An experimental study was performed to determine the characteristics and drying process of mushroom （Lentinus edodes） by 6 different hot-air drying methods namely isothermal drying, uniform raise drying, non-uniform...An experimental study was performed to determine the characteristics and drying process of mushroom （Lentinus edodes） by 6 different hot-air drying methods namely isothermal drying, uniform raise drying, non-uniform raise drying, uniform intermittent drying, non-uniform intermittent drying and combined drying. The chemical composition （dry matter, ash, crude protein, crude fat, total sugars, dietary fiber, and energy）, color parameters （L, a＊, b＊, c＊, and h~） and rehydration capacities were determined. Among all the experiments, non-uniform intermittent drying reached a better comprehensive results due to the higher chemical composition, better color quality associated with high bright （26.381＋5.842）, high color tone （73.670＋2.975）, low chroma （13.349a：3.456） as well as the highest rehydration （453.76% weigh of dried body）. Nine kinds of classical mathematical model were used to obtained moisture data and the Midili-kucuk model can be described by the drying process with the coefficient （R2 ranged from 0.99790 to 0.99967）, chi-square （X2 ranged from 0.00003 to 0.00019） and root mean square error （RMSE ranged from 0.000486 to 0.0012367）.展开更多
Background:To predict the moisture ratio of Radix isatidis extract during drying.Methods:Artificial neural networks were designed using the MATLAB neural network toolbox to produce a moisture ratio prediction model of...Background:To predict the moisture ratio of Radix isatidis extract during drying.Methods:Artificial neural networks were designed using the MATLAB neural network toolbox to produce a moisture ratio prediction model of Radix isatidis extract during hot air drying and vacuum drying,where regression values and mean squared error were used as evaluation indexes to optimize the number of hidden layer nodes and determine the topological structure of artificial neural networks model.In addition,the drying curves for the different drying parameters were analyzed.Results:The optimal topological structure of the moisture ratio prediction model for hot air drying and vacuum drying of Radix isatidis extract were“4-9-1”and“5-9-1”respectively,and the regression values between the predicted value and the experimental value is close to 1.This indicates that it has a high prediction accuracy.The moisture ratio gradually decreases with an increase in the drying time,reducing the loading,initial moisture content,increasing the temperature,and pressure can shorten the drying time and improve the drying efficiency.Conclusion:Artificial neural networks technology has the advantages of rapid and accurate prediction,and can provide a theoretical basis and technical support for online prediction during the drying process of the extract.展开更多
Pufferfish is prone to deterioration due to abundant nutrients and high moisture content.Drying technology can extend the shelf life and enhance the flavor quality of aquatic products.The study investigated the effect...Pufferfish is prone to deterioration due to abundant nutrients and high moisture content.Drying technology can extend the shelf life and enhance the flavor quality of aquatic products.The study investigated the effect of hot air drying(HAD),microwave vacuum drying(MVD)and hot air assisted radio frequency drying(HARFD)on the taste and volatile profiles of Takifugu obscurus.Different drying methods had significant influence on the color,rehydration,5’-nucleotides,free amino acids and volatile components(P<0.05).The results showed that HAD and HARFD could promote the flavor of T.obscurus by producing higher equivalent umami concentration(EUC)values,which were about two times of MVD group,and more pronounced pleasant odor according to sensory analysis.HAD is more appropriate for industrial application than HARFD and MVD considering the economic benefits.This study could provide a reference for the industrial application of drying T.obscurus.展开更多
花椒热风干燥降速期水分含量低,水分扩散慢,导致热风干燥耗时长。为提高干燥效率,并通过热风与微波组合干燥,分别进行热风干燥、微波干燥和热风-微波组合干燥实验,探究不同干燥参数对花椒失水特性的影响,以确定合理的干燥转换临界点和...花椒热风干燥降速期水分含量低,水分扩散慢,导致热风干燥耗时长。为提高干燥效率,并通过热风与微波组合干燥,分别进行热风干燥、微波干燥和热风-微波组合干燥实验,探究不同干燥参数对花椒失水特性的影响,以确定合理的干燥转换临界点和最优组合干燥模型,并将傅里叶准则数(F_(0))引入Fick第二扩散定律方程,求解有效水分扩散系数(D_(eff))。研究结果表明:热风和微波单独干燥时,升高风温风速和增加微波功率均有利于缩短干燥时间;热风-微波组合干燥花椒时,热风段转微波段的最佳目标含水率即为热风干燥的临界点含水率(65%(w.b)),且高热风温度和高微波功率均可使微波干燥段获得高失水速率;热风-微波组合干燥花椒热风段和微波段对应的最优模型分别为Wang and Singh模型和Page模型,D_(eff)范围分别为1.908×10^(-9)~3.547×10^(-9)m^(2)/s和1.883×10^(-8)~3.321×10^(-8)m^(2)/s。热风-微波组合干燥方式能够显著提高干燥效率,促进花椒内部水分扩散,干燥模型可为优化干燥工艺和设计干燥设备提供理论依据。展开更多
基金supported by the National High-Tech R&D Program of China(863 Program,2011AA100805-2)the Project from Chongqing Science and Technology Committee(CSTC2011AC1010)supported by the National Natural Science Foundation of China(31271825)
文摘An experimental study was performed to determine the characteristics and drying process of mushroom （Lentinus edodes） by 6 different hot-air drying methods namely isothermal drying, uniform raise drying, non-uniform raise drying, uniform intermittent drying, non-uniform intermittent drying and combined drying. The chemical composition （dry matter, ash, crude protein, crude fat, total sugars, dietary fiber, and energy）, color parameters （L, a＊, b＊, c＊, and h~） and rehydration capacities were determined. Among all the experiments, non-uniform intermittent drying reached a better comprehensive results due to the higher chemical composition, better color quality associated with high bright （26.381＋5.842）, high color tone （73.670＋2.975）, low chroma （13.349a：3.456） as well as the highest rehydration （453.76% weigh of dried body）. Nine kinds of classical mathematical model were used to obtained moisture data and the Midili-kucuk model can be described by the drying process with the coefficient （R2 ranged from 0.99790 to 0.99967）, chi-square （X2 ranged from 0.00003 to 0.00019） and root mean square error （RMSE ranged from 0.000486 to 0.0012367）.
基金found by Guizhou Province Science and Technology Plan Project(No.Qiankeheji-ZK(2021)General 533)Domestic First-Class Discipline Construction Project in Guizhou Province(No.GNYL(2017)008)Guizhou Province Drug New Formulation New Process Technology Innovation Talent Team Project(No.Qiankehe Platform Talents(2017)5655).
文摘Background:To predict the moisture ratio of Radix isatidis extract during drying.Methods:Artificial neural networks were designed using the MATLAB neural network toolbox to produce a moisture ratio prediction model of Radix isatidis extract during hot air drying and vacuum drying,where regression values and mean squared error were used as evaluation indexes to optimize the number of hidden layer nodes and determine the topological structure of artificial neural networks model.In addition,the drying curves for the different drying parameters were analyzed.Results:The optimal topological structure of the moisture ratio prediction model for hot air drying and vacuum drying of Radix isatidis extract were“4-9-1”and“5-9-1”respectively,and the regression values between the predicted value and the experimental value is close to 1.This indicates that it has a high prediction accuracy.The moisture ratio gradually decreases with an increase in the drying time,reducing the loading,initial moisture content,increasing the temperature,and pressure can shorten the drying time and improve the drying efficiency.Conclusion:Artificial neural networks technology has the advantages of rapid and accurate prediction,and can provide a theoretical basis and technical support for online prediction during the drying process of the extract.
基金supported by The National Natural Science Foundation of China (32001824, 31972198, 31901813, 31901816, 32001827)Startup Fund for Youngman Research at SJTU (SFYR at SJTU)
文摘Pufferfish is prone to deterioration due to abundant nutrients and high moisture content.Drying technology can extend the shelf life and enhance the flavor quality of aquatic products.The study investigated the effect of hot air drying(HAD),microwave vacuum drying(MVD)and hot air assisted radio frequency drying(HARFD)on the taste and volatile profiles of Takifugu obscurus.Different drying methods had significant influence on the color,rehydration,5’-nucleotides,free amino acids and volatile components(P<0.05).The results showed that HAD and HARFD could promote the flavor of T.obscurus by producing higher equivalent umami concentration(EUC)values,which were about two times of MVD group,and more pronounced pleasant odor according to sensory analysis.HAD is more appropriate for industrial application than HARFD and MVD considering the economic benefits.This study could provide a reference for the industrial application of drying T.obscurus.
文摘花椒热风干燥降速期水分含量低,水分扩散慢,导致热风干燥耗时长。为提高干燥效率,并通过热风与微波组合干燥,分别进行热风干燥、微波干燥和热风-微波组合干燥实验,探究不同干燥参数对花椒失水特性的影响,以确定合理的干燥转换临界点和最优组合干燥模型,并将傅里叶准则数(F_(0))引入Fick第二扩散定律方程,求解有效水分扩散系数(D_(eff))。研究结果表明:热风和微波单独干燥时,升高风温风速和增加微波功率均有利于缩短干燥时间;热风-微波组合干燥花椒时,热风段转微波段的最佳目标含水率即为热风干燥的临界点含水率(65%(w.b)),且高热风温度和高微波功率均可使微波干燥段获得高失水速率;热风-微波组合干燥花椒热风段和微波段对应的最优模型分别为Wang and Singh模型和Page模型,D_(eff)范围分别为1.908×10^(-9)~3.547×10^(-9)m^(2)/s和1.883×10^(-8)~3.321×10^(-8)m^(2)/s。热风-微波组合干燥方式能够显著提高干燥效率,促进花椒内部水分扩散,干燥模型可为优化干燥工艺和设计干燥设备提供理论依据。
