• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国卫生研究院文献>Journal of Food Science and Technology >Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network
【2h】

Hot air drying characteristics of mango ginger: Prediction of drying kinetics by mathematical modeling and artificial neural network

机译：芒果姜的热风干燥特性：通过数学建模和人工神经网络预测干燥动力学

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Mango ginger (Curcuma amada) was dried in a through-flow dryer system at different temperatures (40–70 °C) and air velocities (0.84 – 2.25 m/s) to determine the effect of drying on drying rate and effective diffusivity. As the temperature and air velocity increased, drying time significantly decreased. Among the ten different thin layer drying models considered to determine the kinetic drying parameters, semi empirical Midilli et al., model gave the best fit for all drying conditions. Effective moisture diffusivity varied from 3.7 × 10−10 m2/s to 12.5 × 10−10 m2/s over the temperature and air velocity range of study. Effective moisture diffusivity regressed well with Arrhenius model and activation energy of the model was found to be 32.6 kJ/mol. Artificial neural network modeling was also employed to predict the drying behaviour and found suitable to describe the drying kinetics with very high correlation coefficient of 0.998.Electronic supplementary materialThe online version of this article (doi:10.1007/s13197-013-0941-y) contains supplementary material, which is available to authorized users.
机译：芒果姜（姜黄）在不同温度（40–70°C）和风速（0.84 – 2.25m / s）下通过流通式干燥机进行干燥，以确定干燥对干燥速率和有效扩散率的影响。随着温度和空气速度的增加，干燥时间明显减少。在确定动力学干燥参数的十种不同的薄层干燥模型中，半经验的Midilli等人的模型对所有干燥条件均提供了最佳拟合。有效水分扩散率从3.7×10 −10 m 2 / s到12.5×10 −10 m 2 / s在研究的温度和空气速度范围内。有效水分扩散率在Arrhenius模型中回归良好，模型的活化能为32.6 kJ / mol。还使用人工神经网络建模来预测干燥行为，发现适合描述干燥动力学，具有很高的相关系数0.998。电子补充材料本文的在线版本（doi：10.1007 / s13197-013-0941-y）包含补充材料，授权用户可以使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号