AIMC Topic: Pesticide Residues

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Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea.

Food chemistry
Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employi...

Multi-Pesticide Residue Analysis Method Designed for the Robot Experimenters.

Journal of agricultural and food chemistry
Robots replacing humans as the executioners is crucial work for intelligent multi-pesticide residue analysis to maximize reproducibility and throughput while minimizing the expertise required to perform the entire process. Traditional analysis method...

Deep Learning-Based Multicapturer SERS Platform on Plasmonic Nanocube Metasurfaces for Multiplex Detection of Organophosphorus Pesticides in Environmental Water.

Analytical chemistry
In situ rapid detection of contaminants in environmental water is crucial for protecting the ecological environment and human health; however, it is always hindered by the complexity of sample matrices, trace content, and unknown species. Herein, we ...

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...

rGO-NS SERS-based coupled chemometric prediction of acetamiprid residue in green tea.

Journal of food and drug analysis
Pesticide residue in food is of grave concern in recent years. In this paper, a rapid, sensitive, SERS (Surface-enhanced Raman scattering) active reduced-graphene-oxide-gold-nano-star (rGO-NS) nano-composite nanosensor was developed for the detection...

Prediction of Collision Cross-Section Values for Small Molecules: Application to Pesticide Residue Analysis.

Analytical chemistry
The use of collision cross-section (CCS) values obtained by ion mobility high-resolution mass spectrometry has added a third dimension (alongside retention time and exact mass) to aid in the identification of compounds. However, its utility is limite...

Persistence after prohibition: Revealing the drivers of traditional and novel organochlorine pesticide residues in river sediments.

Environmental research
Legacy organochlorine pesticides (OCPs) persist as global environmental threats despite international bans, while novel OCPs have been widely adopted as alternatives; however, the spatiotemporal dynamics and regulatory drivers of both legacy and nove...

Machine Learning-Assisted Multicolor Fluorescence Assay for Visual Data Acquisition and Intelligent Inspection of Multiple Food Hazards Regardless of Matrix Interference.

ACS sensors
Regarding the significant health risks of pesticide residue in foods, while current sensors still suffer from limited efficiency and stability, as well as difficulties in qualitative identification and quantitative detection of mixtures, development ...

The fluorescence spectrum combined with a broad learning system to characterize the content of difenoconazole in cabbage.

Analytical methods : advancing methods and applications
Pesticide residue detection plays an important role in vegetable quality and food safety. In this work, we propose a method for detecting difenoconazole pesticide residues based on fluorescence spectroscopy technology and machine learning algorithms....

Analysis of pesticide residues by a support vector machine combined with fluorescence spectroscopy.

Applied optics
Pesticide residues enter a lake through the water cycle, causing harm to the water environment and human health. It is necessary to select highly sensitive fluorescence spectroscopy to detect pesticides (bifenthrin, prochloraz, and cyromazine), and a...