AIMC Topic: Pesticides

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Integrating transformer-based machine learning with SERS technology for the analysis of hazardous pesticides in spinach.

Journal of hazardous materials
This study introduces an innovative strategy for the rapid and accurate identification of pesticide residues in agricultural products by combining surface-enhanced Raman spectroscopy (SERS) with a state-of-the-art transformer model, termed SERSFormer...

Deep Learning Model for Classifying and Evaluating Soybean Leaf Disease Damage.

International journal of molecular sciences
Soybean ( (L.) Merr.) is a major source of oil and protein for human food and animal feed; however, soybean crops face diverse factors causing damage, including pathogen infections, environmental shifts, poor fertilization, and incorrect pesticide us...

Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach.

Scientific reports
Chlorpyrifos and pyrimethanil are widely used insecticides/fungicides in agriculture. The residual pesticides/fungicides remaining in fruits and vegetables may do harm to human health if they are taken without notice by the customers. Therefore, it i...

Taylor Remora optimization enabled deep learning algorithms for percentage of pesticide detection in grapes.

Environmental science and pollution research international
In the world, grapes are considered as the most significant fruit, and it comprises various nutrients, like Vitamin C and it is utilized to produce wines and raisins. The major six general grape leaf diseases and pests are brown spots, leaf blight, d...

A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide.

Analytical and bioanalytical chemistry
A novel deep learning-enabled smartphone platform is developed to assist a colorimetric aptamer biosensor for fast and highly sensitive detection of dimethoate. The colorimetric determination of dimethoate is based on the specific binding of dimethoa...

Precision agricultural robotic sprayer with real-time Tobacco recognition and spraying system based on deep learning.

PloS one
Precision agricultural techniques try to prevent either an excessive or inadequate application of agrochemicals during pesticide application. In recent years, it has become popular to combine traditional agricultural practices with artificial intelli...

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 ...

Portable Deep Learning-Driven Ion-Sensitive Field-Effect Transistor Scheme for Measurement of Carbaryl Pesticide.

Sensors (Basel, Switzerland)
This research proposes a multiple-input deep learning-driven ion-sensitive field-effect transistor (ISFET) scheme to predict the concentrations of carbaryl pesticide. In the study, the carbaryl concentrations are varied between 1 × 10-1 × 10 M, and t...

A deep learning model to detect novel pore-forming proteins.

Scientific reports
Many pore-forming proteins originating from pathogenic bacteria are toxic against agricultural pests. They are the key ingredients in several pesticidal products for agricultural use, including transgenic crops. There is an urgent need to identify no...

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...