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Rapid on-line non-destructive detection of the moisture content of corn ear by bioelectrical impedance spectroscopy 被引量:3
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作者 Zhao Pengfei Zhang Hanlin +5 位作者 Zhao Dongjie Wang Zhijie Fan Lifeng Huang Lan Ma Qin Wang Zhongyi 《International Journal of Agricultural and Biological Engineering》 SCIE EI CAS 2015年第6期37-45,共9页
Moisture content of corn directly affects its quality and storage time,and the rapid on-line detection of the moisture content of corn ears not threshed or in vivo in the fields is required.Because of the special shap... Moisture content of corn directly affects its quality and storage time,and the rapid on-line detection of the moisture content of corn ears not threshed or in vivo in the fields is required.Because of the special shape of corn ear,the rapid,low cost and non-destructive bioelectrical impedance measurement is more suitable for its moisture content detection.Using the four-electrode method with the Agilent E4980A precision LCR meter,the electrical impedance spectroscopies of the sweet corn ears and waxy corn ears at different moisture contents were acquired.The frequency range of the detection was from 20 Hz to 2 MHz and to enhance the contact,the attached-type electrodes were wrapped in cotton soaked with 0.1%NaCl solution.The impedance data over the frequency range from 300 Hz to 5 kHz were used to obtain the parameters of the bio-impedance Cole-Cole model.The results showed a good linear correlation(coefficient of determination R2=0.960)between the equivalent parallel resistance R∞of sweet corn ear and the moisture content value determined by standard chemical method.The research proved that the bioelectrical impedance spectroscopy can be used for detecting the moisture content of corn ear. 展开更多
关键词 moisture content non-destructive detection bioelectrical impedance spectroscopy corn ear
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Corn ear test using SIFT-based panoramic photography and machine vision technology 被引量:1
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作者 Xinyi Zhang Jiexin Liu Huaibo Song 《Artificial Intelligence in Agriculture》 2020年第1期162-171,共10页
Corn ear test is important to modern corn breeding.The test indexesmainly include lengths,radiuses,rows and numbers of corn ears and the kernels they bear,which can benefit the study on breeding new and fine corn vari... Corn ear test is important to modern corn breeding.The test indexesmainly include lengths,radiuses,rows and numbers of corn ears and the kernels they bear,which can benefit the study on breeding new and fine corn varieties.These corn traits are often collected by traditional manual measurement,which is difficult to meet the needs of high throughput corn ear test.In this study,image sequences of corn ear samples were captured by building a panoramic photography collecting system.And then,to get the lengths and radiuses indexes,the corn area images were processed based on Lab color space and adaptive threshold segmentation.The sequence images were then matched and the panoramic image of a corn surface were extracted using Scale-invariant feature transform(SIFT).Finally,by using Exponential transformation(ETR)and Sobel-Hough algorithm,ears and rows indexes were acquired.Test results showed that the accuracy of the radiuses and lengths were 93.84%and 94.53%,respectively.Meanwhile,the accuracy of kernels and rows indexes were 98.12%and 96.14%,whichwere 4.03%and 7.25%higher than that of common mosaiced panoramic image.And the accuracy of kernel area and length-width ratio were 95.36%and 97.42%,respectively.All the results showed that the proposed method can be used for corn ear test effectively. 展开更多
关键词 corn ear Panoramic photography Image segmentation Image stitching Image rectification
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