AIMC Topic: Food Contamination
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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...
Machine Learning Applied to the Detection of Mycotoxin in Food: A Systematic Review.
Toxins
Jun 12, 2024
Mycotoxins, toxic secondary metabolites produced by certain fungi, pose significant threats to global food safety and public health. These compounds can contaminate a variety of crops, leading to economic losses and health risks to both humans and an...
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...
Tracing the origin and authenticity of Spanish PDO honey using metagenomics and machine learning.
International journal of food microbiology
Jun 8, 2024
The Protected Designation of Origin (PDO) indication for foods intends to guarantee the conditions of production and the geographical origin of regional products within the European Union. Honey products are widely consumed due to their health-promot...
Deep learning assisted logic gates for real-time identification of natural tetracycline antibiotics.
Food chemistry
May 30, 2024
The overuse and misuse of tetracycline (TCs) antibiotics, including tetracycline (TTC), oxytetracycline (OTC), doxycycline (DC), and chlortetracycline (CTC), pose a serious threat to human health. However, current rapid sensing platforms for tetracyc...
Detection of milk adulteration using coffee ring effect and convolutional neural network.
Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment
May 30, 2024
A low-cost and effective method is reported to identify water and synthetic milk adulteration of cow's milk using coffee ring patterns. The cow's milk samples were diluted with tap water (TW), distilled water (DW) and mineral water (MW) and drop cast...
Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS.
Toxins
May 23, 2024
Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate anal...
Machine learning to predict the relationship between Vibrio spp. concentrations in seawater and oysters and prevalent environmental conditions.
Food research international (Ottawa, Ont.)
May 10, 2024
Vibrio parahaemolyticus and Vibrio vulnificus are bacteria with a significant public health impact. Identifying factors impacting their presence and concentrations in food sources could enable the identification of significant risk factors and preven...
Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques.
Scientific reports
May 7, 2024
Discriminating different cultivars of maca powder (MP) and detecting their authenticity after adulteration with potent adulterants such as maize and soy flour is a challenge that has not been studied with non-invasive techniques such as near infrared...
Improving the detection accuracy of the dual SERS aptasensor system with uncontrollable SERS "hot spot" using machine learning tools.
Analytica chimica acta
Apr 19, 2024
BACKGROUND: Simultaneous detection of food contaminants is crucial in addressing the collective health hazards arising from the presence of multiple contaminants. However, traditional multi-competitive surface-enhanced Raman scattering (SERS) aptasen...
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