AIMC Topic: Food Analysis

Clear Filters Showing 21 to 30 of 90 articles

An artificial intelligence handheld sensor for direct reading of nickel ion and ethylenediaminetetraacetic acid in food samples using ratiometric fluorescence cellulose paper microfluidic chip.

International journal of biological macromolecules Aug 30, 2024
User-friendly in-field sensing protocol is crucial for the effective tracing of intended analytes under less-developed countries or resources-limited environments. Nevertheless, existing sensing strategies require professional technicians and expensi...
Fluorescence Biosensing Techniques Food Analysis Artificial Intelligence Paper Edetic Acid Lab-On-A-Chip Devices Quantum Dots Nickel Cellulose
View on PubMed DOI

Application of untargeted liquid chromatography-mass spectrometry to routine analysis of food using three-dimensional bucketing and machine learning.

Scientific reports Jul 18, 2024
For the detection of food adulteration, sensitive and reproducible analytical methods are required. Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is a highly sensitive method that can be used to obtain analytical finger...
Honey Machine Learning Food Analysis Liquid Chromatography-Mass Spectrometry Food Contamination
View on PubMed DOI

An eco-friendly approach for analysing sugars, minerals, and colour in brown sugar using digital image processing and machine learning.

Food research international (Ottawa, Ont.) Jun 28, 2024
Brown sugar is a natural sweetener obtained by thermal processing, with interesting nutritional characteristics. However, it has significant sensory variability, which directly affects product quality and consumer choice. Therefore, developing rapid ...
Sugars Sweetening Agents Minerals Algorithms Sucrose Image Processing, Computer-Assisted Machine Learning Food Analysis Smartphone Color
View on PubMed DOI

Ensuring food safety by artificial intelligence-enhanced nanosensor arrays.

Advances in food and nutrition research Jun 18, 2024
Current analytical methods utilized for food safety inspection requires improvement in terms of their cost-efficiency, speed of detection, and ease of use. Sensor array technology has emerged as a food safety assessment method that applies multiple c...
Artificial Intelligence Machine Learning Biosensing Techniques Humans Food Contamination Nanostructures Nanotechnology Food Analysis Food Safety
View on PubMed DOI

Machine learning powered CN-coordinated cobalt nanoparticles embedded cellulosic nanofibers to assess meat quality via clenbuterol monitoring.

Biosensors & bioelectronics Jun 13, 2024
The World Anti-Doping Agency (WADA) has prohibited the use of clenbuterol (CLN) because it induces anabolic muscle growth while potentially causing adverse effects such as palpitations, anxiety, and muscle tremors. Thus, it is vital to assess meat qu...
Metal Nanoparticles Limit of Detection Meat Carbon Electrochemical Techniques Clenbuterol Aniline Compounds Nanofibers Cobalt Animals Biosensing Techniques Food Analysis Cellulose Food Contamination Machine Learning
View on PubMed DOI

Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.

Scientific reports Jun 11, 2024
In the food industry, the increasing use of automatic processes in the production line is contributing to the higher probability of finding contaminants inside food packages. Detecting these contaminants before sending the products to market has beco...
Machine Learning Algorithms Microwaves Food Contamination Support Vector Machine Food Analysis Food Packaging Beverages
View on PubMed DOI

Machine learning methods in near infrared spectroscopy for predicting sensory traits in sweetpotatoes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy May 4, 2024
It has been established that near infrared (NIR) spectroscopy has the potential of estimating sensory traits given the direct spectral responses that these properties have in the NIR region. In sweetpotato, sensory and texture traits are key for impr...
Humans Machine Learning Spectroscopy, Near-Infrared Ipomoea batatas Algorithms Food Analysis Models, Statistical Food Quality Plant Breeding Sensation
View on PubMed DOI

Food for Thought: Optical Sensor Arrays and Machine Learning for the Food and Beverage Industry.

ACS sensors Apr 10, 2024
Arrays of cross-reactive sensors, combined with statistical or machine learning analysis of their multivariate outputs, have enabled the holistic analysis of complex samples in biomedicine, environmental science, and consumer products. Comparisons ar...
Food Analysis Humans Beverages Machine Learning Food Industry
View on PubMed DOI

Vision-based food nutrition estimation via RGB-D fusion network.

Food chemistry May 17, 2023
With the development of deep learning technology, vision-based food nutrition estimation is gradually entering the public view for its advantage in accuracy and efficiency. In this paper, we designed one RGB-D fusion network, which integrated multimo...
Nutritive Value Food Analysis Nutrients Deep Learning
View on PubMed DOI

Neural network in food analytics.

Critical reviews in food science and nutrition Nov 2, 2022
Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpo...
Food Technology Deep Learning Humans Food Analysis Food Safety Neural Networks, Computer Food Supply
View on PubMed DOI
Popular Topics
Recent Journals