Sains Malaysiana 40(10)(2011): 1105–1113

Quantitative Determination of Ammonium Ion in Aqueous Environment

Using Riegler’s Solution and Artificial Neural Network

(Penentuan Kuantitatif Ion Ammonium dalam Persekitaran Akueus Menggunakan Larutan

Riegler dan Jaringan Neural Tiruan)

Tan Ling Ling, Musa Ahmad & Lee Yook Heng*

School of Chemical Sciences and Food Technology, Universiti Kebangsaan Malaysia

43600 Bangi, Selangor D.E. Malaysia

Diserahkan: 12 August 2008/Diterima: 22 April 2009

ABSTRACT

A quantitative analysis has been conducted to determine the concentration of ammonium (NH4+) ion in solution by using Ultraviolet-visible spectrophotometry method and artificial neural network (ANN). Riegler’s reagent was used to form Riegler-NH4+ complex. The characterisations of Riegler’s reagent in solution such as photostability, pH effect, reagent concentration, dynamic range and reproducibility were conducted. The colour change of the Riegler’s reagent after reaction with NH4+ was yellow to red. The Riegler’s reagent responds linearly to NH4+ ion concentration in the range of 1-7 ppm with optimum response at pH7. Satisfactory reproducibility (2.0-2.8%) were obtained with this reagent. The effect of interfering ions that may contain in the leachate on the determination of NH4+ ion was also studied. The application of ANN enabled the extension of the useful dynamic concentration range of NH4+ ion to 1–24 ppm. The best ANN architecture for Riegler-NH4+ complex was built from 29 hidden neurons, 21,389 epochs number and 0.001% learning rate which produced sum square error (SSE) value of 0.0483 with an average calibration error of 1.4136.

Keywords: Ammonium ion; artificial neural network; Riegler’s reagent; ultraviolet-visible spectrophotometry

ABSTRAK

Analisis kuantitatif telah dilakukan untuk menentukan kepekatan ion ammonium (NH4+) dalam larutan dengan menggunakan kaedah spektrofotometri utralembahyung-nampak dan jaringan neural tiruan (ANN). Reagen Riegler telah digunakan untuk membentuk kompleks Riegler-NH4+. Pencirian terhadap reagen Riegler dalam larutan termasuk analisis kestabilan foto reagen, kesan pH, kesan kepekatan reagen, julat kepekatan dinamik dan kebolehulangan telah dilakukan. Perubahan warna reagen Riegler selepas bertindak balas dengan NH4+ adalah kuning ke merah. Reagen Riegler memberi rangsangan linear kepada ion NH4+ dalam julat 1-7 ppm dengan rangsangan optimum pada pH7. Kebolehulangan yang memuaskan (2.0-2.8%) telah diperolehi dengan reagen ini. Kesan ion pengganggu yang boleh didapati dalam air larut lesap dalam penentuan ion NH4+ juga dikaji. Penggunaan ANN telah berupaya memanjangkan julat kepekatan dinamik ion NH4+ sehingga julat kepekatan 1 – 24 ppm. Arkitektur jaringan ANN yang terbaik untuk kompleks Riegler-NH4+ dibina daripada 29 neuron terlindung, 21,389 unit bilangan kitaran dan kadar pembelajaran 0.001% yang menghasilkan nilai ralat jumlah kuasa dua (SSE) sebanyak 0.0483 dengan purata ralat sebanyak 1.4136.

Kata kunci: Ion ammoniumk; jaringan neural tiruan; reagen Riegler’s; spektrofotometri utralembahyung-nampa

RUJUKAN

Abass, A.K., Hart, J.P., Cowell, D.C. & Chappell, A. 1998. Development of an amperometric assay for NH4+ based on a chemically modified screen-printed NADH sensor. Analytica Chimica Acta 373: 1-8.

Aminot, A., Kerouel, R. & Birot, D. 2001. A flow injection-fluorometri method for the determination of ammonium in fresh and saline waters with a view to in situ analyses. Wat. Res. 35(7): 1777-1785.

Andrew, K.N., Worsfold, P.J. & Comber, M. 1995. On-line flow injection monitoring of ammonia in industrial liquid effluents. Analytica Chimica Acta 314: 33-43.

Azizul Isha, Nor Azah Yusof, Musa Ahmad, Dedy Suhendra, Wan Md Zin Wan Yunus & Zulkarnain Zainal. 2006. A chemical sensor for trace V(V) ion determination based fatty hydroxamic acid immobilised in polymethylmethacrylate. Sensor and Actuators B 114: 344-349.

Boer, W.D., Gunnewiek, P.A.K., Laanbroek, H.J. 1995. Ammonium-oxidation at low pH by a chemolithotrophic bacterium belonging to the genus Nitrosospira. Soil Biol. Biochem. 27: 127132.

Chang, R. 2002. Chemistry. (7^th ed.). New York: Mc Graw Hill.

Cherian, T. & Narayana, B. 2006. A new system for the spectrophotometric determination of trace amounts of nitrite in environmental samples. J. Braz. Chem. Soc. 17(3): 577-581.

Deyhimi, F. & Choobar, B.G. 2005. Potentiometric determination of activity coefficients for NH4Cl in the ternary NH4Cl/LiCl/H2O mixed electrolyte system. Journal of Electroanalytical Chemistry 584: 141-146.

Faiz Bukhari Mohd Suah, Musa Ahmad & Mohd Nasir Taib. 2003a. Applications of artificial neural network on signal processing of optical fibre pH sensor based on bromophenol blue doped with sol-gel film. Sensors and Actuators B 90: 182-188.

Faiz Bukhari Mohd Suah, Musa Ahmad & Mohd Nasir Taib. 2003b. Optimisation of the range of an optical fibre pH sensor using feed-forward artificial neural network. Sensors and Actuators B 90: 175-181.

Hassan, S.S.M., Marei, S.A., Badr, I.H. & Arida, H.A. 2001. Novel solid-state ammonium ion potentiometric sensor based on zirconium titanium phosphate ion exchanger. Analytica Chimica Acta 427: 21-28.

Icardo, M.C., Torro, I.G., Zamora, L.L. & Calatayud, J.M. 1999. Flow spectrophotometric determination of ammonium ion. Analytica Chimica Acta 398: 311-318.

Krishnan, G. 2006. They’re dragging their feet. The Star, 25(4): 12.

Kuo, C.T., Wang, P.Y. & Wu, C.H. 2005. Fluorometric determination of ammonium ion by ion chromatography using postcolumn derivatization with o-phthaldialdehyde. Journal of Chromatography A 1085: 91-97.

Kwan, R.C.H., Hon, P.Y.T. & Renneberg, R. 2005. Amperometric determination of ammonium with bienzyme/poly(carbamoyl) sulfonate hydrogel-based biosensor. Sensors and Actuators B 107: 616-622.

Li, Q.P., Zhang, J.Z., Millero, F.J. & Hansell, D.A. 2005. Continuous colorimetric determination of trace ammonium in seawater with a long-path liquid waveguide capillary cell. Marine Chemistry 107: 73-85.

Nor Azah Yusof & Musa Ahmad. 2002. A flow cell optosensor for lead based on immobilised gallocynin in chitosan membrane. Talanta 58: 459-466.

Parham, H. & Mobarakzadeh, M. 2002. Solvent extraction-spectrophotometric determination of trace amounts of ammonium, barium and potassium in a mixture by dicyclohexyl-18-crown-6 and orange II. Talanta 58: 281-287.

Pranaityte, B., Jermak, S., Naujalis, E. & Padarauskas, A. 2007. Capillary electrophoretic determination of ammonia using headspace single-drop microextraction. Microchemical Journal 86: 48-52.

Renault, N.J., Senillou, A., Martelet, C., Wan, K. & Chovelon, J.M. 1999. ISFET mocrosensors for the detection of pollutants in liquid media. Sensors and Actuators B 59: 154-164.

Robert, C.W. 1972. Handbook of Chemistry and Physics. (53^rd ed.). Cranwood Parkway: The Chemical Rubber Co.

Senthilkumar, M. & Selvakumar, N. 2005. Achieving expected depth of shade in reactive dye application using artificial neural network technique. Dyes and Pigments 68: 89-94.

Staden, J.F.V. & Taljaard, R.E. 1997. Determination of ammonia in water and industrial effluent streams with the indophenol blue method using sequential injection analysis. Analytica Chimica Acta 344: 281-289.

Strotmann, U.J. & Windecker, G. 1997. Kinetics of ammonium removal with suspended and immobilized nitrifying bacteria in different reactor systems. Chemosphere 35: 2939-2952.

Taylor, A.E. & Bottomley, P.J. 2006. Nitrite production by Nitrosomonas europaea and Nitrosospira sp. AV in soils at different solution concentrations of ammonium. Soil Biology & Biochemistry 38: 828-836.

Trinkel, M., Trettnak, W., Reininger, F., Benes, R., O’Leary, P. & Wolfbeis, O.S. 1996. Study of the performance of an optochemical sensor for ammonia. Analytica Chimica Acta 320: 235-243.

Vogel, A.I. 1979. Textbook of Macro and Semimicro Qualitative Inorganic Analysis. (5^th ed.) London: Longman Group Limited.1113

*Pengarang untuk surat-menyurat; email: yh11000@ukm.my