Validation of model of multivariate calibration: An application to the determination of biodiesel blend levels in diesel by near-infrared spectroscopy

Journal of Chemometrics

Volumn 26, Issue 8-9, 2012, Pages 456-461

  De Carvalho Rocha, Werickson Fortunato ^a   Nogueira, Raquel ^a   Vaz, Boniek Gontigo ^b  

^a INSTITUTO NACIONAL DE METROLOGIA   (Brazil)

^b FEDERAL UNIVERSITY OF GOIÁS   (Brazil)

Author keywords

Biodiesel; Figure of merit; Multivariate calibration; NIR; Validation

Indexed keywords

INFRARED DEVICES; LEAST SQUARES APPROXIMATIONS; NEAR INFRARED SPECTROSCOPY;

BIO-DIESEL BLENDS; BIODIESEL/DIESEL; CALIBRATION MODEL; FIGURE OF MERIT; MULTIVARIATE CALIBRATION; NET ANALYTE SIGNALS; NIR; PARTIAL LEAST-SQUARES; PERFORMANCE; VALIDATION;

BIODIESEL;

EID: 84865154634     PISSN: 08869383     EISSN: 1099128X     Source Type: Journal    
DOI: 10.1002/cem.2420     Document Type: Article

References (29)

1. Lôbo IP, Ferreira SLC, Cruz RS. Biodiesel: parâmetros de qualidade e métodos analíticos. Quím. Nova 2009; 32: 1596-1608.
2. Pimentel MF, Ribeiro GMGS, Cruz RS, Stragevitch L, Filho JGAP, Teixeira LSG. Determination of biodiesel content when blended with mineral diesel fuel using infrared spectroscopy and multivariate calibration. Microchem. J. 2006; 82: 201-206.
3. Pinto AC, Guarieiro LLN, Rezende MJC, Ribeiro NM, Torres EA, Lopes WA, Pereira PAP, Andrade JB. Biodiesel: an overview. J. Braz. Chem. Soc. 2005; 16: 1313-1330.
4. 1H nuclear magnetic resonance spectroscopy. J. Am. Oil Chem. Soc. 2001; 78: 1025-1028.
5. Foglia TA, Jones KC, Phillips JG. Determination of biodiesel and triacylglycerols in diesel fuel by LC. Chromatographia 2005; 62: 115-119.
6. Lira LFB, Albuquerque MS, Pacheco JGA, Fonseca TM, Cavalcanti EHS, Stragevitch K, Pimentel MF. Infrared spectroscopy and multivariate calibration to monitor stability quality parameters of biodiesel. Microchem. J. 2010; 96: 126-131.
7. Macho S, Larrechi MS. Near-infrared spectroscopy and multivariate calibration for the quantitative determination of certain properties in the petrochemical industry. Trends Anal. Chem. 2002; 21: 799-806.
8. Cramer JA, Morris RE, Giordano B, Pehrsson SL. Partial least-squares predictions of nonpetroleum-derived fuel content and resultant properties when blended with petroleum-derived fuels. Energ. Fuel 2009; 23: 894-02.
9. Rocha WFC, Rosa AL, Martins JA, Poppi RJ. Determination and validation of nimesulide in pharmaceutical formulation by near infrared spectroscopy. J. Braz. Chem. Soc. 2010; 21: 1929-1936.
10. Valderrama P, Braga JWB, Poppi RJ. Estado da arte de figuras de mérito em calibração multivariada. Quím. Nova 2009; 32: 1278-1287.
11. Olivieri AC, Goicoechea HC, Inón FA. MVC1: an integrated Matlab toolbox for first-order multivariate calibration. Chemom. Intell. Lab. Syst. 2004; 73: 189-197.
12. Al-Ghouti MA, Al-Degs, YS, Amer M. Application of chemometrics and FTIR for determination of viscosity index and base number of motor oils. Talanta 2010; 81: 1096-1101.
13. Monteiro MR, Ambrozin APPA, Santos S, Boffo EF, Pereira-Filho ER, Lião LM, Ferreira AG. Evaluation of biodiesel-diesel blends quality using 1H NMR and chemometrics. Talanta 2009; 78: 660-664.
14. ABNT NBR ISO/IEC 17025. Requisitos gerais para competência de laboratórios de ensaio e calibração. ABNT: Rio de Janeiro, 2005.
15. Wold S, Trygg J, Berglund A. Some recent developments in PLS modelling. Chemom. Intell. Lab. Syst. 2001; 58: 131-150.
16. Martens H, Naes T. Multivariate Calibration. Wiley: Chichester, UK, 1989.
17. Lindgren F, Geladi P, Rännar S, Wold S. Interactive variable selection (IVS) for PLS. Part 1: theory and application. J. Chemometr. 1994; 8: 349-364.
18. Lorber A, Faber K, Kowalski B. Anal. Chem. 1997; 69: 1620-1626.
19. Bro R, Andersen CM. Theory of net analyte signal vectors in inverse regression. J. Chemometr. 2003; 17: 646-652.
20. Vandeginste BGM, Massart DL, Buydens LMC, Jong S, Lewi PJ, Smeyers-Verbeke J. Handbook of Chemometrics and Qualimetrics: Part B. Elsevier: Amsterdam, 1998.
21. Curie LA. Nomenclature in evaluation of analytical methods including detection and quantification capabilities (IUPAC recommendations 1995). Anal. Chim. Acta 1999; 391: 105-126.
22. Boqué R, Rius FX. Multivariate detection limits estimators. Chemom. Intell. Lab. Syst. 1996; 32: 11-23.
23. Boqué R, Faber NM, Rius FX. Detection limits in classical multivariate calibration models. Anal. Chim. Acta 2000; 423: 41-49.
24. Laasonen M, Harmia-Pulkkinen T, Simard C, Rasanen M, Vuorela H. Development and validation of a near-infrared method for quantification of caffeine in intact single tables. Anal. Chem. 2003; 75: 754-760.
25. Geris R, Santos NAC, Amaral BA, Maia IS, Castro VD, Carvalho JCM. Biodiesel de soja: reação de transesterificação para aulas práticas de química orgânica. Quim. Nova 2007; 30: 1369-1373.
26. Wu Z, Rodgers RP, Marshall AG. Characterization of vegetable oils: detailed compositional fingerprints derived from electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. J. Agric. Food Chem. 2004; 52: 5322-5328.
27. Gunstone FD (ed.) Vegetable Oils in Food Technology: Composition, Properties, and Users. CRC Press: Boca Raton, FL, 2002.
28. Baptista M, Rocha WFC, Poppi RJ. Quality control of the paracetamol drug by chemometrics and imaging spectroscopy in the near infrared region. J. Mol. Struct. 2011; 1002: 167-171.
29. Goicoechea HC, Olivieri AC. Enhanced synchronous spectrofluorometric determination of tetracycline in blood serum by chemometric analysis. Comparison of partial least-squares and hybrid linear analysis calibrations. Anal. Chem. 1999; 71: 4361-4368.