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Reliability and Errors of Identification

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Chemical Identification and its Quality Assurance

Abstract

In this chapter, approaches to estimating reliability and errors of detection and identification are considered. Related terminology is presented; reliability of identification is defined as a probability of its true result. False results are demonstrated to be attributes of determination of low analyte amounts by screening methods. Formulas for calculating rates of true and false, positive and negative results are given. The rates are derived both from tests using analytical standards (blank samples) and upon verification of screening results by confirmatory methods/techniques. A replication of analytical determinations is also considered, including Bayesian statistics. Limit characteristics of detection and identification are treated.

It is noted that confirmatory methods based on spectrometry must be free of identification errors. Nevertheless, errors occur if methods are non-targeted, invalidated, or ad hoc. True and false results obtained with use of spectral techniques are discussed in terms of matching spectra. A best/good or poor matching resulting in a high or low match factor means a good/fair or poor chance respectively of accepting an identification hypothesis. Different match factors calculated in mass spectrometry and also NMR, IR-, and UV–V is spectroscopy are outlined, with many details with regard to searches in reference spectral libraries. Further, a probability interpretation of match factors is considered, which is essential for identification of peptides and proteins in proteomics. Other approaches to deriving a probability of identification from analytical/spectral data are also noted. This kind of probability, as well as the reported result of identification, can be expressed in words.

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Notes

  1. 1.

    I.e., specificity is 100% selectivity.

  2. 2.

    This is

    the minimum concentration or mass of the analyte that can be quantified with acceptable accuracy and precision [60]

    The limit of quantification in such definition is close to the concept of minimum required performance limit (MRPL), i.e.,

    … minimum content of an analyte in a sample, which at least has to be detected and confirmed [44].

    Modern MRPL values, e.g., setting for pharmaceutical residues in animal products are very low at 0.3–1.0 μg/kg [61].

    There is another synonymic term for low limit amount which can be measured. It is lowest calibrated level:

    the lowest concentration (or mass) of analyte with which the determination system is successfully calibrated… [60]

References

  1. Milman BL, Konopelko LA (2000) Identification of chemical substances by testing and screening of hypotheses. I. General. Fresenius J Anal Chem 367:621–628

    Article  CAS  Google Scholar 

  2. Ellison SLR, Fearn T (2005) Characterising the performance of qualitative analytical methods: Statistics and terminology. Trends Anal Chem 24:468–476

    Article  CAS  Google Scholar 

  3. Bethem R, Boison J, Gale J, Heller D, Lehotay S, Loo J, Musser S, Price P, Stein S (2003) Establishing the fitness for purpose of mass spectrometric methods. J Am Soc Mass Spectrom 14:528–541

    Article  CAS  Google Scholar 

  4. Milman BL (2008) Introduction to chemical identification (In Russian). VVM, Saint Petersburg

    Google Scholar 

  5. Google Scholar. http://scholar.google.com. Accessed 14 Oct 2009.

  6. Spiehler VR, O'Donnell CM, Gokhale DV (1988) Confirmation and certainty in toxicology screening. Clin Chem 34:1535–1539

    CAS  Google Scholar 

  7. Ferrara SD, Tedeschi L, Frison G, Brusini G, Castagna F, Bernardelli B, Soregaroli D (1994) Drugs-of-abuse testing in urine: statistical approach and experimental comparison of immunochemical and chromatographic techniques. J Anal Toxicol 18:278–291

    Article  CAS  Google Scholar 

  8. Ellison SLR, Gregory S, Hardcastle WA (1998) Quantifying uncertainty in qualitative analysis. Analyst 123:1155–1161

    Article  CAS  Google Scholar 

  9. McLafferty FW, Stauffer DA, Loh SY, Wesdemiotis C (1999) Unknown identification using reference mass spectra. Quality evaluation of databases. J Am Soc Mass Spectrom 10:1229–1240

    Article  CAS  Google Scholar 

  10. Fawcett T (2006) An introduction to ROC analysis. Pattern Recognit Lett 27:861–874

    Article  Google Scholar 

  11. Nesvizhskii AI, Vitek O, Aebersold R (2007) Analysis and validation of proteomic data generated by tandem mass spectrometry. Nat Methods 4:787–797

    Article  CAS  Google Scholar 

  12. Lloyd E (1984) Handbook of applicable mathematics. Wiley, Chichester

    Google Scholar 

  13. ASTM E 1828 (1996) Standard guide for evaluating the performance characteristics of qualitative chemical spot test kits for lead in paint

    Google Scholar 

  14. Mil'man BL, Konopel'ko LA (2004) Uncertainty of qualitative chemical analysis: general methodology and binary test methods. J Anal Chem 59:1128–1141

    Article  Google Scholar 

  15. Sensitivity in metrology and analytical chemistry. In: IUPAC Gold Book. http://goldbook.iupac.org/S05606.html. Accessed 11 May 2010

  16. Detection limit in analysis. In: IUPAC Gold Book. http://goldbook.iupac.org/D01629.html. Accessed 11 May 2010

  17. Specific in analysis. In: IUPAC Gold Book. http://goldbook.iupac.org/S05788.html. Accessed 11 May 2010

  18. Song R, Schlecht PC, Ashley K (2001) Field screening test methods: performance criteria and performance characteristics. J Hazard Mater 83:29–39

    Article  CAS  Google Scholar 

  19. Dietzen DJ, Ecos K, Friedman D, Beason S (2001) Positive predictive values of abused drug immunoassays on the Beckman Synchron in a veteran population. J Anal Toxicol 25:174–178

    Article  CAS  Google Scholar 

  20. Jehanli A, Brannan S, Moore L, Spiehler VR (2001) Blind trials of an onsite saliva drug test for marijuana and opiates. J Forensic Sci 46:1214–1220

    CAS  Google Scholar 

  21. Kadehjian LJ (2001) Performance of five non-instrumented urine drug-testing devices with challenging near-cutoff specimens. J Anal Toxicol 25:670–679

    Article  CAS  Google Scholar 

  22. Crouch DJ, Hersch RK, Cook RF, Frank JF, Walsh JM (2002) A field evaluation of five on-site drug-testing devices. J Anal Toxicol 26:493–499

    Article  CAS  Google Scholar 

  23. Miki A, Katagi M, Tsuchihashi H (2002) Application of EMIT(R) d.a.u. (TM) for the semiquantitative screening of methamphetamine incorporated in hair. J Anal Toxicol 26:274–279

    Article  CAS  Google Scholar 

  24. Cone EJ, Sampson-Cone AH, Darwin WD, Huestis MA, Oyler JM (2003) Urine testing for cocaine abuse: metabolic and excretion patterns following different routes of administration and methods for detection of false-negative results. J Anal Toxicol 27:386–401

    Article  CAS  Google Scholar 

  25. Ashley K, Fischbach TJ, Song R (1996) Evaluation of a chemical spot-test kit for the detection of airborne particulate lead in the workplace. Am Ind Hyg Assoc J 57:161–165

    Article  CAS  Google Scholar 

  26. Ashley K, Hunter M, Tait LH, Dozier J, Seaman JL, Berry PF (1998) Field investigation of on-site techniques for the measurement of lead in paint films. Field Anal Chem Technol 2:39–50

    Article  CAS  Google Scholar 

  27. García-González DL, Viera M, Tena N, Aparicio R (2007) Evaluation of the methods based on triglycerides and sterols for the detection of hazelnut oil in olive oil. Grasas Aceites 58:344–350

    Google Scholar 

  28. Schepers PGAM, Franke JP, De Zeeuw RA (1983) System evaluation and substance identification in systematic toxicological analysis by the mean list length approach. J Anal Toxicol 7:272–278

    Article  CAS  Google Scholar 

  29. Porter SEG, Stoll DR, Paek C, Rutan SC, Carr PW (2006) Fast gradient elution reversed-phase liquid chromatography with diode-array detection as a high-throughput screening method for drugs of abuse. II. Data analysis. J Chromatogr A 1137:163–172

    Article  CAS  Google Scholar 

  30. Cech NB, Enke CG (2001) Practical implications of some recent studies in electrospray ionization fundamentals. Mass Spectrom Rev 20:362–387

    Article  CAS  Google Scholar 

  31. Milman BL, Alfassi ZB (2005) Detection and identification of cations and anions of ionic liquids by means of electrospray ionization mass spectrometry and tandem mass spectrometry. Eur J Mass Spectrom 11:35–42

    Article  CAS  Google Scholar 

  32. 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 

  33. Ríos A, Barceló D, Buydens L, Cárdenas S, Heydorn K, Karlberg B, Klemm K, Lendl B, Milman B, Neidhart B, Stephany R, Townshend A, Valcárcel M, Zschunke A (2003) Quality assurance of qualitative analysis in the framework of ‘MEQUALAN’ European project. Accred Qual Assur 8:68–77

    Article  Google Scholar 

  34. Pulido A, Ruisánchez I, Boqué R, Rius FX (2003) Uncertainty of results in routine qualitative analysis. Trends Anal Chem 22:647–654

    Article  CAS  Google Scholar 

  35. Plata MR, Pérez-Cejuela N, Rodríguez J, Ríos Á (2005) Development and validation strategies for qualitative spot tests: application to nitrite control in waters. Anal Chim Acta 537:223–230

    Article  CAS  Google Scholar 

  36. Garrido Frenich A, González-Rodríguez MJ, Arrebola FJ, Martínez Vidal JL (2005) Potentiality of gas chromatography–triple quadrupole mass spectrometry in vanguard and rearguard methods of pesticide residues in vegetables. Anal Chem 77:4640–4648

    Article  Google Scholar 

  37. Komar’ NP (1955) Basics of qualitative chemical analysis. Book 1: Ionic equilibria (In Russian). Kharkov University Publisher, Kharkov

    Google Scholar 

  38. Trullols E, Ruisánchez I, Ruis FX (2004) Validation of qualitative analytical methods. Trends Anal Chem 23:137–145

    Article  CAS  Google Scholar 

  39. Panteleimonov AV, Nikitina NA, Reshetnyak EA, Loginova LP, Bugaevskii AA, Kholin YV (2008) Binary response procedures of qualitative analysis: metrological characteristics and calculation aspects (In Russian). Methods Objects Chem Anal 3:128–146, http://www.nbuv.gov.ua/portal/Chem_Biol/moca/2006_2008/pdf/03022008-128.pdf. Accessed 27 Oct 2010

    Google Scholar 

  40. Kholin YV, Nikitina NA, Panteleimonov AV, Reshetnyak EA, Bugaevskii AA, Loginova LP (2008) Metrological characteristics of binary response qualitative methods (In Russian). Timchenko, Kharkov

    Google Scholar 

  41. ISO Standard 11843-1 (1997) Capability of detection. Part 1: Terms and definitions.

    Google Scholar 

  42. Antignac JP, Le Bizec B, Monteau F, Andre F (2003) Validation of analytical methods based on mass spectrometric detection according to the “2002/657/EC” European decision: guideline and application. Anal Chim Acta 483:325–334

    Article  CAS  Google Scholar 

  43. Currie LA (1995) Nomenclature in evaluation of analytical methods, including detection and quantification capabilities (IUPAC Recommendations 1995). Pure Appl Chem 67:1699–1723

    Article  CAS  Google Scholar 

  44. Commission Decision 2002/657/EC, August 12, 2002, implementing Council Directive 96/23/EC concerning the performance of analytical methods and interpretation of results (2002) Off J Eur Commun L 221:8-36. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2002:221:0008:0036:EN:PDF. Accessed 14 May 2010.

  45. ISO Standard 11843-2 (2000) Capability of detection. Part 2: Methodology in the linear calibration case

    Google Scholar 

  46. ISO Standard 11843-4 (2003) Capability of detection. Part 4: Methodology for comparing the minimum detectable value with a given value

    Google Scholar 

  47. DIN 32645:2008-11 (2008) Chemische Analytik – Nachweis-, Erfassungs- und Bestimmungsgrenze unter Wiederholbedingungen – Begriffe, Verfahren, Auswertung. http://www.beuth.de/langanzeige/DIN+32645/110729574.html. Accessed 14 May 2010

  48. Brüggemann L, Morgenstern P, Wennrich R (2010) Comparison of international standards concerning the capability of detection for analytical methods. Accred Qual Assur 15:99–104

    Article  Google Scholar 

  49. Vinci F, Guadagnuolo G, Danese V, Salini M, Serpe L, Gallo P (2005) In-house validation of a liquid chromatography/electrospray tandem mass spectrometry method for confirmation of chloramphenicol residues in muscle according to Decision 2002/657/EC. Rapid Commun Mass Spectrom 19:3349–3355

    Article  CAS  Google Scholar 

  50. Verdon E, Hurtaud-Pessel D, Sanders P (2006) Evaluation of the limit of performance of an analytical method based on a statistical calculation of its critical concentrations according to ISO standard 11843: Application to routine control of banned veterinary drug residues in food according to European Decision 657/2002/EC. Accred Qual Assur 11:58–62

    Article  CAS  Google Scholar 

  51. Rodríguez N, Cruz Ortiz M, Herrero A, Sarabia LA (2007) Performance characteristics according to Commission Decision 2002/657/EC in the fluorimetric determination of tetracycline in the absence and in the presence of magnesium. Luminescence 22:518–526

    Article  Google Scholar 

  52. Samanidou VF, Nisyriou SA, Papadoyannis IN (2007) Development and validation of an HPLC method for the determination of penicillin antibiotics residues in bovine muscle according to the European Union Decision 2002/657/EC. J Sep Sci 30:3193–3201

    Article  CAS  Google Scholar 

  53. Samanidou VF, Nikolaidou KI, Papadoyannis IN (2007) Development and validation of an HPLC confirmatory method for the determination of seven tetracycline antibiotics residues in milk according to the European Union Decision 2002/657/E. J Sep Sci 30:2430–2439

    Article  CAS  Google Scholar 

  54. Christodoulou EA, Samanidou VF (2007) Multiresidue HPLC analysis of ten quinolones in milk after solid phase extraction: Validation according to the European Union Decision 2002/657/EC. J Sep Sci 30:2421–2429

    Article  CAS  Google Scholar 

  55. Resano M, Garcia-Ruiz E, Aramendia M, Belarra MA (2005) Solid sampling-graphite furnace atomic absorption spectrometry for Hg monitoring in soils. Performance as a quantitative and as a screening method. J Anal At Spectrom 20:1374–1380

    Article  CAS  Google Scholar 

  56. Aybar-Muñoz J, Fernández-González E, García-Ayuso LE, González-Casado A, Cuadros-Rodríguez L (2005) Semiqualitative method for detection of pesticide residues over established limits in vegetables by use of GC-μECD and GC-(EI)MS. Chromatography 61:505–513

    Article  Google Scholar 

  57. Lehotay SJ, Mastovska K, Amirav A, Fialkov AB, Martos PA, de Kok A, Fernández-Alba AR (2008) Identification and confirmation of chemical residues in food by chromatography-mass spectrometry and other techniques. Trends Anal Chem 27:1070–1090

    Article  CAS  Google Scholar 

  58. ISO Standard 22892 (2006) Soil quality – Guidelines for the identification of target compounds by gas chromatography and mass spectrometry.

    Google Scholar 

  59. Stolker AAM, Linders SHMA, Van Ginkel LA, Brinkman UAT (2004) Application of the revised EU criteria for the confirmation of anabolic steroids in meat using GC–MS. Anal Bioanal Chem 378:1313–1321

    Article  CAS  Google Scholar 

  60. Method validation and quality control procedures for pesticide residues analysis in food and feed (2009) Document No. SANCO/10684/2009. http://ec.europa.eu/food/plant/protection/resources/qualcontrol_en.pdf. Accessed 14 May 2010

  61. Commission Decision 2003/181/EC, March 13, 2003, amending Decision 2002/657/EC as regards the setting of minimum required performance limits (MRPLs) for certain residues in food of animal origin Off J Eur Commun L 71:17–18. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:071:0017:0018:EN:PDF. Accessed 14 May 2010

  62. Impurities Testing Guideline: Impurities in New Drug Substances (2006) ICH Topic Q 3 B (R2). European Medicines Agency. http://www.ema.europa.eu/pdfs/human/ich/273899en.pdf. Accessed 14 May 2010

  63. Grace WR Material Safety Data Sheet. Product Name: ADVA 190. http://www.na.graceconstruction.com/concrete/download/ADVA%20190%20D-06621%20_Q_.pdf. Accessed 14 May 2010

  64. Savitski MM, Nielsen ML, Zubarev RA (2007) Side-chain losses in electron capture dissociation to improve peptide identification. Anal Chem 79:2296–2302

    Article  CAS  Google Scholar 

  65. Olsen BA, Borer MW, Perry FM, Forbes RA (2002) Screening for counterfeit drugs using near-infrared spectroscopy. Pharm Technol June: 62, 64, 66, 68, 70–71, 95. http://pharmtech.findpharma.com/pharmtech/data/articlestandard/pharmtech/222002/20241/article.pdf. Accessed 14 May 2010

  66. Bodis R (2007) Quantification of spectral similarity: towards automatic spectra verification. Dissertation ETH 17361, Zürich. http://e-collection.ethbib.ethz.ch/eserv/eth:29907/eth-29907-02.pdf. Accessed 15 May 2010

  67. McLafferty FW, Stauffer DB (1985) Retrieval and interpretative computer programs for mass spectrometry. J Chem Inf Comput Sci 25:245–252

    Article  CAS  Google Scholar 

  68. McLafferty FW, Tureĉek F (1993) Interpretation of mass spectra. University Science Book, Sausalito, CA

    Google Scholar 

  69. MassLab Version 1.2 User Guide (1993). VG Organic SD 001126

    Google Scholar 

  70. Stein SE, Scott DR (1994) Optimization and testing of mass spectral library search algorithms for compound identification. J Am Soc Mass Spectrom 5:859–866

    Article  CAS  Google Scholar 

  71. Milman BL, Kovrizhnych MA, Konopelko LA (1999) Identification of chemical substances in analytical measurements. Accred Qual Assur 4:185–190

    Article  CAS  Google Scholar 

  72. Wan KX, Vidavsky I, Gross ML (2002) Comparing similar spectra: from similarity index to spectral contrast angle. J Am Soc Mass Spectrom 13:85–88

    Article  CAS  Google Scholar 

  73. Stein SE (1999) An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J Am Soc Mass Spectrom 10:770–781

    Article  CAS  Google Scholar 

  74. Takegawa Y, Deguchi K, Ito S, Yoshioka S, Sano A, Yoshinari K, Kobayashi K, Nakagawa H, Monde K, Nishimura S (2004) Assignment and quantification of 2-aminopyridine derivatized oligosaccharide isomers coeluted on reversed-phase HPLC/MS by MSn spectral library. Anal Chem 76:7294–7303

    Article  CAS  Google Scholar 

  75. Kameyama A, Kikuchi N, Nakaya S, Ito H, Sato T, Shikanai T, Takahashi Y, Takahashi K, Narimatsu H (2005) A strategy for identification of oligosaccharide structures using observational multistage mass spectral library. Anal Chem 77:4719–4725

    Article  CAS  Google Scholar 

  76. Zhang H, Singh S, Reinhold VN (2005) Congruent strategies for carbohydrate sequencing. 2. FragLib: an MSn spectral library. Anal Chem 77:6263–6270

    Article  CAS  Google Scholar 

  77. Oberacher H, Pavlic M, Libiseller K, Schubert B, Sulyok M, Schuhmacher R, Csaszar E, Köfeler HC (2009) On the inter-instrument and the inter-laboratory transferability of a tandem mass spectral reference library: 2 Optimization and characterization of the search algorithm. J Mass Spectrom 44:494–502

    Article  CAS  Google Scholar 

  78. Kinter M, Sherman NE (2000) Protein sequencing and identification using tandem mass spectrometry. Wiley, New York

    Book  Google Scholar 

  79. Aebersold R, Goodlett DR (2001) Mass spectrometry in proteomics. Chem Rev 101:269–295

    Article  CAS  Google Scholar 

  80. Sechi S (2007) Quantitative proteomics by mass spectrometry. Humana Press, Totowa, NJ

    Book  Google Scholar 

  81. Mascot Scoring Schemes. http://www.matrixscience.com/help/scoring_help.html. Accessed 15 May 2010

  82. Cottrell J. Database searching for protein identification and characterization. http://www.matrixscience.com/pdf/asms_tutorial_2005.pdf. Accessed 15 May 2010

  83. Mascot Search Fields. Instrument. http://www.matrixscience.com/help/search_field_help.html#INSTRUMENT . Accessed 15 May 2010

  84. Tabb DL, MacCoss MJ, Wu CC, Anderson SD, Yates JR (2003) Similarity among tandem mass spectra from proteomic experiments: detection, significance, and utility. Anal Chem 75:2470–2477

    Article  CAS  Google Scholar 

  85. Craig R, Cortens JC, Fenyo D, Beavis RC (2006) Using annotated peptide mass spectrum libraries for protein identification. J Proteome Res 5:1843–1849

    Article  CAS  Google Scholar 

  86. Lam H, Deutsch EW, Eddes JS, Eng JK, King N, Stein SE, Aebersold R (2007) Development and validation of a spectral library searching method for peptide identification from MS/MS. Proteomics 7:655–667

    Article  CAS  Google Scholar 

  87. Liu J, Bell AW, Bergeron JJM, Yanofsky CM, Carrillo B, Beaudrie CEH, Kearney RE (2007) Methods for peptide identification by spectral comparison. Proteome Sci 5:3. doi:10.1186/1477-5956-5-3

    Article  Google Scholar 

  88. Yates JR, Morgan SF, Gatlin CL, Griffin PR, Eng JK (1998) Method to compare collision-induced dissociation spectra of peptides: potential for library searching and subtractive analysis. Anal Chem 70:3557–3565

    Article  CAS  Google Scholar 

  89. Golotvin SS, Vodopianov E, Lefebvre BA, Williams AJ, Spitzer TD (2006) Automated structure verification based on 1H NMR Prediction. Magn Reson Chem 44:524–538

    Article  CAS  Google Scholar 

  90. Golotvin SS, Vodopianov E, Pol R, Lefebvre BA, Williams AJ, Rutkowske RD, Spitzer TD (2007) Automated structure verification based on a combination of 1D 1H NMR and 2D 1H–13C HSQC spectra. Magn Reson Chem 45:803–813

    Article  CAS  Google Scholar 

  91. Keyes P, Hernandez G, Cianchetta G, Robinson J, Lefebvre B (2009) Automated compound verification using 2D-NMR HSQC data in an open-access environment. Magn Reson Chem 47:38–52

    Article  CAS  Google Scholar 

  92. ACD/1D NMR Manager. http://www.acdlabs.com/products/adh/nmr/1d_man/databasing.php. Accessed 15 May 2010

  93. Bally RW, Van Krimpen D, Cleij P, Van'T Klooster HA (1984) An automated library search system for 13C-n.m.r. spectra based on the reproducibility of chemical shifts. Anal Chim Acta 157:227–243

    Article  CAS  Google Scholar 

  94. Farkas M, Bendl J, Welti DH, Pretsch E, Dütsch S, Portmann P, Zürcher M, Clerc JT (1988) Similarity search for a 1H-NMR spectroscopic data base. Anal Chim Acta 206:173–187

    Article  CAS  Google Scholar 

  95. Smith SK, Cobleigh J, Svetnik V (2001) Evaluation of a 1H-13C NMR spectral library. J Chem Inf Comput Sci 41:1463–1469

    Article  CAS  Google Scholar 

  96. Algorithms. https://ftirsearch.com/help/algo.htm. Accessed 15 May 2010

  97. ACD/UV-IR Manager. http://www.acdlabs.com/products/adh/uvir/uvir_man. Accessed 27 Oct 2010

  98. Search Strategies for IR Spectra – Normalization and Euclidean Distance vs. First Derivative Algorithm (2008) Bio-Rad application note 94034-REV200801. http://www.knowitall.com/literature/application_notes/an-search-strat-1.pdf. Accessed 15 May 2010

  99. Varmuza K, Karlovits M, Demuth W (2003) Spectral similarity versus structural similarity: infrared spectroscopy. Anal Chim Acta 490:313–324

    Article  CAS  Google Scholar 

  100. McCreery RL, Horn AJ, Spencer J, Jefferson E (1998) Noninvasive identification of materials inside USP vials with Raman spectroscopy and a Raman spectral library. J Pharm Sci 87:1–8

    Article  CAS  Google Scholar 

  101. 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 52:91–100

    CAS  Google Scholar 

  102. Huber L (1989) Application of diode-array detection in high performance liquid chromatography. Hewlett-Packard Co. Publication number 12-5953-2330.

    Google Scholar 

  103. Hristozov D, Penchev P, Andreev G. Searching in UV/VIS spectral library. http://web.uniplovdiv.bg/plamenpenchev/art14.pdf. Accessed 15 May 2010

  104. Waters ACQUITY UPLC Photodiode Array Detector 71500108703 / Revision A. http://www.waters.com/webassets/cms/support/docs/71500108703ra.pdf. Accessed 15 May 2010

  105. Ellison SLR, Gregory SL (1998) Predicting chance infrared spectroscopic matching frequencies. Anal Chim Acta 370:181–190

    Article  CAS  Google Scholar 

  106. Stein SE (1994) Estimating probabilities of correct identification from results of mass spectral library searches. J Am Soc Mass Spectrom 5:316–323

    Article  CAS  Google Scholar 

  107. NIST Mass Spectral Search Program, version 2.0d, and NIST/EPA/NIH Mass Spectral Library (2005)

    Google Scholar 

  108. Mascot Search Results. http://www.matrixscience.com/cgi/master_results.pl?file=../data/F981122.dat. Accessed 19 Nov 2009

  109. Keller A, Nesvizhskii AI, Kolker E, Aebersold R (2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 74:5383–5392

    Article  CAS  Google Scholar 

  110. Vershinin VI, Derendyaev BG, Lebedev KS (2002) Computer-assisted identification of organic compounds (In Russian). Akademkniga, Moscow

    Google Scholar 

  111. Steinbeck C (2004) Recent developments in automated structure elucidation of natural products. Nat Prod Rep 21:512–518

    Article  CAS  Google Scholar 

  112. Elyashberg M, Blinov K, Molodtsov S, Smurnyy Y, Williams AJ, Churanova T (2009) Computer-assisted methods for molecular structure elucidation: realizing a spectroscopist's dream. J Cheminformatics 1:3. doi:10.1186/1758-2946-1-3

    Article  Google Scholar 

  113. Stein SE (1995) Chemical substructure identification by mass spectral library searching. J Am Soc Mass Spectrom 6:644–655

    CAS  Google Scholar 

  114. Milman BL (2005) Identification of chemical compounds. Trends Anal Chem 24:493–508

    Article  CAS  Google Scholar 

  115. Evett IW, Gill P (1991) A discussion of the robustness of methods for assessing the evidential value of DNA single locus profiles in crime investigations. Electrophoresis 12:226–230

    Article  CAS  Google Scholar 

  116. FAO/WHO Codex Alimentarius. Guidelines on the use of mass spectrometry (MS) for identification, confirmation and quantative determination of residues (2005) CAC/GL 56-2005. http://www.codexalimentarius.net/web/standard_list.jsp. Accessed 16 May 2010

  117. SOFT/AAFS Forensic Laboratory Guidelines (2006). http://www.soft-tox.org/docs/Guidelines%202006%20Final.pdf. Accessed 16 May 2010

  118. Faksness LG, Weiss HM, Daling PS (2002) Revision of the Nordtest methodology for oil spill identification. SINTEF Report STF66 A02028. http://www.nordicinnovation.net/nordtestfiler/tec498.pdf. Accessed 16 May 2010

  119. ASTM D 3415 (1998) Standard practice for identification of waterborne oils

    Google Scholar 

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  1. D.I. Mendeleyev Inst. for Metrology (VNIIM) and Cent. for Ecol. Saf. of Russ. Acad. of Sciences, 65, 9 Morskaya nab, 199226, St. Petersburg, Russia

    Boris L. Milman

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Milman, B.L. (2011). Reliability and Errors of Identification. In: Chemical Identification and its Quality Assurance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15361-7_4

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