A one-dimensional hydraulic HEC-RAS model was developed to forecast the change in salinity in the tributaries of the Co Chien and Hau Rivers in Tra Vinh province, Vietnam. The boundary data includes river discharge at Can Tho and My Thuan, water levels, and salinity at coastal monitoring stations. Six monitoring stations along the Co Chien River and Hau River were selected to study salinity changes. Four scenarios for the period 2020–2050 were selected, including SLR17, SLR22, SLR26L, and SLR26H, corresponding to sea level rise (17, 22, and 26 cm) and upstream river discharge decrease (in the ranges of 100–128% and 80–117% at Can Tho and My Thuan, respectively) in the dry season based on new climate change scenarios in Vietnam and previous studies. The results highlight that when the average discharge at Can Tho and My Thuan reduces, the salinity increases more significantly than the impact of sea level rise. Salinity at the monitoring stations in Tra Vinh province is projected to increase within the ranges of 4–21% and 3–29% along the Co Chien River and Hau River, respectively. In addition, sea level rise is seen to affect the discharge distribution into the Co Chien River. It suggests an urgent need to raise farmers’ awareness of climate change adaptation, investment in production equipment, and appropriate regulation of riverbed mining and activities upstream in the Mekong River.
The hydrolysis of germ rice by the use of α-amylase and glucoamylase enzymes will help increase the reducing sugar content, reduce viscosity, and improve the yield of milk solution compared to the traditional extraction method. The liquefaction experiment was arranged with two factors, which are substrate ratio: α-amylase concentration and α-amylase concentration: different hydrolysis time. The saccharification experiment was carried out based on a multivariate model according to the Central Composite Design method. As a result, a 1 : 2 substrate ratio, 0.5% α-amylase concentration (approx. 11U/g starch) and 50 minutes hydrolysis time were selected as the basis for the next experiment. Analysis of variance in the regression model showed that the quadratic model was significant (p < 0.0001). Lack of fit (p > 0.05) this indicates that the model is suitable for all data. The reliability of the model R2 = 0.993 shows that the built regression model fits the data set 99.3%. CV = 1.19% indicated a better precision and reliability of the experiments carried out. Optimal conditions for hydrolysis of glucoamylase concentration of 0.399% (approx. 119.863U/g starch), temperature of 59.813°C and hydrolysis time of 160.468 minutes gave the highest DE content at 25.245% and higher than the non-enzymatic method (DE = 8.985 ± 0.062).
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