Honey is sold on a global scale and the market can be largely influenced by increasing concerns over product quality and authenticity. Volatile organic compounds (VOCs) are responsible for the aroma of this natural product, providing characteristic aromatic bouquets. The combined effect of several factors contributes to the distinct aromas, namely climate conditions, geographical location of production, flower nectar composition and post-harvest processes. The VOCs identified range both in compound class and molecular weight, with some key distinguishing compounds being present at low levels, making the analytical process challenging and time spent data processing laborious. Here we demonstrate a simple, solvent-free method for fingerprinting different honey qualities through fully-automated sample extraction and enrichment by a high-capacity sorptive extraction technique (HiSorb), coupled to Gas Chromatography Mass Spectrometry. Data mining and chemometrics are combined into one easy-to-use platform, for rapid identification of key differences between the VOC profiles. By identifying unique signatures amongst shared ubiquitous VOCs, we will show how this helps to distinguish between commercial low-cost to luxury brands and locally produced honey.
Aroma Discovery of Low-cost to Luxury Honey Using a High-Capacity Sorptive Extraction Technique (HiSorb) and Gas Chromatography Mass Spectrometry
Damiana Spadafora
Primo
;
2021
Abstract
Honey is sold on a global scale and the market can be largely influenced by increasing concerns over product quality and authenticity. Volatile organic compounds (VOCs) are responsible for the aroma of this natural product, providing characteristic aromatic bouquets. The combined effect of several factors contributes to the distinct aromas, namely climate conditions, geographical location of production, flower nectar composition and post-harvest processes. The VOCs identified range both in compound class and molecular weight, with some key distinguishing compounds being present at low levels, making the analytical process challenging and time spent data processing laborious. Here we demonstrate a simple, solvent-free method for fingerprinting different honey qualities through fully-automated sample extraction and enrichment by a high-capacity sorptive extraction technique (HiSorb), coupled to Gas Chromatography Mass Spectrometry. Data mining and chemometrics are combined into one easy-to-use platform, for rapid identification of key differences between the VOC profiles. By identifying unique signatures amongst shared ubiquitous VOCs, we will show how this helps to distinguish between commercial low-cost to luxury brands and locally produced honey.I documenti in SFERA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
