The volatile profile of bee pollen samples from Central and Eastern Europe was investigated by headspace solid phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry-olfactometry (GC-MS-O). Sampling conditions were optimized for the extraction of volatiles. Pollen odorants were extracted with six different fiber coatings, five various extraction times, three diverse extraction temperatures and three differing desorption times. The most effective combination was the application of divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber coating used at 60°C for 30âmin for extraction and 1âmin for desorption. The optimized method was applied to investigate the volatile profile of 14 pollen samples (three rapeseed, musk thistle, rock-rose, traveler's joy, dropwort, honey locust, sunflower, red poppy, phacelia, sweet cherry, wild blackberry, and dandelion). The volatile profiles of bee pollens were different and were crucially depended on botanical origin. The aroma activity of the samples was generated by 31.0%-48.3% of total volatiles. The number of the identified odorants were between 75 and 101 in the pollen samples by GC-MS, of which 26-42 were aroma-active. The volatile organic compounds (VOCs) were classified into 13 different chemical classes. In most pollen, fatty acids were the predominant volatiles (14.87%-50.58%), while in some samples esters were the most abundant odorants (4.09%-45.46%). Panelists confirmed the presence of six main sensory characteristics described as "green/sour", "fruity", "spicy/herbal", "earthy/mushroom", "sweet/baked/caramel/honey", and "floral" compounds. These results establish the flavor wheel suitable for the comprehensive sensory description of pollen pellets from individual plant species. All samples contained characteristic odorants that may help in their botanical identification.
Volatile Profile of Bee Pollens: Optimization of Sampling Conditions for Aroma Analysis, Identification of Potential Floral Markers, and Establishment of the Flavor Wheel.
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作者:Csóka Mariann, Végh Rita, Sipos László
| 期刊: | Food Science & Nutrition | 影响因子: | 3.800 |
| 时间: | 2025 | 起止号: | 2024 Dec 25; 13(1):e4707 |
| doi: | 10.1002/fsn3.4707 | ||
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