ArticleFood chemistry: X2024
Prediction acrylamide contents in fried dough twist based on the application of artificial neural network.
Article in Food chemistry: X, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Machine learning for food flavor prediction and regulation: models, data integration, and future perspectives.Journal of advanced research · 2026Review
- Mitigation of acrylamide in cookies and crispbread using calcium salts and phenolic acids in combination with asparaginase as well as rosemary extract.Food chemistry: X · 2025Article
- Chemical Migration of Polycyclic Aromatic Hydrocarbons and Other Compounds from Plastic Food Packaging: Assessment of Food Safety Risks and Health Impacts.Foods (Basel, Switzerland) · 2025Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Acrylamide forms through the reaction between reducing sugars and asparagine in the thermal processing of food. Detection measures like LC-MS, HPLC are time-consuming and costly, which inspired us to use back propagation-artificial neural networks (BP-ANN) based on a genetic algorithm to establish an acrylamide prediction model in fried dough twist. The effects of frying time and temperature on acrylamide contents, as well as the color difference and acid value at different time and temperature were determined. Acrylamide content was found significantly correlated with temperature (
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