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The analysis of soluble reactive phosphate (SRP) in water is key to control water quality. In order to continuous monitor orthophosphate content in water during treatment processes and in the effluents of wastewater treatment plants, conventional procedures, usually performed in a laboratory, must be adapted. This means pursuing efforts on miniaturizing systems to operate in situ and automating analytical methods to work on-line. The design, construction and evaluation of an automatic and low cost cyclic olefin copolymer (COC)-based spectrophotometric microanalyzer, capable of operating in unattended conditions, is presented to monitor soluble reactive phosphorous, as orthophosphate ion, in wastewater samples coming from sewage treatment plants. The microsystem, constructed by CNC micromilling and using a multilayer approach, integrates microfluidics to carry out the phosphomolybdenum blue (PMB) reaction and an optical flow-cell for the spectrophotometric orthophosphate determination in a single polymeric substrate smaller than a credit card. It is connected to a compact optical detection system composed by a LED emitting at 660 nm and a PIN-photodiode, both integrated in a PCB. Flow management is automatically performed by programmed microvalves and micropumps, which control autocalibration processes and allow unattended operation. Analytical features after the optimization of the microfluidic platform and the chemical and the hydrodynamic variables, were a linear range from 0.09 to 32 mg L−1 P and a detection limit of 0.03 mg L−1 P with a sampling rate of 24 samples h−1, demonstrating the microanalyzer suitability for SRP monitoring in water. Moreover, real samples were analyzed obtaining promising results.

A colorimetric flow injection-system for the determination of Cu(II) in waters based on complexation reaction with 4-(2-pyridylazo)-resorcinol, usually termed PAR, is described. Performing measurements in 0.25 mol l −1 HNO 3 medium allowed improved selectivity of the analytical method. The lack of sensitivity deriving from the low complex absorption under acidic conditions was balanced by the insertion of an immobilised poly(ethylenimine) (PEI) column where Cu(II) pre-concentration in neutral media occurs. Using sample volumes ranging from 2 to 4 ml, sampling rates of 24 and 12 samples h −1 within a detection limit of 25 and 13 μg l −1 , respectively, were accomplished. Accuracy of the developed methodology was assessed by comparison with atomic absorption spectrometry being the relationship [FIA] mg l −1 =1.00 (±0.03)×[AAS] mg l −1 +0.00 (±0.02) obtained after analysing 15 samples. Precision was also evaluated using two samples of 0.05 and 0.5 mg l −1 copper, and a relative standard deviation (R.S.D.) better than 3% was attained for both.

A novel autoadaptative sequential injection system for the analysis of nitrite is described. The automatic determination uses a direct spectrophotometric method, based on the Griess–Ilosvay reaction. In this method the absorbance of the purple azo dye formed is measured at 555 nm. In the sequential injection operation, the sample and the reagent are aspirated and mixed by reverse flow. The sequencing and overlapping of stacked (reagent) zones as well as selection of volumes have been studied in detail. The proposed analytical system is intelligent, simple and robust, allowing for nitrite determination in a double concentration range, by a simple and automatic programmable operation change. These two ranges are 0.0–3.0 and 0.0–20.0 ppm with detection limits being 0.048 and 0.4 ppm, respectively. Next surroundings have been developed allowing autocalibration and independent monitoring of nitrite concentration. The experimental set-up has been evaluated applying it to real samples analysis of very diverse concentration samples coming from a WWTP. The throughput of the method was 12 samples per hour.

There are a number of variables that are useful to determine the optimal moment for the fruit collection such as starch content, sugar content, acidity and firmness. Other variables, including calcium and potassium concentrations, may establish better the state of ripeness of fruit and can help to optimise the collection process as well as augmenting the nutritional value of fruits. At present, these novel parameters cannot be used for the control of fruit collection due to the slow standard methods required. The need for in situ and in real-time ion measurements calls for fast response sensors and simpler and portable instrumentation. Solid-state sensors respond to these requirements. This work describes the application of ISFET sensors to analyse calcium, potassium and nitrates in several apple varieties, both in juice and in situ fruit. Results show that the analysis of potassium, calcium and nitrate permits to distinguish among apple varieties and can also be used to determine correctly the concentrations of these ions.

Earlier work of potentiometric Ion-selective electrodes (ISEs) sensitive to nonionic surfactants of the polyethoxylate type is further extended. The ISEs constructed were all-solid-state sensors with plasticized PVC membranes. The sensing material was a tetraphenylborate salt of the barium complex with a polyethoxylate nonionic surfactant. As membrane component, the combinations of two polyethoxylates of the nonylphenoxy type, which differed in the number of oxyethylene units (5 or 12), and two different plasticizers, (o-nitrophenyloctyl ether and o-nitrophenylphenyl ether), were tested. The response of these electrodes to different nonionic surfactants and the interference effect of several species has been evaluated. For all the types of tested electrodes, the sensitivities shown were ca. 30.0 mV dec−1 and the limit of detection, ca. 10−5 M, when a nonylphenoxyde with 12 oxyethylene units was used as standard. The membrane with the best response characteristics was then applied in potentiometric titrations of this kind of surfactants in the presence of Ba2+ ion and using tetraphenylborate as the titrant.

An experimental comparison between the relative performances of the Powell and simplex methods for the optimization of a Flow Injection Analysis (FIA) system for the determination of nitrite in water is reported. An evaluation of the advantages of using a weighted linear combination of two variables (related to sensitivity and sample throughput rate) as the response function in the guidance of the optimization procedures towards different practical requirements is also included. Both methods proved to be effective for the optimization, none having shown definite advantages over the other. The use of a weighted response function in these optimization methods proved to be useful for assessing the versatility of FIA systems.