检测蜜蜂疾病:使用半导体气体传感器阵列的静脉曲张

A. Szczurek, M. Maciejewska, B. Bak, Jakub Wilk, J. Wilde, M. Siuda
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引用次数: 7

摘要

本文主要研究了基于气体传感器测量蜂巢空气的蜂群瓦螨入侵检测方法。检测主要包括确定菌落侵染率是否为0%或不同。在测量中使用了一组部分选择性气体传感器。它包括以下半导体气体传感器:TGS832, TGS2602, TGS823, TGS826, TGS2603和TGS2600。传感器在动态条件下暴露。采用分类方法解决了虫害检测问题。分类的基础是特征向量。它们由传感器的响应组成,是气体传感器阵列的元件。所利用的响应与动态暴露和再生期间记录的传感器信号的各个部分相关联。作为参考,我们用漂浮法估算了蜂群的毁灭性毁灭性害虫侵害率。最小的误分类误差为17%,使用k-NN分类器可以实现。试验研究是在野外条件下进行的。它包括各种各样的蜂群,安置在不同材料制成的蜂箱里,在不同的位置,在不同的大气条件下,在一天的不同时间进行检查。考虑到这一点,在17%的水平上的检测误差是一个有希望的结果。它证明了使用部分选择性传感器阵列检测静脉曲张的可能性。
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Detection of Honeybee Disease: Varrosis using a Semiconductor Gas Sensor Array
The presented study was focussed on the detection of Varroa destructor infestation of honeybee colonies, based on gas sensor measurements of beehive air. The detection consisted in determination whether the colony infestation rate was 0% or different. An array of partially selective gas sensors was used in measurements. It included the following semiconductor gas sensors: TGS832, TGS2602, TGS823, TGS826, TGS2603 and TGS2600. The sensors were exposed in dynamic conditions. The infestation detection problem was solved using a classification approach. The basis for classification were feature vectors. They were composed of responses of sensors, elements of the gas sensor array. The utilised responses were associated with various parts of the sensor signal recorded during dynamic exposure and regeneration. As a reference, we used the V. destructor infestation rate of bee colonies estimated using a flotation method. The smallest misclassification error was 17% and it was achieved with the k-NN classifier. The experimental study was performed in field conditions. It included honeybee colonies of various kinds, settled in beehives made of various materials, differently located, examined in various atmospheric conditions, at different times of the day. Taking this into consideration, the detection error at the level of 17 % is a promising result. It demonstrates the possibility to detect varroosis using an array of partially selective sensors.
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