采用X射线三维重构技术检测厚皮柑橘的体积可食率
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TG115.28+1

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国家现代农业产业技术体系项目(CARS-26)


Detecting volumetric edible rate of thick-skinned citrus using X-ray three-dimensional reconstruction
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    摘要:

    针对传统无损检测技术无法定量分析厚皮柑橘体积可食率的问题,为此开发了一套线阵X射线图像采集和三维重构装置,包括果实旋转升降、数据采集、辐射防护及运动控制,实现厚皮柑橘果实的体积可食率检测。以“不知火”柑橘为检测对象,利用X射线投影图的信息熵为评价依据,根据果实大小对检测参数进行优化,得到X射线源的管电压为67 kV,管电流为0.92 mA,线阵探测器的积分时间为1 ms。以旋转角度2.0°为间隔,在圆周方向采集180幅X射线投影图并生成正弦图,通过滤波反向投影(filtered back projection, FBP)算法将正弦图重构为切面图,再利用图像滤波、图像增强、阈值分割对切面图进行图像分割处理,分割出背景区域、果皮区域、果肉区域和空腔区域,然后基于区域面积比定义切面图像可食率。同时,测量了柑橘基本物理参数,计算了切面图像可食率,并建立了与柑橘体积可食率之间的相关关系。结果表明,切面图像可食率与体积可食率相关性最高,相关系数为0.93。最后,选择切面图像可食率作为数学模型的输入特征,利用线性回归模型对厚皮柑橘体积可食率进行定量分析,其预测集决定系数(coefficient of determination of prediction, Rp2)、预测集均方根误差(root mean square error of prediction, RMSEp)、相对分析误差(residual predictive deviation, RPD)分别为0.86、4.81%和2.71。综上,利用X射线三维重构技术对厚皮柑橘体积可食率进行无损检测可行,可为其他农产品内部品质无损检测提供参考。

    Abstract:

    Citrus rich in nutrients is one of the most favorite fruits in recent years. But the thick-skinned citrus is often accompanied by the fruit hollow, skin thick floating, leading to the low actual volumetric edible rate. Furthermore, traditional nondestructive testing cannot accurately and rapidly detect the volumetric edible rate. In this study, the line array X-ray image acquisition and three-dimensional reconstruction were developed to detect the volumetric edible rate of thick-skinned citrus fruits, including the fruit rotation and lifting, data acquisition, radiation protection and motion control. The fruit rotating device consisted of a rotating table and a gear motor; the fruit lifting device consisted of a lifting platform and a stepping motor. The data acquisition device included an X-ray emission source, a line array X-ray detector, and upper computer software. The radiation protection device was a lead plate with a thickness of 2mm, which was used to prevent the radiation generated by X-rays from leaking to the external environment. The motion control part consisted of a programmable logic controller and upper computer software. Taking the Ugli fruit as the detection object, the information entropy of the X-ray projection map was evaluated to optimize the detection parameters. The optimal tube voltage and current of X-ray source were obtained to be 67 kV and 0.92 mA, respectively. The integration time of the line array detector was 1 ms. Dark-field correction and bright-field compensation were used to remove the uneven pixel distribution and the noisy background in the initial state of the X-ray detector before the experiment. A series of 180 X-ray projections were collected in the circumferential direction at intervals of 2.0° rotation. The samples were rotated by 120° with the mid-axis of the fruit as the center of rotation. A series of citrus X-ray projection maps were captured at three angles of 0°, 120° and 240°, respectively. The X-ray projection maps were converted to sinograms using the Radon transform. After that, the sinograms under the three angles were reconstructed as the slice maps using the FBP (Filtered Back Projection). Image segmentation was carried out on the slice maps using image filtering, enhancement, and thresholding segmentation, in order to form the background, pericarp, pulp, and cavity region. Moreover, the regional area ratio was defined using the ratio of citrus pulp region to fruit region, whereas, the slice map edible rate was defined using the regional area ratio. The physical parameters were measured, such as transversal diameter, vertical diameter, mass, volume, density and fruit shape index of citrus fruits. The true volumetric edible rate of citrus was calculated using the specific gravity of citrus pulp to the volume of the whole fruit. There was the better correlation between the physical parameters and volumetric edible rate of citrus. The results showed that there was the higher correlation between fruit density and slice map edible rate and citrus volumetric edible rate, with the highest correlation 0.93 for slice map edible rate. Finally, the slice map edible rate was selected as the input feature of the model. The linear regression model was used to quantify the volumetric edible rate of thick-skinned citrus, with the values of Rp2 (Coefficient of Determination of Prediction), RMSEP (Root Mean Square Error of Prediction), and RPD (Residual Predictive Deviation) of 0.86, 4.81%, and 2.71, respectively. In conclusion, it is feasible to quantitatively analyze the volumetric edible rate of thick-skinned citrus using X-ray three-dimensional reconstruction. The developed approach can also be applied in the nondestructive testing of the quality of agricultural products. Therefore, the nondestructive testing techniques can be expected to evaluate the internal tissue lesions and external quality of agricultural products.

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蔡健荣,梁小祥,许骞,夏中岩,孙力,马立鑫.采用X射线三维重构技术检测厚皮柑橘的体积可食率[J].农业工程学报,2024,40(1):293-300. DOI:10.11975/j. issn.1002-6819.202309084

CAI Jianrong, LIANG Xiaoxiang, XU Qian, XIA Zhongyan, SUN Li, MA Lixin. Detecting volumetric edible rate of thick-skinned citrus using X-ray three-dimensional reconstruction[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE),2024,40(1):293-300. DOI:10.11975/j. issn.1002-6819.202309084

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  • 收稿日期:2023-09-11
  • 最后修改日期:2023-12-04
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  • 在线发布日期: 2024-01-27
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