development of colorimetric sensor array based on metal ion complexes fordiscrimination and adulteration detection of lime juice samples

The quality assurance of beverages are important growing need of both industry and consumers.lime, is one of the most important citrus species cultivated. lime fruits are rich in nutrients suchas vitamins, fiber, minerals, carotenoids, phenolic compounds, flavanones, hesperidin anderiocitrin [1]. thus, lime juice quality control is importance because of synthetic product effectsconsumers’ health. until now, several analytical methods have been used to find a method to detectadulteration in lime, lemon and other citrus juice. gas chromatography–mass spectrometry (gcms), liquid chromatography–mass spectrometry (lc-ms), high performance liquidchromatography (hplc), solid-phase microextraction followed by gc-ms (spme-gcms),hplc coupled with diode-array detection, electrospray ionization tandem mass spectrometry(hplc-dad-ms/ms), near-infrared spectroscopy (nir) and fourier-transform infraredspectroscopy (ftir) are common methods for detection of adulteration. however, they areexpensive, time consuming, destructive, need professional operator, and don’t have point-ofneedcapabilities [2-3].in this work a simple colorimetric sensor array made of 32 metal ion complexes including 4chemical responsive dyes and 4 metal ions in 2 buffered and non-buffered environments, wasprepared by dropping the solutions of metal ion complexes on a hydrophobic paper. thecolorimetric sensor array responses to volatile organic compounds (vocs) in the head-space of11 hand-made lime juice samples, 12 commercial samples of different brands and 15 adulteratedsamples, were evaluated using sensor images recorded by an ordinary flatbed scanner. thedeveloped sensor array produced color difference map patterns as a unique fingerprint, fordifferent types of the lime juice samples. multivariate rgb responses of the designed sensor wereanalyzed with statistical unsupervised pattern recognition methods including principal componentanalysis (pca) and hierarchical clustering analysis (hca) without any preprocessing. the sensorarray was provided an acceptable discrimination between commercial, natural and adulteratedlime juice samples. besides, analysis of the sensor array data by discriminant analysis methodresulted in correct identification of the commercial sample brands. in addition, the array coulddiscriminate natural lime juices prepared in three consecutive years. this sensor array can be usedup to 1 month after production with a small deviation of 5.25% with fresh sensor responses andprovide reproducible responses.