AIMC Topic: Meat

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Assessment of POPs in foods from western China: Machine learning insights into risk and contamination drivers.

Environment international
Persistent organic pollutants (POPs), including PCDD/Fs, PCBs, and PBDEs, are major environmental and food safety concerns due to their bioaccumulative and toxic properties. However, comprehensive research on the concentrations and influencing factor...

Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.

Sensors (Basel, Switzerland)
Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. Hyperspectral imaging (HSI) offers a non-invasive mechanism to capture detailed spatial and spectral information, ena...

Monitoring of veterinary drug residues in mutton based on hyperspectral combined with explainable AI: A case study of OFX.

Food chemistry
Veterinary drug residues in meat seriously harm human health. Rapid and accurate detection of veterinary drug residues is necessary to minimize contamination. Taking ofloxacin (OFX) residues in mutton as an example, the near-infrared hyperspectral im...

Machine Vision with a CMOS-Based Hyperspectral Imaging Sensor Enables Sensing Meat Freshness.

ACS sensors
Imaging spectral information of materials and analysis of its properties have become an intriguing tool for consumer electronics used for food inspection, beauty care, etc. Those sensory physical quantities are difficult to quantify. Hyperspectral im...

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano
The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept.

Journal of food science
Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line processing technologies for rapid detection of muscle meat quality defects. At production plants, technolog...

Exploration of the prediction and generation patterns of heterocyclic aromatic amines in roast beef based on Genetic Algorithm combined with Support Vector Regression.

Food chemistry
Heterocyclic aromatic amines (HAAs) are harmful byproducts in food heating. Therefore, exploring the prediction and generation patterns of HAAs is of great significance. In this study, genetic algorithm (GA) and support vector regression (SVR) are us...

Online chicken carcass volume estimation using depth imaging and 3-D reconstruction.

Poultry science
Variability in the size of slaughtered chickens remains a longstanding challenge in the standardization of the poultry industry. To address this issue, we present a novel approach that uses volume as a grading metric for chicken carcasses. This innov...

Modeling and predicting meat yield and growth performance using morphological features of narrow-clawed crayfish with machine learning techniques.

Scientific reports
In recent studies, artificial intelligence and machine learning methods give higher accuracy than other prediction methods in large data sets with complex structures. Instead of statistical methods, artificial intelligence, and machine learning are u...

Sensor-Enhanced Smart Gripper Development for Automated Meat Processing.

Sensors (Basel, Switzerland)
Grasping and object manipulation have been considered key domains of Cyber-Physical Systems (CPS) since the beginning of automation, as they are the most common interactions between systems, or a system and its environment. As the demand for automati...