A novel method for classification of wine based on organic acids
Authorized Users Only
2019
Authors
Milovanović, MiodragZeravik, Jiri
Oboril, Michal
Pelcova, Marta
Lacina, Karel
Čakar, Uroš

Petrović, Aleksandar V.

Glatz, Zdenek
Skladal, Petr
Article (Published version)

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Show full item recordAbstract
Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods - principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classif...ication.
Keywords:
Carboxylic acids / Capillary electrophoresis / Biosensor / Principal component analysis / Self-organizing mapSource:
Food Chemistry, 2019, 284, 296-302Publisher:
- Elsevier Sci Ltd, Oxford
Funding / projects:
- Masaryk University - MUNI/A/1100/2017
DOI: 10.1016/j.foodchem.2019.01.113
ISSN: 0308-8146
PubMed: 30744861
WoS: 000458119700038
Scopus: 2-s2.0-85060937630
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Institution/Community
PharmacyTY - JOUR AU - Milovanović, Miodrag AU - Zeravik, Jiri AU - Oboril, Michal AU - Pelcova, Marta AU - Lacina, Karel AU - Čakar, Uroš AU - Petrović, Aleksandar V. AU - Glatz, Zdenek AU - Skladal, Petr PY - 2019 UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3296 AB - Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods - principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classification. PB - Elsevier Sci Ltd, Oxford T2 - Food Chemistry T1 - A novel method for classification of wine based on organic acids VL - 284 SP - 296 EP - 302 DO - 10.1016/j.foodchem.2019.01.113 ER -
@article{ author = "Milovanović, Miodrag and Zeravik, Jiri and Oboril, Michal and Pelcova, Marta and Lacina, Karel and Čakar, Uroš and Petrović, Aleksandar V. and Glatz, Zdenek and Skladal, Petr", year = "2019", abstract = "Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods - principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classification.", publisher = "Elsevier Sci Ltd, Oxford", journal = "Food Chemistry", title = "A novel method for classification of wine based on organic acids", volume = "284", pages = "296-302", doi = "10.1016/j.foodchem.2019.01.113" }
Milovanović, M., Zeravik, J., Oboril, M., Pelcova, M., Lacina, K., Čakar, U., Petrović, A. V., Glatz, Z.,& Skladal, P.. (2019). A novel method for classification of wine based on organic acids. in Food Chemistry Elsevier Sci Ltd, Oxford., 284, 296-302. https://doi.org/10.1016/j.foodchem.2019.01.113
Milovanović M, Zeravik J, Oboril M, Pelcova M, Lacina K, Čakar U, Petrović AV, Glatz Z, Skladal P. A novel method for classification of wine based on organic acids. in Food Chemistry. 2019;284:296-302. doi:10.1016/j.foodchem.2019.01.113 .
Milovanović, Miodrag, Zeravik, Jiri, Oboril, Michal, Pelcova, Marta, Lacina, Karel, Čakar, Uroš, Petrović, Aleksandar V., Glatz, Zdenek, Skladal, Petr, "A novel method for classification of wine based on organic acids" in Food Chemistry, 284 (2019):296-302, https://doi.org/10.1016/j.foodchem.2019.01.113 . .