A novel method for classification of wine based on organic acids
Samo za registrovane korisnike
2019
Autori
Milovanović, MiodragZeravik, Jiri
Oboril, Michal
Pelcova, Marta
Lacina, Karel
Čakar, Uroš D.
Petrović, Aleksandar

Glatz, Zdenek
Skladal, Petr
Članak u časopisu (Objavljena verzija)

Metapodaci
Prikaz svih podataka o dokumentuApstrakt
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.
Ključne reči:
Carboxylic acids / Capillary electrophoresis / Biosensor / Principal component analysis / Self-organizing mapIzvor:
Food Chemistry, 2019, 284, 296-302Izdavač:
- Elsevier Sci Ltd, Oxford
Finansiranje / projekti:
- 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
Institucija/grupa
Poljoprivredni fakultetTY - JOUR AU - Milovanović, Miodrag AU - Zeravik, Jiri AU - Oboril, Michal AU - Pelcova, Marta AU - Lacina, Karel AU - Čakar, Uroš D. AU - Petrović, Aleksandar AU - Glatz, Zdenek AU - Skladal, Petr PY - 2019 UR - http://aspace.agrif.bg.ac.rs/handle/123456789/5035 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 EP - 302 SP - 296 VL - 284 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 D. and Petrović, Aleksandar 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", pages = "302-296", volume = "284", doi = "10.1016/j.foodchem.2019.01.113" }
Milovanović, M., Zeravik, J., Oboril, M., Pelcova, M., Lacina, K., Čakar, U. D., Petrović, A., 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 UD, Petrović A, 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 D., Petrović, Aleksandar, 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 . .