Development of a new spectral database of photo-induced pesticide compounds for an automatic monitoring and identification system

IF 5.7 2区 化学 Q1 CHEMISTRY, ANALYTICAL
Coumba Faye , El Hadji T. Bodian , Diène D. Thiaré , Diéry Diouf , Ndeye A. Diop , Jean-Pierre Bakhoum , Lamine Cisse , Pape A. Diaw , Atanasse Coly , Philippe Giamarchi
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引用次数: 0

Abstract

Background

Due to the widespread use of pesticides, it is necessary to monitor surface water quality for environmental protection, industrial use and tap water production. Many analytical methods based on chromatographic separations and mass spectrometry detection can be used, but they are complex and expensive. They also require sampling and transport to the laboratory, which delays the results. We therefore need automatic monitoring systems that can detect and identify pesticides at low cost and with simple technology.

Results

As many pesticides are non-fluorescent, we have chosen the photoinduced fluorescence method for detection. However this method lacks of specificity. To improve this, we present a new fluorescence database of photoinduced pesticide compounds. It is designed in an original way to be lightweight, containing only four spectra of each pesticide concatenated into a single 'combined fluorescence spectrum'. It can therefore be used with a simple spreadsheet to identify pesticides by spectral similarity. The database is then combined with an automated pesticide monitoring system using photo-induced fluorescence to add identification capability.
Analytical applications are carried out on-line to determine rimsulfuron and sulfometuron-methyl, with good analytical results. The identification process using the database is then self-tested against the spectra of these two pesticides, leading to correct results.

Significance

This work presents the first spectrofluorimetric database of photoinduced compounds of pesticides. It has been designed to be easy to use, even by an unskilled user. Combined with an automated monitoring system, it becomes the first to allow simultaneous detection and identification of pesticides in surface water. The results showed good identification results and good analytical performance.

Abstract Image

Abstract Image

为自动监测和识别系统开发新的光诱导农药化合物光谱数据库。
背景由于农药的广泛使用,有必要对地表水水质进行监测,以保护环境、工业用水和自来水生产。可以使用许多基于色谱分离和质谱检测的分析方法,但这些方法复杂而昂贵。此外,这些方法还需要取样并运送到实验室,从而延误了结果的得出。因此,我们需要能以低成本和简单技术检测和识别农药的自动监测系统。结果 由于许多农药是非荧光性的,我们选择了光诱导荧光法进行检测。然而,这种方法缺乏特异性。为了改善这种情况,我们建立了一个新的光诱导农药化合物荧光数据库。该数据库设计新颖,重量轻,只包含每种农药的四个光谱,并将其合并为一个 "组合荧光光谱"。因此,只需使用一个简单的电子表格,就能通过光谱相似性识别农药。然后将该数据库与使用光诱导荧光的自动农药监测系统结合起来,以增加识别能力。分析应用在线进行,以确定嘧磺隆和甲基磺草酮,分析结果良好。然后,使用数据库对这两种农药的光谱进行了自我测试,从而得出了正确的结果。该数据库的设计易于使用,即使是不熟练的用户也能轻松上手。它与自动监测系统相结合,首次实现了对地表水中农药的同步检测和识别。结果表明,该仪器具有良好的鉴定结果和分析性能。
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来源期刊
Analytica Chimica Acta
Analytica Chimica Acta 化学-分析化学
CiteScore
10.40
自引率
6.50%
发文量
1081
审稿时长
38 days
期刊介绍: Analytica Chimica Acta has an open access mirror journal Analytica Chimica Acta: X, sharing the same aims and scope, editorial team, submission system and rigorous peer review. Analytica Chimica Acta provides a forum for the rapid publication of original research, and critical, comprehensive reviews dealing with all aspects of fundamental and applied modern analytical chemistry. The journal welcomes the submission of research papers which report studies concerning the development of new and significant analytical methodologies. In determining the suitability of submitted articles for publication, particular scrutiny will be placed on the degree of novelty and impact of the research and the extent to which it adds to the existing body of knowledge in analytical chemistry.
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