Liu Qi,Wang Li,Hu Jie,Miao Yanni,Wu Zixue,Li Jianrong
A rapid and sensitive analytical method for the determination of main organic acids in wines was developed by capillary electrophoresis (CE) with indirect UV detection. Separation parameters including the pH of electrolyte, chromophore, and its concentration were optimized. The results showed that the optimal electrolyte for the separation of organic acids consisted of 10 mmol L −1 2, 4-dihydroxybenzoic acid (DHBA) at pH 3.6 containing 0.4 mmol L −1 cetyltrimethlammonium bromide (CTAB). DHBA as chromphore was selected based on the close mobility to the analyte and relatively large molar extinction coefficient. The method showed good linearity with limits of detection (LOD), ranging from 0.5 to 7.5 mg L −1 . The relative standard deviation (RSD) of interday precisions for the peak area and the migration time were less than 7.2 and 0.8 %, respectively. The recoveries of the analyte in Chinese rice wine sample were between 90.3 and 106.9 % with RSD ranging from 1.4 to 8.9 %. The method was successfully applied to the commercial rice wine and beer samples with dilution and filtration.
Bifunctional acid urease can not only remove urea from rice wine, but also effectively remove ethyl carbamate (EC), thereby reducing harmful substances in rice wine. Acid urease from Providencia rettgeri JN-B815 was expressed in Escherichia coli BL21(DE3) as an inclusion body . Subsequently, acid urease was refolded gradually using dilution-ultrafiltration and specific activity of 12.3 U mg −1 was obtained. The acid urease thus obtained was immobilized on graphene oxide/chitosan beads. The recovery of immobilized urease was 77% for the graphene oxide/chitosan composite when coupled for 8 h with 5% glutaraldehyde. Steady-state kinetic analysis showed that the optimum temperature for urease activity was 37°C. Time-dependent thermal inactivation studies showed that the stability of the immobilized urease improved at 37°C and the t 1/2 (half-life) of decay in urease activity was 12 h, whereas it was 43 days for soluble and chitosan/graphene oxide immobilized urease at 4°C. A significant change in K m occurred during the immobilization; the Km for urea and EC in the free state were 9.14 mM and 386 mM, respectively, whereas they were 5.28 mM and 180 mM, respectively, in the immobilized state. The values of V max for immobilized EC and urea were 1.08 μmol min −1 and 1.16 μmol min −1 , respectively, whereas they were 0.782 μmol min −1 and 0.931 μmol min −1 , respectively, for soluble EC and urea. Furthermore, 90% of the original activity of graphene oxide/chitosan–urease beads were retained after the beads were used 10 times, indicating excellent reusability.
Zhenbo Wei,Yanan Yang,Luyi Zhu,Weilin Zhang,Jun Wang
In this paper, poly(acid chrome blue K) (PACBK)/AuNP/glassy carbon electrode (GCE), polysulfanilic acid (PABSA)/AuNP/GCE and polyglutamic acid (PGA)/CuNP/GCE were self-fabricated for the identification of rice wines of different brands. The physical and chemical characterization of the modified electrodes were obtained using scanning electron microscopy and cyclic voltammetry, respectively. The rice wine samples were detected by the modified electrodes based on multi-frequency large amplitude pulse voltammetry. Chronoamperometry was applied to record the response values, and the feature data correlating with wine brands were extracted from the original responses using the ‘area method’. Principal component analysis, locality preserving projections and linear discriminant analysis were applied for the classification of different wines, and all three methods presented similarly good results. Extreme learning machine (ELM), the library for support vector machines (LIB-SVM) and the backpropagation neural network (BPNN) were applied for predicting wine brands, and BPNN worked best for prediction based on the testing dataset (R2 = 0.9737 and MSE = 0.2673). The fabricated modified electrodes can therefore be applied to identify rice wines of different brands with pattern recognition methods, and the application also showed potential for the detection aspects of food quality analysis.