An ammonium detection system using Ion-Selective Electrodes (ISEs) in Flow-Injection Analysis (FIA) is described. Because of the low selectivity of the nonactin ammonium selective electrode towards some common ions, different selectivity enhancement techniques have been examined. A Sensor Array Detector (SAD) which comprises ISEs selective for ammonium, sodium, potassium and calcium was used. A modified form of the Nikolskii-Eisenman Equation is proposed in which the charge power function of the interfering ion activity is linearised. Selectivity is quantified for the PVC membrane electrodes (NH4+, Na , K \ Ca ') in terms of constants rather than conventional coefficients. These constants and other electrode parameters such as cell constant and slope are estimated by means of the FIA-SAD approach. The SAD response was modeled via the Nikolskii-Eisenman equation with SIMPLEX regression model The applicability of the resulting values for these parameters is demonstrated through the determination of unknowns by direct solution of the system of modified Nikolskii-Eisenman equations describing the array response. The results show that the use of an array of ISEs under FIA regimes for the detection of ammonium in the concentration range 10 '4 to 10 '2 mol dm'3 gives a much higher improvement in the determination of ammonium in aqueous samples than the use of a single ammonium electrode in steady-state or kinetic measurements. This approach is suitable for use in real-time monitoring applications where batch calibration techniques cannot easily be implemented. Computer controlled laboratory instrumentation is of growing importance both in research and in industry. Different hardware and software approaches may be chosen which allow the development of high quality products, Last trends in hardware and software strategies are analyzed and some general guidelines are given for instrumentation development. The graphical compiler Lab VIEW 3.0 for instrumentation from National Instruments is presented and evaluated in terms of flexibility and low cost for the production of virtual instrumentation for research, biomedical applications and industrial environmental monitoring.