ALBERT

Description: Background Genetic improvement of honey bees is more difficult compared to other livestock, due to the very different reproductive behavior. Estimation of breeding values requires specific adjustment and the use of sires in the pedigree is only possible when mating of queens and drones is strictly controlled. In the breeding program of the National Registry for Italian Queen Breeders and Bee Producers the paternal contribution is mostly unknown. As stronger modeling may compensate for the lack of pedigree information, we tested two models that differed in the way the direct and maternal effects were considered. The two models were tested using 4003 records for honey yield, defensive and swarming behaviors of Italian honey bee queens produced between 2002 and 2014. The first model accounted for the direct genetic effect of worker bees and the genetic maternal effect of the queen, whereas model 2 considered the direct genetic effect of the queen without maternal effect. The analyses were performed by linear (honey production) and threshold (defensive and swarming behavior) single-trait models; estimated genetic correlations among traits were obtained by a three-trait linear-threshold model. Results For all traits, the highest predictability (correlation between breeding values estimated with and without performance records) was obtained with model 2, where direct genetic effect of queens was considered. With this model, heritability estimates were 0.26 for honey yield, 0.36 for defensive behavior, and 0.34 for swarming behavior. Multi-trait estimation resulted in similar or higher heritability estimates for all traits. A low, positive genetic correlation (0.19) was found between honey yield and defensive behavior, whereas the genetic correlation between honey yield and swarming behavior was moderate (0.41). A strong, positive genetic correlation was found between defensive and swarming behaviors (0.62). Predictability for multi-trait evaluations was higher for honey yield (0.46) and defensive behavior (0.30) but almost identical for swarming behavior (0.45) compared to corresponding single-trait predictability. Conclusions Multi-trait evaluation using a model that accounts for the direct genetic effect of queen was the best approach for breeding value estimation of Italian honey bees. The results suggest a new direction for selection of linear and categorical traits in breeding programs where drone origin is unknown.

Description: In the fight against the Varroa destructor mite, selective breeding of honey bee (Apis mellifera L.) populations that are resistant to the parasitic mite stands as a sustainable solution. Selection initiatives indicate that using the suppressed mite reproduction (SMR) trait as a selection criterion is a suitable tool to breed such resistant bee populations. We conducted a large European experiment to evaluate the SMR trait in different populations of honey bees spread over 13 different countries, and representing different honey bee genotypes with their local mite parasites. The first goal was to standardize and validate the SMR evaluation method, and then to compare the SMR trait between the different populations. Simulation results indicate that it is necessary to examine at least 35 single-infested cells to reliably estimate the SMR score of any given colony. Several colonies from our dataset display high SMR scores indicating that this trait is present within the European honey bee populations. The trait is highly variable between colonies and some countries, but no major differences could be identified between countries for a given genotype, or between genotypes in different countries. This study shows the potential to increase selective breeding efforts of V. destructor resistant populations.

Description: Honeybees are of great importance because of their role in pollination as well as for hive products. The population of managed colonies fluctuates over time, and recent monitoring reports show different levels of colony losses in many regions and countries. The cause of this kind of loss is a combination of various factors, such as the parasitic mite Varroa destructor, viruses, pesticides, management practices, climate change, and other stress factors. Having in mind that the economic aspect of honeybee colony losses has not been estimated, a pioneer effort was made for developing a methodology that estimates the economic impact of honeybee colony losses. Winter loss data was based on 2993 answers of the COLOSS standard questionnaire survey of honeybee winter colony losses for 2016/2017. In addition, market and financial data were used for each country. In a comparative analysis, an assessment on the economic impact of colony losses in Austria, Czechia, and Macedonia was made. The estimation considered the value of the colonies and the potential production losses of the lost colonies and of surviving but weak colonies. The direct economic impact of winter honeybee colony losses in 2016/2017 in Austria was estimated to be about 32 Mio €; in Czechia, 21 Mio €; and in Macedonia, 3 Mio €. Economic impact reflects the different value levels in the three countries, national colony populations, and the magnitude of colony losses. This study also suggests that economic losses are much higher than the subsidies, which underlines the economic importance of honeybees for the agricultural sector.