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  • 吴钊龙,巫腾钰,邱展鸿,黄纪民,覃海波,李秉正,黄志民.基于干燥动力学结合LF-NMR分析的不同干燥过程中天麻切片水分变化[J].广西科学院学报,2023,39(4):433-444.    [点击复制]
  • WU Zhaolong,WU Tengyu,QIU Zhanhong,HUANG Jinmin,QIN Haibo,LI Bingzheng,HUANG Zhimin.Determination of Moisture Changes in Gastrodia elata Blume Slices during Different Drying Processes Based on Drying Kinetics and LF-NMR Analysis[J].Journal of Guangxi Academy of Sciences,2023,39(4):433-444.   [点击复制]
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基于干燥动力学结合LF-NMR分析的不同干燥过程中天麻切片水分变化
吴钊龙1, 巫腾钰2, 邱展鸿3, 黄纪民1,4, 覃海波1, 李秉正1,4,5, 黄志民4
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(1.广西科学院大健康研究所, 广西南宁 530007;2.南宁学院食品科学与质量工程学院, 广西南宁 530200;3.广西华泰药业有限公司, 广西贺州 546800;4.广西科学院, 广西微波先进制造技术重点实验室, 广西南宁 530007;5.广西科学院来宾分院, 广西来宾 546100)
摘要:
为探究天麻(Gastrodia elata Blume)切片干燥过程中水分迁移变化规律,并建立其量化表征方法,本研究采用低场核磁共振(Low-Field Nuclear Magnetic Resonance,LF-NMR)技术分析热风干燥(Hot Air Drying,HAD)和微波干燥(Microwave Drying,MWD)过程中不同热风温度(60、70、80 ℃)和不同微波功率密度(2、3、4 W/g)条件下的天麻切片,结合干燥特性曲线建立基于LF-NMR 参数的天麻切片含水量预测模型。结果表明,MWD速率远大于HAD,在热风温度(60-80 ℃)和微波功率密度(2-4 W/g)范围内,高温、高功率密度有利于提高干燥速率,缩短干燥时间。Logarithmic模型可以准确描述天麻切片HAD和MWD过程中含水量的变化。经LF-NMR技术分析,在HAD 和MWD 过程中,天麻切片的横向弛豫时间曲线整体上呈现左移的趋势,各状态水的弛豫峰信号强度不断降低;干燥结束时天麻切片中的自由水完全被脱去,仅存少量的不易流动水和结合水。无论是HAD还是MWD,弛豫峰总面积A2 和天麻片的干基含水量相关性均在0.99以上。研究结果可为阐明天麻切片干燥机制和干燥工艺参数的优选提供参考。
关键词:  天麻  热风干燥  微波干燥  水分  低场核磁
DOI:10.13657/j.cnki.gxkxyxb.20231226.010
投稿时间:2023-08-15修订日期:2023-11-20
基金项目:广西科技计划项目(桂科AB18294028),贺州市创新驱动发展专项(贺科创CX2009009)和广西科学院健康食品创制创新团队启动经费项目(CQ-E-2419)资助。
Determination of Moisture Changes in Gastrodia elata Blume Slices during Different Drying Processes Based on Drying Kinetics and LF-NMR Analysis
WU Zhaolong1, WU Tengyu2, QIU Zhanhong3, HUANG Jinmin1,4, QIN Haibo1, LI Bingzheng1,4,5, HUANG Zhimin4
(1.Institute of Grand Health, Guangxi Academy of Sciences, Nanning, Guangxi, 530007, China;2.College of Food Science and Quality Engineering, Nanning University, Nanning, Guangxi, 530200, China;3.Guangxi Huatai Pharmaceutical Co., Ltd., Hezhou, Guangxi, 546800, China;4.Guangxi Key Laboratory of Advanced Microwave Manufacturing Technology, Guangxi Academy of Sciences, Nanning, Guangxi, 530007, China;5.Laibin Branch, Guangxi Academy of Sciences, Laibin, Guangxi, 546100, China)
Abstract:
Combining drying characteristic curves,a predictive model for Gastrodia elata Blume slice moisture content based on Low-Field Nuclear Magnetic Resonance (LF-NMR) parameters was established.In order to explore the change rule of moisture migration in the drying process of G. elata Blume slices and establish its quantitative characterization method,in this study,LF-NMR technology was used to analyze G. elata Blume slices under different hot air temperatures (60,70,80 ℃) and different microwave power densities (2,3,4 W/g) during Hot Air Drying (HAD) and Microwave Drying (MWD).Combined with the drying characteristic curve,a prediction model of moisture content of G. elata Blume slices based on LF-NMR parameters was established.The results showed that the drying rate of MWD was much higher than that of HAD.In the range of hot air temperature (60-80 ℃) and microwave power density (2-4 W/g),high temperature and high power density were beneficial to improve the drying rate and shorten the drying time.The Logarithmic model can accurately describe the change of moisture content in the process of HAD and MWD of G. elata Blume slices.LF-NMR analysis showed that in the process of HAD and MWD,the transverse relaxation time curve of G. elata Blume slices showed a trend of left shift on the whole,and the relaxation peak signal intensity of each state water decreased continuously.At the end of drying,the free water in the G. elata Blume slices was completely removed,and only a small amount of immobile water and bound water remained.Whether it is HAD or MWD,the correlation between the total area of relaxation peak A2 and the dry basis water content of G. elata Blume slices is above 0.99.The research results provide a reference for elucidating the drying mechanism of G. elata Blume slices and the optimization of drying process parameters.
Key words:  Gastrodia elata Blume  hot air drying  microwave drying  moisture content  Low-Field Nuclear Magnetic Resonance (LF-NMR)

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