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Abstract:

The objective of this work is to report the improvements obtained in the discrimination of complex aroma samples with subtle differences in odor pattern, by the use of a fast procedure suitable for the cases of measurements in the field demanding decision-making in real time using a portable electronic nose. This device consists of a sensor array which records changes in conductivity as a function of time when aroma molecules reach the sensors. The core of the method consists of applying unfolded cluster analysis to selected time windows (UCATW) within the temporal evolution of the aroma profile recorded by the gas sensors, yielding an efficient, fast, and reliable data analysis tool that is easy to perform for electronic nose users. The performance of this data handling was tested in two case studies of food adulteration. The results demonstrated that this methodology enables to discriminate highly similar samples, herewith reducing the probability of achieving a wrong grouping due to the use of flawed data. The automation of this type of analysis is simple and improves the efficiency of the device significantly, herewith reducing the time of sensor’s signal recording that is necessary for a reliable assessment of the studied system. The results were validated by clustering the sample component scores that are obtained by applying parallel factor analysis (PARAFAC) to the original three-dimensional data array. An additional validation was obtained by means of a leave-one-out resampling procedure. © 2014, Springer Science+Business Media New York.

Registro:

Documento: Artículo
Título:Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection
Autor:Rodríguez, S.D.; Barletta, D.A.; Wilderjans, T.F.; Bernik, D.L.
Filiación:Instituto de Química Física de Materiales, Ambiente y Energía (INQUIMAE), Universidad de Buenos Aires, Intendente Güiraldes 2160, Ciudad Universitaria, Buenos Aires, C1428EGA, Argentina
Methodology of Educational Sciences Research Group, Katholieke Universiteit Leuven, Andreas Vesaliusstraat 2, Box 3762, Leuven, 3000, Belgium
Palabras clave:Aroma discrimination; Electronic nose; Food quality assessment; Time-window selection; Unfolded cluster analysis; Chemical sensors; Cluster analysis; Data handling; Decision making; Electronic equipment; Odors; Vehicle routing; Aroma discrimination; Electronic NOSE; Food quality; Food quality controls; Parallel factor analysis; Portable electronic nose; Three-dimensional data; Time windows; Quality control
Año:2014
Volumen:7
Número:10
Página de inicio:2042
Página de fin:2050
DOI: http://dx.doi.org/10.1007/s12161-014-9841-7
Título revista:Food Analytical Methods
Título revista abreviado:Food Anal. Methods.
ISSN:19369751
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_19369751_v7_n10_p2042_Rodriguez

Referencias:

  • Calderisi, M., Livio, A., Frustace, D., Valentini, G., Cecchi, A., New multivariate approach for the handling of electronic nose data applied to composting process. Proceedings of the CMA4CH Mediterranean Meeting “Multivariate Analysis and Chemometrics applied to Environment and Cultural Heritage”, Nemi (RM) (2006) 2–4, , Italy: Europe
  • Chu, W., Ghahramani, Z., Probabilistic models for incomplete multi-dimensional arrays (2009) Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 89-96
  • Fu, J., Huang, C., Xing, J., Zheng, J., Pattern classification using an olfactory model with PCA feature selection in electronic noses: study and application (2012) Sensors, 12, pp. 2818-2830
  • Kiers, H.A.L., Towards a standardized notation and terminology in multiway analysis (2000) J Chemometr, 14, pp. 105-122. , COI: 1:CAS:528:DC%2BD3cXkt1Shsb8%3D
  • Lovino, M., Cardinal, M.F., Zubiri, D.B.V., Bernik, D.L., Electronic nose screening of ethanol release during sol-gel encapsulation. A novel non-invasive method to test silica polymerization (2005) Biosens Bioelectron, 21, pp. 857-862. , COI: 1:CAS:528:DC%2BD2MXhtFKhsbvO
  • MacQueen, J.B., Some methods for classification and analysis of multivariate observations. Proc. 5th Berkeley Symposium on Mathematical Statistics and Probability (1967) Statistics, 1, pp. 281-297
  • Mahmoudi, E., Electronic nose technology and its applications (2009) Sensors Transducers J, 107, pp. 17-25
  • Monge, M.E., Bulone, D., Giacomazza, D., Bernik, D.L., Negri, R.M., Detection of flavour release form pectin gels using electronic noses (2004) Sensors Actuators B Chem, 101, pp. 28-38. , COI: 1:CAS:528:DC%2BD2cXkt1Kitrk%3D
  • Padilla, M., Montoliu, I., Pardo, A., Perera, A., Marco, S., Feature extraction on three way enose signals (2006) Sensors Actuators B, 116, pp. 145-150. , COI: 1:CAS:528:DC%2BD28XltVeqs7k%3D
  • Pennazza, G., Santonicoa, M., FinazziAgrò, A., Narrowing the gap between breathprinting and disease diagnosis, a sensor perspective (2013) Sensors Actuators B, 179, pp. 270-275. , COI: 1:CAS:528:DC%2BC38Xhs1agtrfJ
  • Peris, M., Escuder-Gilabert, L., A 21st century technique for food control: electronic noses (2009) Anal Chim Acta, 638, pp. 1-15. , COI: 1:CAS:528:DC%2BD1MXjs1amsL8%3D
  • Rodríguez, S.D., Monge, M.E., Olivieri, A.C., Negri, R.M., Bernik, D.L., Time dependence of the aroma pattern emitted by an encapsulated essence studied by means of electronic noses and chemometric analysis (2010) Food Res Int, 43, pp. 797-804
  • Rousseeuw, P.J., Silhouettes: a graphical aid to the interpretation and validation of cluster analysis (1987) J Comput Appl Math, 20, pp. 53-65
  • Scott, S.M., James, D., Ali, Z., Data analysis for electronic nose systems (2006) Microchim Acta, 156, pp. 183-207. , COI: 1:CAS:528:DC%2BD28XhtlaitLvO
  • Skov, T., Bro, R., A new approach for modelling sensor based data (2005) Sensors Actuators B Chem, 106, pp. 719-729. , COI: 1:CAS:528:DC%2BD2MXjsFCgt7o%3D
  • Timmerman, M.E., Ceulemans, E., Kiers, H.A.L., Vichi, M., Factorial and reduced k-means reconsidered (2010) Comput Stat Data An, 54, pp. 1858-1871
  • Versari, A., Parpinello, G.P., Ricci, A., Meglioli, M., Relationship between chemical markers and sensory score of traditional balsamic vinegars using a screening approach combined with rapid assessment methods (2013) Food Anal Methods, 6, pp. 1697-1703
  • Vichi, M., Kiers, H.A.L., Factorial k-means analysis for two-way data (2001) Comput Stat Data An, 37, pp. 49-64
  • Vilanova, X., Llobet, E., Alcubilla, R., Sueiras, J.E., Correig, X., Analysis of the conductance transient in thick-film tin oxide gas sensors (1996) Sensors Actuators B Chem, 31, pp. 175-180. , COI: 1:CAS:528:DyaK28XlsVOrsbY%3D
  • Wang, X., Ye, M., Duanmu, C.J., Classification of data from electronic nose using relevance vector machines (2009) Sensors Actuators B, 140, pp. 143-148. , COI: 1:CAS:528:DC%2BD1MXmvFajs78%3D
  • Wedge, D.C., Das, A., Dost, R., Kettle, J., Madec, M.B., Morrison, J.J., Grell, M., Real-time vapour sensing using an OFET-based electronic nose and genetic programming (2009) Sensors Actuat B Chem, 143, pp. 365-372

Citas:

---------- APA ----------
Rodríguez, S.D., Barletta, D.A., Wilderjans, T.F. & Bernik, D.L. (2014) . Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection. Food Analytical Methods, 7(10), 2042-2050.
http://dx.doi.org/10.1007/s12161-014-9841-7
---------- CHICAGO ----------
Rodríguez, S.D., Barletta, D.A., Wilderjans, T.F., Bernik, D.L. "Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection" . Food Analytical Methods 7, no. 10 (2014) : 2042-2050.
http://dx.doi.org/10.1007/s12161-014-9841-7
---------- MLA ----------
Rodríguez, S.D., Barletta, D.A., Wilderjans, T.F., Bernik, D.L. "Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection" . Food Analytical Methods, vol. 7, no. 10, 2014, pp. 2042-2050.
http://dx.doi.org/10.1007/s12161-014-9841-7
---------- VANCOUVER ----------
Rodríguez, S.D., Barletta, D.A., Wilderjans, T.F., Bernik, D.L. Fast and Efficient Food Quality Control Using Electronic Noses: Adulteration Detection Achieved by Unfolded Cluster Analysis Coupled with Time-Window Selection. Food Anal. Methods. 2014;7(10):2042-2050.
http://dx.doi.org/10.1007/s12161-014-9841-7