AIMC Topic: Food Quality

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Automated seafood freshness detection and preservation analysis using machine learning and paper-based pH sensors.

Scientific reports Jul 18, 2025
Seafood, including fish, prawns and various marine products, is a critical component of global nutrition due to its high protein content, essential fatty acids, vitamins and minerals. Traditional methods for assessing seafood freshness such as sensor...
Machine Learning Seafood Food Preservation Food Quality Paper Animals Food Packaging Hydrogen-Ion Concentration Fishes Food Storage
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A Synergistic Approach Using Photoacoustic Spectroscopy and AI-Based Image Analysis for Post-Harvest Quality Assessment of Conference Pears.

Molecules (Basel, Switzerland) Jun 1, 2025
This study presents a non-invasive approach to monitoring post-harvest fruit quality by applying CO laser photoacoustic spectroscopy (COLPAS) to study the respiration of "Conference" pears from local and commercially stored (supermarket) sources. Con...
Ethanol Fruit Spectrum Analysis Artificial Intelligence Image Processing, Computer-Assisted Photoacoustic Techniques Ethylenes Ammonia Food Quality
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Unleashing the power of AI in predicting the technological and phenolic maturity of pomegranates cultivated in Lebanon.

Scientific reports May 30, 2025
The harvesting time of pomegranates is crucial for maximizing their health benefits and market value. However, traditional methods often fail to consider the intricate interactions between environmental conditions and fruit maturity. This study is th...
Machine Learning Phenols Food Quality Lebanon Fruit
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Rapid and chemical-free technique based on hyperspectral imaging combined with artificial intelligence for monitoring quality and shelf life of dried shrimp.

Food research international (Ottawa, Ont.) Apr 18, 2025
A rapid and chemical-free method based on hyperspectral imaging (HSI) integrated with artificial intelligence (AI) for monitoring dried shrimp quality was developed. Dried shrimp was packaged in a polypropylene bag and chronologically monitored for c...
Principal Component Analysis Thiobarbituric Acid Reactive Substances Neural Networks, Computer Food Storage Nitrogen Penaeidae Food Quality Hyperspectral Imaging Shellfish Xanthophylls Artificial Intelligence Animals
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Hyperspectral Imaging and Deep Learning for Quality and Safety Inspection of Fruits and Vegetables: A Review.

Journal of agricultural and food chemistry Apr 16, 2025
Quality inspection of fruits and vegetables linked to food safety monitoring and quality control. Traditional chemical analysis and physical measurement techniques are reliable, they are also time-consuming, costly, and susceptible to environmental a...
Food Safety Food Quality Food Inspection Vegetables Hyperspectral Imaging Humans Fruit Deep Learning Quality Control
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Improvement of near-infrared spectroscopic assessment methods for the quality of Keemun black tea: Utilizing transfer learning.

Food research international (Ottawa, Ont.) Mar 18, 2025
Keemun black tea, a renowned Chinese black tea, presents challenges in quality assessment due to variability in data across different years. To address this, we developed transfer learning algorithms using near-infrared spectral data. The qualitative...
Food Quality Algorithms Quality Control Machine Learning Spectroscopy, Near-Infrared Tea
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Origin traceability of agricultural products: A lightweight collaborative neural network for spectral information processing.

Food research international (Ottawa, Ont.) Mar 6, 2025
The natural conditions of various regions, including climate, soil, and water quality, significantly influence the nutrient composition and quality of agricultural products. Identifying the origin of agricultural products can prevent adulteration, im...
Food Contamination Food Analysis Crops, Agricultural Arachis Neural Networks, Computer Oryza Agriculture Food Quality
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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...
Polyphosphates Carrageenan Food Quality Methylcellulose Fruit Deep Learning Hydrophobic and Hydrophilic Interactions Food Packaging
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Lightweight deep learning algorithm for real-time wheat flour quality detection via NIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 22, 2024
Wheat flour quality, determined by factors such as protein and moisture content, is crucial in food production. Traditional methods for analyzing these parameters, though precise, are time-consuming and impractical for large-scale operations. This st...
Food Quality Triticum Spectroscopy, Near-Infrared Flour Quality Control Deep Learning Neural Networks, Computer Food Analysis Algorithms
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Recent advances on artificial intelligence-based approaches for food adulteration and fraud detection in the food industry: Challenges and opportunities.

Food chemistry Dec 10, 2024
Food adulteration is the deceitful practice of misleading consumers about food to profit from it. The threat to public health and food quality or nutritional valuable make it a major issue. Food origin and adulteration should be considered to safegua...
Food Industry Humans Artificial Intelligence Food Contamination Food Quality Fraud
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