AIMC Topic: Food Analysis

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High-sensitivity direct analysis of aflatoxins in peanuts and cereal matrices by ultra-performance liquid chromatography with fluorescence detection involving a large volume flow cell.

Journal of environmental science and health. Part. B, Pesticides, food contaminants, and agricultural wastes
This paper reports a sensitive and cost effective method of analysis for aflatoxins B1, B2, G1 and G2. The sample preparation method was primarily optimised in peanuts, followed by its validation in a range of peanut-processed products and cereal (ri...

Highly sensitive colorimetric aptasensor for ochratoxin A detection based on enzyme-encapsulated liposome.

Analytica chimica acta
A simple, low-cost, and sensitive liposome-based colorimetric aptasensor has been developed to detect ochratoxin A (OTA). Specifically, a dumbbell-shaped probe was designed, including magnetic beads (MBs), double-stranded DNA (dsDNA), and enzyme-enca...

Development of a partial least squares-artificial neural network (PLS-ANN) hybrid model for the prediction of consumer liking scores of ready-to-drink green tea beverages.

Food research international (Ottawa, Ont.)
In order to develop products that would be preferred by consumers, the effects of the chemical compositions of ready-to-drink green tea beverages on consumer liking were studied through regression analyses. Green tea model systems were prepared by do...

Assessment of beer quality based on foamability and chemical composition using computer vision algorithms, near infrared spectroscopy and machine learning algorithms.

Journal of the science of food and agriculture
BACKGROUND: Beer quality is mainly defined by its colour, foamability and foam stability, which are influenced by the chemical composition of the product such as proteins, carbohydrates, pH and alcohol. Traditional methods to assess specific chemical...

Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.

Food chemistry
The generalization ability of hyperspectral imaging combined with neural networks (NN) in estimating pH and anthocyanin content during ripening was evaluated for vintages and varieties not employed in the NN creation. A NN, from a previously publishe...

Quantification of whey in fluid milk using confocal Raman microscopy and artificial neural network.

Journal of dairy science
In this work, we assessed the use of confocal Raman microscopy and artificial neural network as a practical method to assess and quantify adulteration of fluid milk by addition of whey. Milk samples with added whey (from 0 to 100%) were prepared, sim...

Structure from motion-convolutional neural network model (SfM-CNN) achieved accurate portable Chinese dietary chemical composition estimation for dietary recall.

Food chemistry
Accurately estimating the chemical composition of dietary intake is essential for health and nutrition management, especially in regions with complex culinary diversity like China. This study introduces a novel AI-driven solution using a Structure fr...

Miniaturized spectroscopy and AI-driven probes in food industry automation.

Food research international (Ottawa, Ont.)
Spectroscopy is a rapidly advancing analytical technique, which is increasingly employed in the food industry as a non-destructive and rapid quality control tool. Based on spectral analysis and developed multivariate predictive models this technique ...

Characterize and explore the dynamic changes in the volatility profiles of sauce-flavor baijiu during different rounds by GC-IMS, GC-MS and GC×GC-MS combined with machine learning.

Food research international (Ottawa, Ont.)
The production process of sauce-flavor baijiu (SFB) involves seven distillations, yielding base baijiu of 7 rounds (RSFB), which are then blended to form the final product. Therefore, the quality of the base baijiu is closely related to the quality o...