Wakeham Alison J, Keane Gary, Kennedy Roy
Institute of Science and the Environment, University of Worcester, Henwick Grove, Worcester, WR2 6AJ, UK.
Warwickshire College Group, Pershore College, Avonbank, Pershore, Worcestershire, WR10 3JP.
Plant Dis. 2016 Sep;100(9):1831-1839. doi: 10.1094/PDIS-10-15-1211-RE. Epub 2016 Jun 29.
On-site detection of inoculum of polycyclic plant pathogens could potentially contribute to management of disease outbreaks. A 6-min, in-field competitive immunochromatographic lateral flow device (CLFD) assay was developed for detection of Alternaria brassicae (the cause of dark leaf spot in brassica crops) in air sampled above the crop canopy. Visual recording of the test result by eye provides a detection threshold of approximately 50 dark leaf spot conidia. Assessment using a portable reader improved test sensitivity. In combination with a weather-driven infection model, CLFD assays were evaluated as part of an in-field risk assessment to identify periods when brassica crops were at risk from A. brassicae infection. The weather-driven model overpredicted A. brassicae infection. An automated 7-day multivial cyclone air sampler combined with a daily in-field CLFD assay detected A. brassicae conidia air samples from above the crops. Integration of information from an in-field detection system (CLFD) with weather-driven mathematical models predicting pathogen infection have the potential for use within disease management systems.
现场检测多循环植物病原体的接种体可能有助于疾病爆发的管理。开发了一种6分钟的田间竞争性免疫层析侧流装置(CLFD)检测方法,用于检测甘蓝作物冠层上方空气中的芸苔链格孢(甘蓝作物黑叶斑病的病原菌)。通过肉眼对测试结果进行视觉记录,检测阈值约为50个黑叶斑分生孢子。使用便携式读数器进行评估提高了测试灵敏度。结合天气驱动的感染模型,CLFD检测方法作为田间风险评估的一部分进行了评估,以确定甘蓝作物易受芸苔链格孢感染的时期。天气驱动模型对芸苔链格孢感染的预测过高。一种自动化的7天多瓶旋风式空气采样器与每日田间CLFD检测相结合,检测到了作物上方空气中的芸苔链格孢分生孢子样本。将田间检测系统(CLFD)的信息与预测病原体感染的天气驱动数学模型相结合,有可能在疾病管理系统中得到应用。