Prospects of probiotics in beekeeping: a review for sustainable approach to boost honeybee health

Honeybees are vital for global crop pollination, making indispensable contributions to agricultural productivity. However, these vital insects are currently facing escalating colony losses on a global scale, primarily attributed to parasitic and pathogenic attacks. The prevalent response to combat these infections may involve the use of antibiotics. Nevertheless, the application of antibiotics raises concerns regarding potential adverse effects such as antibiotic resistance and imbalances in the gut microbiota of bees. In response to these challenges, this study reviews the utilization of a probiotic-supplemented pollen substitute diet to promote honeybee gut health, enhance immunity, and overall well-being. We systematically explore various probiotic strains and their impacts on critical parameters, including survival rate, colony strength, honey and royal jelly production, and the immune response of bees. By doing so, we emphasize the significance of maintaining a balanced gut microbial community in honeybees. The review also scrutinizes the factors influencing the gut microbial communities of bees, elucidates the consequences of dysbiosis, and evaluates the potential of probiotics to mitigate these challenges. Additionally, it delineates different delivery mechanisms for probiotic supplementation and elucidates their positive effects on diverse health parameters of honeybees. Given the alarming decline in honeybee populations and the consequential threat to global food security, this study provides valuable insights into sustainable practices aimed at supporting honeybee populations and enhancing agricultural productivity.

Effect of the climate change on honey bee colonies in a temperate Mediterranean zone assessed through remote hive weight monitoring system in conjunction with exhaustive colonies assessment

Honey bee plays the leading role in the pollination of many wild plants and crops, but it currently faces serious threats. Climate change is pointed out as one of the causes of the colony collapse disorder. Understanding the response of bees to the new climate change scenario is essential to face this challenge. Especially in the most sensitive bioclimatic zones, such as the Mediterranean areas. In this work, we remotely monitored the weight of the hives with an electronic device during a flowering period in the beekeeping seasons of 2016 and 2017, marked by extreme episodes of drought and high temperatures. We assessed bee colonies at the beginning, middle and at the end of the flowering as well, considering the adult bee population, bee brood, and pollen and honey reserves. The results showed that the flowering was reduced in three weeks in 2017 in comparison to 2016. In those years weight gain was 7.67 kg and 18.92 kg, respectively. The adverse conditions affected the evolution of the populations of bees and the reserves of honey and pollen in a meaningful way, increasing food stress for bees. It also affected the pollen spectrum and commercial characteristics of honey. Our results provide objective data about the effect of climate change on bees, but it also proved the relevant role of bees in the study of changes in the environment.

Evaluating European Food Safety Authority Protection Goals for Honeybees (Apis mellifera): What Do They Mean for Pollination?

In recent years there has been growing concern regarding the sudden and unexplained failure of honeybee (Apis mellifera) colonies. Several factors have been suggested, including pesticides. In an effort to regulate their impact, guidance published by the European Food Safety Authority (EFSA) has recommended that the magnitude of effects on exposed colonies should not exceed 7% reduction in colony size after 2 brood cycles. However, fears have been raised regarding the practicality of measuring such a loss in the field. It is also unclear how this protection goal relates to maintaining the ecosystem services provided by bees, which we argue should be a primary objective for regulators. Here, we evaluate what these protection goals mean in relation to ecosystems performance using a computational colony model that incorporates mechanisms to simulate both lethal and sublethal pesticide effects. To these simulations, we apply a testing regime similar to that commonly used in field trials to produce standard assessment metrics. By relating these measures to losses in forager activity, we aim to identify which could be used as effective indicators of reduced ecoservice and to quantify acceptable limits below which performance can be maintained. Our findings show that loss of colony size is the best indicator of reduced ecoservice. Metrics that focus on specific colony functions such as increased brood or forager mortality are ineffective indicators for all types of simulated pesticide effects. At the levels of colony loss recommended by EFSA, using our default parameterization, we predict a loss of ecosystems performance of 3% to 4%. However, based on an extensive sensitivity analysis, it is clear that this estimate is subject to substantial uncertainty with losses under alternative parameterizations of up to 14%. Nevertheless, our model provides a valuable framework for assessing protection goals, allowing regulators to test relevant impacts and quantify their magnitude. Integr Environ Assess Manag 2018;14:750-758. © 2018 Crown Copyright and SETAC.

A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.