Significant waste resources are generated in the form of water-oil emulsions.These emulsions cannot be effectively destroyed on an industrial scale by traditional methods that rely on the settling of the aqueous phase...Significant waste resources are generated in the form of water-oil emulsions.These emulsions cannot be effectively destroyed on an industrial scale by traditional methods that rely on the settling of the aqueous phase,and therefore,they accumulate in large quantities.Thermomechanical dehydration,based on the evaporation of the water phase,presents a promising process for recycling such waste.However,within the framework of thermomechanical dehydration,the issue of optimizing energy costs for heating raw materials and controlling the water content in the product arises.Standard methods of determining water content under the boiling conditions of highly stable water-hydrocarbon emulsions are characterized by low efficiency,as they require constant sampling and the involvement of additional equipment and personnel.Consequently,this presents a challenge in predicting and creating an automated thermomechanical dehydration process.Therefore,dynamic curves depicting changes in the water content of these emulsions,depending on the temperature of the boiling liquid,have been obtained.It is proposed to determine the rate of temperature increase(dT/dt)of the boiling emulsion for continuous,real-time monitoring of the residual water content and for recording the moment of complete dehydration.Achieving a boiling emulsion temperature of 130-170℃(or higher)and/or the rate of temperature increase from 3.0 to 5.5(or above)indicates the complete dehydration of the emulsion.The proposed method can be implemented in any industrial or laboratory-scale unit for thermomechanical dehydration without significant capital costs.It is based on the use of simple devices consisting of temperature sensors and a computing unit for determining the temperature and rate of heating.展开更多
In order to ensure that the intake of iodine from iodized salt is adequate, the effects of cooking, storage and iedination on iodine content in iodized salt have been studied. For moni toring the analytical Performanc...In order to ensure that the intake of iodine from iodized salt is adequate, the effects of cooking, storage and iedination on iodine content in iodized salt have been studied. For moni toring the analytical Performance, a qoality control exawhnation was also undertaken. The loss of iodine was greater when salt was stored in plastic bag than in glass bottle. The loss was greater in fortified salt stored at 37℃ and under 76% humidity than in that at 20 ~ 25℃ and under lower humidity. The retention of iodine varied with the kind of has and also was influenced by the water content of cooked food. In general, the retention of iodine during cooking varied considerably (from 36. 6% to 86. 1 % ). The iodine concentration in salts varied greater from 3.0 to 100.3 mg/kg in salt for markets, and from 0 to 90.0 mg/kg in salts for households. 48. 3 % of samples from markets were found to be in compliance with national standards (30 ~ 50 mg/kg), and 72.0% of samples from households were in compliance with national standartl (20 ~ 50 mg/kg). Analytical data collected from 8 of the cooperative laheratories foran analytical reference material showed a 95% codridence interval of the population mean for both precision and accuracy, falling within X± 2SD and passing quality control exdrination展开更多
The change in the maize moisture content during different growth stages is an important indicator to evaluate the growth status of maize.In particular,the moisture content during the grain-filling stage reflects the g...The change in the maize moisture content during different growth stages is an important indicator to evaluate the growth status of maize.In particular,the moisture content during the grain-filling stage reflects the grain quality and maturity and it can also be used as an important indicator for breeding and seed selection.At present,the drying method is usually used to calculate the moisture content and the dehydration rate at the grain-filling stage,however,it requires large sample size and long test time.In order to monitor the change in the moisture content at the maize grain-filling stage using small sample set,the Bootstrap re-sampling strategy-sample set partitioning based on joint x-y distances-partial least squares(Bootstrap-SPXY-PLS)moisture content monitoring model and near-infrared spectroscopy for small sample sizes of 10,20,and 50 were used.To improve the prediction accuracy of the model,the optimal number of factors of the model was determined and the comprehensive evaluation thresholds RVP(coefficient of determination(R^(2)),the root mean square error of cross-validation(RMSECV)and the root mean square error of prediction(RMSEP))was proposed for sub-model screening.The model exhibited a good performance for predicting the moisture content of the maize grain at the filling stage for small sample set.For the sample sizes of 20 and 50,the R^(2) values were greater than 0.99.The average deviations of the predicted and reference values of the model were 0.1078%,0.057%,and 0.0918%,respectively.Therefore,the model was effective for monitoring the moisture content at the grain-filling stage for a small sample size.The method is also suitable for the quantitative analysis of different concentrations using near-infrared spectroscopy and small sample size.展开更多
文摘Significant waste resources are generated in the form of water-oil emulsions.These emulsions cannot be effectively destroyed on an industrial scale by traditional methods that rely on the settling of the aqueous phase,and therefore,they accumulate in large quantities.Thermomechanical dehydration,based on the evaporation of the water phase,presents a promising process for recycling such waste.However,within the framework of thermomechanical dehydration,the issue of optimizing energy costs for heating raw materials and controlling the water content in the product arises.Standard methods of determining water content under the boiling conditions of highly stable water-hydrocarbon emulsions are characterized by low efficiency,as they require constant sampling and the involvement of additional equipment and personnel.Consequently,this presents a challenge in predicting and creating an automated thermomechanical dehydration process.Therefore,dynamic curves depicting changes in the water content of these emulsions,depending on the temperature of the boiling liquid,have been obtained.It is proposed to determine the rate of temperature increase(dT/dt)of the boiling emulsion for continuous,real-time monitoring of the residual water content and for recording the moment of complete dehydration.Achieving a boiling emulsion temperature of 130-170℃(or higher)and/or the rate of temperature increase from 3.0 to 5.5(or above)indicates the complete dehydration of the emulsion.The proposed method can be implemented in any industrial or laboratory-scale unit for thermomechanical dehydration without significant capital costs.It is based on the use of simple devices consisting of temperature sensors and a computing unit for determining the temperature and rate of heating.
文摘In order to ensure that the intake of iodine from iodized salt is adequate, the effects of cooking, storage and iedination on iodine content in iodized salt have been studied. For moni toring the analytical Performance, a qoality control exawhnation was also undertaken. The loss of iodine was greater when salt was stored in plastic bag than in glass bottle. The loss was greater in fortified salt stored at 37℃ and under 76% humidity than in that at 20 ~ 25℃ and under lower humidity. The retention of iodine varied with the kind of has and also was influenced by the water content of cooked food. In general, the retention of iodine during cooking varied considerably (from 36. 6% to 86. 1 % ). The iodine concentration in salts varied greater from 3.0 to 100.3 mg/kg in salt for markets, and from 0 to 90.0 mg/kg in salts for households. 48. 3 % of samples from markets were found to be in compliance with national standards (30 ~ 50 mg/kg), and 72.0% of samples from households were in compliance with national standartl (20 ~ 50 mg/kg). Analytical data collected from 8 of the cooperative laheratories foran analytical reference material showed a 95% codridence interval of the population mean for both precision and accuracy, falling within X± 2SD and passing quality control exdrination
基金This work was financially supported by the grant from the International Cooperation and Exchange of the National Natural Science Foundation of China(No.31811540396),Chinathe National Natural Science Foundation of China(No.31701318),Chinathe Training Project of Heilongjiang Bayi Agricultural University,China(No.XZR2016-09).
文摘The change in the maize moisture content during different growth stages is an important indicator to evaluate the growth status of maize.In particular,the moisture content during the grain-filling stage reflects the grain quality and maturity and it can also be used as an important indicator for breeding and seed selection.At present,the drying method is usually used to calculate the moisture content and the dehydration rate at the grain-filling stage,however,it requires large sample size and long test time.In order to monitor the change in the moisture content at the maize grain-filling stage using small sample set,the Bootstrap re-sampling strategy-sample set partitioning based on joint x-y distances-partial least squares(Bootstrap-SPXY-PLS)moisture content monitoring model and near-infrared spectroscopy for small sample sizes of 10,20,and 50 were used.To improve the prediction accuracy of the model,the optimal number of factors of the model was determined and the comprehensive evaluation thresholds RVP(coefficient of determination(R^(2)),the root mean square error of cross-validation(RMSECV)and the root mean square error of prediction(RMSEP))was proposed for sub-model screening.The model exhibited a good performance for predicting the moisture content of the maize grain at the filling stage for small sample set.For the sample sizes of 20 and 50,the R^(2) values were greater than 0.99.The average deviations of the predicted and reference values of the model were 0.1078%,0.057%,and 0.0918%,respectively.Therefore,the model was effective for monitoring the moisture content at the grain-filling stage for a small sample size.The method is also suitable for the quantitative analysis of different concentrations using near-infrared spectroscopy and small sample size.
