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The R-values of honey: Pollen coefficients

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One of the goals of melissopalynology is to determine the floral sources utilized by honeybees in the production of honey. Be-cause some types of commercial honey are preferred over others, the preferred types are in high demand and are sold at much higher prices. Verification of these preferred (premium) types of honey is often difficult because many of them come from plant sources that are either weak pollen producers or have pollen that is under-represented in honey. In an effort to verify these premium honey types, researchers developed various methods for correcting the pollen data. These methods produce what are known as pollen coefficient (PC) values. Pollen coefficient values are used to verify honey types produced from floral sources that are over or under-represented in the relative pollen counts of a honey sample. We examine the historical development of PC values, the reliabil-ity of PC data, the flaws inherent in the development of various types of PC data, and the steps needed to formulate new types of PC values that would become universally accepted for the verifi-cation of honey types.
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... This filtration process is particularly efficient with large pollen grains, which consequently tend to be underrepresented in honeys. Altogether, we can thus reconstruct the expected quantities of pollen present in the nectar from specific floral sources, and accordingly classify melliferous species into hyperrepresented (large quantities of pollen expected in the nectar), hypo-represented (low quantities of pollen expected), and normally-represented (Bryant and Jones 2001). ...
Chapter
The aim of this chapter is to provide an up-to-date review of the contribution of palynology to the reconstruction of the exploitation of ancient beekeeping and bee-products. After having introduced the reader to some of the main concepts in the palynology of bee-products (§2), the available evidence from Europe and the Mediterranean basin will be presented and discussed (§3). In the concluding section (§4) the palynological approach to ancient bee-products will be conceptualized, and its limits and potentials further discussed.
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... To allow for these considerations we placed the proportion of DNA sequence reads and pollen counts into four broad abundance classes matching the classifications used in melissopalynology (predominant, secondary, important minor and minor) and focus our analyses and conclusions on changes in the frequency of occurrence of the major taxa, classed as predominant and secondary. Both methods capture information on both nectar and pollen plants within the honey, however, certain species can be over or under represented in pollen analysis compared to their relative nectar contribution 49 . Both pollen and nectar plants are required to meet the foraging requirements of pollinators. ...
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The price of honey, as a highly consumed natural product, depends on its botanical source and its production environment, causing honey to be vulnerable to adulteration through mislabeling and inappropriate, fraudulent production. In this study, a fast and simple approach is proposed to tackle this issue through non-target one dimensional zg30 and noesypr1d 1H NMR fingerprint analysis, in combination with multivariate data analysis. Results suggest that composition differences in sugars, amino acids, and carboxylic acid were sufficient to discriminate between the tested honey of Maltese origin and that of non-local origin. Indeed, all chemometric models based on noesypr1d analysis of the whole fraction honey showed better prediction in geographical discrimination. The possibility of discrimination was further investigated through analysis of the honey’s phenolic extract composition. The partial least squares models were deemed unsuccessful to discriminate, however, some of the linear discriminant analysis models achieved a prediction accuracy of 100%. Lastly, the best performing models of both the whole fraction and the phenolic extracts were tested on five samples of unknown geographic for market surveillance, which attained a high agreement within the models. Thus, suggesting the use of non-target 1H NMR coupled with the multivariate-data analysis and machine learning as a potential alternative to the current time-consuming analytical methods.
... Accurately assessing the local forage is especially critical when attempting to collect a monofloral or "varietal" honey (Campbell & Fearns, 2018) which is derived primarily from the nectar of a single species (Bryant & Jones, 2001). Beekeepers in Appalachia have met with some success marketing varietal honeys derived from particular species of melliferous trees (Mattise, 2014); however, site selection may be hindered by the challenge of negotiating access to remote sites with limited knowledge of the available forage. ...
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... › Para una interpretación correcta del origen botánico, es necesario tener en cuenta las características sensoriales y fisicoquímicas de la miel, y en algunos casos el número absoluto de granos de polen obtenido en el análisis cuantitativo. Otras fuentes de variabilidad del contenido polínico de la miel como el enriquecimiento secundario, terciario y cuaternario (Bryant & Jones 2001, Jones & Bryant 2004) requieren cautela en la interpretación de los resultados. APLICACIÓN DEL ANÁLISIS POLÍNICO. ...
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Libro de técnicas de laboratorio para análisis de mieles de abejas.
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