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The intensive use of toxic and remanent pesticides in agriculture has prompted research into novel performant, yet cost-effective and fast analytical tools to control the pesticide residue levels in the environment and food. In conjunction with multivariate data analysis tools, there is strong potential to reduce the total time until a result is yielded from days to a few minutes. We find that fast simultaneous determination of several global environmental parameters characterizing wastewaters is possible with this kind of biosensor array, in particular because of the link between the sensor responses and the biological effect onto the ecosystem into which the wastewater would be released. From investigating the influences of individual sensors in the array, it was found that the best models were in most cases obtained when all sensors in the array were included in the PLS-R model. With the help of partial least squares regression (PLS-R), we could link the sensor responses to the Microtox® toxicity parameter, as well as to global organic pollution parameters (COD, BOD, and TOC). We used principal component analysis (PCA) to decompose the array's responses, and found that wastewater with different degrees of pollution can be differentiated. In order to resolve the complex composition of the wastewater, the array consists of several sensing elements which yield a multidimensional response. Wastewater samples from a Swedish chemi-thermo-mechanical pulp (CTMP) mill collected at different purification stages in a wastewater treatment plant (WWTP) were analyzed with an amperometric enzyme-based biosensor array in a flow-injection system. To simplify interpretation of results, the measured data were treated with multivariate analysis–principal component analysis (PCA). The developed biosensor array was evaluated on wastewater samples. The detection limits for pesticides and phenols were in the nanomolar and micromolar ranges, respectively. The achieved relative standard deviation values calculated for different enzyme substrates (10 measurements) were typically below 7% and one assay was completed within less than 10 min.
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All measurements were performed in an electrochemical steady state system specially constructed for eight channel screen-printed electrode arrays. Hydrogen peroxide was generated in the presence of glucose by co-immobilised glucose oxidase (GOx). The substrates for the enzymes were acetylthiocholine for cholinesterases (ChEs), cellobiose for CDH and hydrogen peroxide for peroxidases. Mainly cross-linking with glutaraldehyde was employed for enzyme immobilisation.
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Cholinesterases (AChE and BChE), tyrosinase (TYR), peroxidases (SBP, soybean and HRP, horseradish) and cellobiose dehydrogenase (CDH) were combined on the same array consisting of one Ag/AgCl reference electrode surrounded by eight radially distributed working electrodes of either carbon or platinum. Amperometric screen-printed biosensor arrays for detection of pesticides (organophosphates and carbamates) and phenols have been developed.
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