Lab-made electronic-nose with polyaniline sensor array used in classification of different aromas in gummy candies
Graphical abstract
Introduction
Confectionery products represent approximately 39% of the world's sweet consumption (Godshall, 2016). The positive prospects for market growth in gummy candy consumption increase sensory requirements demanded by the consumers, such as; texture, good clarity and gloss, absence of turbidity, and attractive flavor and aroma (Periche, Heredia, Escriche, Andrés, & Castelló, 2014; Pizzoni, Compagnone, Di Natale, D'Alessandro, & Pittia, 2015).
Aroma, as well as flavor, are used as a quality parameter and product conformity indicator, intimately related to the product's acceptance by the consumers. For instance, the flavor of any food is strongly influenced by its aroma, since the chemical perception provided by the food flavor is due to the presence of sufficient volatile small molecules that reach the nasal sensory receptors while eating (Firestein, 2001; Plutowska & Waldemar, 2007; Santonico et al., 2008).
Aroma profile monitoring is one of the key factors that lead consumers to either accept or not the product (Santonico et al., 2008). Interactions between food matrix components and aroma compounds could decrease the release of aroma volatiles causing different product odor perceptions, disturbing the aroma profile.
Limitations on the sensory analysis technique, commonly used in aromas monitoring (Banerjee et al., 2012), reinforces the need for the use of complementary instrumental methods, allowing a more detailed qualitative analysis (Wyllie, 2008).
Electronic nose (E-nose) systems based on an array of non-specific or low-selectivity chemical sensors, especially the ones based on multi-constituent and global selectivity analysis have called great attention on the detection of volatile compounds released from the aromas of various products, mainly due to fast analysis and a non-destructive characteristic (Wei, Wang, & Zhang, 2015). The development of signal processing methods based on Artificial Intelligence (AI) and of patterns recognition contributes significantly to the development of sensors' science and technology. A wide variety of sensors has been developed using conductive polymers as the active layer (Bai & Shi, 2007). Among the conductive polymers, polyaniline (Pani) has been at the forefront due to its ease of polymerization, stable electric conduction mechanisms, high chemical stability at room temperature, low cost, and reversible chemical doping (Fratoddi, Iole, Cesare, & Maria, 2015).
E-nose systems have been properly used in the analysis of aromas release profile from different food matrices (Bakouri, José, José, Eva, & Hilario, 2010; Drake, Stephenie, Floyd, Stephanie, & Michael, 2008; Loutfi, Silvia, Ganesh, Prabakaran, & John, 2015; Wilson & Baietto, 2009). The data of different food matrix composition obtained by this sytem could be discriminate and classify with statistical techniques (Pizzoni et al., 2015).
This work reports the use of a lab-made E-nose system based on an array of different Pani sensors on the discrimination of different concentrations from 3 different artificial aromas (apple, strawberry and grape), added to the gummy candies. The different sensory units have been made using different Pani synthesis, deposited on gold interdigitated microelectrodes (IDEs) using two different methods (in-situ and LbL). The processing methods used were based on patterns recognition and multivariate analysis done with the Linear Discrimination Analysis (LDA).
Section snippets
Sample preparation
The gummy candies were prepared as described by Periche et al. (2014). 6–10% of gelatin powder (Synth) was hydrated with 40% of distilled water for ±10 min and then, 50–54% of sucrose (Gasparin) was added to the solution. Then, aroma concentrations of 0; 2.5; 5; 7.5 and 10 ppm w/v were added to the solution. The apple, strawberry, and grape artificial aromas were obtained from Duas Rodas Company (Brazil) and used as received. According to the Company, each aroma composition is described as
Characterization of gas sensors with different Pani films
The successful Pani and Pani/PSS films formation obtained respectively by in situ and LbL depositions was confirmed by ATR/FTIR spectroscopy, Fig. 3. The main vibrational bands were observed at 1592–1580 cm−1, attributed to CN quinone ring stretching vibrations, at 1490 cm−1 associated with CN benzene ring stretching vibrations, and to 1308 cm−1 attributed to CN stretching mode (McCarthy, Jianyu, Sze-Cheng, & Hsing-Lin, 2002). The 1200 cm−1 band shifting in Pani film spectrum at 1592 cm−1 to a
Conclusion
ATR/FTIR technique confirmed the adequate Pani and Pani/PSS adsorption in the films on IDEs, respectively using the in situ and LbL deposition methods. Deposition methods influenced the particle structure of different Pani films, which was verified with the different Rrms values obtained using AFM technique.
The Pani-in situ/PSS LbL sensing unit presented the best sensitivity and limit of detection to different concentrations of aromas added to gummy candies. All investigated gas sensors showed
Acknowledgments
The authors thank to FAPESP, CNPq and Capes for the financial support. Acknowledgments are also given to Angelo L. Gobbi and Maria H. O. Piazzetta for use of Microfabrication Laboratory facilities (LMF/LNNano-LNLS).
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