Support vector regression for determination of component of compound oxytetracycline powder on near-infrared spectroscopy

Analytical Biochemistry

Volumn 355, Issue 1, 2006, Pages 1-7

  Zou, Tingting ^a   Dou, Ying ^a   Mi, Hong ^b   Zou, Jiying ^c   Ren, Yulin ^a  

^a JILIN UNIVERSITY   (China)

^b CHANGCHUN UNIVERSITY OF CHINESE MEDICINE   (China)

^c JILIN INSTITUTE OF CHEMICAL TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

INFRARED DEVICES; NEAR INFRARED SPECTROSCOPY;

OXYTETRACYCLINES (OTC);

SUPPORT VECTOR REGRESSION;

OXYTETRACYCLINE;

ANALYTIC METHOD; COMPUTER ANALYSIS; COMPUTER PROGRAM; MACHINE; MATHEMATICAL ANALYSIS; MICROCOMPUTER; NEAR INFRARED SPECTROSCOPY; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; REGRESSION ANALYSIS; REVIEW; SUPPORT VECTOR MACHINE;

EID: 33745889031     PISSN: 00032697     EISSN: 10960309     Source Type: Journal    
DOI: 10.1016/j.ab.2006.04.025     Document Type: Review

References (28)

1. Cozzolino D., Chree A., Scaife J.R., and Murray I. Usefulness of near-infrared reflectance (NIR) spectroscopy and chemometrics to discriminate fishmeal batches made with different fish species. J. Agric. Food Chem. 53 (2005) 4459-4463
2. Miralbes C. Prediction chemical composition and alveograph parameters on wheat by near-infrared transmittance spectroscopy. J. Agric. Food Chem. 51 (2003) 6335-6339
3. Breitkreitz M.C., Raimundo Jr. I.M., Rohwedder J.J.R., Pasquini C., Dantas Filho H.A., José G.E., and Araújo M.C.U. Determination of total sulfur in diesel fuel employing NIR spectroscopy and multivariate calibration. Analyst 128 (2003) 1204-1207
4. Blanco M., Coello J., García Fraga J.M., Iturriaga H., Maspoch S., and Pagès J. Determination of finishing oils in acrylic fibres by near-infrared reflectance spectrometry. Analyst 122 (1997) 777-781
5. Sekulic S.S., Ward H.W., Brannegan D.R., Stanley E.D., Evans C.L., Sciavolino S.T., Hailey P.A., and Aldridge P.K. On-line monitoring of powder blend homogeneity by near-infrared spectroscopy. Anal. Chem. 68 (1996) 509-513
6. Blanco M., and Villar A. Polymorphic analysis of a pharmaceutical preparation by NIR spectroscopy. Analyst 125 (2000) 2311-2314
7. Broad N.W., Jee R.D., Moffat A.C., and Smith M.R. Application of transmission near-infrared spectroscopy to uniformity of content testing of intact steroid tablets. Analyst 126 (2001) 2207-2211
8. Scafi S.H.F., and Pasquini C. Identification of counterfeit drugs using near-infrared spectroscopy. Analyst (2001) 2218-2224
9. Wulfert F., Kok W.T., and Smilde A.K. Influence of temperature on vibrational spectra and consequences for predictive ability of multivariate models. Anal. Chem. 70 (1998) 1761-1767
10. Trafford A.D., Jee R.D., Moffat A.C., and Graham P. A rapid quantitative assay of intact paracetamol tablets by reflectance near-infrared spectroscopy. Analyst 124 (1999) 163-167
11. Coffey C., Cooley Jr. B.E., and Walker D.S. Real time quantitation of a chemical reaction by fiber optic near-infrared spectroscopy. Anal. Chim. Acta 395 (1999) 335-341
12. Blanco M., Coello J., Iturriaga H., Maspoch S., and Pagès J. Calibration in non-linear near infrared reflectance spectroscopy: a comparison of several methods. Anal. Chim. Acta 384 (1999) 207-214
13. Despagne F., Massart D.L., and Chabot P. Development of a robust calibration model for nonlinear in-line process data. Anal. Chem. 72 (2000) 1657-1665
14. Blanco M., and Pagès J. Classification and quantitation of finishing oils by near infrared spectroscopy. Anal. Chim. Acta 463 (2002) 295-303
15. Cortes C., and Vapnik V. Support-vector networks. Machine Learn. 20 (1995) 273-297
16. Yuan Z., Bailey T.L., and Teasdale R.D. Prediction of protein B-factor profiles. Proteins 58 (2005) 905-912
17. Song M., Breneman C.M., Bi J., Sukumar N., Bennett K.P., Cramer S., and Tugcu N. Prediction of protein retention times in anion-exchange chromatography systems using support vector regression. J. Chem. Inf. Comput. Sci. 42 (2002) 1347-1357
18. Rege K., Ladiwala A., Tugcu N., Breneman C.M., and Cramer S.M. Parallel screening of selective and high-affinity displacers for proteins in ion-exchange systems. J. Chromatogr. A 1033 (2004) 19-28
19. Thissena U., van Brakela R., de Weijerb A.P., Melssena W.J., and Buydens L.M.C. Using support vector machines for time series prediction. Chemometrics Intell. Lab. 69 (2003) 35-49
20. Zhao C.Y., Zhang R.S., Liu H.X., Xue C.X., Zhao S.G., Zhou X.F., Liu M.C., and Fan B.T. Diagnosing anorexia based on partial least squares, back propagation neural network, and support vector machines. J. Chem. Inf. Comput. Sci. 44 (2004) 2040-2046
21. Mayr T., Igel C., Liebsch G., Klimant I., and Wolfbeis O.S. Cross-reactive metal ion sensor array in a micro titer plate format. Anal. Chem. 75 (2003) 4389-4396
22. Vapnik V. The Nature of Statistical Learning Theory (1995), Springer Verlag, New York
23. Vapnik V. Statistical Learning Theory (1998), John Wiley, New York
24. C.C. Chang, C.J. Lin, National Taiwan University, 2005, www.csie.ntu.edu.tw/_cjlin/libsvm.
25. 2-0001-89.
26. Hawkins D.M. The problem of overfitting. J. Chem. Inf. Comput. Sci. 44 (2004) 1-12
27. Brereton R.G. Introduction to multivariate calibration in analytical chemistry. Analyst 125 (2000) 2125-2154
28. Liu Y. A comparative study on feature selection methods for drug discovery. J. Chem. Inf. Comput. Sci. 44 (2004) 1823-1828