Evaluating the seasonal efficacy of commonly used chemical treatments on Varroa destructor (Mesostigmata: Varroidae) population resurgence in honey bee colonies

Innovations in Varroa mite management

Varroa mites, the main pest of honey bees, are notoriously difficult to control. We present a novel approach to mite management emphasising the role of immigration. We argue that how mite numbers increase within the colony determines the most effective varroa management techniques. That is, varroa infestations go through phases, where their rate of increase is either driven by varroa reproduction (Chronic phase) or is strongly influenced by immigration into the hive (Acute phase). Identifying chronic and acute phases will enable current varroa control methods to be better targeted. For example, control methods reducing reproduction rates will be most effective during the chronic phase. Identifying when immigration is important to varroa in-hive population increases (acute phase) may enable existing bee management techniques, for example, those that limit the access of some bees into hives, to be co-opted into varroa management. This change in perspective emphasises that in-hive varroa control will be improved by understanding the subtleties of how and when varroa enter hives; it will also identify other gaps in our knowledge of varroa's behavioural ecology that could lead to new varroa control methods. Therefore, this novel approach to mite management will enable Integrated Pest Management to be better tailored to this pest.

Sensitivity and Resistance of Parasitic Mites (Varroa destructor, Tropilaelaps spp. and Acarapis woodi) Against Amitraz and Amitraz-Based Product Treatment: A Systematic Review

Resistance to amitraz in Varroa destructor mites poses a significant challenge to global beekeeping, leading to the declining efficacy of treatments and increased colony losses. This study aims to comprehensively map, characterize, and analyze the status of amitraz efficacy and resistance in Varroa and other parasitic mites such as Tropilaelaps spp. and Acarapis woodi. A systematic review, following PRISMA 2020 guidelines, examined 74 studies, revealing substantial variability in experimental protocols, mite origins, and environmental factors, all of which impacted toxicity assessments. These findings highlight the urgent need for standardized methodologies to ensure consistency and reliability. Resistance ratios (RR) and indices (RI) showed significant geographical variation, reflecting localized resistance development. Laboratory studies highlighted inconsistencies in detecting resistance, underscoring the importance of combining bioassays, molecular diagnostics, and field efficacy tests. Understanding the genetic and physiological mechanisms driving amitraz resistance, as well as their prevalence, is vital to devising sustainable management strategies. Establishing national monitoring programs and revising testing protocols are pivotal steps toward ensuring the continued effectiveness of acaricides. These measures, combined with coordinated efforts by researchers, beekeepers, and policymakers, are essential to safeguarding global honey bee populations and supporting the long-term sustainability of apiculture.

An AI-Based Digital Scanner for Varroa destructor Detection in Beekeeping

Beekeeping is a crucial agricultural practice that significantly enhances environmental health and food production through effective pollination by honey bees. However, honey bees face numerous threats, including exotic parasites, large-scale transportation, and common agricultural practices that may increase the risk of parasite and pathogen transmission. A major threat is the Varroa destructor mite, which feeds on honey bee fat bodies and transmits viruses, leading to significant colony losses. Detecting the parasite and defining the intervention thresholds for effective treatment is a difficult and time-consuming task; different detection methods exist, but they are mainly based on human eye observations, resulting in low accuracy. This study introduces a digital portable scanner coupled with an AI algorithm (BeeVS) used to detect Varroa mites. The device works through image analysis of a sticky sheet previously placed under the beehive for some days, intercepting the Varroa mites that naturally fall. In this study, the scanner was tested for 17 weeks, receiving sheets from 5 beehives every week, and checking the accuracy, reliability, and speed of the method compared to conventional human visual inspection. The results highlighted the high repeatability of the measurements (R2 ≥ 0.998) and the high accuracy of the BeeVS device; when at least 10 mites per sheet were present, the device showed a cumulative percentage error below 1%, compared to approximately 20% for human visual observation. Given its repeatability and reliability, the device can be considered a valid tool for beekeepers and scientists, offering the opportunity to monitor many beehives in a short time, unlike visual counting, which is done on a sample basis.

Combined treatment with amitraz and thymol to manage Varroa destructor mites (Acari: Varroidae) in Apis mellifera honey bee colonies (Hymenoptera: Apidae)

The parasitic mite Varroa destructor (Anderson and Trueman) is one of the greatest stressors of Apis mellifera (L.) honey bee colonies. When Varroa infestations reach damaging levels during fall, rapid control is necessary to minimize damage to colonies. We performed a field trial in the US Southeast to determine if a combination of registered treatments (Apivar, amitraz-based; and Apiguard, thymol-based) could provide rapid and effective control of Varroa. We compared colonies that received this combination treatment against colonies that received amitraz-based positive control treatments: (i) Apivar alone; or (ii) amitraz emulsifiable concentrate ("amitraz EC"). While not registered, amitraz EC is used by beekeepers in the United States in part because it is thought to control Varroa more rapidly and effectively than registered products. Based on measurements of Varroa infestation rates of colonies after 21 days of treatment, we found that the combination treatment controlled Varroa nearly as rapidly as the amitraz EC treatment: this or other combinations could be useful for Varroa management. At the end of the 42-day trial, colonies in the amitraz EC group had higher bee populations than those in the Apivar group, which suggests that rapid control helps reduce Varroa damage. Colonies in the combination group had lower bee populations than those in the amitraz EC group, which indicates that the combination treatment needs to be optimized to avoid damage to colonies.