A Single-Source Pilot Study of Machine Learning-Assisted Microwave S-Parameter Screening for Glucose Syrup and Water Adulteration in Grape Molasses. [PDF]
Sensors (Basel)Engin MA, Cakir M, Cakil T.
europepmc +1 more source
An Interpretable Kolmogorov-Arnold Network for FTIR Detection and Quantification of Adulteration Across Diverse Food Matrices. [PDF]
FoodsBatayhi A, Özgölet M, Sagdic O.
europepmc +1 more source
Food characterization in the omics era: current advances, analytical approaches, and future perspectives. [PDF]
Front NutrIbrahim MS +5 more
europepmc +1 more source
Determining the Authenticity of Ghanaian Honeys Using Stable Isotope Ratio Analysis (SIRA). [PDF]
MoleculesKpattah L +4 more
europepmc +1 more source
Colorimetric Sensor Arrays Technology in Food Quality and Safety Analysis. [PDF]
Micromachines (Basel)Cao J, Qiu Y, Gao Y, Cheng G.
europepmc +1 more source
Novel Analytical Workflow for Tracing Synthetic Caffeine Adulteration in Amazonian Guaraná (Paullinia cupana) Using Low-Field 1H NMR Fingerprinting and Chemometrics. [PDF]
J Agric Food Chemde Andrade JC +5 more
europepmc +1 more source
AI-Driven Food Fraud Detection Systems: A Critical Systematic Review of the Detection-Prevention Gap. [PDF]
FoodsMeneses Quelal O +2 more
europepmc +1 more source
Microfluidics-Integrated Spectroscopic Technologies for Food Safety and Quality Assessment: From Complex-Matrix Processing to On-Site Decision-Making. [PDF]
FoodsZhu J +5 more
europepmc +1 more source
Artificial Intelligence-Driven Dairy Quality Assessment: From Advanced Sensing Technologies to Explainable Intelligence. [PDF]
FoodsSong X +6 more
europepmc +1 more source
Smart detection of juice adulteration: An approach based on ion mobility spectrometry and machine learning. [PDF]
J Sci Food AgricCalle JLP +2 more
europepmc +1 more source