AIMC Topic: Food Quality

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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...
Image Processing, Computer-Assisted Ethanol Fruit Artificial Intelligence Food Quality Photoacoustic Techniques Ethylenes Spectrum Analysis Ammonia
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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...
Lebanon Machine Learning Fruit Food Quality Phenols
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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...
Humans Deep Learning Fruit Food Inspection Hyperspectral Imaging Food Safety Food Quality Quality Control Vegetables
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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...
Algorithms Spectroscopy, Near-Infrared Tea Machine Learning Quality Control Food Quality
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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 Quality Food Contamination Food Analysis Crops, Agricultural Arachis Oryza Neural Networks, Computer Agriculture
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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...
Food Packaging Methylcellulose Hydrophobic and Hydrophilic Interactions Carrageenan Fruit Deep Learning Food Quality Polyphosphates
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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...
Quality Control Flour Food Quality Food Analysis Triticum Spectroscopy, Near-Infrared Deep Learning Neural Networks, Computer 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...
Humans Artificial Intelligence Food Quality Fraud Food Contamination Food Industry
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Enhanced food authenticity control using machine learning-assisted elemental analysis.

Food research international (Ottawa, Ont.) Nov 13, 2024
With the increasing attention being paid to the authenticity of food, efficient and accurate techniques that can solve relevant problems are crucial for improving public trust in food. This review explains two main aspects of food authenticity, namel...
Quality Control Metals, Heavy Food Contamination Food Quality Food Analysis Food, Organic Machine Learning Algorithms
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Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network.

Meat science Nov 10, 2024
The quality of beef meatballs during repeated freeze-thaw (F-T) cycles was assessed by multiple indicators. This study introduced a novel quality evaluation method using hyperspectral imaging (HSI) and multi-task learning. Seventeen quality indicator...
Meat Products Quality Control Hyperspectral Imaging Animals Cattle Food Quality Freezing Red Meat Neural Networks, Computer
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