AIMC Topic: Food Packaging

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Unveiling Hidden Health Risks: Machine Learning Enhanced Modeling of Plastic Additive Release Kinetics in Fresh Produce Packaging.

Environmental science & technology Jun 10, 2025
Fresh produce packaging (FPP) plays a critical role in protecting fruits and vegetables from various environmental factors. However, the presence, migration, and human health risks of additives in FPP have received limited attention. This study inves...
Humans Machine Learning Fruit Vegetables Plasticizers Food Packaging Plastics Kinetics
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Prediction of the packaging chemical migration into food and water by cutting-edge machine learning techniques.

Scientific reports Mar 6, 2025
Chemicals transfer from the packaging materials and their dissolution in food and water can create health risks. Due to the costly and time-intensive nature of experimental measurements, employing artificial intelligence (AI) methodologies is benefic...
Food Contamination Water Food Packaging Neural Networks, Computer Machine Learning Algorithms
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Identifying plastic materials in post-consumer food containers and packaging waste using terahertz spectroscopy and machine learning.

Waste management (New York, N.Y.) Feb 18, 2025
Accurate identification of plastic materials from post-consumer food container and packaging waste is crucial for enhancing the purity and added value of recycled materials, thereby promoting recycling and addressing the issue of plastic pollution. H...
Recycling Food Packaging Polyethylene Terephthalates Bayes Theorem Terahertz Spectroscopy Machine Learning Plastics
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An intelligent fruit freshness monitoring system using hydrophobic indicator labels based on methylcellulose, k-carrageenan, and sodium tripolyphosphate, combined with deep learning.

International journal of biological macromolecules Jan 17, 2025
As the demand for food quality and safety continues to rise, pH-responsive intelligent packaging technologies have found widespread application in the monitoring of food freshness. This study introduces a methylcellulose (MC)-based indicator label de...
Deep Learning Hydrophobic and Hydrophilic Interactions Carrageenan Food Quality Food Packaging Methylcellulose Fruit Polyphosphates
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Effect-directed analysis of genotoxicants in food packaging based on HPTLC fractionation, bioassays, and toxicity prediction with machine learning.

Analytical and bioanalytical chemistry Nov 23, 2024
Many chemicals in food packaging can leach as complex mixtures to food, potentially including substances hazardous to consumer health. Detecting and identifying all of the leachable chemicals are impractical with current analytical instrumentation an...
Mutagens Chromatography, Thin Layer Biological Assay Tandem Mass Spectrometry Machine Learning Animals Food Packaging
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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...
Beverages Microwaves Food Packaging Food Contamination Algorithms Food Analysis Machine Learning Support Vector Machine
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Innovative AI methods for monitoring front-of-package information: A case study on infant foods.

PloS one May 16, 2024
Front-of-package (FOP) is one of the most direct communication channels connecting manufacturers and consumers, as it displays crucial information such as certification, nutrition, and health. Traditional methods for obtaining information from FOPs o...
Artificial Intelligence Infant Food Packaging Infant Food Food Labeling Humans
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Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Meat science Mar 31, 2024
Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns...
Food Microbiology Neural Networks, Computer Oxygen Swine Machine Learning Volatile Organic Compounds Food Storage Food Packaging Animals Pork Meat Mass Spectrometry
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An Innovative Machine Learning Approach to Predict the Dietary Fiber Content of Packaged Foods.

Nutrients Sep 14, 2021
Underconsumption of dietary fiber is prevalent worldwide and is associated with multiple adverse health conditions. Despite the importance of fiber, the labeling of fiber content on packaged foods and beverages is voluntary in most countries, making ...
Food Packaging Nutrition Policy Food Analysis Fast Foods Feeding Behavior Humans Diet Australia Food Labeling Nutritive Value Beverages Machine Learning Energy Intake Automation Dietary Fiber Algorithms Nutrients Nutritional Status
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Artificial Intelligence Methods for Constructing Wine Barrels with a Controlled Oxygen Transmission Rate.

Molecules (Basel, Switzerland) Jul 21, 2020
Oxygen is an important factor in the wine aging process, and the oxygen transmission rate (OTR) is the parameter of the wood that reflects its oxygen permeation. OTR has not been considered in the cooperage industry yet; however, recent studies propo...
Wine Food Packaging Artificial Intelligence Wood Oxidation-Reduction Time Factors Oxygen
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