Characterizing the Volatile and Sensory Profiles, and Sugar Content of Beeswax, Beebread, Bee Pollen, and Honey

Bee products are a well-known remedy against numerous diseases. However, from the consumers’ perspective, it is essential to define factors that can affect their sensory acceptance. This investigation aimed to evaluate the volatile and sensory profiles, and sugar composition of beeswax, beebread, pollen, and honey. According to the HS-SPME/GC-MS results, 20 volatiles were identified in beeswax and honey, then 32 in beebread, and 33 in pollen. Alkanes were found to dominate in beeswax, beebread, and pollen, while aldehydes and monoterpenes in honey. In the case of sugars, a higher content of fructose was determined in beebread, bee pollen, and honey, whereas the highest content of glucose was assayed in beeswax. In the QDA, the highest aroma intensity characterized as honey-like and sweet was found in honey, while the acid aroma was typical of beebread. Other odor descriptors, including waxy, pungent, and plant-based aromas were noted only in beeswax, honey, and pollen, respectively.

The Flavor Chemistry of Fortified Wines—A Comprehensive Approach

For centuries, wine has had a fundamental role in the culture and habits of different civilizations. Amongst numerous wine types that involve specific winemaking processes, fortified wines possess an added value and are greatly honored worldwide. This review comprises the description of the most important characteristics of the main worldwide fortified wines—Madeira, Port, Sherry, Muscat, and Vermouth—structured in three parts. The first part briefly describes the chemistry of wine flavor, the origin of typical aroma (primary, secondary and tertiary), and the influencing parameters during the winemaking process. The second part describes some specificities of worldwide fortified wine, highlighting the volatile composition with particular emphasis on aroma compounds. The third part reports the volatile composition of the most important fortified wines, including the principal characteristics, vinification process, the evolution of volatile organic compounds (VOCs) during the aging processes, and the most important odor descriptors. Given the worldwide popularity and the economic relevance of fortified wines, much research should be done to better understand accurately the reactions and mechanisms that occur in different stages of winemaking, mainly during the oxidative and thermal aging.

Identifying the Primary Odor Perception Descriptors by Multi-Output Linear Regression Models

Semantic odor perception descriptors, such as “sweet”, are widely used for product quality assessment in food, beverage, and fragrance industries to profile the odor perceptions. The current literature focuses on developing as many as possible odor perception descriptors. A large number of odor descriptors poses challenges for odor sensory assessment. In this paper, we propose the task of narrowing down the number of odor perception descriptors. To this end, we contrive a novel selection mechanism based on machine learning to identify the primary odor perceptual descriptors (POPDs). The perceptual ratings of non-primary odor perception descriptors (NPOPDs) could be predicted precisely from those of the POPDs. Therefore, the NPOPDs are redundant and could be disregarded from the odor vocabulary. The experimental results indicate that dozens of odor perceptual descriptors are redundant. It is also observed that the sparsity of the data has a negative correlation coefficient with the model performance, while the Pearson correlation between odor perceptions plays an active role. Reducing the odor vocabulary size could simplify the odor sensory assessment and is auxiliary to understand human odor perceptual space.

Sacha Inchi Seed (Plukenetia volubilis L.) Oil: Terpenoids

Sacha inchi oil is a product obtained from oilseed (Plukenetia volubilis L.) and is an excellent source of bioactive compounds, especially in polyunsaturated fatty acids, tocopherols, and sterols. These compounds are causally related to their positive impact on human health. In this study summarizes some monoterpenes, sesquiterpenes, and triterpenes reported in Sacha inchi oil seeds and reviews their sensory properties. The terpenoids that characterize Sacha inchi seed oil are: α-pinene, sabinene, limonene, aristolene, cycloartenol, 24-methylene cycloartenol, lanosterol, β-sitosterol, stigmasterol, campesterol and phytol. The sensory properties of this oil are due to a set of volatile compounds including terpenoids, the odor descriptors of monoterpenes, sesquiterpenes and diterpenes are: flower, pine, turpentine, pepper, wood, lemon, orange, and sweet. These compounds were characterized by gas chromatography with different detectors.

Impact of malolactic fermentation with Lactobacillus plantarum on volatile compounds of sea buckthorn juice

Malolactic fermentation using sea buckthorn (Hippophaë rhamnoides) juice as raw material was performed with six different strains of Lactobacillus plantarum. Increasing juice pH from 2.7 to 3.5 or adapting cells to low pH (i.e., acclimation) prior to inoculation allowed malolactic fermentation with all tested strains. Moreover, reducing pH of the growth medium from 6 to 4.5 with l-malate had little or no impact on biomass production. Volatile profile of sea buckthorn juice was analyzed with HS-SPME–GC–MS before and after fermentation. A total of 92 volatiles were tentatively identified and semi-quantified from sea buckthorn juice, majority of which were esters with fruity odor descriptors. Esters and terpenes were decreased in both inoculated and control juices during incubation. Microbial activity increased the levels of acetic acid (vinegar like), free fatty acids (cheese like), ketones (buttery like), and alcohols with fruity descriptors. Conversely, aldehydes associated with “green” aroma were decreased as a result of fermentation. Juices fermented with DSM 1055 had the highest acid and alcohol content, while fermentation with DSM 13273 resulted in the highest content of ketones. Compared to inoculation with other strains, fermentation with strains DSM 16365 and DSM 100813 resulted in rapid malolactic fermentation, less production of volatile acids, and lower loss of esters and terpenes important for natural sea buckthorn flavor.

The type of microorganism and substrate determines the odor fingerprint of dried bacteria targeting microbial protein production

ABSTRACT The rapidly increasing demand for protein has led to the pursuit of new protein sources, among which microbial protein (MP) is one of the most promising. Although the nutritional properties of MP are important and often well-studied, the sensory properties of the microbial cells will in part determine the commercial success of the product and are much less investigated. Here we assessed the odor fingerprint of dried bacteria originating from pure cultures and enriched mixed microbial communities using an electronic nose (e-nose). The e-nose discriminated between the different MP sources, while the choice of culture and substrate substantially affected their volatile organic compound (VOC) profile. The most dominant odor descriptors (>20% of VOC peak area) were sweet, fruity and fishy, while the mixed cultures presented higher peak areas indicating potentially more intense aromas than the pure cultures. The e-nose can detect the suitability of new MP sources and determine their best end-use.

Mapping the semantic organization of the English odor vocabulary using natural language data

Olfactory experiences are hard to verbalize, partly because most languages lack devoted odor vocabularies. Yet, there is a need for a standardized odor vocabulary, but no descriptive system for describing the full range of odor experiences has been agreed upon. Many studies of the English odor vocabulary have been based on perceptual data such as odor-descriptor ratings, thereby being limited to a small set of pre-selected descriptors. In the present study, we present a data-driven approach that automatically identifies odor descriptors in English, and then derive their semantic organization on the basis of their distributions in natural texts. Olfactory descriptors are automatically identified on the basis of their degree of olfactory association, and their semantic organization is derived with a distributional-semantic word embedding model. We identify and derive the semantic organization of the descriptors most frequently used to describe odors and flavors in English, both within and across source-based, abstract and evaluative descriptor categories. Our method is to a large extent able to capture semantic differences between descriptors related to aroma and flavor qualities, rather than e.g. functional or linguistic aspects, in that it primarily differentiates descriptors with respect to valence and edibility, and the semantic space derived from it is qualitatively similar to a space derived from perceptual data.

Multivariate Analysis of Olfactory Profiles for 140 Perfumes as a Basis to Derive a Sensory Wheel for the Classification of Feminine Fragrances

In order to guide consumers in their purchase of a new fragrance, one approach is to visualize the spectrum of men’s or women’s fragrances on a two-dimensional plot. One of such sensory maps available is the Hexagon of Fragrance Families. It displays 91 women’s perfumes inside a polygon, so that each side accounts for a different olfactory class. In order to discuss this chart, odor profiles were obtained for these fragrances and additional feminine ones (140 in total, launched from 1912 to 1990). An olfactory dataset was arranged by coding numerically the descriptions obtained from Fragrantica and Osmoz websites, as well as from a perfume guide. By applying principal component analysis, a sensory map was obtained that properly reflected the similarities between odor descriptors. Such representation was equivalent to the map of feminine fragrances called Givaudan Analogies, comprised of five major categories. Based on the results, a modified version of the Hexagon based on 14 categories was proposed. The first principal component explained preference for daytime versus nighttime wear, and regression models were fitted in order to estimate such preferences according to the odor profiles. The second component basically discriminated floral versus chypre (mossy–woody) fragrances. Results provide a fundamental basis to develop standard sensory maps of women’s fragrances.

Understanding the Perceptual Spectrum of Commercial Perfumes as a Basis for a Standard Sensory Wheel of Fragrances

Given the enormous number of perfumes available on the market, it is of interest to guide consumers in their purchase of a new fragrance. One approach is to project the multidimensional perceptual space of scents on a two-dimensional sensory map based on meaningful dimensions. One of the pioneering studies on this issue mapped 94 commercial perfumes according to two axes. Such an odor map is discussed here in detail by applying Principal Component Analysis to the numeric odor description of 176 fragrances. Quantitative odor profiles were obtained from Fragrantica’s website and three fragrances guides published by Haarmann & Reimer, Michael Edwards, and the French Society of Perfumers. A sensory map was obtained that reflected the similarities and dissimilarities between those odor descriptors most commonly used in perfumery. This representation was consistent with other related plots that have been previously reported. One dimension discriminated between fragrances targeted at men versus women. An orthogonal factor distinguished perfumes for daytime versus nighttime wear. These ratings, as well as seasonal preferences, could be estimated based on the main odor character attributes applied to describe the scent. The results provide a scientific basis for the comprehensive classification of commercial perfumes compiled by Edwards according to his famous “Fragrance Wheel”.