AIMC Topic: Vegetables

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Pseudo-random Number Generator Influences on Average Treatment Effect Estimates Obtained with Machine Learning.

Epidemiology (Cambridge, Mass.) Aug 16, 2024
BACKGROUND: The use of machine learning to estimate exposure effects introduces a dependence between the results of an empirical study and the value of the seed used to fix the pseudo-random number generator.
Humans Diet Pre-Eclampsia Vegetables Fruit Pregnancy Female Machine Learning Adult Algorithms
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Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.

Journal of hazardous materials Aug 10, 2024
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...
China Agriculture Humans Environmental Monitoring Machine Learning Vegetables Risk Assessment Monte Carlo Method Metals, Heavy Food Contamination Soil Pollutants
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Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables.

Food chemistry Jul 17, 2024
Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT...
Metal Nanoparticles Limit of Detection Copper Carbon Electrochemical Techniques Bridged Bicyclo Compounds, Heterocyclic Nitrites Polymers Vegetables Machine Learning Food Contamination
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Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.

Scientific reports Jun 28, 2024
Remote sensing has been increasingly used in precision agriculture. Buoyed by the developments in the miniaturization of sensors and platforms, contemporary remote sensing offers data at resolutions finer enough to respond to within-farm variations. ...
Solanum lycopersicum Vegetables India Solanum melongena Agriculture Crops, Agricultural Deep Learning Remote Sensing Technology
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Surface-Enhanced Raman Scattering Imaging Assisted by Machine Learning Analysis: Unveiling Pesticide Molecule Permeation in Crop Tissues.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Jun 24, 2024
Surface-enhanced Raman scattering (SERS) imaging technology faces significant technical bottlenecks in ensuring balanced spatial resolution, preventing image bias induced by substrate heterogeneity, accurate quantitative analysis, and substrate prepa...
Vegetables Crops, Agricultural Pesticides Silver Fruit Spectrum Analysis, Raman Metal Nanoparticles Machine Learning
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Rapid detection of residual chlorpyrifos and pyrimethanil on fruit surface by surface-enhanced Raman spectroscopy integrated with deep learning approach.

Scientific reports Nov 13, 2023
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...
Spectrum Analysis, Raman Fungicides, Industrial Humans Vegetables Chlorpyrifos Fruit Deep Learning Pesticides
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Large-scale automatic extraction of agricultural greenhouses based on high-resolution remote sensing and deep learning technologies.

Environmental science and pollution research international Sep 21, 2023
Widely used agricultural greenhouses are critical in the development of facility agriculture because of not only their huge capacity in food and vegetable supplies, but also their environmental and climatic effects. Therefore, it is important to obta...
Vegetables Conservation of Natural Resources Deep Learning Agriculture China Remote Sensing Technology
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Fruit Sizing in Orchard: A Review from Caliper to Machine Vision with Deep Learning.

Sensors (Basel, Switzerland) Apr 10, 2023
Forward estimates of harvest load require information on fruit size as well as number. The task of sizing fruit and vegetables has been automated in the packhouse, progressing from mechanical methods to machine vision over the last three decades. Thi...
Deep Learning Trees Fruit Vegetables
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Detection of Green Asparagus Using Improved Mask R-CNN for Automatic Harvesting.

Sensors (Basel, Switzerland) Nov 28, 2022
Advancements in deep learning and computer vision have led to the discovery of numerous effective solutions to challenging problems in the field of agricultural automation. With the aim to improve the detection precision in the autonomous harvesting ...
Vegetables Algorithms Neural Networks, Computer Automation Agriculture
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Improved Classification Approach for Fruits and Vegetables Freshness Based on Deep Learning.

Sensors (Basel, Switzerland) Oct 26, 2022
Classification of fruit and vegetable freshness plays an essential role in the food industry. Freshness is a fundamental measure of fruit and vegetable quality that directly affects the physical health and purchasing motivation of consumers. In addit...
Motivation Fruit Humans Consumer Behavior Vegetables Deep Learning
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