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Vicia faba, also known as “bakla” in Turkey, is a species of Fabaceae family that is widely grown in Africa and Asia. It is rich in levodopa, a medicinal substance used to treat Parkinson's disease. Levodopa produced by chemical synthesis is expensive and causes various side effects. Therefore, it is recommended to use natural levodopa sources to prevent possible side effects. A Central Composite Design technique has been used in this study to optimize levodopa extraction from Vicia faba. First, a single factor analysis examined 3 variables such as extraction temperature, extraction time, and concentration of acetic acid. The purpose of this study was to assess the effects of variables chosen on levodopa's extraction performance. By using variance and regression analyses, a second-order regression equation was determined as a predicted model. The value of R2 is 0.9882, which shows that the equation fits well. The best conditions are as follows: a temperature of 59.85 °C, an extraction time of 18.74 min, and an acetic acid content of 0.28%. Under optimum conditions, the maximum levodopa yield calculated from the predicted module was 4.53%. Extraction efficiency was determined as 4.54% experimentally under optimum conditions. A good relationship has been found between the experimental result and the predicted value.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
281--288
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
autor
- Uşak University, Uşak 64200, Turkey
Bibliografia
- [1] Pulikkalpura, H.; Kurup, R.; Mathew, P. J.; Baby, S. Sci. Rep. 2015, 5, 11078.
- [2] Baranowska, I.; Płonka, J. Food Anal. Methods 2015, 8, 963.
- [3] Pugalenthi, M.; Vadivel, V. Food 2007, 1, 322.
- [4] FAO Food and Agriculture Organization of the United Nations. Agriculture Database. 2016. Available online: http://www.fao.org/faostat/en/#data/QC (accessed on 22 October 2018).
- [5] Jankovic J. Neurology 2002, 58, 19.
- [6] Fahn S. Ann. NY Acad. Sci. 2003, 991, 1.
- [7] Purves, R. W.; Zhang, H.; Khazaei, H.; Vandenberg, A. Int. J. Ion Mobil. Spectrom. 2017, 20, 125.
- [8] Etemadi, F.; Hashemi, M.; Randhir, R. Z.; Vakili, O. Ebadi, A. Crop J. 2018, 6, 426.
- [9] Cardador, M. A.; Maya, O. K.; Ortiz, M. A.; Herrera, C. B. E.; Dávila, O. G.; Múzquiz, M.; Martín, P. M.; Burbano, C.; Cuadrado, C.; Jiménez, M. C. J. Food Qual. 2012, 35, 419.
- [10] Bezerra, M. A.; Santelli, R. E.; Oliveira, E. P.; Villar, L. S.; Escaleira, L. A. Talanta 2008, 76, 965.
- [11] Chen, Y. Y.; Luo, H. Y.; Gao, A. P.; Zhu, M. Food Anal. Methods 2012, 5, 800.
- [12] Liu, X. L.; Mu, T. H.; Sun, H. N.; Zhang, M. Food Chem. 2013, 141, 3034.
- [13] Wu, S. H.; Gong, G. L.; Wang, Y. Y.; Li, F. Int. J. Biol. Macromol. 2013, 61, 63.
- [14] Lan, M. B.; Guo, J.; Zhao, H. L.; Yuan, H. H. Asian J. Chem. 2012, 24, 2290.
- [15] Hong, Y. K.; Liu, W. J.; Li, T.; She, S. Y. Carbohydr. Polym. 2013, 92, 1761.
- [16] Maran, J. P.; Manikandan, S.; Thirugnanasambandham, K.; Nivetha, C. V.; Dinesh, R. Carbohydr. Polym. 2013, 92, 604.
- [17] Zhu, T.; Heo, H. J.; Row, K. H. Chem. Res. Chin. Univ. 2012, 28, 620.
- [18] Maran, J. P.; Mekala, V.; Manikandan, S. Carbohydr. Polym. 2013, 92, 2018.
- [19] Box, G. E. P.; Hunter, J. S. Ann. Math. Stat. 1957, 28, 195.
- [20] Samavati V. Int. J. Biol. Macromol. 2013, 61, 142.
- [21] Maran, J. P.; Sivakumar, V.; Sridhar, R.; Immanuel, V. P. Ind. Crops Prod. 2013, 42, 159.
- [22] Atkinson, A. C.; Donev, A. N. Clarendon Press. Britain 1992, 132.
- [23] Polanowska, K.; Lukasik, R. M.; Kuligowski, M.; Nowak, J. Molecules. 2019, 24, 2325.
- [24] Xu, D. P.; Zhou, Y.; Zheng, J.; Li, S.; Li, A. N.; Li, H. B. Molecules 2016, 21, 18.
Uwagi
PL
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7229687c-c9f3-4dad-95be-4cd44fb94b92