Published at : 21 Apr 2020
Volume : IJtech Vol 11, No 2 (2020)
DOI : https://doi.org/10.14716/ijtech.v11i2.3225
|A.A. Arrieta||Department of Biology and Chemistry – University of Sucre, Carrera 28 # 5-267 Barrio Puerta Roja, P.C 700008, Sincelejo, Colombia|
|Y.E. Nuñez||Universidade Tecnológica Federal do Paraná, ua Dep. Heitor Alencar Furtado, 5000 – Campo Comprido, Curitiba – PR, 81280-340, Brazil|
|J.M. Mendoza||Department of Mechanical Engineering, University of Cordoba, Carrera 6 No. 76-103, C.P. 14014, Montería, Colombia|
This paper presents a mini-electronic tongue that used a polymeric sensor array made from polypyrrole to discriminate between coffee samples of different geographical origin. The electronic tongue consisted of a system with a voltammetric sensor array coupled to a multichannel measuring device (multi-potentiostat) that was controlled by a multivariable data collection and processing application. The samples analyzed comprised two types: a series of substances with different chemical and taste properties and a group of samples of coffee of the Arabica variety harvested from different geographical areas of Colombia. The electronic tongue demonstrated the ability to discriminate between solutions with different gustatory properties. In the analysis of the coffee samples, each sensor showed a particular voltammetric response to each of the samples studied. A principal component analysis was undertaken, which resulted in clear discrimination between each of the coffee samples. It was concluded that the portable electronic tongue equipped with polymer sensors is able to discriminate between samples of coffee of different geographical origin.
Coffee; Electronic tongue; Electrochemistry; Polypyrrole; Sensors
Coffee is undoubtedly one of the most popular drinks around the world, and for this reason, it has been widely studied (Mahachandra et al., 2017; Iswanto et al., 2019; Haryuni et al., 2019). Its commercialization occupies a very important place in the economies of countries like Colombia, Brazil, and Vietnam, among others. In Colombia, several dozen municipalities produce coffee; however, each producing area generates grains with different organoleptic characteristics that differentiate them from each other and from the varieties of coffee grown in other countries (Sanja et al., 2008; Athanassiou et al., 2016; Mehari et al., 2016; Thorburn-Burns et al., 2017).
Accordingly, the concept of denomination of origin was generated, which guarantees the quality and provenance of a product. In Colombia, there are more than 10 denominations of origin, and each offers a coffee with particular features and certain quality specifications. It is thus very important for this sector to be able to acquire technology that will allow its members to quickly and easily differentiate between and classify their products by denomination of origin. Several authors have attempted to discriminate between, classify, and determine the authenticity of coffee varieties by analyzing the chemical compounds present in the products using conventional analytical methods such as chromatography or mass spectrophotometry (Sanja et al., 2008; Mehari et al., 2016). However, more than a thousand different chemical compounds can exist in a single sample of coffee. At present, sensorial analysis is the most commonly used method to analyze the organoleptic qualities of a coffee and to determine its characteristics, among them, its geographical origin and the conditions of the crop and harvest.
These sensorial methods aim to evaluate the sensations produced by a particular coffee as a whole. Sensory analysis can be defined as the experimentation and analysis of the global characteristics of a product through the senses; such features are known as organoleptic characteristics. The senses of smell and taste are known as chemical biosensors because they respond directly to stimuli produced by molecules that cause nervous excitation. Thus, the olfactory and gustative systems serve as inspiration for the development of devices seeking in some way to mimic their ability to classify and discriminate between complex substances. These systems are known as electronic noses and electronic tongues (Parra et al., 2006; Di Rosa et al., 2017).
Electronic tongues are used mainly to analyze substances in the liquid phase and have been applied successfully to test numerous beverages (Parra et al., 2006; Chen et al., 2008; Arrieta et al., 2010; Arrieta and Tarazona, 2014; Fuentes et al., 2017). An electronic tongue device consists of three parts: a sensor array that is responsible for sensing analytical samples, a multichannel electronic system, and a computer system equipped with multivariate statistical analysis tools. Although electronic tongues have been used in numerous applications, their use in the discrimination and classification of coffee has rarely been reported (Buratti et al., 2014; Lopetcharat et al., 2016). Indeed, to the best of our knowledge, there are no studies in which coffee samples have been classified according to their geographical origin using this new technology. Accordingly, this work explores the potential of a voltammetric electronic tongue to discriminate between coffee samples with organoleptic characteristics, which is important when validating the origin of these types of products.
The aim of this work was to evaluate the application of a mini-electronic tongue to discriminate between coffee samples from different geographic regions. The device comprised a polymeric sensor array made from polypyrrole (PPy) modified with different counterions, a multichannel electronic device based on programmable system-on-chip (PSoC) technology coupled to a computer system with multivariable analysis tools.
In this study, an electronic tongue device with PSoC technology that was integrated with a polymeric sensor array with PPy modified using different counterions was shown to be capable of discriminating between simple substances with distinct chemistry and gustatory properties: NaCl (saltiness), sucrose (sweetness), caffeine (bitterness), citric acid (sourness), and vanillin (bitterness). Each sensor presented a different signal for each analyzed sample, demonstrating cross-selectivity, and this allowed the sensor to generate a fingerprint of the sample. This information was then extracted through principal component analysis, enabling the sensor to discriminate between each substance. The mini-electronic tongue device was able to discriminate between samples of coffee harvested from different geographical areas (although the samples were of the same varieties and processed similarly). In this study, it was concluded that the information provided by the sensor array could collect and supply sufficient information to discriminate between the coffee samples from different origin denominations. Additionally, the results showed that this discrimination was related to the geographical similarities of the areas of origin of the samples. This type of study opens the possibility of applying the electronic tongue not only in the coffee sector, but also for use with other products where the designations of origin are synonymous with quality and have a significant impact on the price of, and market for, the products.
The authors acknowledge the financial support
provided by the Administrative Department of Science, Technology and Innovation
(Colciencias) and the University of Sucre.
Arrieta, A.A., Apetrei, C., Rodríguez-Méndez, M.L., De Saja, J.A., 2004. Voltammetric Sensor Array based on Conducting Polymer-modified Electrodes for the Discrimination of Liquids. Electrochimica Acta, Volume 49(26), pp. 4543–4551
Arrieta, A.A., Fuentes, O., 2016. Electronic Tongue: New Tool for Food Analysis Based a PSoC (Programmable System-on-Chip) Technology. Advance Journal of Food Science and Technology, Volume 12(11), pp. 603–608
Arrieta, A.A., Rodríguez-Méndez, M.L., De Saja, J.A., Blanco, C.A., Nimubona, D., 2010. Prediction of Bitterness and Alcoholic Strength in Beer using an Electronic Tongue. Food Chemistry, Volume 123(3), pp. 642–646
Arrieta, A.A., Tarazona, R., 2014. Electronic Tongue and Neural Networks, Biologically Inspired Systems Applied to Classifying Coffee Samples. American Journal of Analytical Chemistry, Volume 5(4), pp. 266–274
Athanassiou, C.G., Chiou, A., Rumbos, C.I., Karagiannis, A., Nikolidaki, E.K., Panagopoulou, E.A., Kouvelas, A., Karathanos, V.T., 2016. Effects of Electric Infrared Heating with Light Source Penetration on Microbial and Entomological Loads of Dried Currants and Their Organoleptic Characteristics. Journal of Pest Science, Volume 89(4), pp. 931–943
Buratti, S., Sinelli, N., Bertone, E., Venturello, A., Casiraghi, E., Geobaldo, F., 2014. Discrimination between Washed Arabica, Natural Arabica and Robusta Coffees by using Near Infrared Spectroscopy, Electronic Nose and Electronic Tongue Analysis. Journal of the Science of Food and Agriculture, Volume 95(11), pp. 2192–2200
Chen, Q., Zhao, J., Vittayapadung, S., 2008. Identification of the Green Tea Grade Level using Electronic Tongue and Pattern Recognition. Food Research International, Volume 41(5), pp. 500–504
Di Rosa, A.R., Leone, F., Cheli, F., Chiofalo, V., 2017. Fusion of Electronic Nose, Electronic Tongue and Computer Vision for Animal Source Food Authentication and Quality Assessment – A Review. Journal of Food Engineering, Volume 210, pp. 62–75
Dias, L.A., Peres, A.M., Veloso, A.C., Reis, F.S., Vilas-Boas, M., Machado, A.A., 2009. An Electronic Tongue Taste Evaluation: Identification of Goat Milk Adulteration with Bovine Milk. Sensors and Actuators B: Chemical, Volume 136(1), pp. 209–217
Fuentes, E., Alcañiz, M., Contat, L., Baldeón, E., Barat, J.M., Grau, R., 2017. Influence of Potential Pulses Amplitude Sequence in a Voltammetric Electronic Tongue (VET) Applied to Assess Antioxidant Capacity in Aliso. Food Chemistry, Volume 224(1), pp. 233–241
Haryuni, Dewi, T.S.K., Suprapti, E., Rahman, S.F., Gozan, M., 2019. The Effect of Beauveria bassiana on the Effectiveness of Nicotiana tabacum Extract as Biopesticide against Hypothenemus hampei to Robusta Coffee. International Journal of Technology, Volume 10(1), pp. 159–166
Iswanto, T., Hendrianie, N., Shovitri, M., Altway, A., Widjaja, T., 2019. The Effect of Mixed Biological Pretreatment and PEG 4000 on Reducing Sugar Production from Coffee Pulp Waste. International Journal of Technology, Volume 10(3), pp. 453–462
Lopetcharat, K., Kulapichitr, F., Suppavorasatit, I., Chodjarusawad, T., Phatthara-aneksin, A., Pratontep, S., Borompichaichartkul, C., 2016. Relationship between Overall Difference Decision and Electronic Tongue: Discrimination of Civet Coffee. Journal of Food Engineering, Volume 180, pp. 60–68
Mahachandra, M., Munzayanah, S., Yassierli, 2017. The Efficacy of One-time and Intermittent Intake of Coffee as a Countermeasure to Sleepiness on Partially Sleep-deprived Drivers. International Journal of Technology, Volume 8(2), pp. 300–310
Mehari, B., Redi-Abshiro, M., Chandravanshi, B.S., Combrinck, S., Atlabachew, M., McCrindle, R., 2016. Profiling of Phenolic Compounds using UPLC-MS for Determining the Geographical Origin of Green Coffee Beans from Ethiopia. Journal of Food Composition and Analysis, Volume 45, pp. 16–25
Parra, V., Arrieta, A.A., Fernández-Escudero, J., Rodríguez-Méndez, M.L., De Saja, J.A., 2006. Electronic Tongue based on Chemically Modified Electrodes and Voltammetry for the Detection of Adulterations in Wines. Sensors and Actuators B, Volume 118(1-2), pp. 448–453
Sanja, R.A., Carasekb, E., Janusz, P., 2008. Headspace Solid-phase Microextraction–gas Chromatographic–Time-of-Flight Mass Pectrometric Methodology for Geographical Origin Verification of Coffee. Analytica Chimica Acta, Volume 617(1-2), pp. 72–84
Thorburn-Burns, D., Tweed, L., Walker, M.J., 2017. Ground Roast Coffee: Review of Analytical Strategies to Estimate Geographic Origin, Species Authenticity and Adulteration by Dilution. Food Analytical Methods, Volume 10(7), pp. 2302–2310