English abstract
Honey is a supersaturated natural solution of sugars produced by bees from floral
nectar. Throughout history, some kinds of honey, especially monofloral types, have
been valued for its unique flavour, medicinal properties and heritage significance.
Volatile Organic Compounds play a significant role in defining the aroma and
facilitating the identification of honey's botanical origins. Understanding the chemical
composition and sensory properties of honey is crucial for ensuring its quality and
authenticity in the market. In this study, six types of Omani honey (i.e. Sumer, Sidr,
Luban, Eatam, Tulh and Rub’ Al-Khali honey) were subjected to physicochemical
(moisture, TSS, ash, protein, sugars, pH, HMF and CIELAB colour parameters) and
aroma profile analyses using E-nose and SPME-GC-MS. Furthermore, this study is
the first attempt to analyse the headspace aroma profile of Omani honey.
The results of physicochemical showed that Rub’ Al-Khali honey had the highest
moisture (16.39%), Talh honey had highest TSS (79.17 °Brix), whereas Sumer honey
presented the highest total ash, protein and sugar content (1.18% ,1.77% and 65.27%,
respectively) and Sidr had the highest pH level (5.55). The highest HMF content was
found in Talh honey (305.61 mg/kg), while the HMF contents of all tested honey were
within the GSO standard recommended limit (0-44.37 mg/kg), and they confirmed that
the tested honey was free of any heat treatment. All six types of tested honey presented
a safe moisture content (14.39 – 16.39%) and pH for (2.97 to 5.55) storage and
consumption. All tested honey had a total sugar content over 60%, except for Talh
honey, with 59.67%). All honey samples can be classified as light honeys based on
CIELAB colour analysis, except for Talh honey.
Aroma profile analysis revealed the efficacy of the E-nose method in distinguishing
between different honey types and categorizing them into different groups based on
their botanical origins. In E-nose analysis, LDA gives better classification of honey
samples than PCA. On the other hand, the artificial neural network (ANN) gives
91.11% accurate classification. The GC-MS analysis identified 185 volatile organic
compounds (VOCs) including 31, 50, 42, 57, 45, and 126 VOCs in Sumer, Sidr, Atum,
Talh, Rub’ Al-Khali and Luban respectively. Common VOCs were identified between
each tested sample. However, 10 VOCs were detected in all tested samples. Several
VOCs were detected only in specific honey and these compounds can be considered
as markers. A total of 71 compounds were only detected in Luban honey. These
findings highlight the significant variations in aroma profiles that are attributed to the
specific floral sources of the honeys. The discernible differences confirm the pivotal
role of floral origin in shaping the sensory characteristics of honey, thereby
contributing to a deeper understanding of honey quality and consumer preferences.
