PDF(Pubmed)
Abstract：
An electronic device based on the detection of volatile substances was developed in response to the need to distinguish between fungal infestations in food and was applied to wheat grains. The most common pathogens belong to the fungi of the genus Fusarium: F. avenaceum, F. langsethiae, F. poae, and F. sporotrichioides. The electronic nose prototype is a low-cost device based on commercially available TGS series sensors from Figaro Corp. Two types of gas sensors that respond to the perturbation are used to collect signals useful for discriminating between the samples under study. First, an electronic nose detects the transient response of the sensors to a change in operating conditions from clean air to the presence of the gas being measured. A simple gas chamber was used to create a sudden change in gas composition near the sensors. An inexpensive pneumatic system consisting of a pump and a carbon filter was used to supply the system with clean air. It was also used to clean the sensors between measurement cycles. The second function of the electronic nose is to detect the response of the sensor to temperature disturbances of the sensor heater in the presence of the gas to be measured. It has been shown that features extracted from the transient response of the sensor to perturbations by modulating the temperature of the sensor heater resulted in better classification performance than when the machine learning model was built from features extracted from the response of the sensor in the gas adsorption phase. By combining features from both phases of the sensor response, a further improvement in classification performance was achieved. The E-nose enabled the differentiation of F. poae from the other fungal species tested with excellent performance. The overall classification rate using the Support Vector Machine model reached 70 per cent between the four fungal categories tested.
摘要：
针对区分食品中真菌感染的需要，开发了一种基于挥发性物质检测的电子设备，并将其应用于小麦谷物。最常见的病原体属于镰刀菌属真菌：F.avenaceum，F.langsathiae,F.poae,和F.孢子richioides。电子鼻原型是基于FigaroCorp.的市售TGS系列传感器的低成本设备响应扰动的两种类型的气体传感器用于收集用于区分所研究样品的信号。首先,例如,电子鼻检测传感器对从清洁空气到被测量气体的存在的操作条件的变化的瞬态响应。使用简单的气室来在传感器附近产生气体成分的突然变化。使用由泵和碳过滤器组成的廉价气动系统向系统供应清洁空气。它还用于在测量周期之间清洁传感器。电子鼻的第二个功能是在存在待测气体的情况下检测传感器对传感器加热器的温度扰动的响应。已经表明,通过调制传感器加热器的温度从传感器对扰动的瞬态响应中提取的特征导致比在从气体吸附阶段中的传感器的响应中提取的特征建立机器学习模型时更好的分类性能。通过组合来自传感器响应的两个阶段的特征,分类性能进一步提高。E-nose能够将F.poae与其他测试的真菌物种区分开来，并具有出色的性能。在所测试的四个真菌类别之间，使用支持向量机模型的总体分类率达到了70％。
