Duarte Pedro A, Menze Lukas, Abdelrasoul Gaser N, Yosinski Shari, Kobos Zak, Stuermer Riley, Reed Mark, Yang Jian, Li Xiujie S, Chen Jie
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada.
School of Engineering and Applied Science, Yale University, New Haven, CT 06511, USA.
Lab Chip. 2020 Sep 29;20(19):3644-3652. doi: 10.1039/d0lc00426j.
Smart-agriculture technologies comprise a set of management systems designed to sustainably increase the efficiency and productivity of farming. In this paper, we present a lab-on-a-chip device that can be employed as a plant disease forecasting tool for canola crop. Our device can be employed as a platform to forecast potential outbreaks of one of the most devastating diseases of canola and other crops, Sclerotinia stem rot. The system consists of a microfluidic chip capable of detecting single airborne Sclerotinia sclerotiorum ascospores. Target ascospores are injected into the chip and selectively captured by dielectrophoresis, while other spores in the sample are flushed away. Afterward, captured ascospores are released into the flow stream of the channel and are detected employing electrochemical impedance spectroscopy and coplanar microelectrodes. Our device provides a design for a low-cost, miniaturized, and automated platform technology for airborne spore detection and disease prevention.
智能农业技术包括一系列旨在可持续提高农业效率和生产力的管理系统。在本文中，我们展示了一种芯片实验室设备，它可作为油菜作物的植物病害预测工具。我们的设备可作为一个平台，用于预测油菜和其他作物中最具毁灭性的病害之一——菌核病的潜在爆发。该系统由一个能够检测单个空气中的核盘菌子囊孢子的微流控芯片组成。目标子囊孢子被注入芯片，并通过介电泳进行选择性捕获，而样品中的其他孢子则被冲走。之后，捕获的子囊孢子被释放到通道的流动流中，并采用电化学阻抗谱和共面微电极进行检测。我们的设备为空气传播孢子检测和疾病预防提供了一种低成本、小型化和自动化的平台技术设计。
