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White radish sliced at 4 mm thickness was dehydrated by traditional osmotic dehydration (TOD) with nine types of osmotic solutions prepared by a randomized combining three levels concentration of sucrose and sodium chloride. The mass transfer characteristics were evaluated through the moisture diffusivity (Dm) and solid diffusivity (Ds), the fit of model was also estimated based on three popular models, including Newton, Henderson, and Pabis and Weibull. The results showed that white radish had the highest Dm and Ds value in the 4% salt and 15% sucrose solution, which presented that the fastest transfer process occurred in this solution. In addition, the Weibull model was the best model due to the highest R2 and the lowest root mean square error and chi-square, which means this model could fully describe the mass transfer (moisture/solid transfer) behavior of white radish.

This study evaluated surface water quality changes in Ben Tre province using multivariate statistical analyses. The water monitoring data were collected from the Department of Natural Resources and Environment of Ben Tre province in 2020, which 13 water parameters have been measured, including pH, water temperature (T), salinity (Sal), turbidity (Turb), total suspended solids (TSS), dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonium (NH4+_N), nitrate (NO3-_N), orthophosphate (PO43-_P), iron (Fe) and coliform bacteria. Water quality was assessed using national technical regulations on surface water quality of QCVN 08-MT: 2015/BTNMT. Spatiotemporal variation of water quality was evaluated using cluster analysis (CA) while potential pollution sources and key water variables influencing water quality were evaluated using principal component analysis (PCA). The findings showed that the water parameters of turbidity, salinity, TSS, DO, BOD, COD, NH4+_N, PO43-_P, Fe and coliform exceeded the allowable limits of QCVN 08-MT:2015/BTNMT. The water parameters of BOD, COD, NO3-_N, PO43-_P in the rainy season tended to be higher than those in the dry season. Cluster analysis divided surface water quality into 7 clusters, thus reducing 8 sampling sites, and 2 monitoring times of frequency. Principal component analysis identified 13 potential pollution sources affecting surface water quality in the study area, in which, 76.10 % of the variation in surface water quality were contributed by PC1, PC2, PC3, PC4 and PC5. PCA results also showed that 13 observed water parameters significantly contribute to the variation in water quality. The current study results could be very useful in reducing sites and frequency of surface water quality monitoring in Ben Tre province. HIGHLIGHTS The water quality in the study area was polluted by suspended particulate matters, organics, nutrients, heavy metals and salinity. Thirteen potential water pollution sources have been identified by principal component ananlysis (PCA), in which, 76.1 % of surface water quality variations were explained by five key sources sources of PC1-PC5 The water quality parameters of BOD, COD, NO3-_N, PO43-_P in the rainy season tended to be higher than those in the dry season Cluster analysis (CA) suggested the current surface water monitoring sites and frequency of the sampling could be reduced by 8 and 2, respectively, thus, saving the monitoring cost GRAPHICAL ABSTRACT