Quantification of Jatropha methyl biodiesel in mixtures with diesel using mid-infrared spectrometry and interval variable selection methods

References

• Abed, K. A., M. S. Gad, A. K. El Morsi, M. M. Sayed, and S. A. Elyazeed. 2019. Effect of biodiesel fuels on diesel engine emissions. Egyptian Journal of Petroleum 28(2):183–8. doi: 10.1016/j.ejpe.2019.03.001.
   Google Scholar
• ABNT. 2008. Biodiesel - Determination of biodiesel content in diesel fuel oil by mid infrared spectroscopy. Brazilian Association of Technical Standards, 1–13. Accessed May 17, 2018. https://www.target.com.br/produtos/normas-tecnicas/40641/nbr15568-biodiesel-determinacao-do-teor-de-biodiesel-em-oleo-diesel-por-espectroscopia-na-regiao-do-infravermelho-medio.
   Google Scholar
• Achten, W. M. J., L. Verchot, Y. J. Franken, E. Mathijs, V. P. Singh, R. Aerts, and B. Muys. 2008. Jatropha bio-diesel production and use. Biomass and Bioenergy 32(12):1063–84. doi: 10.1016/j.biombioe.2008.03.003.
   Web of Science ®Google Scholar
• Andersen, C. M., and R. Bro. 2010. Variable selection in regression-a tutorial. Journal of Chemometrics 24(11-12):728–37. doi: 10.1002/cem.1360.
   Web of Science ®Google Scholar
• ANP. 2018. Agência Nacional do Petróleo, Gá Natural e Biocombustíveis. Perfil Nacional de Materias-primas Consumidas para Produção de Biodiesel. Accessed May 21, 2019. www.anp.gov.br/images/PROD…/Biodiesel/Processamento_de_materias-primas.xlsx.
   Google Scholar
• Aprobio. 2018. Matérias-primas alternativas batem recorde de participação no biodiesel. Accessed June 17, 2019. https://aprobio.com.br/2018/12/26/materias-primas-alternativas-batem-recorde-de-participacao-no-biodiesel/.
   Google Scholar
• Araújo, D., F. da Silva, I. C. Araújo, I. C. G. Costa, C. V. Ô. Rodarte de Moura, M. H. Chaves, and E. C. E. Araújo. 2014. Study of degumming process and evaluation of oxidative stability of methyl and ethyl biodiesel of Jatropha curcas L. oil from three different Brazilian states. Renewable Energy 71:495–501. doi: 10.1016/j.renene.2014.06.001.
   Web of Science ®Google Scholar
• ASTM E1655-05. 2012. Standard practices for infrared multivariate quantitative analysis. ASTM International 5:29. doi: 10.1520/E1655-05R12.
   Google Scholar
• Atabani, A. E., T. M. I. Mahlia, H. H. Masjuki, I. A. Badruddin, H. W. Yussof, W. T. Chong, and K. T. Lee. 2013. A comparative evaluation of physical and chemical properties of biodiesel synthesized from edible and non-edible oils and study on the effect of biodiesel blending. Energy 58:296–304. doi: 10.1016/j.energy.2013.05.040.
   Web of Science ®Google Scholar
• Bergmann, J., D. Tupinambá, O. Y. Costa, J. R. Almeida, C. Barreto, and B. Quirino. 2013. Biodiesel production in Brazil and alternative biomass feedstocks. Renewable and Sustainable Energy Reviews 21:411–20. doi: 10.1016/j.rser.2012.12.058.
   Web of Science ®Google Scholar
• Berman, P., N. Meiri, C. Linder, and Z. Wiesman. 2016. 1H low field nuclear magnetic resonance relaxometry for probing biodiesel autoxidation. Fuel 177:315–25. doi: 10.1016/j.fuel.2016.03.002.
   Web of Science ®Google Scholar
• Borin, A., and R. J. Poppi. 2005. Application of mid infrared spectroscopy and iPLS for the quantification of contaminants in lubricating oil. Vibrational Spectroscopy 37(1):27–32. doi: 10.1016/j.vibspec.2004.05.003.
   Web of Science ®Google Scholar
• Coates, J. 2006. Interpretation of infrared spectra, a practical approach. In Encyclopedia of analytical chemistry, ed. R. A. Meyer, 10815–37. Chichester: John Wiley & Sons Ltd.
   Google Scholar
• Colthup, N. B., L. H. Daly, and S. E. Wiberley. 1990. The theoretical analysis of molecular vibrations. In Peter Larkin (ed.). Introduction to Infrared and Raman Spectroscopy, 483–542. Amsterdam, The Netherlands: Academic Press; Elsevier. doi: 10.1016/B978-0-08-091740-5.50017-X.
   Google Scholar
• Corona, F., Z. Zhu, A. H. De Souza Júnior, M. Mulas, E. Muru, L. Sassu, G. Barreto, and R. Baratti. 2015. Supervised distance preserving projections: Applications in the quantitative analysis of diesel fuels and light cycle oils from NIR spectra. Journal of Process Control 30:10–21. doi: 10.1016/j.jprocont.2014.11.005.
   Web of Science ®Google Scholar
• Correia, R. M., E. Domingos, V. M. Cáo, B. R. F. Araujo, S. Sena, L. U. Pinheiro, A. M. Fontes, L. F. M. Aquino, E. C. Ferreira, P. R. Filgueiras, et al. 2018. Portable near infrared spectroscopy applied to fuel quality control. Talanta 176:26–33. doi: 10.1016/j.talanta.2017.07.094.
   PubMed Web of Science ®Google Scholar
• De Oliveira, F. C., and S. T. Coelho. 2017. History, evolution, and environmental impact of biodiesel in Brazil: A review. Renewable and Sustainable Energy Reviews 75:168–79. doi: 10.1016/j.rser.2016.10.060.
   Web of Science ®Google Scholar
• Dupuy, N., Z. Brahem, S. Amat, and J. Kister. 2015. Near-infrared spectroscopy analysis of heavy fuel oils using a new diffusing support. Applied Spectroscopy 69(10):1137–43. doi: 10.1366/14-07725.
   PubMed Web of Science ®Google Scholar
• Ferrão, M. F., J. Z. Francesquett, M. S. Viera, R. H. Lovato, D. Fachini, A. E. Gerbase, and A. B. Costa. 2010. Modelos de regressão multivariada empregando seleção de intervalos para a quantificação do biodiesel em blendas biodiesel/diesel. Tecno-Lógica 14(2):87–92. doi: 10.17058/tecnolog.v14i2.1459.
   Google Scholar
• Ferreira, M. M. C., A. M. Antunes, M. S. Melgo, and P. L. O. Volpe. 1999. Quimiometria I: Calibração multivariada, um tutorial. Química Nova 22(5):724–31. doi: 10.1590/S0100-40421999000500016.
   Web of Science ®Google Scholar
• Gaydou, V., J. Kister, and N. Dupuy. 2011. Evaluation of multiblock NIR/MIR PLS predictive models to detect adulteration of diesel/biodiesel blends by vegetal oil. Chemometrics and Intelligent Laboratory Systems 106(2):190–7. doi: 10.1016/j.chemolab.2010.05.002.
   Web of Science ®Google Scholar
• Gofferjé, G., M. Gebhardt, A. Stäbler, U. Schweiggert-Weisz, and E. Flöter. 2014. Screening of impact factors on the enzymatic neutralization of Jatropha crude oil. European Journal of Lipid Science and Technology 116(2):185–92. doi: 10.1002/ejlt.201300177.
   Web of Science ®Google Scholar
• Gontijo, L. C., E. Guimarães, H. Mitsutake, F. B. de Santana, D. Q. Santos, and W. Borges Neto. 2014. Quantification of soybean biodiesels in diesel blends according to ASTM E1655 using mid-infrared spectroscopy and multivariate calibration. Fuel 117(PART B):1111–4. doi: 10.1016/j.fuel.2013.10.043.
   Google Scholar
• González, A. G., M. A. Herrador, and A. G. Asuero. 1999. Intra-laboratory testing of method accuracy from recovery assays. Talanta 48(3):729–36. doi: 10.1016/S0039-9140(98)00271-9.
   PubMed Web of Science ®Google Scholar
• Guimarães, E., H. Mitsutake, L. C. Gontijo, F. B. de Santana, D. Q. Santos, and W. Borges Neto. 2015. Infrared spectroscopy and multivariate calibration for quantification of soybean oil as adulterant in biodiesel fuels. Journal of the American Oil Chemists' Society 92(6):777–82. doi: 10.1007/s11746-015-2656-x.
   Web of Science ®Google Scholar
• Hupp, A. M., J. Perron, N. Roques, J. Crandall, S. Ramos, and B. Rohrback. 2018. Analysis of biodiesel-diesel blends using ultrafast gas chromatography (UFGC) and chemometric methods: Extending ASTM D7798 to biodiesel. Fuel 231:264–70. doi: 10.1016/j.fuel.2018.05.102.
   Web of Science ®Google Scholar
• Jiang, H., G. Liu, C. Mei, S. Yu, X. Xiao, and Y. Ding. 2012. Measurement of process variables in solid-state fermentation of wheat straw using FT-NIR spectroscopy and synergy interval PLS algorithm. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 97:277–83. doi: 10.1016/j.saa.2012.06.024.
   PubMed Web of Science ®Google Scholar
• Jiang, J.-H., R. J. Berry, H. W. Siesler, and Y. Ozaki. 2002. Wavelength interval selection in multicomponent spectral analysis by moving window partial least-squares regression with application to mid-infrared and near-infrared spectroscopic data. Analytical Chemistry 74(14):3555–65. doi: 10.1021/ac011177u.
   PubMed Web of Science ®Google Scholar
• Kamel, D. A., H. A. Farag, N. K. Amin, A. A. Zatout, and R. M. Ali. 2018. Smart utilization of jatropha (Jatropha curcas Linnaeus) seeds for biodiesel production: Optimization and mechanism. Industrial Crops and Products 111:407–13. doi: 10.1016/j.indcrop.2017.10.029.
   Web of Science ®Google Scholar
• Kennard, R. W., and L. A. Stone. 1969. Computer aided design of experiments. Technometrics 11(1):137–48. doi: 10.1080/00401706.1969.10490666.
   Web of Science ®Google Scholar
• Leardi, R., and L. Nørgaard. 2004. Sequential application of backward interval partial least squares and genetic algorithms for the selection of relevant spectral regions. Journal of Chemometrics 18(11):486–97. doi: 10.1002/cem.893.
   Web of Science ®Google Scholar
• Lin, J.-J., and Y.-W. Chen. 2017. Production of biodiesel by transesterification of Jatropha oil with microwave heating. Journal of the Taiwan Institute of Chemical Engineers 75:43–50. doi: 10.1016/j.jtice.2017.03.034.
   Web of Science ®Google Scholar
• Lôbo, I. P., S. L. C. Ferreira, and R. S. da Cruz. 2009. Biodiesel: Parâmetros de qualidade e métodos analíticos. Química Nova 32(6):1596–608. doi: 10.1590/S0100-40422009000600044.
   Google Scholar
• Lorber, A. 1986. Error propagation and figures of merit for quantification by solving matrix equations. Analytical Chemistry 58(6):1167–72. doi: 10.1021/ac00297a042.
   Web of Science ®Google Scholar
• Lorber, A., K. Faber, and B. R. Kowalski. 1997. Net analyte signal calculation in multivariate calibration. Analytical Chemistry 69(8):1620–6. doi: 10.1021/ac960862b.
   Web of Science ®Google Scholar
• Mark, H., and J. Workman. 2003. The F statistic. In Statistics in spectroscopy, ed. H. Mark and J. Workman, 2nd ed., 205–11. New York: Academic Press; Elsevier. doi: 10.1016/B978-012472531-7/50065-2.
   Google Scholar
• Martens, H., and T. Naes. 1989. Multivariate calibration. New York, NY: John & Sons.
   Google Scholar
• Mazivila, S. J. 2018. Trends of non-destructive analytical methods for identification of biodiesel feedstock in diesel-biodiesel blend according to European Commission Directive 2012/0288/EC and detecting diesel-biodiesel blend adulteration: A brief review. Talanta 180:239–47. doi: 10.1016/j.talanta.2017.12.057.
   PubMed Web of Science ®Google Scholar
• Mazivila, S. J., and A. C. Olivieri. 2018. Chemometrics coupled to vibrational spectroscopy and spectroscopic imaging for the analysis of solid-phase pharmaceutical products: A brief review on non-destructive analytical methods. TrAC Trends in Analytical Chemistry 108:74–87. doi: 10.1016/j.trac.2018.08.013.
   Web of Science ®Google Scholar
• McMurry, J. 2017. Química Orgânica - Combo. Tradução da 9a Edição Norte-Americana, ed. R. M. Matos, 9a Edição. São Paulo: Cengage Learning.
   Google Scholar
• Mogollon, N. G. S., F. A. de L. Ribeiro, M. M. Lopez, L. W. Hantao, R. J. Poppi, and F. Augusto. 2013. Quantitative analysis of biodiesel in blends of biodiesel and conventional diesel by comprehensive two-dimensional gas chromatography and multivariate curve resolution. Analytica Chimica Acta 796:130–6. doi: 10.1016/j.aca.2013.07.071.
   PubMed Web of Science ®Google Scholar
• Nørgaard, L., A. Saudland, J. Wagner, J. P. Nielsen, L. Munck, and S. B. Engelsen. 2000. Interval partial least-squares regression (iPLS): A comparative chemometric study with an example from near-infrared spectroscopy. Applied Spectroscopy 54(3):413–9. doi: 10.1366/0003702001949500.
   Web of Science ®Google Scholar
• Olivieri, A. C., N. M. Faber, J. Ferré, R. Boqué, J. H. Kalivas, and H. Mark. 2006. Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report). Pure and Applied Chemistry 78(3):633–61. doi: 10.1351/pac200678030633.
   Web of Science ®Google Scholar
• Paiva, E. M., J. J. R. Rohwedder, C. Pasquini, M. F. Pimentel, and C. F. Pereira. 2015. Quantification of biodiesel and adulteration with vegetable oils in diesel/biodiesel blends using portable near-infrared spectrometer. Fuel 160:57–63. doi: 10.1016/j.fuel.2015.07.067.
   Web of Science ®Google Scholar
• Pavia, D. L., G. M. Lampman, G. S. Kriz, and J. R. Vyvyan. 2016. Introdução à espectriscopia - Tradução da 5a. edição Norte-Americana, ed. P. Barros and R. Torrejon, 2a. Edição. São Paulo: Cengage Learning.
   Google Scholar
• Rocha, W. F. C., B. G. Vaz, G. F. Sarmanho, L. H. C. Leal, R. Nogueira, V. F. Silva, and C. N. Borges. 2012. Chemometric techniques applied for classification and quantification of binary biodiesel/diesel blends. Analytical Letters 45(16):2398–411. doi: 10.1080/00032719.2012.686135.
   Web of Science ®Google Scholar
• Rocha, W. F. C. 2007. Utilização do sinal analítico líquido para validação de modelos de calibração multivariada através do cálculo de figuras de mérito e de cartas de controle. PhD diss., Universidade Estadual de Campinas, Campinas, SP.
   Google Scholar
• Ruschel, C. F. C., C. Te Huang, D. Samios, M. F. Ferrão, C. I. Yamamoto, and R. C. B. Plocharski. 2015. Environmentally friendly determination of quality parameters of biodiesel/diesel blends using Fourier transform infrared spectra. Journal of the American Oil Chemists' Society 92(3):309–15. doi: 10.1007/s11746-015-2601-z.
   Web of Science ®Google Scholar
• Schirmer, W. N., and C. B. Ribeiro. 2017. Panorama dos combustíveis e biocombustíveis no Brasil e as emissões gasosas decorrentes do uso da gasolina/etanol. BIOFIX Scientific Journal 2(2):16–22. doi: 10.5380/biofix.v2i2.53539.
   Google Scholar
• Shimamoto, G. G., and M. Tubino. 2016. Alternative methods to quantify biodiesel in standard diesel-biodiesel blends and samples adulterated with vegetable oil through UV–Visible spectroscopy. Fuel 186:199–203. doi: 10.1016/j.fuel.2016.08.076.
   Web of Science ®Google Scholar
• Shimamoto, G. G., and M. Tubino. 2018. Simultaneous determination of six quality parameters of biodiesel through 1H NMR spectroscopy and partial least squares. Talanta 179:816–21. doi: 10.1016/j.talanta.2017.12.001.
   PubMed Web of Science ®Google Scholar
• Skibsted, E. T. S., H. F. M. Boelens, J. A. Westerhuis, A. K. Smilde, N. W. Broad, D. R. Rees, and D. T. Witte. 2005. Net analyte signal based statistical quality control. Analytical Chemistry 77(22):7103–14. doi: 10.1021/ac048138d.
   PubMed Web of Science ®Google Scholar
• Smith, B. C. 2011. Fundamentals of Fourier transform infrared spectroscopy, 2nd ed. New York, NY: CRC Press; Taylor & Francis Group.
   Google Scholar
• Sun, D.-W. 2009. Infrared spectroscopy for food quality analysis and control, 1st ed. New York, NY: Academic Press/Elsevier.
   Google Scholar
• Tercini, A. C. B., M. Pinesi, G. Cyntia Calera, R. Sequinel, R. R. Hatanaka, J. E. de Oliveira, and D. L. Flumignan. 2018. Ultrafast gas chromatographic method for quantitative determination of total FAMEs in biodiesel: An analysis of 90 s. Fuel 222:792–9. doi: 10.1016/j.fuel.2018.03.008.
   Web of Science ®Google Scholar
• Valderrama, P., J. W. B. Braga, and R. J. Poppi. 2009. Estado da arte de figuras de mérito em calibração multivariada. Quimica Nova 32(3):567–70. doi: 10.1590/S0100-40422009000500034.
   Google Scholar
• Walczak, B., and D. L. Massart. 1998. Multiple outlier detection revisited. Chemometrics and Intelligent Laboratory Systems 41(1):1–15. doi: 10.1016/S0169-7439(98)00034-3.
   Web of Science ®Google Scholar
• Xiaobo, Z., Z. Jiewen, M. J. W. Povey, M. Holmes, and M. Hanpin. 2010. Variables selection methods in near-infrared spectroscopy. Analytica Chimica Acta 667(1-2):14–32. doi: 10.1016/j.aca.2010.03.048.
   PubMed Web of Science ®Google Scholar
• Zou, X., J. Zhao, and Y. Li. 2007. Selection of the efficient wavelength regions in FT-NIR spectroscopy for determination of SSC of “Fuji” apple based on BiPLS and FiPLS models. Vibrational Spectroscopy 44(2):220–7. doi: 10.1016/j.vibspec.2006.11.005.
   Web of Science ®Google Scholar