AI Medical Compendium Journal:
Journal of food science

Showing 1 to 10 of 35 articles

A rapid, non-destructive, and accurate method for identifying citrus granulation using Raman spectroscopy and machine learning.

Journal of food science
Citrus fruits are widely consumed for their nutritional value and taste; however, juice sac granulation during fruit storage poses a significant challenge to the citrus industry. This study used Raman spectroscopy coupled with machine learning algori...

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...

Detection of mussels contaminated with cadmium by near-infrared reflectance spectroscopy based on RELS-TSVM.

Journal of food science
Eating mussels contaminated with cadmium (Cd) can seriously harm health. In this study, a non-destructive and rapid detection method for Cd-contaminated mussels based on near-infrared reflectance spectroscopy was studied. The spectral data of Cd-cont...

Nondestructive freshness prediction of large yellow croaker (Pseudosciaena crocea) using computer vision and machine learning techniques based on pupil color.

Journal of food science
Conventional methods for evaluating of fish freshness based on physiological and biochemical methods are often destructive, complicated, and costly. This study aimed to predict the freshness of large yellow croaker which was sampled every second day ...

Predicting physicochemical properties of papayas (Carica papaya L.) using a convolutional neural networks model approach.

Journal of food science
The current state of quality assessment methods for agricultural produce, particularly fruits, heavily relies on manual inspection techniques, which could be subjective, time-consuming, and prone to human errors. Consequently, there have been emergin...

Fusion of visible and fluorescence imaging through deep neural network for color value prediction of pelletized red peppers.

Journal of food science
A non-destructive method for determining the color value of pelletized red peppers is crucial for pepper processing factories. This study aimed to investigate the potentiality of visible and fluorescence images for the determination of color value of...

Dielectric spectroscopy technology combined with machine learning methods for nondestructive detection of protein content in fresh milk.

Journal of food science
To quickly achieve nondestructive detection of protein content in fresh milk, this study utilized a network analyzer and an open coaxial probe to analyze the dielectric spectra of milk samples at 100 frequency points within the 2-20 GHz range, focusi...

High-precision identification of highly similar Pinelliae Rhizoma and adulterated Rhizoma pinelliae pedatisectae through deep neural networks based on vision transformers.

Journal of food science
Pinelliae Rhizoma is a key ingredient in botanical supplements and is often adulterated by Rhizoma Pinelliae Pedatisectae, which is similar in appearance but less expensive. Accurate identification of these materials is crucial for both scientific an...

Artificial intelligence as a tool for predicting the quality attributes of garlic (Allium sativum L.) slices during continuous infrared-assisted hot air drying.

Journal of food science
Effective drying methods are a highly suitable solution for ensuring stable food supply chains, reducing postharvest agricultural losses, and preventing the spoilage of perishable fruits and vegetables. Moreover, machine learning techniques are innov...

Enhancing dietary analysis: Using machine learning for food caloric and health risk assessment.

Journal of food science
In the wake of growing concerns regarding diet-related health issues, this study investigates the application of machine learning methods to estimate the energy content and classify the health risks of foods based on the USDA National Nutrient Databa...