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食品研究与开发:2022,43(13):77-83
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响应面法优化黄秋葵热风干燥工艺
(1.山东建筑大学热能工程学院,山东 济南 250101;2.齐鲁工业大学(山东省科学院)山东省科学院能源研究所山东省生物质气化技术重点实验室,山东 济南 250353;3.齐鲁工业大学(山东省科学院)能源与动力工程学院,山东 济南 250353;4.中华全国供销合作总社济南果品研究院,山东 济南 250220)
Optimization of Hot-Air Drying Okra by Response Surface Methodology
(1.School of Thermal Engineering,Shandong Jianzhu University,Jinan 250101,Shandong,China;2.Shandong Provincial Key Laboratory of Biomass Gasification Technology,Energy Institute of Shandong Academy of Scinces,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,Shandong,China;3.School of Energy and Power Engineering,Qilu University of Technology(Shandong Academy of Sciences),Jinan 250353,Shandong,China;4.Jinan Fruit Research Institute All China Federation of Supply and Marketing Co-operatives,Jinan 250220,Shandong,China)
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投稿时间:2021-06-17    
中文摘要: 为提高黄秋葵干燥效率和质量,通过单因素试验考察黄秋葵的热风干燥温度和风速2个因素对干燥品质的影响,以复水比和色泽为指标,利用响应曲面法研究热风温度、风速和铺料厚度对黄秋葵热风干燥工艺的影响,分析各因素之间的交互作用,获得黄秋葵复水比和色泽的影响特性,建立黄秋葵热风干燥的回归数学模型,确定黄秋葵热风干燥的最优工艺参数。结果表明:黄秋葵热风干燥工艺的最优工艺为热风干燥温度58℃、风速0.62 m/s、铺料层数为1层,所得黄秋葵复水比2.96、色差13.67,试验值与模型预测值吻合度高,误差小于1%。
Abstract:To improve the efficiency and quality of okra drying,the effects of hot air temperatures and speeds on these factors were evaluated via single-factor experimentation.The response surface method was used to study the interaction between the rehydration ratio and chromatic aberration,which were used as indicators of the air temperatures,speeds and material thicknesses under study.A regression mathematical model was established,the influence characteristics of each index were obtained,and the optimal process parameters were determined.Results showed that the optimum process parameters of hot air drying of okra were drying temperature 58℃,wind speed 0.62 m/s and single-layer material.Corresponding indicators were rehydration ratio 2.96 and chromatic aberration 13.67.Experimental values of the two groups of target parameters agree well with the predicted values of the model,and the errors are all less than 1%.
文章编号:202213011     中图分类号:    文献标志码:
基金项目:山东省科学院国际科技合作项目(2019GHZD12);山东省重点研发计划(2019GNC106019)
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