  • Guo Y, Ni Y, Kokot S (2016) Evaluation of chemical components and properties of the jujube fruit using near infrared spectroscopy and chemometrics. Spectrochim Acta A Mol Biomol Spectrosc 153:79–86. https://doi.org/10.1016/j.saa.2015.08.006

    Article  CAS  Google Scholar 

  • HondrogiannisE, EhrlingerE, MiziolekAW (2013) Spectroscopy methods for identifying the country of origin. 8726:8726–8727

  • Huang H, Yu H, Xu H, Ying Y (2008) Near infrared spectroscopy for on/in-line monitoring of quality in foods and beverages: a review. J Food Eng 87(3):303–313. https://doi.org/10.1016/j.jfoodeng.2007.12.022

    Article  CAS  Google Scholar 

  • Juvé V, Portelli R, Boueri M, Baudelet M, Yu J (2008) Space-resolved analysis of trace elements in fresh vegetables using ultraviolet nanosecond laser-induced breakdown spectroscopy. Spectrochim Acta B At Spectrosc 63(10):1047–1053. https://doi.org/10.1016/j.sab.2008.08.009

    Article  Google Scholar 

  • Kays SE, Windham WR, Barton FE (1996) Prediction of total dietary fiber in cereal products using near-infrared reflectance spectroscopy. J Agric Food Chem 44(8):2266–2271. https://doi.org/10.1021/jf960053t

    Article  CAS  Google Scholar 

  • Kim JH, Baik SH (2016) Molecular identification of economically motivated adulteration of red pepper powder by species-specific PCR of nuclear rDNA-ITS regions in garlic and onion. Food Anal Methods 9(12):3287–3297. https://doi.org/10.1007/s12161-016-0519-1

    Article  Google Scholar 

  • Kumar P, Gupta VK, Misra AK, Modi DR, Pandey BK (2009) Potential of molecular markers in plant biotechnology. Plant Omics 2:141–162

    CAS  Google Scholar 

  • Li H, He J, Li F, Zhang Z, Li R, Su J, Zhang J, Yang B (2016) Application of NIR and MIR spectroscopy for rapid determination of antioxidant activity of Radix Scutellariae from different geographical regions. Phytochem Anal 27(1):73–80. https://doi.org/10.1002/pca.2602

    Article  CAS  Google Scholar 

  • Lohumi S, Lee S, Lee H, Cho B-K (2015) A review of vibrational spectroscopic techniques for the detection of food authenticity and adulteration. Trends Food Sci Technol 46(1):85–98. https://doi.org/10.1016/j.tifs.2015.08.003

    Article  CAS  Google Scholar 

  • Lutz M, Mäntele W (1991) Vibrational spectroscopy of chlorophylls. In: Scheer H (ed) Chlorophylls. CRC Press, Boca Raton, FL

    Google Scholar 

  • Ma F, Dong D (2014) A measurement method on pesticide residues of apple surface based on laser-induced breakdown spectroscopy. Food Anal Methods 7(9):1858–1865. https://doi.org/10.1007/s12161-014-9828-4

    Article  Google Scholar 

  • Marschner H (1995a) Functions of mineral nutrients: macronutrients. In: Mineral nutrition of higher plants, 2nd edn. Academic Press, London, pp 229–312. https://doi.org/10.1016/B978-012473542-2/50010-9

    Chapter  Google Scholar 

  • Marschner H (1995b) Functions of mineral nutrients: micronutrients. In: Mineral nutrition of higher plants, 2nd edn. Academic Press, London, pp 313–404. https://doi.org/10.1016/B978-012473542-2/50011-0

    Chapter  Google Scholar 

  • McClure W (2003) Review: 204 years of near infrared technology: 1800–2003. J Near Infrared Spectrosc 11(6):487–518. https://doi.org/10.1255/jnirs.399

    Article  CAS  Google Scholar 

  • Miller C (2001) Chemical principles of near infrared technology. In: Williams P, Norris K (eds) Near infrared technology in the agricultural and food industries. American Association of Cereal Chemist, St. Paul, pp 9–29

    Google Scholar 

  • Moncayo S, Rosales JD, Izquierdo-Hornillos R, Anzano J, Caceres JO (2016) Classification of red wine based on its protected designation of origin (PDO) using laser-induced breakdown spectroscopy (LIBS). Talanta 158:185–191. https://doi.org/10.1016/j.talanta.2016.05.059

    Article  CAS  Google Scholar 

  • Naes T, Isakson T, Fearn T, Davies TA (2002) A user-friendly guide to multivariate calibration and classification. NIR Publications, Chichester

    Google Scholar 

  • Nafie LA (2001) Theory of Raman scattering. In: Lewis IR, Edwards HGM (eds) Handbook of Raman spectroscopy from the research laboratory to the process line. Talor and Francis Group, New York

    Google Scholar 

  • Kramida, A., Ralchenko, Y., Reader, J., & NIST Atomic spectra database (version 5.4) (2017) National Institute of Standards and Technology http://physics.nist.gov/asd. Accessed April 2017

  • OsborneBG, FearnT, HindlePH, HindlePT (1993) Practical NIR spectroscopy with applications in food and beverage analysis. Longman Scientific & Technical

  • Salguero-Chaparro L, Gaitán-Jurado AJ, Ortiz-Somovilla V, Peña-Rodríguez F (2013) Feasibility of using NIR spectroscopy to detect herbicide residues in intact olives. Food Control 30(2):504–509. https://doi.org/10.1016/j.foodcont.2012.07.045

    Article  CAS  Google Scholar 

  • Santos D Jr, Nunes LC, de Carvalho GGA, Gomes MS, de Souza PF, Leme FO, dos Santos LGC, Krug FJ (2012) Laser-induced breakdown spectroscopy for analysis of plant materials: a review. Spectrochim Acta B At Spectrosc 71–72:3–13

    Article  Google Scholar 

  • SantosAF, SilvaFM, LenziMK, PintoJC (2013) Infrared (MIR, NIR), Raman, and other spectroscopic methods. In: Monitoring polymerization reactions. John Wiley & Sons, p 107–134. doi:https://doi.org/10.1002/9781118733813.ch6

  • Schulz H, Baranska M (2007) Identification and quantification of valuable plant substances by IR and Raman spectroscopy. Vib Spectrosc 43(1):13–25. https://doi.org/10.1016/j.vibspec.2006.06.001

    Article  CAS  Google Scholar 

  • SeptemberFJD (2011) Detection and quantification of spice adulteration by near infrared hyperspectral imaging. Stellenbosch University

  • Sezer B, Bilge G, Boyaci IH (2016) Laser-induced breakdown spectroscopy based protein assay for cereal samples. J Agric Food Chem 64(49):9459–9463. https://doi.org/10.1021/acs.jafc.6b04828

    Article  CAS  Google Scholar 

  • Sharma A (2006) Irradiation to decontaminate herbs and spices vol 3 Handbook of herbs and spices. Woodhead Publishing Limited, Cambridge

    Google Scholar 

  • Steven FA (1981) The theory of linear models and multivariate analysis. Wiley-Blackwell, USA

    Google Scholar 

  • Strother T (2009) NIR and Raman: complementary techniques for raw material identification. Thermo Fisher Scientific Instruments LLC, Madison

    Google Scholar 

  • Sun H, Wang F, Ai L (2007) Determination of banned 10 azo-dyes in hot chili products by gel permeation chromatography–liquid chromatography–electrospray ionization-tandem mass spectrometry. J Chromatogr A 1164(1-2):120–128. https://doi.org/10.1016/j.chroma.2007.06.075

    Article  CAS  Google Scholar 

  • Trevizan LC, Santos D Jr, Samad RE, Vieira ND Jr, Nunes LC, Rufini IA, Krug FJ (2009) Evaluation of laser induced breakdown spectroscopy for the determination of micronutrients in plant materials. Spectrochim Acta B At Spectrosc 64(5):369–377. https://doi.org/10.1016/j.sab.2009.04.003

    Article  Google Scholar 

  • Viuda-Martos M, Ruiz-Navajas Y, Fernandez-Lopez J, Perez-Alvarez JA (2011) Spices as functional foods. Crit Rev Food Sci Nutr 51(1):13–28. https://doi.org/10.1080/10408390903044271

    Article  CAS  Google Scholar 

  • WangJ, ZhengP, LiuH, FangL (2016) Classification of Chinese tea leaves by laser-induced breakdown spectroscopy combined with discriminant analysis method. Anal Methods:3204–3209

  • Williams P (2001) Implementation of near infrared technology. In: Williams P, Norris K (eds) Near infrared technology in the agricultural and food industries, 2nd edn. American Association of Cereal Chemist, St Paul, pp 145–196

    Google Scholar 

  • Withnall R, Chowdhry BZ, Silver J, Edwards HGM, de Oliveira LF (2003) Raman spectra of carotenoids in natural products. Spectrochim Acta A 59(10):2207–2212. https://doi.org/10.1016/S1386-1425(03)00064-7

    Article  Google Scholar 

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Correspondence to Ismail Hakki Boyaci.

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Elif Ercioglu declares that she has no conflict of interest. Hasan Murat Velioglu declares that he has no conflict of interest. İsmail Hakki Boyaci declares that he has no conflict of interest.

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Ercioglu, E., Velioglu, H.M. & Boyaci, I.H. Chemometric Evaluation of Discrimination of Aromatic Plants by Using NIRS, LIBS. Food Anal. Methods 11, 1656–1667 (2018). https://doi.org/10.1007/s12161-018-1145-x

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