Literature Review on Linear Regression Equations for Relating Water Activity to Moisture Content in Floral Honeys: Development of a Weighted Average Equation

Nectar, humidity, honey bees ( Apis mellifera) and varroa in summer: a theoretical thermofluid analysis of the fate of water vapour from honey ripening and its implications on the control of Varroa destructor

This theoretical thermofluid analysis investigates the relationships between honey production rate, nectar concentration and the parameters of entrance size, nest thermal conductance, brood nest humidity and the temperatures needed for nectar to honey conversion. It quantifies and shows that nest humidity is positively related to the amount, and water content of the nectar being desiccated into honey and negatively with respect to nest thermal conductance and entrance size. It is highly likely that honeybees, in temperate climates and in their natural home, with much smaller thermal conductance and entrance, can achieve higher humidities more easily and more frequently than in man-made hives. As a consequence, it is possible that Varroa destructor, a parasite implicated in the spread of pathogenic viruses and colony collapse, which loses fecundity at absolute humidities of 4.3 kPa (approx. 30 gm^-3) and above, is impacted by the more frequent occurrence of higher humidities in these low conductance, small entrance nests. This study provides the theoretical basis for new avenues of research into the control of varroa, via the modification of beekeeping practices to help maintain higher hive humidities.

Relationship between Water Activity and Moisture Content in Floral Honey

The water activity (Aw) and moisture content (MC) data of floral honey at five temperatures were determined using the Aw method and it was found that temperature significantly affected the Aw/MC data. The linear equation could be used to express the relationship between Aw and MC of honeys. The empirical regression equations between parameters and temperature were established. To evaluate the factors affecting the Aw/MC data, we used categorical tests of regression analysis to assess the effect of the correlation between Aw and MC of honey and examined the factors affecting the regression parameters. Six datasets from five countries were selected from the literature. The significance of the levels of qualitative categories was tested by t-test. The slope of the relationship between Aw and MC was affected by the state of honey (liquid and crystallized). The intercepts were significantly affected by honey type (flower or honeydew), harvesting year, geographical collection site, botanical source and other factors. The outliers in the datasets significantly affected the results. With modern regression analysis, useful information on the correlation between Aw and MC could be found. The results indicated that no universal linear equation for Aw and MC could be used. The Aw value could be used as a criterion for the honey industry; then, the MC of honey could be calculated by the specific linear equation between Aw and MC.