AIMC Topic: Freezing

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Color Dynamics, Pigments and Antioxidant Capacity in Pouteria sapota Puree During Frozen Storage: A Correlation Study Using CIELAB Color Space and Machine Learning Models.

Plant foods for human nutrition (Dordrecht, Netherlands)
The accurate prediction of bioactive compounds and antioxidant activity in food matrices is critical for optimizing nutritional quality and industrial applications. This study compares the performance of multiple linear regression (MLR) and artificia...

Tracking nutritional and quality changes in frozen pork: A 12-month study using 7 categories of meat parameters and VIS/NIR spectroscopy.

Food chemistry
Frozen pork stocks are critical for stabilizing food security and prices, but assessing nutritional and physicochemical changes during freezing remains challenging. This study conducted a 12-month frozen storage experiment at -20 °C on 50 pigs' longi...

Freeze-Thaw Imaging for Microorganism Classification Assisted with Artificial Intelligence.

ACS nano
Fast and cost-effective microbial classification is crucial for clinical diagnosis, environmental monitoring, and food safety. However, traditional methods encounter challenges including intricate procedures, skilled personnel needs, and sophisticate...

Freeze-Thaw-Induced Patterning of Extracellular Vesicles with Artificial Intelligence for Breast Cancers Identifications.

Small (Weinheim an der Bergstrasse, Germany)
Extracellular vesicles (EVs) play a crucial role in the occurrence and progression of cancer. The efficient isolation and analysis of EVs for early cancer diagnosis and prognosis have gained significant attention. In this study, for the first time, a...

Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network.

Meat science
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...

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.

Journal of pharmaceutical sciences
Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morpholo...

Prediction of directional solidification in freeze casting of biomaterial scaffolds using physics-informed neural networks.

Biomedical physics & engineering express
Freeze casting, a manufacturing technique widely applied in biomedical fields for fabricating biomaterial scaffolds, poses challenges for predicting directional solidification due to its highly nonlinear behavior and complex interplay of process para...

Deep learning for unravelling features of heterogeneous ice nucleation.

Proceedings of the National Academy of Sciences of the United States of America

Bioinspired Freeze-Tolerant Soft Materials: Design, Properties, and Applications.

Small (Weinheim an der Bergstrasse, Germany)
In nature, many biological organisms have developed the exceptional antifreezing ability to survive in extremely cold environments. Inspired by the freeze resistance of these organisms, researchers have devoted extensive efforts to develop advanced f...

Analysis on frosting of heat exchanger and numerical simulation of heat transfer characteristics using BP neural network learning algorithm.

PloS one
The study is aimed at the frosting problem of the air source heat pump in the low temperature and high humidity environment, which reduces the service life of the system. First, the frosting characteristics at the evaporator side of the air source he...