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基于微流控芯片富集与无透镜衍射图像处理的温室番茄灰霉病菌孢子快速检测方法

A Rapid Detection Method for Tomato Gray Mold Spores in Greenhouse Based on Microfluidic Chip Enrichment and Lens-Less Diffraction Image Processing.

作者信息

Wang Yafei, Mao Hanping, Zhang Xiaodong, Liu Yong, Du Xiaoxue

机构信息

School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China.

Key Laboratory of Modern Agricultural Equipment and Technology, Ministry of Education, Jiangsu University, Zhenjiang 212013, China.

出版信息

Foods. 2021 Dec 5;10(12):3011. doi: 10.3390/foods10123011.

Abstract

It is of great significance to find tomato gray mold in time and take corresponding control measures to ensure the production of tomato crops. This study proposed a rapid detection method for spores of in green-house based on microfluidic chip enrichment and lens-free diffraction image processing. Microfluidic chip with a regular triangular inner rib structure was designed to achieve the enrichment of spores. In order to obtain the diffraction image of the diseased spores, a lens-less diffraction imaging system was built. Furthermore, the collected spore diffraction images were processed and counted. The simulation results showed that the collection efficiency of 16 μm particles was 79%, 100%, and 89% at the inlet flow rate of 12, 14 and 16 mL/min, respectively. The experimental verification results were observed under a microscope. The results showed that when the flow rate of the microfluidic chip was 12, 14 and 16 mL/min, the collection efficiency of spores was 70.65%, 87.52% and 77.96%, respectively. The spores collected in the experiment were placed under a microscope for manual counting and compared with the automatic counting results based on diffraction image processing. A total of 10 sets of experiments were carried out, with an error range of the experiment was 5.13~8.57%, and the average error of the experiment was 6.42%. The Bland-Altman method was used to analyze two methods based on diffraction image processing and manual counting under a microscope. All points are within the 95% consistency interval. Therefore, this study can provide a basis for the research on the real-time monitoring technology of tomato gray mold spores in the greenhouse.

摘要

及时发现番茄灰霉病并采取相应防治措施对确保番茄作物产量具有重要意义。本研究提出了一种基于微流控芯片富集和无透镜衍射图像处理的温室番茄灰霉病菌孢子快速检测方法。设计了具有规则三角形内肋结构的微流控芯片以实现番茄灰霉病菌孢子的富集。为了获取染病孢子的衍射图像,搭建了无透镜衍射成像系统。此外,对采集到的孢子衍射图像进行处理和计数。模拟结果表明,在进样流速为12、14和16 mL/min时,16μm颗粒的收集效率分别为79%、100%和89%。通过显微镜观察进行实验验证。结果表明,当微流控芯片流速为12、14和16 mL/min时,番茄灰霉病菌孢子的收集效率分别为70.65%、87.52%和77.96%。将实验收集的番茄灰霉病菌孢子置于显微镜下进行人工计数,并与基于衍射图像处理的自动计数结果进行比较。共进行了10组实验,实验误差范围为5.13%~8.57%,实验平均误差为6.42%。采用Bland-Altman方法对基于衍射图像处理和显微镜下人工计数的两种方法进行分析。所有点均在95%一致性区间内。因此,本研究可为温室番茄灰霉病菌孢子实时监测技术研究提供依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be66/8701817/ceddfb4086d2/foods-10-03011-g001.jpg

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