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Building an antibody-based pathogen specific plant disease monitoring device for agriculture pest management

机译:建立用于农业病虫害管理的基于抗体的病原体特异性植物病害监测装置

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Current plant disease forecasting models require collection of information on inoculum density or pathogen load. This information is typically collected using subjective assessments or laborious and slow spore trapping or pathogen culturing methods, which in turn limit the amount of data that can be collected and may delay results past the time that disease control decisions can be made. In this article, we have selected Sclerotinia sclerotiorum, the causal agent of stem rot of canola and many other economically important plant diseases, as our model target organism. We have shown that the conductivity of the nanoparticle-ascospore complexes is correlated with the number of spores. These signals could be easily processed electronically and converted to rapidly distributable results, e.g. to smart phones.
机译:当前的植物病害预测模型需要收集有关接种量或病原体负荷的信息。通常使用主观评估或费力且缓慢的孢子捕获或病原体培养方法来收集此信息,这反过来限制了可以收集的数据量,并且可能导致结果延迟到可以做出疾病控制决策的时间为止。在本文中,我们选择了油菜菌(Sclerotiania sclerotiorum),油菜茎腐病的病原体以及许多其他在经济上很重要的植物病害,作为我们的模型目标生物。我们已经表明,纳米颗粒-孢子复合物的电导率与孢子的数量有关。这些信号可以很容易地以电子方式处理并转换为可快速分配的结果,例如到智能手机。

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