Honey Botanical Origin Authentication Using HS-SPME-GC-MS Volatile Profiling and Advanced Machine Learning Models (Random Forest, XGBoost, and Neural Network)

This study develops a comprehensive workflow integrating Headspace Solid-Phase Microextraction Gas Chromatography–Mass Spectrometry (HS-SPME-GC-MS) with advanced supervised machine learning to authenticate the botanical origin of honeys from five distinct floral sources—coriander, orange blossom, as...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Amir Pourmoradian, Mohsen Barzegar, Ángel A. Carbonell-Barrachina, Luis Noguera-Artiaga
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-01-01
Schriftenreihe:	Foods
Schlagworte:	honey authentication chromatography volatile compounds GC—MS botanical origin chemometrics
Online-Zugang:	https://www.mdpi.com/2304-8158/15/2/389
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