AI Medical Compendium Journal:
Food chemistry

Showing 111 to 120 of 202 articles

Label-free detection of trace level zearalenone in corn oil by surface-enhanced Raman spectroscopy (SERS) coupled with deep learning models.

Food chemistry
Surface-enhanced Raman spectroscopy (SERS) and deep learning models were adopted for detecting zearalenone (ZEN) in corn oil. First, gold nanorods were synthesized as a SERS substrate. Second, the collected SERS spectra were augmented to improve the ...

Deep learning-assisted smartphone-based portable and visual ratiometric fluorescence device integrated intelligent gel label for agro-food freshness detection.

Food chemistry
Here, a smartphone-assisted dual-color ratiometric fluorescence smart gel label-based visual sensing platform was constructed for real-time evaluation of the freshness of agro-food based on the biogenic amines responses. Green-emission fluorescence c...

A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imaging.

Food chemistry
The purpose of this study was to develop a deep learning method involving wavelet transform (WT) and stacked denoising autoencoder (SDAE) for extracting deep features of heavy metal lead (Pb) detection of oilseed rape leaves. Firstly, the standard no...

A TastePeptides-Meta system including an umami/bitter classification model Umami_YYDS, a TastePeptidesDB database and an open-source package Auto_Taste_ML.

Food chemistry
Taste peptides with umami/bitterness play a role in food attributes. However, the taste mechanisms of peptides are not fully understood, and the identification of these peptides is time-consuming. Here, we created a taste peptide database by collecti...

Deep learning drives efficient discovery of novel antihypertensive peptides from soybean protein isolate.

Food chemistry
As a potential and effective substitute for the drugs of antihypertension, the food-derived antihypertensive peptides have arisen great interest in scholars recently. However, the traditional screening methods for antihypertensive peptides are at con...

Multivariate versus machine learning-based classification of rapid evaporative Ionisation mass spectrometry spectra towards industry based large-scale fish speciation.

Food chemistry
Detection and prevention of fish food fraud are of ever-increasing importance, prompting the need for rapid, high-throughput fish speciation techniques. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has quickly established itself as a powerf...

Application of hyperspectral imaging assisted with integrated deep learning approaches in identifying geographical origins and predicting nutrient contents of Coix seeds.

Food chemistry
Coix seed (CS, Coix lachryma-jobi L. var. ma-yuen (Roman.) Stapf) has rich nutrients, including starch, protein and oil. The geographical origin with a protected geographical indication and high levels of nutrient contents ensures the quality of CS, ...

Identification of liquors from the same brand based on ultraviolet, near-infrared and fluorescence spectroscopy combined with chemometrics.

Food chemistry
Accurate identification of various liquors from the same brand is of great significance for safeguarding the rights and interests of consumers and the market economy. Here, the spectral properties of liquors were studied based on ultraviolet (UV), ne...

Rapid identification of fish species by laser-induced breakdown spectroscopy and Raman spectroscopy coupled with machine learning methods.

Food chemistry
There has been an increasing demand for the rapid verification of fish authenticity and the detection of adulteration. In this work, we combined LIBS and Raman spectroscopy for the fish species identification for the first time. Two machine learning ...

Deep learning accurately predicts food categories and nutrients based on ingredient statements.

Food chemistry
Determining attributes such as classification, creating taxonomies and nutrients for foods can be a challenging and resource-intensive task, albeit important for a better understanding of foods. In this study, a novel dataset, 134 k BFPD, was collect...