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Chemical Qualitative Analysis II

  • Boris L. MilmanEmail author
Chapter
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Abstract

Qualitative analysis II is identification/classification/authentication of such objects as foodstuffs, products, specimens, materials, pollutions, living organisms, and others. Typical procedures of this sort are authentication of food, determination of its adulteration, oil spill identification, and that of microorganisms. Identification of an object is based on recognition of its indicative component(s), measuring ratios between several components of a sample, or fingerprinting overall sample signals. Almost all analytical techniques are applicable for the purpose, with an indispensable role for chemometrics/multivariate statistics in processing of analytical data. In the same way as in identification of individual chemical compounds, quality of identification II is assured by validation of methods, the use of reference materials, and availability of standard/valid reference data. Examples of qualitative analysis of vegetable oils, honey, wine, and some non-food samples are given.

Keywords

Honey Sample Isotopic Ratio Mass Spectrometry Electronic Tongue Diagnostic Ratio Codex Alimentarius Commission 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Milman BL (2008) Introduction to chemical identification (In Russian). VVM, Saint PetersburgGoogle Scholar
  2. 2.
    Valcárcel M, Cárdenas S, Barceló D, Buydens L, Heydorn K, Karlberg B, Klemm K, Lendl B, Milman B, Neidhart B, Ríos A, Stephany R, Townshend A, Zschunke A (2002) Metrology of qualitative chemical analysis. Report EUR 20605. EC, Luxembourg.Google Scholar
  3. 3.
    Valcárcel M, Cárdenas S, Simonet BM, Carrillo-Carrión C (2007) Principles of qualitative analysis in the chromatographic context. J Chromatogr A 1158:234–240CrossRefGoogle Scholar
  4. 4.
    Erudium Glossary. http://www.erudium.polymtl.ca/html-eng/glossaire.php#A. Accessed 5 April 2010
  5. 5.
  6. 6.
    Aparicio R, Aparicio-Ruíz R (2000) Authentication of vegetable oils by chromatographic techniques. J Chromatogr A 881:93–104CrossRefGoogle Scholar
  7. 7.
    Aparicio R, Harwood J (2000) Handbook of olive oil: analysis and properties. Aspen Publishers, GaithersburgGoogle Scholar
  8. 8.
    Baeten V, Aparicio R (2000) Edible oils and fats authentication by Fourier transform Raman spectrometry. Biotechnol Agron Soc Environ 4:196–203Google Scholar
  9. 9.
    Osborne BG (2000) Near-infrared spectroscopy in food analysis. In: Meyers RA (ed) Encyclopedia of analytical chemistry. Wiley, Chichester, http://www2.hcmuaf.edu.vn/data/phyenphuong/Near%20Infrared%20Spectroscopy%20in%20Food%20Analysis.pdf. Accessed 4 Nov 2010Google Scholar
  10. 10.
    Nollet L (2004) Food authentication by HPLC. http://www.labint-online.com/fileadmin/pdf/pdf_general/food-authentication-by-hplc.pdf. Accessed 12 June 2010
  11. 11.
    Cserhati T, Forgacs E, Deyl Z, Miksik I (2005) Chromatography in authenticity and traceability tests of vegetable oils and dairy products: a review. Biomed Chromatogr 19:183–190CrossRefGoogle Scholar
  12. 12.
    Downey G, Kelly JD (2006) Food authentication using infrared spectroscopic methods. Project RMIS No. 4907 Final report. Ashtown Food Research Centre, Dublin. http://www.teagasc.ie/research/reports/foodprocessing/4907/eopr-4907.pdf. Accessed 5 April 2010
  13. 13.
    Downey G, Kelly JD, Rodriguez CP (2006) Food authentication – has near infrared spectroscopy a role? Spectrosc Eur 18:10–14, http://www.spectroscopyeurope.com/images/stories/ArticlePDfs/NIR_18_3.pdf. Accessed 12 June 2010Google Scholar
  14. 14.
    Sadecka J, Tothova J (2007) Fluorescence spectroscopy and chemometrics in the food classification – a review. Czech J Food Sci 25:159–173Google Scholar
  15. 15.
    Mafra I, Ferreira IMPLVO, Oliveira MBPP (2008) Food authentication by PCR-based methods. Eur Food Res Technol 227:649–665CrossRefGoogle Scholar
  16. 16.
    Sun DW (2009) Infrared spectroscopy for food quality analysis and control. Academic, BurlingtonGoogle Scholar
  17. 17.
    Alishahi A, Farahmand H, Prieto N, Cozzolino D (2010) Identification of transgenic foods using NIR spectroscopy: a review. Spectrochim Acta A 75:1–7CrossRefGoogle Scholar
  18. 18.
    Nollet LML, Toldra F (2010) Handbook of dairy foods analysis. CRC Press, Boca Raton, FLGoogle Scholar
  19. 19.
    NORDTEST method NT CHEM 001, 2nd edn. Oil spill identification. http://www.nordicinnovation.net/nordtestfiler/chem001.pdf. Accessed 12 June 2010
  20. 20.
    Wang Z, Fingas M, Page DS (1999) Oil spill identification. J Chromatogr A 843:369–411CrossRefGoogle Scholar
  21. 21.
    ASTM D 5739 (2006) Standard practice for oil spill source identification by gas chromatography and positive ion electron impact low resolution mass spectrometryGoogle Scholar
  22. 22.
    Faksness LG, Weiss HM, Daling PS (2008) Revision of the Nordtest methodology for oil spill identification. SINTEF Report STF66 A02028. http://www.nordicinnovation.net/nordtestfiler/tec498.pdf. Accessed 12 June 2010
  23. 23.
    Bohaychuk VM, Gensler GE, King RK, Wu JT, McMullen LM (2005) Evaluation of detection methods for screening meat and poultry products for the presence of foodborne pathogens. J Food Prot 68:2637–2647Google Scholar
  24. 24.
    Oberreuter H, Seiler H, Scherer S (2002) Identification of coryneform bacteria and related taxa by Fourier-transform infrared (FT–IR) spectroscopy. Int J Syst Evol Microbiol 52:91–100Google Scholar
  25. 25.
    Preisner O, Lopes JA, Guiomar R, Machado J, Menezes JC (2007) Fourier transform infrared (FT–IR) spectroscopy in bacteriology: towards a reference method for bacteria discrimination. Anal Bioanal Chem 387:1739–1748CrossRefGoogle Scholar
  26. 26.
    Bruker Bacteria Identification. http://www.brukeroptics.com/bac.html. Accessed 12 June 2010
  27. 27.
    Wang Z, Dunlop K, Long SR, Li L (2002) Mass spectrometric methods for generation of protein mass database used for bacterial identification. Anal Chem 74:3174–3182CrossRefGoogle Scholar
  28. 28.
    Dworzanski JP, Snyder AP, Chen R, Zhang H, Wishart D, Li L (2004) Identification of bacteria using tandem mass spectrometry combined with a proteome database and statistical scoring. Anal Chem 76:2355–2366CrossRefGoogle Scholar
  29. 29.
    Keys CJ, Dare DJ, Sutton H, Wells G, Lunt M, McKenna T, McDowall M, Shah HN (2004) Compilation of a MALDI–TOF mass spectral database for the rapid screening and characterisation of bacteria implicated in human infectious diseases. Infect Genet Evol 4:221–242CrossRefGoogle Scholar
  30. 30.
    Dworzanski JP, Deshpande SV, Chen R, Jabbour RE, Snyder AP, Wick CH, Li L (2006) Mass spectrometry-based proteomics combined with bioinformatic tools for bacterial classification. J Proteome Res 5:76–87CrossRefGoogle Scholar
  31. 31.
    Hsieh SY, Tseng CL, Lee YS, Kuo AJ, Sun CF, Lin YH, Chen JK (2007) Highly efficient classification and identification of human pathogenic bacteria by MALDI–TOF MS. Mol Cell Proteomics 7:448–456CrossRefGoogle Scholar
  32. 32.
    Demirev PA, Fenselau C (2008) Mass spectrometry in biodefense. J Mass Spectrom 43:1441–1457CrossRefGoogle Scholar
  33. 33.
    Christensen JH (2005) Chemometrics as a tool to analyse complex chemical mixtures. Environmental forensics and fate of oil spills. PhD Thesis, Roskilde University. http://www2.dmu.dk/1_viden/2_Publikationer/3_Ovrige/rapporter/phd_jch.pdf. Accessed 12 June 2010
  34. 34.
    Golan E, Krissoff B, Kuchler F (2004) Food traceability: One ingredient in a safe and efficient food supply. http://www.ers.usda.gov/amberwaves/april04/pdf/featureFoodTraceability.pdf. Accessed 12 June 2010
  35. 35.
    Dennis MJ (1998) Recent developments in food authentication. Analyst 123:151R–156RCrossRefGoogle Scholar
  36. 36.
    Ghidini S, Ianieri A, Zanardi E, Conter M, Boschetti T, Iacumin P, Bracchi PG (2006) Stable isotopes determination in food authentication: a review. Ann Fac Medic Vet di Parma 26:193–204, http://www.unipr.it/arpa/facvet/annali/2006/193_204.pdf. Accessed 12 June 2010Google Scholar
  37. 37.
    Guy PA, Fenaille F (2006) Contribution of mass spectrometry to assess quality of milk-based products. Mass Spectrom Rev 25:290–326CrossRefGoogle Scholar
  38. 38.
    Sun DW (2008) Modern techniques for food authentication. Academic, BurlingtonGoogle Scholar
  39. 39.
    Fauhl C, Reniero F, Guillou C (2000) 1H NMR as a tool for the analysis of mixtures of virgin olive oil with oils of different botanical origin. Magn Reson Chem 38:436–443CrossRefGoogle Scholar
  40. 40.
    Ogrinc N, Košir IJ, Spangenberg JE, Kidrič J (2003) The application of NMR and MS methods for detection of adulteration of wine, fruit juices, and olive oil. A review. Anal Bioanal Chem 376:424–430CrossRefGoogle Scholar
  41. 41.
    Vigli G, Philippidis A, Spyros A, Dais P (2003) Classification of edible oils by employing 31P and 1H NMR spectroscopy in combination with multivariate statistical analysis. A proposal for the detection of seed oil adulteration in virgin olive oils. J Agric Food Chem 51:5715–5722CrossRefGoogle Scholar
  42. 42.
    Goodacre R, Kell DB (1996) Pyrolysis mass spectrometry and its applications in biotechnology. Curr Opin Biotechnol 7:20–28CrossRefGoogle Scholar
  43. 43.
    Ellis DI, Dunn WB, Griffin JL, Allwood JW, Goodacre R (2007) Metabolic fingerprinting as a diagnostic tool. Pharmacogenomics 8:1243–1266CrossRefGoogle Scholar
  44. 44.
    Eggins BR (2002) Chemical sensors and biosensors. Wiley, ChichesterGoogle Scholar
  45. 45.
    Cosio MS, Ballabio D, Benedetti S, Gigliotti C (2006) Geographical origin and authentication of extra virgin olive oils by an electronic nose in combination with artificial neural networks. Anal Chim Acta 567:202–210CrossRefGoogle Scholar
  46. 46.
    Vlasov Y, Legin A, Rudnitskaya A, Di Natale C, D'Amico A (2005) Nonspecific sensor arrays (“electronic tongue”) for chemical analysis of liquids. Pure Appl Chem 77:1965–1983CrossRefGoogle Scholar
  47. 47.
    Karoui R, De Baerdemaeker J (2007) A review of the analytical methods coupled with chemometric tools for the determination of the quality and identity of dairy products. Food Chem 102:621–640CrossRefGoogle Scholar
  48. 48.
    Arvanitoyannis IS, Chalhoub C, Gotsiou P, Lydakis-Simantiris N, Kefalas P (2005) Novel quality control methods in conjunction with chemometrics (multivariate analysis) for detecting honey authenticity. Crit Rev Food Sci Nutr 45:193–203CrossRefGoogle Scholar
  49. 49.
    Comission regulation (EEC) No 2568/91 of 11 July 1991 on the characteristics of olive oil and olive-residue oil and on the relevant methods of analysis (1991). Off J L 248:1–112. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CONSLEG:1991R2568:20080101:EN:PDF. Accessed 4 Nov 2010
  50. 50.
    Commission Regulation (EC) No 656/95 of 28 March 1995 amending Regulation (EEC) No 2568/91 on the characteristics of olive oil and olive-residue oil and on the relevant methods of analysis and Council Regulation (EEC) No 2658/87 on the tariff and statistical nomenclature and on the Common Customs Tariff (1995) Off J L 069:1–12. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:31995R0656:EN:HTML. Accessed 4 Nov 2010
  51. 51.
    FAO/WHO Food Standards. Codex Alimentarius. http://www.codexalimentarius.net/web/index_en.jsp#. Accessed 13 June 2010
  52. 52.
    ASTM Standards and Engineering Digital Library. http://www.astm.org/DIGITAL_LIBRARY/index.shtml. Accessed 13 June 2010
  53. 53.
    Official Methods of Analysis of AOAC International, 18th edn (2005, revis 2006) AOAC, Gaithersburg. Ch. 37:21–22, 33–37, Ch. 44:33–36, 38–39Google Scholar
  54. 54.
    Latorre MJ, Peña R, García S, Herrero C (2000) Authentication of Galician (N.W. Spain) honeys by multivariate techniques based on metal content data. Analyst 125:307–312CrossRefGoogle Scholar
  55. 55.
    Roussel S, Bellon-Maurel V, Roger JM, Grenier P (2003) Fusion of aroma, FT–IR and UV sensor data based on the Bayesian inference. Application to the discrimination of white grape varieties. Chemom Intell Lab Syst 65:209–219CrossRefGoogle Scholar
  56. 56.
    Ruoff K, Luginbühl W, Künzli R, Bogdanov S, Bosset JO, Von der Ohe K, Von der Ohe W, Amado R (2006) Authentication of the botanical and geographical origin of honey by front-face fluorescence spectroscopy. J Agric Food Chem 54:6858–6866CrossRefGoogle Scholar
  57. 57.
    Toher D, Downey G, Murphy TB (2007) A comparison of model-based and regression classification techniques applied to near infrared spectroscopic data in food authentication studies. Chemom Intell Lab Syst 89:102–115CrossRefGoogle Scholar
  58. 58.
    Downey G (1998) Food and food ingredient authentication by mid-infrared spectroscopy and chemometrics. Trends Anal Chem 17:418–424CrossRefGoogle Scholar
  59. 59.
    ASTM E 1790 (2000) Standard practice for near infrared qualitative analysisGoogle Scholar
  60. 60.
    Downey G, Fouratier V, Kelly JD (2003) Detection of honey adulteration by addition of fructose and glucose using near infrared transflectance spectroscopy. J Near Infrared Spectrosc 11:447–456CrossRefGoogle Scholar
  61. 61.
    Corbella E, Cozzolino D (2005) The use of visible and near infrared spectroscopy to classify the floral origin of honey samples produced in Uruguay. J Near Infrared Spectrosc 13:63–68CrossRefGoogle Scholar
  62. 62.
    FDA Center for Veterinary Medicine Guidance for Industry Guidance for Industry. Bioanalytical Method Validation (2001). http://www.docstoc.com/docs/24786912/Bioanalytical-method-validation. Accessed 13 June 2010
  63. 63.
    Milman BL (2005) Towards a full reference library of MSn spectra. Testing of a library containing 3126 MS2 spectra of 1743 compounds. Rapid Commun Mass Spectrom 19:2833–2839CrossRefGoogle Scholar
  64. 64.
    Milman BL, Zhurkovich IK (2009) Tandem mass spectral library of pesticides and its use in identification. Proceedings of the 18th International Mass Spectrometry Conference, BremenGoogle Scholar
  65. 65.
    Saiz-Abajo MJ, Gonzales-Saiz JM, Pizarro C (2004) Classification of wine and alcohol vinegar samples based on near-infrared spectroscopy. Feasibility study on the detection of adulterated vinegar samples. J Agric Food Chem 52:7711–7719CrossRefGoogle Scholar
  66. 66.
    Aparicio R Chemometrics as an aid in olive oil authentication. http://www.eurofedlipid.org/divisions/oliveoil/chemometrics.pdf. Accessed 13 June 2010
  67. 67.
    Sharpless KE, Thomas JB, Christopher SJ, Greenberg RR, Sander LC, Schantz MM, Welch MJ, Wise SA (2007) Standard reference materials for foods and dietary supplements. Anal Bioanal Chem 389:171–178CrossRefGoogle Scholar
  68. 68.
    Wang Z, Hollebone B, Yang C, Fingas M, Landriault M. Source identification of an unknown spill (2002) from Quebec by the multi-criterion analytical approach and lab simulation of the spill sample. http://www.iosc.org/papers/IOSC%202005%20a157.pdf. Accessed 13 June 2010
  69. 69.
    Lísa M, Holčapek M (2008) Triacylglycerols profiling in plant oils important in food industry, dietetics and cosmetics using high-performance liquid chromatography-atmospheric pressure chemical ionization mass spectrometry. J Chromatogr A 1198–1199:115–130Google Scholar
  70. 70.
    Wang Z, Yang C, Hollebone B, Brown C, Landriault M. Source identification of spilled diesel using diagnostic sesquiterpanes and diamondoids. http://www.iosc.org/papers/2008%20051.pdf. Accessed 13 June 2010
  71. 71.
    Kelly S (2007) The development of methods to determine the geographical origin of poultry. UK Food Standards Agency Report Q01086. http://www.foodbase.org.uk/admintools/reportdocuments/268-1-489_Q01086%5BIFR%5D_GEOPOULTRY_Final_Report.pdf. Accessed 13 June 2010
  72. 72.
    Hu P, Liang QL, Luo GA, Zhao ZZ, Jiang ZH (2005) Multi-component HPLC fingerprinting of Radix Salviae Miltiorrhizae and its LC–MS–MS identification. Chem Pharm Bull 53:677–683CrossRefGoogle Scholar
  73. 73.
    Jung J, Jaufmann T, Hener U, Münch A, Kreck M, Dietrich H, Mosandl A (2006) Progress in wine authentication: GC–C/P–IRMS measurements of glycerol and GC analysis of 2, 3-butanediol stereoisomers. Eur Food Res Technol 223:811–820CrossRefGoogle Scholar
  74. 74.
    Phillips KM, Wolf WR, Patterson KY, Sharpless KE, Amanna KR, Holden JM (2007) Summary of reference materials for the determination of the nutrient composition of foods. Accred Qual Assur 12:126–133CrossRefGoogle Scholar
  75. 75.
    INFOODS. http://www.fao.org/infoods/index_en.stm. Accessed 13 June 2010
  76. 76.
    Merchant AT, Dehghan M (2006) Food composition database development for between country comparisons. Nutr J 5:2. doi: 10.1186/1475-2891-5-2 CrossRefGoogle Scholar
  77. 77.
    USDA Agricultural Research Service. Nutrient Data Laboratory. http://www.ars.usda.gov/main/site_main.htm?modecode=12-35-45-00. Accessed 13 June 2010
  78. 78.
    Speight JC (1999) The chemistry and technology of petroleum, 3rd edn. Marcel Dekker, New YorkCrossRefGoogle Scholar
  79. 79.
    Ulberth F, Buchgraber M (2000) Authenticity of fats and oils. Eur J Lipid Sci Technol 102:687–694CrossRefGoogle Scholar
  80. 80.
    Peña F, Cárdenas S, Gallego M, Valcárcel M (2005) Direct olive oil authentication: detection of adulteration of olive oil with hazelnut oil by direct coupling of headspace and mass spectrometry, and multivariate regression techniques. J Chromatogr A 1074:215–221CrossRefGoogle Scholar
  81. 81.
    Buchgraber M, Ulberth F, Emons H, Anklam E (2004) Triacylglycerol profiling by using chromatographic techniques. Eur J Lipid Sci Technol 106:621–648CrossRefGoogle Scholar
  82. 82.
    Lee PJ, Di Gioia AJ (2009) Rapid seed oil analysis using UPLC for quality control and authentication. Lipid Technol 21:112–115CrossRefGoogle Scholar
  83. 83.
    Flamini R, Panighel A (2006) Mass spectrometry in grape and wine chemistry II: The consumer protection. Mass Spectrom Rev 25:741–774CrossRefGoogle Scholar
  84. 84.
    Cozzolino D, Cynkar WU, Shah N, Dambergs RG, Smith PA (2009) A brief introduction to multivariate methods in grape and wine analysis. Int J Wine Res 2009:123–130CrossRefGoogle Scholar
  85. 85.
    Fauhl-Hassek C (2009) Trends in wine authentication. Bull de l'OIV 82:93–100Google Scholar
  86. 86.
    Siret R, Boursiquot JM, Merle MH, Cabanis JC, This P (2000) Toward the authentication of varietal wines by the analysis of grape (Vitis vinifera L.) residual DNA in must and wine using microsatellite markers. J Agric Food Chem 48:5035–5040CrossRefGoogle Scholar
  87. 87.
    Downey G, Briandet R, Wilson RH, Kemsley EK (1997) Near- and mid-infrared spectroscopies in food authentication: coffee varietal identification. J Agric Food Chem 45:4357–4361CrossRefGoogle Scholar
  88. 88.
    Hanneguella S, Thibault JN, Naulet N, Martin GJ (1992) Authentication of essential oils containing linalool and linalyl acetate by isotopic methods. J Agric Food Chem 40:81–87CrossRefGoogle Scholar
  89. 89.
    Molkentin J (2009) Authentication of organic milk using δ13C and the α-linolenic acid content of milk fat. J Agric Food Chem 57:785–790CrossRefGoogle Scholar
  90. 90.
    Engelhardt UH (2007) Authenticity of tea (C. sinensis) and tea products. ACS Symp Ser 952:138–146CrossRefGoogle Scholar
  91. 91.
    Wang Z, Stout SA, Fingas M (2006) Forensic fingerprinting of biomarkers for oil spill characterization and source identification. Environ Forensics 7:105–146CrossRefGoogle Scholar
  92. 92.
    Yang C, Wang Z, Hollebone B, Brown CE, Landriault M. Application of statistical analysis in the selection of diagnostic ratios for forensic identification of an oil spill source. http://www.iosc.org/papers/2008%20052.pdf. Accessed 13 June 2010
  93. 93.
    Gaines R, Hall G, Frysinger G, Gronlund W, Juaire K (2006) Chemometric determination of target compounds used to fingerprint unweathered diesel fuels. Environ Forensics 7:77–87CrossRefGoogle Scholar
  94. 94.
    Lay JO, Borgmann S, Liyanage R, Wilkins CL (2006) Problems with the “omics”. Trends Anal Chem 25:1046–1056CrossRefGoogle Scholar
  95. 95.
    Roy SM, Becker CH (2007) Quantification of proteins and metabolites by mass spectrometry without isotopic labeling. Methods Mol Biol 359:87–105CrossRefGoogle Scholar
  96. 96.
    Dunn WB, Bailey NJC, Johnson HE (2005) Measuring the metabolome: current analytical technologies. Analyst 130:606–625CrossRefGoogle Scholar
  97. 97.
    Idborg H, Zamani L, Edlund PO, Schuppe-Koistinen I, Jacobsson SP (2005) Metabolic fingerprinting of rat urine by LC/MS Part 2. Data pretreatment methods for handling of complex data. J Chromatogr B 828:14–20CrossRefGoogle Scholar
  98. 98.
    Hilario M, Kalousis A, Pellegrini C, Müller M (2006) Processing and classification of protein mass spectra. Mass Spectrom Rev 25:409–449CrossRefGoogle Scholar
  99. 99.
    Kind T, Tolstikov V, Fiehn O, Weiss RH (2007) A comprehensive urinary metabolomic approach for identifying kidney cancer. Anal Biochem 363:185–195CrossRefGoogle Scholar
  100. 100.
    Styczynski MP, Moxley JF, Tong LV, Walther JL, Jensen KL, Stephanopoulos GN (2007) Systematic identification of conserved metabolites in GC/MS data for metabolomics and biomarker discovery. Anal Chem 79:966–973CrossRefGoogle Scholar
  101. 101.
    Ramautar R, Somsen GW, De Jong GJ (2009) CE–MS in metabolomics. Electrophoresis 30:276–291CrossRefGoogle Scholar
  102. 102.
    Clark RJH (2002) Pigment identification by spectroscopic means: an arts/science interface. C R Chimie 5:7–20CrossRefGoogle Scholar
  103. 103.
    Zadrożna I, Połeć-Pawlak K, Głuch I, Ackacha MA, Mojski M, Witowska-Jarosz J, Jarosz M (2003) Old master paintings – A fruitful field of activity for analysts: Targets, methods, outlook. J Sep Sci 26:996–1004CrossRefGoogle Scholar
  104. 104.
    Olsen BA, Borer MW, Perry FM, Forbes RA (2002) Screening for counterfeit drugs using near-infrared spectroscopy. Pharm Technol 26:62–71Google Scholar
  105. 105.
    MacCrehan WA, Smith KD, Rowe WF (1998) Sampling protocols for the detection of smokeless powder residues using capillary electrophoresis. J Forensic Sci 43:119–124Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.D.I. Mendeleyev Inst. for Metrology (VNIIM) and Cent. for Ecol. Saf. of Russ. Acad. of SciencesSt. PetersburgRussia

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