Abstract
Cyclic voltammograms recorded with a single platinum microelectrode were used along with a non-supervised pattern recognition, namely, Principal Component Analysis, to conduct a qualitative analysis of sixteen different brands of carbonated soft drinks (Kuat, Soda Antarctica, H2OH!, Sprite 2.0, Guarana Antarctica, Guarana Antarctica Zero, Coca-Cola, Coca-Cola Zero, Coca-Cola Plus, Pepsi, Pepsi Light, Pepsi Twist, Pepsi Twist Light, Pepsi Twist 3, Schin Cola, and Classic Dillar’s). In this analysis, soft drink samples were not subjected to pre-treatment. Good differentiation among all the analysed soft drinks was achieved using the voltammetric data. An analysis of the loading plots shows that the potentials of −0.65 V, −0.4 V, 0.4 V, and 0.750 V facilitated the discrimination process. The electrochemical processes related to this potential are the reduction of hydrogen ions and inhibition of the platinum oxidation by the caffeine adsorption on the electrode surface. Additionally, the single platinum microelectrode was useful for the quality control of the soft drink samples, as it helped to identify the time at which the beverage was opened.
Highlights
The food market is one of the fastest growing economic sectors in the world
The development of new smart devices for identifying adulteration, detecting alteration of organoleptic properties, and consistently implementing storage processes [1,2,3,4] could enhance the value of food products and thereby prevent product losses
The development of devices that could be used to identify the origins of food products would be very useful
Summary
The food market is one of the fastest growing economic sectors in the world. The development of new smart devices for identifying adulteration, detecting alteration of organoleptic properties, and consistently implementing storage processes [1,2,3,4] could enhance the value of food products and thereby prevent product losses. The development of devices that could be used to identify the origins of food products would be very useful. Much work has already been carried out on the quantification of individual compounds in food samples [5, 6] using expensive and complex techniques. The use of techniques to differentiate between food products based on fingerprints of food samples has been increasing over the last ten years [1, 4, 7,8,9,10]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
