对不同含水量粳稻谷T2峰面积和MRI图像的定量分析

doi:10.3864/j.issn.0578-1752.2015.22.013

摘要/Abstract

摘要： 【目的】水分含量是影响粳稻谷储藏、干燥的主要因素之一，探讨粳稻谷的反演峰与其含水量的数学关系式，通过提取MRI图像灰度值，拟合灰度值与含水量的数学方程，为快速测定粳稻谷水分提供新方法并为分析粳稻谷水分状态和分布提供新思路。【方法】将粳稻谷含水量分别调节为14.963%、15.830%、16.232%、16.299%、18.340%、19.581%、20.707%、22.290%和24.259%，平衡水分之后基于低场核磁（LF-NMR）技术采集不同含水量的粳稻谷数据，利用低场核磁自带CONTIN程序对数据进行定性反演和成像，对不同反演峰进行定量分析，拟合出粳稻谷含水量与其T₂₁峰、T₂₂峰之间的数学关系式，使用MATLAB软件对不同含水量粳稻谷MRI图像进行灰度值采集，并将灰度值与水分进行方程拟合，探究LF-NMR数据与水分的内在关系。【结果】不同含水量粳稻谷的不同反演峰的峰值时间是相对稳定的，但随着含水量的增加，粳稻谷水质子的自由度增高，峰值时间略微增大。利用线性拟合得到粳稻谷含水量与其低场核磁反演峰T₂₁峰面积的拟合方程为y=0.0013x-2.0938(r²=0.9984，P<0.01)；含水量低于16%的粳稻谷T₂₂峰不出现，粳稻谷含水量较高时，T₂₂峰面积随着水分含量的增加而不断增大，并且具有显著的相关性（P<0.01），拟合方程为y=0.0082x+16.074（r²=0.9817），T₂₃的峰面积随着粳稻谷含水量的增加不断减小。当粳稻谷含水量不断增高，图像平均灰度值则不断降低，对图像的平均灰度值进行回归分析，得到回归方程y=-2.251x+42.712（r²=0.861），利用MATLAB R2014a软件对图像灰度数据进行采集、分析，建立图形发现低水分含量粳稻谷图像的灰度级比高水分含量粳稻谷图像灰度等级跨度大；但同一灰度等级下，高水分含量粳稻谷的灰度像素出现频率比低水分含量灰度像素出现频率高。体现了高水分粳稻谷整体质子密度和质子信号强度较为均匀，而低水分粳稻谷的质子密度和质子信号强度均匀性较差，证明了水分过低时稻谷内部的水分分布的不均匀性，结合MRI图像可知低水分稻谷水分主要集中在胚部和背部，而高水分粳稻谷内部水分分布较为均匀。【结论】粳稻谷的含水量与低场核磁数据具有极高的相关性，可以利用LF-NMR技术快速检测粳稻谷水分含量和水分分布，通过粳稻谷MRI图像可以直观观测粳稻谷内部水分状态。

关键词: 粳稻谷, 低场核磁, 含水量, 峰面积, 灰度值, 储藏

Abstract: 【Objective】Moisture content is one of the main factors that influence the storage and drying of japonica rice, this study is mainly to discuss the mathematical relationship between the signal per mass and moisture content of japonica rice by extracting the MRI image grey value and fitting the mathematical equation of grey and moisture content which provide a new way for rapid moisture determination of japonica rice. 【Method】 The japonica rice moisture content was adjusted to 14.963%, 15.830%, 16.232%, 16.299%, 18.340%, 19.581%, 20.707%, 22.290%, and 24.259%, while data collection of japonica rice with different moisture content after equilibrium moisture content was based on low field NMR technology (LF-NMR). The qualitative inversion and imaging of the data was applied in low field NMR CONTIN program, and fitting the mathematical relationship between the moisture content and the peak of T₂₁,T₂₂ of Japonica rice. Acquiring the data of grey value of MRI image of japonica with different moisture contents by using MATLAB software, fitting the equation of grey value and moisture content, and explore the inner relationship of LF-NMR data and moisture content. 【Result】 Experimental research shows that, different inversion peak of japonica rice with different containing moisture of peak time is relatively stable, but with the increasing of moisture content, japonica rice moisture protons of degrees of freedom is increasing, and peak time slightly increases. To obtain the fitting equation of moisture content and low-field nuclear magnetic inversion peak T₂₁ area by using the linear fitting method. The equation is y=0.0013x-2.0938 (r²=0.9984, P<0.01). The T₂₂ peak of japonica rice which less than 16% is not appear. When japonica rice with higher moisture content, T₂₂ peak area increases with the increase of moisture content, and has a significant correlation. The fitting equation is y=0.0082x+16.074 (r²=0.9817). The peak area of T₂₃ decreased with the increase of moisture content in japonica rice. When the moisture content of Japonica rice increased, the average gray value image is decreasing. The average gray value of the image was analyzed and the regression equation was obtained which is y=-2.251x+42.712 (r²=0.861). The gray data of the image was collected, analyzed and built by R2014a MATLAB. We find that the low moisture content of gray level is higher than the high moisture content of gray level. However, under the same gray level, pixel gray of japonica rice with high moisture content appear frequency is higher than low moisture content of japonica rice, reflecting proton density and signal intensity of japonica rice with high moisture content is more uniform than the japonica rice with low moisture content which is proved that the distribution of moisture in japonica rice is not uniform when the moisture is too low. Combined with MRI images, the moisture of the rice was mainly concentrated in the embryo and back of the japonica rice, the high moisture content of japonica rice overall proton density and proton signal intensity is uniform and low moisture content of japonica rice of proton density and proton signals of uniform strength is poor. It is proved that the low moisture content of rice internal moisture distribution inhomogeneity, combined with MRI image shows low moisture content of japonica rice’s moisture mainly concentrated in the embryo and back, and high moisture content of japonica’s internal moisture distribution is more uniform. 【Conclusion】It has a high correlation between moisture contents and LF-NMR data of japonica rice. Rapid detection of moisture content of japonica rice and moisture distribution can be used LF-NMR technology, with japonica rice MRI image we can have a direct observation of Japonica rice moisture status.

Key words: japonica rice, LF-NMR, moisture content, peak area, grey level, storage

宋伟，李冬珅，乔琳，苏安祥，胡婉君. 对不同含水量粳稻谷T₂峰面积和MRI图像的定量分析[J]. 中国农业科学, 2015, 48(22): 4529-4538.

SONG Wei, LI Dong-shen, QIAO Lin, SU An-xiang, HU Wan-jun. Quantitative Analysis of T₂Peak Area and the MRI Images of Japonica Rice with Different Moisture Contents[J]. Scientia Agricultura Sinica, 2015, 48(22): 4529-4538.

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对不同含水量粳稻谷T₂峰面积和MRI图像的定量分析

Quantitative Analysis of T₂Peak Area and the MRI Images of Japonica Rice with Different Moisture Contents

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