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Sampling Methods for Detection and Monitoring of the Asian Citrus Psyllid (Hemiptera: Psyllidae)

机译:亚洲柑橘木虱(半翅目:木虱)的检测和监测抽样方法

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摘要

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama is a key pest of citrus due to its role as vector of citrus greening disease or "huanglongbing." ACP monitoring is considered an indispensable tool for management of vector and disease. In the present study, datasets collected between 2009 and 2013 from 245 citrus blocks were used to evaluate precision, sensitivity for detection, and efficiency of five sampling methods. The number of samples needed to reach a 0.25 standard error-mean ratio was estimated using Taylor's power law and used to compare precision among sampling methods. Comparison of detection sensitivity and time expenditure (cost) between stem-tap and other sampling methodologies conducted consecutively at the same location were also assessed. Stem-tap sampling was the most efficient sampling method when ACP densities were moderate to high and served as the basis for comparison with all other methods. Protocols that grouped trees near randomly selected locations across the block were more efficient than sampling trees at random across the block. Sweep net sampling was similar to stem-taps in number of captures per sampled unit, but less precise at any ACP density. Yellow sticky traps were 14 times more sensitive than stem-taps but much more time consuming and thus less efficient except at very low population densities. Visual sampling was efficient for detecting and monitoring ACP at low densities. Suction sampling was time consuming and taxing but the most sensitive of all methods for detection of sparse populations. This information can be used to optimize ACP monitoring efforts.
机译:亚洲柑桔木虱(Adiaphorina citri Kuwayama)是柑桔的主要害虫,因为它是柑桔绿化病或“黄龙病”的媒介。 ACP监测被认为是控制病媒和疾病必不可少的工具。在本研究中,使用2009年至2013年从245个柑橘类植物中收集的数据集来评估精度,检测灵敏度和五种采样方法的效率。使用泰勒幂定律估算达到0.25标准误均值比所需的样本数量,并将其用于比较采样方法之间的精度。还评估了在同一地点连续进行的抽头抽查和其他采样方法之间的检测灵敏度和时间花费(成本)的比较。当ACP密度从中到高时,茎抽采样是最有效的采样方法,并作为与所有其他方法进行比较的基础。在整个区块中随机选择的位置附近对树木进行分组的协议比在整个区块中随机抽样树更有效。扫网采样在每个采样单元的捕获次数上与茎抽类似,但是在任何ACP密度下精度都不高。黄色粘性陷阱的灵敏度是茎尖的14倍,但耗时更多,因此效率较低,除非人口密度非常低。视觉采样可以有效地检测和监视低密度的ACP。抽吸采样既费时又费力,但在所有检测稀疏人口的方法中最敏感。此信息可用于优化ACP监视工作。

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