AIMC Topic: Food Handling

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Distributional uniformity quantification in heterogeneous prepared dishes combined the hyperspectral imaging technology with Moran's I: A case study of pizza.

Food chemistry Oct 5, 2024
Quality detection is critical in the development of prepared dishes, with distributional uniformity playing a significant role. This study used hyperspectral imaging (HSI) and Moran's I to quantify distributional uniformity, employing pizza as case. ...
Image Processing, Computer-Assisted Quality Control Support Vector Machine Hyperspectral Imaging Food Handling Principal Component Analysis
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Analysis of sediment re-formation factors after ginseng beverage clarification based on XGBoost machine learning algorithm.

Food chemistry Sep 17, 2024
The aim of this study was to explore the sediment re-formation factors of ginseng beverages subjected to four clarification ways (11 subgroups) including the ethanol precipitation, enzymatic treatment, clarifier clarification, and Hollow Fiber Column...
Machine Learning Algorithms Beverages Saponins Antioxidants Plant Extracts Food Handling Panax
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Predictive modeling of rice milling degree for three typical Chinese rice varieties using interpretative machine learning methods.

Journal of food science Sep 1, 2024
Brown rice over-milling causes high economic and nutrient loss. The rice degree of milling (DOM) detection and prediction remain a challenge for moderate processing. In this study, a self-established grain image acquisition platform was built. Degree...
Oryza China Food Handling Image Processing, Computer-Assisted Color Machine Learning Edible Grain
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Valorization of tomato processing by-products: Predictive modeling and optimization for ultrasound-assisted lycopene extraction.

Ultrasonics sonochemistry Aug 30, 2024
Lycopene is a carotenoid highly valuable to the food, pharmaceutical, dye, and cosmetic industries, present in ripe tomatoes and other fruits with a distinctive red color. The main source of lycopene is tomato crops. This bioactive component can be s...
Solanum lycopersicum Chemical Fractionation Ultrasonic Waves Neural Networks, Computer Temperature Lycopene Food Handling Carotenoids
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Characterization and exploration of dynamic variation of volatile compounds in vine tea during processing by GC-IMS and HS-SPME/GC-MS combined with machine learning algorithm.

Food chemistry Jul 31, 2024
It is imperative to unravel the dynamic variation of volatile components of vine tea during processing to provide guidance for tea quality evaluation. In this study, the dynamic changes of volatile compounds of vine tea during processing were charact...
Ion Mobility Spectrometry Gas Chromatography-Mass Spectrometry Odorants Food Handling Solid Phase Microextraction Volatile Organic Compounds Algorithms Machine Learning Camellia sinensis Tea
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Non-targeted metabolomics and explainable artificial intelligence: Effects of processing and color on coniferyl aldehyde levels in Eucommiae cortex.

Food chemistry Jul 25, 2024
Eucommia ulmoides, a plant native to China, is valued for its medicinal properties and has applications in food, health products, and traditional Chinese medicine. Processed Eucommiae Cortex (EC) has historically been a highly valued medicine. Ancien...
Color Food Handling Aldehydes Eucommiaceae Zingiber officinale Plant Extracts Metabolomics Artificial Intelligence
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Infusion of active compound into sliced button mushrooms through vacuum impregnation to improve functionality: Comparing response surface methodology and artificial neural network.

Journal of food science Jun 26, 2024
The present study explores the infusion of active compounds (ascorbic acid and calcium lactate) into sliced button mushrooms (Agaricus bisporus) to increase the nutritional value and reduce the browning effect of sliced mushrooms using the vacuum imp...
Hydrogen-Ion Concentration Ascorbic Acid Food Handling Vacuum Nutritive Value Neural Networks, Computer Agaricus Temperature
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A deep learning-based quantitative prediction model for the processing potentials of soybeans as soymilk raw materials.

Food chemistry May 14, 2024
Current technologies as correlation analysis, regression analysis and classification model, exhibited various limitations in the evaluation of soybean possessing potentials, including single, vague evaluation and failure of quantitative prediction, a...
Glycine max Soy Milk Odorants Humans Deep Learning Taste Food Handling
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Optimization of α-L-arabinofuranosidase CcABF on clarification and beneficial active substances in fermented ginkgo kernel juice by artificial neural network and genetic algorithm.

Food chemistry Apr 15, 2024
This study aimed at using α-L-arabinofuranosidase CcABF to improve the clarity and active substances in fermented ginkgo kernel juice by artificial neural network (ANN) modeling and genetic algorithm (GA) optimization. A credible three-layer feedforw...
Glycoside Hydrolases Ginkgo biloba Neural Networks, Computer Fruit and Vegetable Juices Antioxidants Food Handling Algorithms Fermentation
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Modelling tomato pericarp microstructure as force control reference for harvesting robot.

Journal of the science of food and agriculture Mar 25, 2024
BACKGROUND: The harvest of fruit can be significantly advanced with the thriving development of intelligent and automated robot technologies. Nevertheless, the picking success rate of tomato fruit still requires improvement as some fruits are unexpec...
Food Handling Solanum lycopersicum Fruit Algorithms Robotics
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