ZHENG Songjin, ZHANG Yujie, ZHONG Liang, DUAN Haitao, WANG Danli, NIU Lina, WANG Haitao, LIU Yubin, YANG Yi. Quantifying tobacco moisture content based on low-field nuclear magnetic resonanceJ. Tobacco Science & Technology, 2020, 53(8): 65-71. DOI: 10.16135/j.issn1002-0861.2019.0236
Citation: ZHENG Songjin, ZHANG Yujie, ZHONG Liang, DUAN Haitao, WANG Danli, NIU Lina, WANG Haitao, LIU Yubin, YANG Yi. Quantifying tobacco moisture content based on low-field nuclear magnetic resonanceJ. Tobacco Science & Technology, 2020, 53(8): 65-71. DOI: 10.16135/j.issn1002-0861.2019.0236

Quantifying tobacco moisture content based on low-field nuclear magnetic resonance

  • In order to accurately determine the moisture content in tobacco during processing, a rapid method based on the CPMG signals of low-field nuclear magnetic resonance (LF-NMR) was established. The results were compared with those determined by the conventional oven moisture method. The results showed that:1) With the LF-NMR method, CPMG sequences were better than FID sequences, and the optimized sample volume and scanning numbers were 7 g and 16 respectively. 2) The established LF-NMR method featured good precision and high accuracy with the variation coefficients of intra- and inter-day precision less than 2%. 3) The LF-NMR method was more stable and accurate than the oven method, in addition the test time (2 min) was much shorter than that (150 min) of the oven method. The established method is suitable for the rapid and accurate determination of moisture content in tobacco.
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