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基于光相干断层扫描的瓜籽病筛查光学检测方法

Optical sensing method for screening disease in melon seeds by using optical coherence tomography.

机构信息

School of Electrical Engineering and Computer Science, Kyungpook National University, 1370, Sankyuk-dong, Buk-gu, Daegu 702-701, Korea.

出版信息

Sensors (Basel). 2011;11(10):9467-77. doi: 10.3390/s111009467. Epub 2011 Oct 10.

Abstract

We report a noble optical sensing method to diagnose seed abnormalities using optical coherence tomography (OCT). Melon seeds infected with Cucumber green mottle mosaic virus (CGMMV) were scanned by OCT. The cross-sectional sensed area of the abnormal seeds showed an additional subsurface layer under the surface which is not found in normal seeds. The presence of CGMMV in the sample was examined by a blind test (n = 140) and compared by the reverse transcription-polymerase chain reaction. The abnormal layers (n = 40) were quantitatively investigated using A-scan sensing analysis and statistical method. By utilizing 3D OCT image reconstruction, we confirmed the distinctive layers on the whole seeds. These results show that OCT with the proposed data processing method can systemically pick up morphological modification induced by viral infection in seeds, and, furthermore, OCT can play an important role in automatic screening of viral infections in seeds.

摘要

我们报告了一种使用光学相干断层扫描(OCT)诊断种子异常的光学传感方法。使用 OCT 扫描感染了黄瓜绿斑驳花叶病毒(CGMMV)的甜瓜种子。异常种子的横截面感测区域在表面下显示出一个额外的亚表面层,而在正常种子中则没有发现。通过盲测(n = 140)和逆转录-聚合酶链反应(RT-PCR)进行了样本中 CGMMV 的存在检查。使用 A 扫描传感分析和统计方法对异常层(n = 40)进行了定量研究。通过利用 3D-OCT 图像重建,我们在整个种子上确认了具有特征性的层。这些结果表明,具有所提出的数据处理方法的 OCT 可以系统地检测到种子中由病毒感染引起的形态变化,并且,OCT 可以在种子中病毒感染的自动筛选中发挥重要作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cec9/3231267/dfaa4268f90e/sensors-11-09467f1.jpg

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