Artificial neural network implementation in single low-cost chip for the detection of insecticides by modeling of screen-printed enzymatic sensors response

Computers and Electronics in Agriculture

Volumn 74, Issue 2, 2010, Pages 223-229

  Alonso, Gustavo A ^a   Istamboulie, Georges ^b   Ramirez Garcia Alfredo A ^a   Noguer, Thierry ^b   Marty, Jean Louis ^b   Muñoz, Roberto ^a  

^a DEPARTAMENTO DE FÍSICA   (Mexico)

^b Centre de Phytopharmacie   (France)

Author keywords

Acetylcholinesterase; Artificial neural networks; DsPIC ; Hardware implementation; Pesticides

Indexed keywords

ACETYLCHOLINESTERASE; AMPEROMETRIC; ANALYTICAL CHEMICALS; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; CHLORPYRIFOS-OXON; HARDWARE IMPLEMENTATION; HARDWARE IMPLEMENTATIONS; SCREEN-PRINTED; SPECIALIZED TOOLS; TEST SAMPLES;

AGRICULTURAL CHEMICALS; BIOSENSORS; HARDWARE; PESTICIDES;

NEURAL NETWORKS;

ARTIFICIAL NEURAL NETWORK; ENZYME ACTIVITY; HARDWARE; INSECTICIDE; PERFORMANCE ASSESSMENT; SENSOR;

EID: 78049289934     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2010.08.003     Document Type: Article

References (39)

1. Andreescu S., Barthelmebs L., Marty J.L. Immobilization of acetylcholinesterase on screen-printed electrodes: comparative study between three immobilization methods and applications to the detection of organophosphorus insecticides. Anal. Chim. Acta 2002, 464:171-180.
2. Andreescu S., Marty J.L. Twenty years research in cholinesterase biosensors: from basic research to practical applications. Biomol. Eng. 2006, 23:1-15.
3. Betancourt A.M., Carr R.L. The effect of chlorpyrifos and chlorpyrifos-oxon on brain cholinesterase, muscarinic receptor binding, and neurotrophin levels in rats following early postnatal exposure. Toxicol. Sci. 2004, 77:63-71.
4. Campàs M., Prieto-Simón B., Marty J.L. A review of the use of genetically engineered enzymes in electrochemical biosensors. Semin. Cell Dev. Biol. 2009, 20:3-9.
5. Castro U.P., Ibarra J.E., Flores B.R. A Methodology for Implementation of the Execution Phase of Artificial Neural Networks in Digital Hardware Devices. Robotics and Automotive Mechanics Conference 2008.
6. Cheng-Jian L., Hung-Ming T. FPGA implementation of a wavelet neural network with particle swarm optimization learning. Math. Comput. Modell. 2008, 47:982-996.
7. Decision 2455/2001/EC, 2001. Establishing a list of priority substances in the field of water policy and amending directive2000/60/EC. Off. J. Eur. Comm. L331.
8. Deo R.P., Wang J., Block I., Mulchandani A., Joshic K.A., Trojanowicz M., Scholz F., Chen W., Lin Y. Determination of organophosphate pesticides at a carbon nonotube/organophosphorus hydrolase electrochemical biosensor. Anal. Chim. Acta 2005, 539:185-189.
9. Desai K.M., Vaidya B.K., Singhal R.S., Bhagwat S.S. Use of artificial neural network in modeling yeast biomass and yield of β-glucan. Process Biochem. 2005, 40:1617-1626.
10. Dias F.M., Antunes A., Mota A.M. Artificial neural networks: a review of commercial hardware. Eng. Appl. Artif. Intel. 2004, 17:945-952.
11. Ecobichon D.J. Toxic effects of pesticides. Cassarett and Doull's Toxicology: The Basic Science of Poisons 1996, McGraw-Hill, New York. D. Klaassen (Ed.).
12. Ellman G.L., Courtney K.D., Andres V. A new and rapid colorimetric determination of acetylcholinesterase activity. Biochem. Pharmacol. 1961, 7:88.
13. Frankowiak M.R., Grosvenor R.I., Prickett P.W. A petri-net based distributed monitoring system using PIC microcontroller. Microprocess. Microsyst. 2005, 29:189-196.
14. Ghosh S., Tian Y. Optimum two level fractional factorial plans for model identification and discrimination. J. Multivariate Anal. 2006, 6:1437-1450.
15. Gonçalves C., Alpendurada M.F. Assessment of pesticide contamination in soil samples from an intensive horticulture area, using ultrasonic extraction and gas chromatography-mass spectrometry. Talanta 2005, 5:1179-1189.
16. Huang C.Y., Syu M.J., Chang Y.S., Chang C.H., Chou T.C., Liu B.D. A portable potentiostat for the bilirubin-specific sensor prepared from molecular imprinting. Biosens. Bioelectron. 2007, 22:1694-1699.
17. Istamboulie G., Cortina-Puig M., Marty J.L., Noguer T. The use of artificial neural networks for the selective detection of two organophosphate insecticides: chlorpyrifos and chlorfenvinfos. Talanta 2009, 79:507-511.
18. Istamboulie G., Fournier D., Marty J.L., Noguer T. Phosphotriesterase: a complementary tool for the selective detection of two organophosphate insecticides: chlorpyrifos and chlorfenvinfos. Talanta. 2009, 5:1627-1631.
19. Koch D., Lu C., Fisker-Andersen J., Jolley L., Fenske R.A. Temporal association of children's pesticide exposure and agricultural spraying: report of a longitudinal biological monitoring study. Environ. Health Perspect. 2002, 110:829-833.
20. Krantz-Rülcker C., Stenberg M., Winquist F., Lundström I. Electronic tongues for environmental monitoring based on sensor arrays and pattern recognition: a review. Anal. Chim. Acta 2001, 2:217-226.
21. Li B., He Y., Xu C. Simultaneous determination of three organophosphorus pesticides residues in vegetables using continuous-flow chemiluminescence with artificial neural network calibration. Talanta 2007, 72:223-230.
22. Li Q.F., Yao X.J., Chen X.G., Liu M.C., Zhang R.S., Zhang X.Y. Application of artificial neural networks for the simultaneous determination of a mixture of fluorescent dyes by synchronous fluorescence. Analyst 2000, 125:2049-2053.
23. Luciano G., Traverso P., Letardi P. Applications of chemometric tools in corrosion studies. Corros. Sci. 2010, 52:2750-2757.
24. Montgomery D. Design and analysis of experiments 2000, 5. John Wiley S, New York, NY.
25. Moreno-Barón L., Cartas R., Merkoçi A., Alegre S., del Valle M., Leija L., Hernandez P.R., Muñoz R. Application of the wavelet transform coupled with artificial neural networks for quantification purposes in a voltammetric electronic tongue. Sens. Actuators B1 2006, 487-499.
26. Müller U.A., Gunzinger A., Guggenbühl W. Fast neural net simulation with DSP processor array. IEEE Trans. Neural Networ. 1995, 6:203-213.
27. Nascimento C.A., Giudici R., Guardani R. Neural network based approach for optimization of industrial chemical process. Comput. Chem. Eng. 2000, 24:2303-2314.
28. Ni Y., Zhang G., Kokot S. Simultaneous spectrophotometric determination of maltol, ethyl maltol, vanillin and ethyl vanillin in foods by multivariate calibration and artificial neural networks. Food Chem. 2005, 89:465-473.
29. Nunes S., Jeanty G., Marty J.L. Enzyme immobilization procedures on screen-printed electrodes used for the detection of anticholinesterase pesticides comparative study. Anal. Chim. Acta 2004, 523:107-115.
30. Qian, Y., Li, A., Wang, Q., 2007. Design and implementation of a general purpose neural network processor. In Lectures Notes in Computer Science, Nanjing, China, 689-698.
31. Steinberg M.D., Lowe C.R. A micropower amperometric potentiostat. Sens. Actuators B97 2004, 284-289.
32. Sung S.K., Seul J. Hardware implementation of a real time neural network controller with a DSP and FPGA for non linear systems. In Proceedings of the International Conference on Robotics and Automation 2004, 4639-4644.
33. Turkoglu I. Hardware implementation of varicap diodeós ANN Model using PIC microcontrollers. Sens. Actuators B 2007, 138:288-293.
34. U.S. Environmental Protection Agency (EPA), 2009. Chemical References Index Friday. Available from: (accessed 10.04.09). http://www.epa.gov/enviro/html/emci/chemref/short_index.html.
35. Vas P., Stronach A.F., Rashed M., Neuroth M. Implementation of ANN-based sensorless induction motor drive. Presented at the International Conference on Electrical Machines and Drives 1999.
36. Won E. A hardware implementation of artificial neural network using a Field Programmable Gate Array. Nucl. Instrum. Methods A 2007, 581:816-820.
37. Yu R.Q., Jiang J.H. Advancement of three chemometric tools: network architecture, unsupervised learning and nonlinear feature extraction. Chemometr. Intell. Lab. 1999, 45:191-198.
38. Zhu, J., Sutton, P., 2003. FPGA implementations of neural networks - A survey of a decade of progress. In Lectures Notes in Computer Science, Berlin, Germany, September, 1062-1066.
39. Zupan J., Gasteiger J. Neural Network in Chemistry and Drug Design 1999, Wiley-VCH, Weinheim, Germany, 157-172. 2 ed.