AIMC Topic: Food Analysis

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Nondestructive Detection for Egg Freshness Based on Hyperspectral Scattering Image Combined with Ensemble Learning.

Sensors (Basel, Switzerland)
Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy, and explain it...

A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin.

Food chemistry
We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific detection of the fish allergen parvalbumin. SDS-PAGE and ELISA were used to validate the new method. T...

Milk Source Identification and Milk Quality Estimation Using an Electronic Nose and Machine Learning Techniques.

Sensors (Basel, Switzerland)
In this study, an electronic nose (E-nose) consisting of seven metal oxide semiconductor sensors is developed to identify milk sources (dairy farms) and to estimate the content of milk fat and protein which are the indicators of milk quality. The dev...

Accurate Prediction of Sensory Attributes of Cheese Using Near-Infrared Spectroscopy Based on Artificial Neural Network.

Sensors (Basel, Switzerland)
The acceptance of a food product by the consumer depends, as the most important factor, on its sensory properties. Therefore, it is clear that the food industry needs to know the perceptions of sensory attributes to know the acceptability of a produc...

Sensor Failure Tolerable Machine Learning-Based Food Quality Prediction Model.

Sensors (Basel, Switzerland)
For the agricultural food production sector, the control and assessment of food quality is an essential issue, which has a direct impact on both human health and the economic value of the product. One of the fundamental properties from which the qual...

Monitoring Mixing Processes Using Ultrasonic Sensors and Machine Learning.

Sensors (Basel, Switzerland)
Mixing is one of the most common processes across food, chemical, and pharmaceutical manufacturing. Real-time, in-line sensors are required for monitoring, and subsequently optimising, essential processes such as mixing. Ultrasonic sensors are low-co...

Classification of Dried Strawberry by the Analysis of the Acoustic Sound with Artificial Neural Networks.

Sensors (Basel, Switzerland)
In this paper, the authors used an acoustic wave acting as a disturbance (acoustic vibration), which travelled in all directions on the whole surface of a dried strawberry fruit in its specified area. The area of space in which the acoustic wave occu...

Aroma perceptual interactions of benzaldehyde, furfural, and vanillin and their effects on the descriptor intensities of Huangjiu.

Food research international (Ottawa, Ont.)
Aldehydes are important in the aroma of Huangjiu and contribute the almond and sweet aromas to Huangjiu. The perceptual interactions of 3 important aldehyde compounds were investigated using S-curves. Three volatiles, benzaldehyde, furfural, and vani...

Laser-based classification of olive oils assisted by machine learning.

Food chemistry
Olive oil is an essential diet component in all Mediterranean countries having a considerable impact on the local economies, which are producing almost 90% of the world production. Therefore, the quality assessment of olive oil in terms of its acidit...

Discovery of food identity markers by metabolomics and machine learning technology.

Scientific reports
Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to...