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首页> 外文期刊>LWT-Food Science & Technology >Low-field NMR relaxation and NMR-imaging as tools in differentiation between potato sample and determination of dry matter content in potatoes
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Low-field NMR relaxation and NMR-imaging as tools in differentiation between potato sample and determination of dry matter content in potatoes

机译:低场NMR弛豫和NMR成像作为区分马铃薯样品和确定马铃薯中干物质含量的工具

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摘要

Correlations between dry matter content and parameters determined by low-field nuclear magnetic resonance (NMR) relaxation and T-1 weighted magnetic resonance imaging (MR-imaging) were investigated in four raw potato varieties using partial least-squares regression. The low-field NMR relaxation parameters T-1(r = -0.85) and full Carr-Purcell-Meiboom-Gill (CPMG) relaxation curves (r = 0.95) were correlated with the dry matter content of the potatoes. Furthermore. the amplitudes M-21 and M-22 of the two characteristic transverse relaxation (T-2) time constants T-21 and T-22 obtained upon bi-exponential analysis of CPMG relaxation curves. were also highly correlated with the dry matter content (r = -0.66 and 0.78. respectively). MR-images showed very large visual differences between tissues, varieties and maturity. However. the applied image analysis features based on the histogram analysis were not correlated with dry matter content in whole potatoes in the present study. Thus. MR-imaging did not complement the correlations between NMR data and dry matter content. This means that the way the spatial distribution of water in the material was determined did not cover the full information about dry matter content. Therefore, the image analysis of MR-images requires more attention in the future.
机译:利用偏最小二乘回归法研究了四个生马铃薯品种中干物质含量与通过低场核磁共振弛豫和T-1加权磁共振成像(MR成像)确定的参数之间的相关性。低场NMR弛豫参数T-1(r = -0.85)和完整的Carr-Purcell-Meiboom-Gill(CPMG)弛豫曲线(r = 0.95)与马铃薯的干物质含量相关。此外。通过CPMG弛豫曲线的双指数分析获得的两个特征横向弛豫(T-2)时间常数T-21和T-22的振幅M-21和M-22。与干物质含量也高度相关(分别为r = -0.66和0.78)。 MR图像显示组织,品种和成熟度之间存在很大的视觉差异。然而。在本研究中,基于直方图分析的应用图像分析功能与整个马铃薯中的干物质含量无关。从而。 MR成像不能补充NMR数据与干物质含量之间的相关性。这意味着确定材料中水的空间分布的方式并未涵盖有关干物质含量的全部信息。因此,未来对MR图像的图像分析需要更多的关注。

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