Modeling and optimization of non-isothermal convective drying process of Lavandula × allardii

IF 7.7 Q1 AGRICULTURE, MULTIDISCIPLINARY
Vasileios Chasiotis, Konstantinos-Stefanos Nikas, Andronikos Filios
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引用次数: 0

Abstract

Non-isothermal convective drying schemes were examined for Lavandula × allardii leaves and inflorescences. Drying process parameters were optimized using response surface methodology (RSM) to ensure the peak operational performance. The effects of temperature increase rate (2–4 °C/h) and the airflow velocity (1–3 m/s) on the essential oil yield, drying duration and consumption, were investigated. A face-centered central composite design was deployed and the experimental data was adapted to the most suitable polynomial models, as determined by the regression analysis. Analysis of variance was applied to assess the effects of the process variables, their interactions and the statistical significance of the examined models. Both factors of temperature increase rate and airflow velocity had a significant impact on the drying duration. Airflow velocity had a greater effect on leaves’ essential oil yield and inflorescences’ process energy consumption, whereas the rates of temperature increase had a greater influence on the inflorescences’ essential oil yield and leaves’ energy consumption. The minimum drying duration and energy consumption were obtained for the maximum temperature increasing rate at 3 and 1 m/s airflow velocities respectively; and the highest essential oil yield was obtained for the least rate of temperature increase and airflow velocity for both leaves and inflorescences. Numerical optimization was performed for minimizing drying duration and energy consumption by maximizing the essential oil yield. The rate of temperature increases of 4 °C/h and the airflow velocity of 1 m/s, were proposed as the optimum non-isothermal drying conditions for both leaves and inflorescences of Lavandula × allardii. Predicted values of essential oil content have been 1.387/3.05 mL/g, 4.21/4.18 h drying time and 0.809/0.732 kWh energy consumption at the optimum operation point for leaves and inflorescences, respectively. The resulted optimized non-stationary temperature scheme considerably improved the drying kinetics and the process consumption by achieving a similar essential oil recovery with the standard low-temperature convective drying. The present study aimed to eliminate the preexisting gap of the optimum selection of the process parameters for the particular type of the examined non-isothermal drying schemes. Previous findings could be utilized for designing dryers and drying schedules aiming to retain the qualitative attributes, by reducing the cost and duration of the drying operations.

薰衣草非等温对流干燥过程的建模与优化
对薰衣草叶片和花序的非等温对流干燥方案进行了研究。采用响应面方法(RSM)对干燥工艺参数进行了优化,以确保达到最佳操作性能。研究了升温速率(2-4 °C/h)和气流速度(1-3 m/s)对精油产量、干燥持续时间和消耗量的影响。采用了面心中心复合设计,并根据回归分析确定的最合适的多项式模型对实验数据进行了调整。采用方差分析来评估工艺变量的影响、它们之间的相互作用以及所研究模型的统计意义。温度上升率和气流速度这两个因素对干燥持续时间都有显著影响。气流速度对叶片精油产量和花序加工能耗的影响更大,而温度上升率对花序精油产量和叶片能耗的影响更大。在气流速度分别为 3 米/秒和 1 米/秒时,温度升高速率最大时的干燥持续时间和能耗最小;而在温度升高速率和气流速度最小时,叶片和花序的精油产量最高。为了最大限度地提高精油产量,减少干燥时间和能耗,进行了数值优化。结果表明,4 °C/h 的升温速率和 1 m/s 的气流速度是薰衣草叶片和花序的最佳非等温干燥条件。在最佳操作点,叶片和花序的精油含量预测值分别为 1.387/3.05 毫升/克、4.21/4.18 小时干燥时间和 0.809/0.732 千瓦时能耗。优化后的非稳态温度方案大大改善了干燥动力学和工艺消耗,实现了与标准低温对流干燥相似的精油回收率。本研究旨在消除针对特定类型的非等温干燥方案在工艺参数优化选择方面存在的差距。以前的研究结果可用于设计干燥机和干燥计划,以便通过降低干燥操作的成本和缩短干燥操作的时间来保留质量属性。
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来源期刊
Information Processing in Agriculture
Information Processing in Agriculture Agricultural and Biological Sciences-Animal Science and Zoology
CiteScore
21.10
自引率
0.00%
发文量
80
期刊介绍: Information Processing in Agriculture (IPA) was established in 2013 and it encourages the development towards a science and technology of information processing in agriculture, through the following aims: • Promote the use of knowledge and methods from the information processing technologies in the agriculture; • Illustrate the experiences and publications of the institutes, universities and government, and also the profitable technologies on agriculture; • Provide opportunities and platform for exchanging knowledge, strategies and experiences among the researchers in information processing worldwide; • Promote and encourage interactions among agriculture Scientists, Meteorologists, Biologists (Pathologists/Entomologists) with IT Professionals and other stakeholders to develop and implement methods, techniques, tools, and issues related to information processing technology in agriculture; • Create and promote expert groups for development of agro-meteorological databases, crop and livestock modelling and applications for development of crop performance based decision support system. Topics of interest include, but are not limited to: • Smart Sensor and Wireless Sensor Network • Remote Sensing • Simulation, Optimization, Modeling and Automatic Control • Decision Support Systems, Intelligent Systems and Artificial Intelligence • Computer Vision and Image Processing • Inspection and Traceability for Food Quality • Precision Agriculture and Intelligent Instrument • The Internet of Things and Cloud Computing • Big Data and Data Mining
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