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基于氣載微流控芯片的作物病害孢子流式動態(tài)檢測方法
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江蘇大學農(nóng)裝學部項目(NZXB20200205)、國家自然科學基金項目(32171895,、32071905),、水稻生物學國家重點實驗室開放項目(20200303)和江蘇省優(yōu)勢學科項目(PAPD)


Crop Disease Spore Flow Dynamic Detection Method Based on Airborne Microfluidic Chip
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    摘要:

    為解決微流控芯片孢子檢測復用率低的問題,提出一種基于氣載微流控芯片的作物病害孢子流式動態(tài)檢測方法,。根據(jù)微尺度下作物病害孢子氣體動力學特征設(shè)計平行雙鞘流聚焦的微流控芯片,實現(xiàn)孢子的聚焦流動,;利用光路聚焦原理和雙向Mie散射原理設(shè)計光電檢測結(jié)構(gòu),;將微流控芯片和光電檢測結(jié)構(gòu)組合搭建光電檢測系統(tǒng),根據(jù)前向散射光強信息建立粒徑與光強的檢測模型,,并融合前向和側(cè)向散射光強信息,,實現(xiàn)稻曲病孢子和聚苯乙烯微球的有效分類。仿真和實驗結(jié)果表明:樣品在芯片入口流速為2.5mL/min,、鞘流流速為12mL/min時,,粒子聚焦寬度為8μm,,粒子富集率可達96.7%;稻曲病孢子和聚苯乙烯微球粒徑與光強檢測模型的決定系數(shù)為0.9666,平均檢測誤差為7.04%,,芯片復用率提高約9倍,。研究結(jié)果為作物病害檢測傳感器的研發(fā)提供了理論基礎(chǔ)。

    Abstract:

    Crop disease monitoring has always been a research hotspot in the field of agricultural engineering because of its serious damage to the world’s food. In recent years, the use of microfluidic chip microbial sensors for crop disease detection has received attention from scholars. However, most of current microfluidic chips have the defect of low reuse rate. In response to this problem, a parallel double sheath flow focusing microfluidic chip was proposed, which was composed of an injection channel, a double sheath flow channel, a partial pressure channel, a detection channel and a circular chamber. Fungal spores entered the chip from the sampling channel with the airflow, and then were arranged in the center of the chip by the action of the double sheath airflow. Air pressure was controlled by the partial pressure channel to ensure that the fungal spores entered the detection area of the chip at the speed required by the test. Subsequently, fungal spores followed the airflow into the circular enrichment area. Experimental data showed that the spore velocity was decreased with the increase of the chamber diameter. Circular chamber diameter of 2500μm had the best enrichment effect, and the particle enrichment rate can reach 96.7%. An air pump was connected to the outlet of the chip to extract fungal spores, which can improve the reuse rate of the chip. Rice spores used were from the China National Rice Research Institute, and polystyrene microsphere samples were purchased from Tianjin Daye Technology Co., Ltd.. The experimental platform was built by aerosol generator, semiconductor laser, microfluidic chip, circuit board, focusing optical path device and other equipment. In order to realize the focused arrangement of fungal spores, the sample inlet flow rate and sheath flow rate needed to be optimized. Optimization results showed that, when the sampling flow rate and sheath flow rate of the chip were 2.5mL/min and 12mL/min, respectively, the particle focus width was 8μm, which can realize the particle focus arrangement and flow through the detection area in a row. The entire detection system was also composed of a focusing optical path device and a signal acquisition circuit. The focusing optical path device was composed of a filter, a half lens with a focal length of 14mm and an aperture surface of 10μm, which can focus the light source to about 10μm. The laser would excite spores passing through the detection area to produce forward and side scattered light, and then these two scattered lights would be collected by the signal collection circuit and transmitted to the upper computer. The forward scattered light signal contained the size information of the particles. Based on the experimental results, a detection model for the particle size and light intensity was established, with coefficient of determination of 0.9666, which had a good linearity. The side-scattered light signal contained the complexity of the particles. The forward and sidescattered light intensity information was fused to achieve effective classification of rice spore spores and polystyrene microspheres, with an average detection error of 7.04%, and the chip reuse rate was increased by about 9 times. The research result can provide a basis for the research and development of crop disease monitoring sensors.

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楊寧,張素亮,王亞飛,袁壽其,毛罕平,張曉東.基于氣載微流控芯片的作物病害孢子流式動態(tài)檢測方法[J].農(nóng)業(yè)機械學報,2022,53(10):318-325. YANG Ning, ZHANG Suliang, WANG Yafei, YUAN Shouqi, MAO Hanping, ZHANG Xiaodong. Crop Disease Spore Flow Dynamic Detection Method Based on Airborne Microfluidic Chip[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(10):318-325.

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  • 收稿日期:2021-12-02
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  • 在線發(fā)布日期: 2022-01-12
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