ABSTRACT
The variations of volatile organic compounds (VOCs) and microbial communities of three pickles during storage at 4°C for one week were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), high-throughput sequencing, and Spearman correlation analysis. A total of 50 VOCs were identified from three pickles. During storage, most alcohols, aldehydes, ketones, and esters decreased, while acids increased, and sulfides, alkenes, and phenols were relatively equal. Firmicutes, Cyanobacteria, and Proteobacteria were the predominant bacterial phyla, and Weissella, Streptophyta, Leuconostoc, Bacillariophyta, and Lactobacillus were the predominant bacterial genera in three pickles. The bacterial diversity level significantly decreased during storage (P < 0.05). Spearman correlation coefficient indicated that Leuconostoc, Lactobacillus, and Weissella were highly correlated with the flavor of pickles, while Bacillariophyta and Streptophyta were highly correlated with the flavor formation of pickles during storage. These results could contribute to a better understanding of the impact of bacteria in flavor formation during pickle storage.
Subject(s)
Fermented Foods , Microbiota , Volatile Organic Compounds , Volatile Organic Compounds/analysis , Gas Chromatography-Mass Spectrometry/methods , Food , Bacteria/genetics , Fermented Foods/analysisABSTRACT
In this study, the optimal extraction conditions for the total flavonoids of Sedum aizoon L. (STF) were optimized by response surface methodology. Evaluation of the antioxidant in vitro of STF, and modulatory effects of glucolipid metabolism, and oxidative stress in mice with type 1 diabetes mellitus (T1DM). STF showed good antioxidant capacity in vitro. STF could improve glucolipid metabolism, organ coefficients, and antioxidant stress enzymes in T1DM mice effectively, reduce the damage to liver tissue, and regulate redox imbalance in the organism by modulating the Nrf2/Keap1/ARE signaling pathway. The results of this study could provide a theoretical reference for the application of Sedum aizoon L. in the development of auxiliary hypoglycemic functional foods and improvement of diabetes.
ABSTRACT
Snowmelt runoff is the main non-point pollution source of receiving water in the high latitude cities of north China in Spring. In order to control the pollution of surface water body by the snowmelt runoff, the pollution characteristics of 6 kinds of underlying surfaces and 18 sampling points in the main urban area of Harbin were analyzed from late March to early April 2015. Through software SPSS 22.0 and its principal component analysis method, BOD5, COD, ammonia nitrogen, TP (total phosphorus), petroleum and TN (total nitrogen) were identified as the significant pollution indexes of the snowmelt runoff in the main urban area of Harbin. Single factor ANOVA (Analysis of Variance) and its LSD (Least Significant Difference) multiple comparisons method were adopted to analyze the pollution difference among underlying surface groups and between two kinds of underlying surfaces. The results of AVOVA analysis showed that the difference of TP in all kinds of underlying surface was the largest and that of BOD5 was the least, and the significant levels (Sig.) were 0.342 and 0.631, respectively. The results of multiple comparisons showed that the MeanDiffs (Mean Difference) between two underlying surfaces of different pollutants were different, and the contribution rates of different pollution index were different too. Meanwhile, due to the influence of geographical position, for the same pollutant, there were differences in different sampling points of the same underlying surface, especially in city road and pavement. Pollution characteristics of snowmelt runoff on different underlying surface showed that the snowmelt runoff pollution in the main urban area of Harbin was mainly affected by the traffic flow, human activities, coal fired heating in winter and industrial emissions.
