Abstract
Copaiba oil is a non-timber forest product utilized in popular medicine, in addition to the pharmaceutical, cosmetic, and food industries. Brazil is a chief producer and supplier of this oil, and due to an increasing demand and elevated market value, it causes for this product to be subject to adulterations. Thus, the goal of this study was to develop a direct, fast, and simple method to quantify the purity of the oil extracted from Copaifera langsdorffii Desf., specifically, when the oil was adulterated with soybean oil. Quantification was performed utilizing a portable NIR spectrometer and partial least squares regression (PLSR). In the development and validation of the method, 53 samples of copaiba oil expressing a purity ranging from 50 up to 100% were used. Of the 53 samples, 15 were pure, 31 were adulterated with unused soybean oil, 6 were adulterated with soybean oil used for frying, and 1 adulterated with an unknown vegetable oil. Four models were developed and the best among them presented RMSEP = 1.5%, R 2 = 0.991, and REP lower than 2.0% and expressed precision with deviations below 0.7%. These results indicate that the method is suitable for quality control analysis. In addition, it was accurate in the identification of samples with that were not present in the developed model.
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References
Addou S, Fethi F, Chikri M, Rrhioua A (2016) Detection of argan oil adulteration with olive oil using fluorescence spectroscopy and chemometrics tools. J Mater Environ 7(8):2689–2698
Aguilar CL, Lima K, Manno M, Tavares FB, Souza VP, Neto DL (2013) Effect of copaiba essential oil on broiler chickens’ performance. Acta Scientiarum Animal. Sciences 35(2):145–151. https://doi.org/10.4025/actascianimsci.v35i2.15376
Barbosa K, Scudeller VV, Rosa AL (2009a) Potencial de produção de óleo resina de Copaifera multijuga Hayne nos dois períodos climáticos amazônicos na Reserva de Desenvolvimento Sustentável do Tupé, Manaus-AM. In Diversos, Biotupé: Meio Físico, Diversidade Biológica e Sociocultural do Baixo Rio Negro, Amazônia Central volume 2, UEA Edições, Manaus, pp 143–153
Barbosa K, Yoshida M, Scudeller V (2009b) Detection of adulterated copaiba (Copaifera multijuga Hayne) oil-resins by refractive index and thin layer chromatography. Braz J Pharmacogn 19(1A):57–60. https://doi.org/10.1590/S0102-695X2009000100013
Barbosa P, Wiedemann L, Medeiros R, Sampaio P, Vieira G, Veiga-Junior V (2013) Phytochemical fingerprints of copaiba oils (Copaifera multijuga Hayne) determined by multivariate analysis. Chem Biodivers 10:1350–1360. https://doi.org/10.1002/cbdv.201200356
Basri KN, Hussain MN, Bakar J, Sharif Z, Khir MF, Zoolfakar AS (2017) Classification and quantification of palm oil adulteration via portable NIR spectroscopy. Spectrochim Acta A Mol Biomol Spectrosc 173:335–342. https://doi.org/10.1016/j.saa.2016.09.028
Biavatti M, Dossin D, Deschamps F, Lima M (2006) Análise de óleos-resinas de copaíba: contribuição para seu controle de qualidade. Braz J Pharmacogn 16(2):230–235. https://doi.org/10.1590/S0102-695X2006000200017
Braga JWB, Poppi RJ (2004) Validação de modelos de calibração multivariada: uma aplicação na determinação de pureza polimórfica de carbamazepina por espectroscopia no infravermelho próximo. Quim Nova 27(6):1004–1011. https://doi.org/10.1590/S0100-40422004000600027
Braga JWB, Junior AAS, Martins IS (2014) Determination of viscosity index in lubrificant oils by infrared spectroscopy and PLSR. Fuel (Guildford) 120:171–178. https://doi.org/10.1016/j.fuel.2013.12.017
EN ISO 5509, I (1978) EN ISO 5509: animal and vegetable fats and oils: preparation of methyl esters of fatty acids. International Organization for Standardization, London
Ferreira MMC (2015) Quimiometria-Conceitos, Métodos e Aplicações. Editora da Unicamp, Campinas
Gemperline PJ, Booksh KS, Kalivas JH, Brown SD, Lavine BK, Davidson CE, Walmsley A (2006) Practical guide to chemometrics, 2th edn. CRC Press, Boca Raton
Grobério TS, Zacca JJ, Talhavini M, Braga JWB (2014) Quantification of cocaine hydrochloride in seized drug samples by infrared spectroscopy and PLSR. J Braz Chem Soc 25:1696–1703. https://doi.org/10.5935/0103-5053.20140164
IBGE (2014) Sistema IBGE de Recuperação Automática-SIDRA-Instituto Brasileiro de Geografia e Estatística. (IBGE) http://wwwsidraibgegovbr/bda/pesquisas/pevs/defaultasp?o=30&i=P Acessed 11 May 2016
ISO 11843 (2000) Capability of detection. International Standards Organization, Geneva
Jackson JE, Mudholkar GS (1979) Control procedures for residuals associated with principal component analysis. Technometrics 21(3):341–349. https://doi.org/10.2307/1267757
Lutz OMD, Bonn GK, Rode BM, Huck CW (2014) Reproducible quantification of ethanol in gasoline via a customized mobile near-infrared spectrometer. Anal Chim Acta 826:61–68. https://doi.org/10.1016/j.aca.2014.04.002
Ma J, Zhang H, Tuchida T, Miao Y, Chen JY (2014) Rapid determination of degradation of frying oil using near-infrared spectroscopy. Food Sci Technol Res 20(2):217–223. https://doi.org/10.3136/fstr.20.217
Marangon CA, Martins VCA, Leite PMF, Santos DA, Nitschke M, Plepis AMG (2017) Chitosan/gelatin/copaiba oil emulsion formulation and its potential on controlling the growth of pathogenic bacteria. Ind Crop Prod 99:163–171. https://doi.org/10.1016/j.indcrop.2017.02.007
Marques EJN, Freitas ST, Pimentel MF (2016) Rapid and non-destructive determination of quality parameters in the ‘Tommy Atkins’ mango using a novel handheld near infrared spectrometer. Food Chem 197:1207–1214. https://doi.org/10.1016/j.foodchem.2015.11.080
Miller-Ihli NJ, O'Haver TC (1984) Calibration and curve fitting for extended range AAS. Spectrochim Acta B 12:1603–1614. https://doi.org/10.1016/0584-8547(84)80189-5
Moura LV, Oliveira ER, Fernandes ARM, Gabriel AMA, Silva LHX, Takiya CS, Cônsolo NRB, Rodrigues GCG, Lemos T, Gandra JR (2017) Feed efficiency and carcass traits of feedlot lambs supplemented either monensin or increasing doses of copaiba (Copaifera spp.) essential oil. Anim Feed Sci Technol 232:110–118. https://doi.org/10.1016/j.anifeedsci.2017.08.006
Nagata N, Bueno MIMS, Peralta-Zamora PG (2001) Métodos matemáticos para correção de interferências espectrais e efeitos interelementos na análise quantitativa por fluorescência de raios-x. Quim Nova 24(4):531–539. https://doi.org/10.1590/S0100-40422001000400015
Ortiz MC, Sarabia LA, Herrero A, Sánchez MS, Sanz MB, Rueda ME, Giménez D, Meléndez ME (2003) Capability of detection of an analytical method evaluating false positive and false negative (ISO 11843) with partial least squares. Chemom Intell Lab Syst 69:21–33. https://doi.org/10.1016/S0169-7439(03)00110-2
Paiva EM, Rohwedder JJR, Pasquini C, Pimentel MF, Pereira CF (2015) Quantification of biodiesel and adulteration with vegetable oils in diesel/biodiesel blends using portable near-infrared spectrometer. Fuel 160:57–63. https://doi.org/10.1016/j.fuel.2015.07.067
Pieri FA, Mussi MC, Moreira MAS (2009) Óleo de coapíba (Copaifera sp.): histórico, extração, aplicações industriais e propriedades medicinais. Rev Bras Pl Med 11(4):465–472. https://doi.org/10.1590/S1516-05722009000400016
Riu J, Rius FX (1997) Method comparison using regression with uncertainties in both axes. Trac-Trends Anal Chem 16(4):211–216. https://doi.org/10.1016/S0165-9936(97)00014-9
Santana FB, Gontijo LC, Mitsutake H, Mazivila SJ, Souza LM, Neto WB (2016) Non-destructive fraud detection in rosehip oil by MIR spectroscopy and chemometrics. Food Chem 209:228–233. https://doi.org/10.1016/j.foodchem.2016.04.051
Souza AM, Poppi RJ (2012) Experimento didático de quimiometria para análise exploratória de óleos vegetais comestíveis por espectroscopia no infravermelho médio e Análise de Componentes Principais: Um tutorial, parte I. Quim Nova 35(1):223–229. https://doi.org/10.1590/S0100-40422012000100039
Tappin MRR, Pereira JFG, Lima LA, Siani AC, Mazzei JL, Ramos MFS (2004) Análise química quantitativa para a padronização do óleo de copaíba por cromatografia em fase gasosa de alta resolução. Quim Nova 27(2):236–240. https://doi.org/10.1590/S0100-40422004000200012
Valderrama P, Braga JWB, Poppi RJ (2007) Variable selection, outlier detection, and figures of merit estimation in a partial least-squares regression multivariate calibration model. A case study for the determination of quality parameters in the alcohol industry by near-infrared spectroscopy. J Agric Food Chem 55(21):8331–8338. https://doi.org/10.1021/jf071538s
Vasconcelos AFF, Godinho OES (2002) Uso de métodos analíticos convencionados no estudo da autenticidade do óleo de copaiba. Quim Nova 25(6B):1057–1060. https://doi.org/10.1590/S0100-40422002000700002
Veiga VF Jr, Pinto AC (2002) O Gênero Copaifera L. Quim Nova 25:273–286. https://doi.org/10.1590/S0100-40422002000200016
Veiga VF Jr, Patitucci ML, Pinto AC (1997) Controle de autenticidade de óleos de copaíba comerciais por cromatografia gasosa de alta resolução. Quim Nova 20(6):612–615. https://doi.org/10.1590/S0100-40421997000600007
Workman J Jr (2001) The handbook of organic compounds—functional groupings and calculated locations in nanometers (nm) for NIR spectroscopy (Vol. 1). Academic Press, Orlando
Workman Jr J, Weyer L (2012) Alkenes and alkynes. In: Practical guide and spectral atlas for interpretative near-infrared spectroscopy, 2nd edn. CRC Press, Boca Raton, p 33–37
Zhong J, Qin X (2016) Rapid quantitative analysis of corn starch adulteration in Konjac Glucomannan by Chemometrics-assisted FT-NIR spectroscopy. Food Anal Methods 9:61–67. https://doi.org/10.1007/s12161-015-0176-9
Zontov YV, Balyklova KS, Titova AV, Rodionova OY, Pomerantsev AL (2016) Chemometric aided NIR portable instrument for rapid assessment of medicine quality. J Pharm Biomed Anal 131:87–93. https://doi.org/10.1016/j.jpba.2016.08.008
Acknowledgements
The authors wish to thank the farmers Luis Carlos Vasconcelos and Ronan Vasconcelos for the donation of the samples.
Funding
This study was funded by the Brazilian National Council for Scientific and Technological Development (CNPq) (grant no. 308748/2015-8) in the National Institute of in Bioanalytica (INCTBio) (grant no. 5736672/2008-3) and the Support Research of the Federal District Foundation (FAPDF).
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Alessandro C. de O. Moreira declares that he has no conflict of interest. Angelo H. de L. Machado declares that he has no conflict of interest. Fernanda V. de Almeida declares that she has no conflict of interest. Jez W. B. Braga declares that he has no conflict of interest.
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de Oliveira Moreira, A.C., de Lira Machado, A.H., de Almeida, F.V. et al. Rapid Purity Determination of Copaiba Oils by a Portable NIR Spectrometer and PLSR. Food Anal. Methods 11, 1867–1877 (2018). https://doi.org/10.1007/s12161-017-1079-8
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DOI: https://doi.org/10.1007/s12161-017-1079-8