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利用“电子鼻”检测绵羊的皮肤蝇蛆病。

Detection of cutaneous myiasis in sheep using an 'electronic nose'.

机构信息

Animal Research Institute, Queensland Primary Industries and Fisheries,Yeerongpilly 4105, Queensland, Australia.

出版信息

Vet Parasitol. 2009 Dec 23;166(3-4):293-8. doi: 10.1016/j.vetpar.2009.08.025. Epub 2009 Sep 4.

Abstract

Cutaneous myiasis (flystrike), in Australia caused primarily by Lucilia cuprina [Diptera: Calliphoridae], is a debilitating, painful and potentially lethal disease of sheep. Early detection of flystrike is difficult and continual flock surveillance is required to enable timely treatment of struck sheep. Electronic nose technology offers the potential for early and automated detection of flystrike. An electronic nose consisting of six metal oxide semiconductor sensors and temperature and humidity sensors was used to measure odours collected by dynamic headspace sampling during flystrike development in four experiments and from urine- and faeces-stained fleece in one experiment. Non-linear signal measurement techniques and linear discriminant analysis (LDA) were used to extract signal features and process those features for analysis of categorical separation of odour groups. The results from LDA indicated that the electronic nose accurately distinguished flystrike odour on days 1, 2 and 3 of development from that of dry wool in all experiments (P<0.05). The electronic nose was also able to discriminate flystrike odour on the day of larval implantation (day 0) in three of the four studies. In the experiment with urine- and faeces-stained wool, these odours were accurately distinguished from both dry wool and flystrike (P<0.05). This study provides proof-of-concept for the detection of flystrike using electronic nose technology. Practical methods for collection of odour in the field and suitable detection algorithms will be required for development to commercial application.

摘要

皮肤蝇蛆病(蝇蛆病),在澳大利亚主要由 Lucilia cuprina [双翅目:Calliphoridae]引起,是一种使绵羊衰弱、疼痛且潜在致命的疾病。蝇蛆病的早期检测很困难,需要持续对羊群进行监测,以便及时治疗受感染的绵羊。电子鼻技术为蝇蛆病的早期和自动检测提供了潜力。一个由六个金属氧化物半导体传感器和温度和湿度传感器组成的电子鼻用于测量在四个实验中蝇蛆病发展过程中通过动态顶空采样收集的气味,以及在一个实验中从尿液和粪便污染的羊毛中收集的气味。非线性信号测量技术和线性判别分析(LDA)用于提取信号特征,并对这些特征进行处理,以分析气味组的分类分离。LDA 的结果表明,电子鼻在所有实验中准确地区分了蝇蛆病发展第 1、2 和 3 天的气味与干燥羊毛的气味(P<0.05)。电子鼻还能够在四个研究中的三个研究中区分幼虫植入日(第 0 天)的蝇蛆病气味。在尿液和粪便污染羊毛的实验中,这些气味与干燥羊毛和蝇蛆病的气味都得到了准确区分(P<0.05)。本研究为使用电子鼻技术检测蝇蛆病提供了概念验证。需要开发实用的现场气味收集方法和合适的检测算法,以将其推向商业应用。

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