Design and fabrication of artificial neural network-digital image-based colorimeter for protein assay in natural rubber latex and medical latex gloves

Microchemical Journal

Volumn 106, Issue , 2013, Pages 270-275

  Bang iam, Nontawat ^a   Udnan, Yuthapong ^b   Masawat, Prinya ^a  

^a NARESUAN UNIVERSITY   (Thailand)

^b Mahidol University   (Thailand)

Author keywords

Artificial neural network; Digital image based colorimetry; Extractable protein; Medical latex gloves; Natural rubber latex

Indexed keywords

EID: 84868302379     PISSN: 0026265X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.microc.2012.08.003     Document Type: Article

References (26)

1. Pumphrey R.S.H. Allergy to Hevea latex. Clin. Exp. Immunol. 1994, 98:358-360.
2. American Society for Testing and Materials international Annual Book of ASTM Standards 1995, American Society for Testing and Materials, United State of America.
3. Sapan C.V., Lundblad R.L., Price N.C. Colorimetric protein assay techniques. Biotechnol. Appl. Biochem. 1999, 29:99-108.
4. Lopez-Molinero A., Liñan D., Sipiera D., Falcon R. Chemometric interpretation of digital image colorimetry. Application for titanium determination in plastics. Microchem. J. 2010, 96:380-385.
5. Suo X.M., Jiang Y.T., Yang M., Li S.K., Wang K.R., Wang C.T. Artificial neural network to predict leaf population chlorophyll content from cotton plant images. Agric. Sci. China 2010, 9:38-45.
6. Goddijn L.M., White M. Using a digital camera for water quality measurements in Galway Bay. Estuar. Coast. Shelf Sci. 2006, 66:429-436.
7. Raja A.S., Sankaranarayanan K. Use of RGB color sensor in colorimeter for better clinical measurement of blood glucose. Int. J. Bioinform. Med. Eng. 2006, 6:23-28.
8. Huo D.Q., Zhang G.P., Hou C.J., Dong J.L., Zhang Y.C., Liu Z., Luo X.G., FA H.B., Zhang S.Y. A colorimetric sensor array for identification of natural amino acids. Chin. J. Anal. Chem. 2010, 38:1115-1120.
9. Yang C.X., Sun X.Y., Liu B., Lian H.T. Determination of total phosphorus in water sample by digital imaging colorimetry. Chin. J. Anal. Chem. 2007, 35:850-853.
10. Suzuki Y., Endo M., Jin J., Iwase K., Iwatsuki M. Tristimulus colorimetry using a digital still camera and its application to determination of iron and residual chlorine in water samples. Anal. Sci. 2006, 22:411-414.
11. Gaiao E.N., Martins V.L., Lyra W.S., Almeida L.F., Silva E.C., Araujo M.C.U. Digital image-based titrations. Anal. Chim. Acta 2006, 570:283-290.
12. Wongwilai W., Lapanantnoppakhun S., Grudpan S., Grudpan K. Webcam camera as a detector for a simple lab-on-chip time based approach. Talanta 2010, 81:1137-1141.
13. Maleki N., Safavi A., Sedaghatpour F. Single-step calibration, prediction and real samples data acquisition for artificial neural network using a CCD camera. Talanta 2004, 64:830-835.
14. Jha G.H. Artificial neutral networks and it applications (online) available from. http://www.iasri.res.in/ebook/EBADAT/5-Modeling%20and%20Forecasting%20Techniques%20in%20Agriculture/5-ANN_GKJHA_2007.pdf.
15. Chuang L., Hwang J.Y., Chang H.C., Chang F.M., Jong S.B. Rapid and simple quantitative measurement of a-fetoprotein by combining immunochromatographic strip test and artificial neural network image analysis system. Clin. Chim. Acta 2004, 348:87-93.
16. Mohammadi H., Nemati M., Allahmoradi Z., Raissi H.F., Esmaili S.S., Sheikhani A. Ultrasound estimation of fetal weight in twins by artificial neural network. J. Biomed. Sci. Eng. 2011, 4:46-50.
17. Safavi A., Moradlou O., Maesum S. Simultaneous kinetic determination of sulfite and sulfide using artificial neural networks. Talanta 2004, 62:51-56.
18. Afkhami A., Abbasi-Tarighat M., Khanmohammadi H. Simultaneous determination of Co2+, Ni2+, Cu2+ and Zn2+ ions in foodstuffs and vegetables with a new Schiff base using artificial neural networks. Talanta 2009, 77:995-1001.
19. Safavi A., Abdollahi H., Hormozi-Nezhad M.R. Artificial neural networks for simultaneous spectrophotometric differential kinetic determination of Co(II) and V(IV). Talanta 2003, 59:515-523.
20. Bahmani M., Sharifi Kh., Shirvani M. Product yields prediction of tehran refinery hydrocracking unit using artificial neural networks. Iran. J. Chem. Eng. 2010, 7(4):50-63.
21. Chow H., Chen H., Ng T., Myrdal P., Yalkowsky S.H. Using backpropagation networks for the estimation of aqueous activity coefficients of aromatic organic compounds. J. Chem. Inf. Comput. Sci. 1995, 35:723-728.
22. Elmolla E.S., Chaudhuri M., Eltoukhy M.M. The use of artificial neural network (ANN) for modeling of COD removal from antibiotic aqueous solution by the Fenton process. J. Hazard. Mater. 2010, 179:127-134.
23. Yetilmezsoy K., Demirel S. Artificial neural network (ANN) approach for modeling of Pb(II) adsorption from aqueous solution by Antep pistachio (Pistacia Vera L.) shells. J. Hazard. Mater. 2008, 153:1288-1300.
24. Twomey J.M., Smith A.E. Validation and verification. Artificial Neural Networks for Civil Engineers: Fundamentals and Applications 1996, ASCE Press, Chapter 4. N. Kartam, I. Flood, J. Garrett (Eds.).
25. Salle C.T.P., Guahyba A.S., Wald V.B., Silva A.B., Salle F.O. Use of artificial neural networks to estimate production variables of broilers breeders in the production phase. Br. Poult. Sci. 2003, 44(2):211-217.
26. American Society of Anesthesiologists Natural rubber latex allergy: considerations for anesthesiologists (online) available from. http://ecommerce.asahq.org/publicationsAndServices/latexallergy.pdf.