Abstract
Mid-infrared fiberoptics reflectance spectroscopy (mid-IR FORS) is a very interesting technique for artwork characterization purposes. However, the fact that the spectra obtained are a mixture of surface (specular) and volume (diffuse) reflection is a significant drawback. The physical and chemical features of the artwork surface may produce distortions in the spectra that hinder comparison with reference databases acquired in transmission mode. Several studies attempted to understand the influence of the different variables and propose procedures to improve the interpretation of the spectra. This article is focused on the application of mid-IR FORS and multivariate calibration to the analysis of easel paintings. The objectives are the evaluation of the influence of the surface roughness on the spectra, the influence of the matrix composition for the classification of unknown spectra, and the capability of obtaining pigment composition mappings. A first evaluation of a fast procedure for spectra management and pigment discrimination is discussed. The results demonstrate the capability of multivariate methods, principal component analysis (PCA), and partial least squares discrimination analysis (PLS-DA), to model the distortions of the reflectance spectra and to delimitate and discriminate areas of uniform composition. The roughness of the painting surface is found to be an important factor affecting the shape and relative intensity of the spectra. A mapping of the major pigments of a painting is possible using mid-IR FORS and PLS-DA when the calibration set is a palette that includes the potential pigments present in the artwork mixed with the appropriate binder and that shows the different paint textures.
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References
Rosi F, Burnstock A, Van den Berg KJ et al (2009) Spectrochim Acta A Mol Biomol Spectrosc 71:1655–1662
Miliani C, Rosi F, Brunetti BG, Sgamellotti A (2010) Acc Chem Res 43:728–738
Sessa C, Bagán H, García JF (2013) Spectrochim Acta A Mol Biomol Spectrosc 115:617–628
Miliani C, Rosi F, Daveri A, Brunetti B (2012) Appl Phys A Mater Sci Process 106:295–307
Milosevic MSLB (2002) Appl Spectrosc Rev 37:347–364
Price BA, Boris P, (eds) (2007) Infrared and Raman Users Group Spectral Database. 2007 ed. Vol. 1 & 2. Philadelphia: IRUG, 2009. Infrared and Raman Users Group Spectral Database. Web. 20 June 2014. <www.irug.org>
Ricci C, Miliani C, Brunetti BG, Sgamellotti A (2006) Talanta 69:1221–1226
Poli T, Alice E, Chiantore O (2009) e-Preserv Sci 6:174–179
Rosi F, Daveri A, Miliani C et al (2009) Anal Bioanal Chem 395:2097–2106
Poli T, Chiantore O, Nervo M, Piccirillo A (2011) Anal Bioanal Chem 400:1161–1171
Wu C, Jacobson AR, Laba M, Baveye PC (2009) Geoderma 152:171–180
Dupuis G, Menu M (2006) Appl Phys A 83:469–474. doi:10.1007/s00339-006-3522-3
Dupuis G, Elias M, Simonot L (2002) Appl Spectrosc 56:1329–1336
Fabbri M, Picollo M, Porcinai S, Bacci M (2001) Appl Spectrosc 55:428–433
Bacci M, Chiari R, Porcinai S, Radicati B (1997) Chemom Intell Lab Syst 39:115–121
Sarmiento A, Pérez-Alonso M, Olivares M et al (2011) Anal Bioanal Chem 399:3601–3611
Fabbri M, Picollo M, Porcinai S, Bacci M (2001) Appl Spectrosc 55:420–427
Marengo E, Cristina Liparota M, Robotti E, Bobba M (2005) Anal Chim Acta 553:111–122
Rosi F, Federici A, Brunetti BG et al (2011) Anal Bioanal Chem 399:3133–3145
Bouchard M, Rivenc R, Menke C, Learner T (2009) Sect Title Hist Educ Doc 6:27–37
Montagner C, Sanches D, Pedroso J et al (2013) Spectrochim Acta A Mol Biomol Spectrosc 103:409–416
Giaccai J (2008) Sect Title Hist Educ Doc:1047
Miliani C, Rosi F, Burnstock A et al (2007) Appl Phys A Mater Sci Process 89:849–856
Melling PJ, Thomson M (2002) Handbook Vib Spectrosc
Geladi P, Kowalski BR (1986) Anal Chim Acta 185:1–17
Barker M, Rayens W (2003) J Chemom 17:166–173
Westerhuis J, Hoefsloot HJ, Smit S et al (2008) Metabolomics 4:81–89
Manuel P, Ruis I, Andrikopoulos KS et al (2008) Talanta 75:926–936
Ramos PM, Ruisánchez I (2006) Anal Chim Acta 558:274–282
Van Den Berg F, Engelsen SB (2009) Trends Anal Chem 28:1201–1222
Bromba M, Ziegler H (1981) Anal Chem 1:1583–1586
Seah MP, Dench WA (1989) Sect Title Opt Electron Mass Spectrosc Other Relat Prop 48:43–54
Azzouz T, Puigdomenech A, Aragay M, Tauler R (2003) Anal Chim Acta 484:121–134
Muehlethaler C, Massonnet G, Esseiva P (2011) Forensic Sci Int 209:173–182
Fearn T, Riccioli C, Garrido-Varo A, Guerrero-Ginel JE (2009) Chemom Intell Lab Syst 96:22–26
Rinnan Å, Nørgaard L, Berg F van den et al (2009) Infrared Spectrosc Food Qual Anal Control 29–50
Baronti S, Casini A, Lotti F, Porcinai S (1997) Chem Intel Lab Syst 39:103–114
Sessa C, Vila A, García JF (2011) Anal Bioanal Chem 400:2241–2251
Berg JDJ van den (2002) Analytical chemical studies on traditional linseed oil paints. Univ Amst 6:291
Acknowledgments
The authors thank N. Ferrer (SCT-UB) for her kind advice regarding the use of the infrared spectrometer and interpretation of the resulting spectra, as well as Romà Tauler of the Institute for Chemical and Environmental Research (CID-CSIC) for his support during the data treatment phase.
They thank Silvia Centeno and the Scientific Department of the Metropolitan Museum of Art for the permission to perform the XRF measurements.
The authors are grateful for financial support to the Spanish Ministerio de Educación y Ciencia (HAR2011-29654 2011–2013 and PhD Grant FPU/AP2009-2575).
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Sessa, C., Bagán, H. & García, J.F. Influence of composition and roughness on the pigment mapping of paintings using mid-infrared fiberoptics reflectance spectroscopy (mid-IR FORS) and multivariate calibration. Anal Bioanal Chem 406, 6735–6747 (2014). https://doi.org/10.1007/s00216-014-8091-2
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DOI: https://doi.org/10.1007/s00216-014-8091-2