Field Application of an Innovative Approach to Assess Honeybee Health and Nutritional Status.

Environment, forage quality, management practices, pathogens, and pesticides influence honeybee responses to stressors. This study proposes an innovative approach to assess colony health and performance using molecular diagnostic tools by correlating hemolymph proteins with common measures of colony strength, prevalent honeybee pathogens (Varroa destructor and Nosema spp.), and essential trace elements (iron, zinc and copper). Colonies were selected from four apiaries located in different environmental and foraging conditions in the province of Bologna (Italy). Hemolymph samples were taken from June to October 2019. The Varroa infestation of the colonies was estimated by assessing the natural mortality of the mites, while the bees were tested for Nosema spp. spores using a microscopic method. Hemolymph proteins were quantified and separated using SDS-PAGE, and colony performance was assessed by determining adult bees, total brood, honey, and pollen reserves. The biomarkers measured proved to be useful for monitoring changes in performance and trophic conditions during summer and early autumn. Significant correlations were found between hemolymph proteins and colony performance measures. A positive correlation between pollen reserves, vitellogenin, and hexamerin 70a highlights the importance of these proteins for successful overwintering. In October, Varroa infestation was negatively correlated with total proteins, vitellogenin, apolipophorin II, transferrin, and hexamerin 70a, with negative implications for overwintering; furthermore, Varroa infestation was also negatively correlated with iron content, potentially affecting iron homeostasis.

Functional redundancy and niche specialization in honeybee and Varroa microbiomes.

The honeybee (Apis mellifera) is a key pollinator critical to global agriculture, facing threats from various stressors, including the ectoparasitic Varroa mite (Varroa destructor). Previous studies have identified shared bacteria between Varroa mites and honeybees, yet it remains unclear if these bacteria assemble similarly in both species. This study builds on existing knowledge by investigating co-occurrence patterns in the microbiomes of both Varroa mites and honeybees, shedding light on potential interactions. Leveraging 16S rRNA datasets, we conducted co-occurrence network analyses, explored Core Association Networks (CAN) and assess network robustness. Comparative network analyses revealed structural differences between honeybee and mite microbiomes, along with shared core features and microbial motifs. The mite network exhibited lower robustness, suggesting less resistance to taxa extension compared to honeybees. Furthermore, analyses of predicted functional profiling and taxa contribution revealed that common central pathways in the metabolic networks have different taxa contributing to Varroa mites and honeybee microbiomes. The results show that while both microbial systems exhibit functional redundancy, in which different taxa contribute to the functional stability and resilience of the ecosystem, there is evidence for niche specialization resulting in unique contributions to specific pathways in each part of this host-parasite system. The specificity of taxa contribution to key pathways offers targeted approaches to Varroa microbiome management and preserving honeybee microbiome. Our findings provide valuable insights into microbial interactions, aiding farmers and beekeepers in maintaining healthy and resilient bee colonies amid increasing Varroa mite infestations.

Origins, diversity, and adaptive evolution of DWV in the honey bees of the Azores: the impact of the invasive mite Varroa destructor.

Deformed wing virus (DWV) is a honey bee virus, whose emergence from relative obscurity is driven by the recent host-switch, adaptation, and global dispersal of the ectoparasitic mite Varroa destructor (a highly efficient vector of DWV) to reproduction on honey bees (Apis mellifera). Our study examines how varroa affects the continuing evolution of DWV, using the Azores archipelago, where varroa is present on only three out of the eight Islands, as a natural experimental system for comparing different evolutionary conditions and trajectories. We combined qPCR of 494 honey bee colonies sampled across the archipelago with amplicon deep sequencing to reveal how the DWV genetic landscape is altered by varroa. Two of the varroa-free Islands were also free of DWV, while a further two Islands were intriguingly dominated by the rare DWV-C major variant. The other four Islands, including the three varroa-infested Islands, were dominated by the common DWV-A and DWV-B variants. The varroa-infested Islands had, as expected, an elevated DWV prevalence relative to the uninfested Islands, but not elevated DWV loads, due the relatively high prevalence and loads of DWV-C on the varroa-free Islands. This establishes the Azores as a stable refuge for DWV-C and provides the most convincing evidence to date that at least some major strains of DWV may be capable of not just surviving, but actually thriving in honey bees in the absence of varroa-mediated transmission. We did not detect any change in DWV genetic diversity associated with island varroa status but did find a positive association of DWV diversity with virus load, irrespective of island varroa status.

Diagnostic study on major honeybee disease, pests and predators in North Western Ethiopia.

BACKGROUND: The study was conducted in Pawe district from Benishangul-Gumuz and Jawi and Fagita Lekoma districts from the Amhara region to investigate major honeybee pests, predators and diseases. METHODS: Using a purposive sampling technique, 183 households were interviewed, and 240 samples were collected for laboratory analysis of bee disease; data were analysed using descriptive statistics. RESULTS: The share of hive types owned by sampled respondents was 88.6%; overall, 1.1% and 10.3% were traditional, transitional and modern beehives, respectively. About 92% of the sample respondents acquired their base colonies by catching swarm bees on the apex of trees. The majority of beekeepers executed external inspections of their colony, whereas only 50% carried out internal inspections. Based on the responses of beekeepers, around 48.9%, 56.3% and 23.1% of colonies absconded every year from Pawe, Jawi and Fagita Lekoma districts, respectively. Ants, wax moths, bee lice, beetles, spiders, birds, monkeys and honey badgers were the major honeybee pests and predators discovered in study areas in decreasing order. Concerning the incidence of Varroa mites, Nosema apis and amoeba disease, 27.5%, 60% and 71.6% of samples showed positive results in study locations, respectively. CONCLUSIONS: From this result, we observed that ants, wax moths, bee lice, beetles, spiders, birds, monkeys and honey badgers were the major honeybee pests and predators. The prevalence of amoeba disease was comparatively higher in highland areas and in the summer season. This finding suggests the need for the alertness of beekeepers in controlling bee disease and pests and strengthening bee colonies through seasonal colony management. There should be a strict quarantine, and check-up undertaken when a new colony is purchased from one region to another is essential.

Assessing lethal and sublethal effects of pesticides on honey bees in a multifactorial context.

The registration of novel pesticides that are subsequently banned because of their unexpected negative effects on non-target species can have a huge environmental impact. Therefore, the pre-emptive evaluation of the potential effects of new compounds is essential. To this aim both lethal and sublethal effects should be assessed in a realistic scenario including the other stressors that can interact with pesticides. However, laboratory studies addressing such interactive effects are rare, while standardized laboratory-based protocols focus on lethal effects and not on sub-lethal effects. We propose to assess both lethal and sublethal effects in a multifactorial context including the other stressors affecting the non-target species. We tested this approach by studying the impact on honey bees of the insecticide sulfoxaflor in combination with a common parasite, a sub-optimal temperature and food deprivation. We studied the survival and the transcriptome of honey bees, to assess both the lethal and the potential sublethal effects of the insecticide, respectively. With this method we show that a field realistic concentration of sulfoxaflor in food does not affect the survival of honey bees; however, the significant impact on some key genes indicates that sublethal effects are possible in a realistically complex scenario. Moreover, our results demonstrate the feasibility and reliability of a novel approach to hazard assessment considering the interactive effects of pesticides. We anticipate our approach to be a starting point for a paradigm shift in toxicology: from an unifactorial, mortality-centered assessment to a multifactorial, comprehensive approach. This is something of the utmost importance to preserve pollination, thus contributing to the sustainability of our food production system.

Varroa Mite Counting Based on Hyperspectral Imaging.

Varroa mite infestation poses a severe threat to honeybee colonies globally. This study investigates the feasibility of utilizing the HS-Cam and machine learning techniques for Varroa mite counting. The methodology involves image acquisition, dimensionality reduction through Principal Component Analysis (PCA), and machine learning-based segmentation and classification algorithms. Specifically, a k-Nearest Neighbors (kNNs) model distinguishes Varroa mites from other objects in the images, while a Support Vector Machine (SVM) classifier enhances shape detection. The final phase integrates a dedicated counting algorithm, leveraging outputs from the SVM classifier to quantify Varroa mite populations in hyperspectral images. The preliminary results demonstrate segmentation accuracy exceeding 99% and an average precision of 0.9983 and recall of 0.9947 across all the classes. The results obtained from our machine learning-based approach for Varroa mite counting were compared against ground-truth labels obtained through manual counting, demonstrating a high degree of agreement between the automated counting and manual ground truth. Despite working with a limited dataset, the HS-Cam showcases its potential for Varroa counting, delivering superior performance compared to traditional RGB images. Future research directions include validating the proposed hyperspectral imaging methodology with a more extensive and diverse dataset. Additionally, the effectiveness of using a near-infrared (NIR) excitation source for Varroa detection will be explored, along with assessing smartphone integration feasibility.

Beekeepers Support the Use of RNA Interference (RNAi) to Control Varroa destructor.

Current Varroa mite management strategies rely heavily on the use of pesticides, adversely affecting honey bee health and leaving toxic residues in hive products. To explore the likelihood of RNAi technology being utilised as an alternative control method for pests like Varroa, the opinions of beekeepers on the use of this new biotechnology were obtained using a mixed-methodology approach. In-person surveys and focus groups using the Q method were conducted to discover the willingness of beekeepers to utilise Varroa-targeting RNAi treatments in their hives, and to gain feedback to inform decisions before the implementation of this new technology. Overall, the beekeepers saw potential in RNAi being used to control Varroa in their hives and were eager to have access to an alternative to pesticide treatments. Participants raised concerns about unknown long-term effects on bees and other non-target species, and the potential of an uninformed public preventing them from accessing a new Varroa treatment. While further research and discussion is needed before RNAi treatments for Varroa become commercially available, RNAi technology presents a promising, species-specific and non-toxic solution for Varroa management.

From consumption to excretion: Lithium concentrations in honey bees (Apis mellifera) after lithium chloride application and time-dependent effects on Varroa destructor.

BACKGROUND: Owing to its systemic mode-of-action and ease of application, lithium chloride (LiCl) is an ideal varroacide for the control of Varroa destructor infestations in honey bee colonies. To better understand how LiCl functions within a colony, we screened different parts of honey bee anatomy for lithium accumulation. We wanted to elucidate the time-dependent effects of LiCl on V. destructor and its metabolism within honey bees when they were fed continuous LiCl treatments, as well as evaluate potential adverse effects such as accumulation in the hypopharyngeal glands of nurse bees, which could negatively impact queens and larvae. RESULTS: Cage experiments reveal rapid acaricidal onset, with >95% mite mortality within 48 h of treatment. Bee hemolymph analysis supports these observations, showing a rapid increase in lithium concentration within 12 h of treatment, followed by stabilization at a constant level. Lithium accumulates in the rectum of caged bees (≤475.5 mg kg-1 after 7 days of feeding 50 mm LiCl), reflecting the bees' metabolic and excretion process. Despite concerns about potential accumulation in hypopharyngeal glands, low lithium levels of only 0.52 mg kg-1 suggest minimal risk to the queen and 1st- and 2nd-instar larvae. Cessation of LiCl treatment results in a rapid decline in mite mortality in the first 5 days, which increases again thereafter, resulting in mite mortality of 77-90% after 10 days. CONCLUSION: These findings help optimize LiCl application in colonies to achieve high Varroa mortality without unwanted adverse effects and provide important baseline data for future registration. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Analysis of Varroa Mite Colony Infestation Level Using New Open Software Based on Deep Learning Techniques.

Varroa mites, scientifically identified as Varroa destructor, pose a significant threat to beekeeping and cause one of the most destructive diseases affecting honey bee populations. These parasites attach to bees, feeding on their fat tissue, weakening their immune systems, reducing their lifespans, and even causing colony collapse. They also feed during the pre-imaginal stages of the honey bee in brood cells. Given the critical role of honey bees in pollination and the global food supply, controlling Varroa mites is imperative. One of the most common methods used to evaluate the level of Varroa mite infestation in a bee colony is to count all the mites that fall onto sticky boards placed at the bottom of a colony. However, this is usually a manual process that takes a considerable amount of time. This work proposes a deep learning approach for locating and counting Varroa mites using images of the sticky boards taken by smartphone cameras. To this end, a new realistic dataset has been built: it includes images containing numerous artifacts and blurred parts, which makes the task challenging. After testing various architectures (mainly based on two-stage detectors with feature pyramid networks), combination of hyperparameters and some image enhancement techniques, we have obtained a system that achieves a mean average precision (mAP) metric of 0.9073 on the validation set.

Comparison of Brain Gene Expression Profiles Associated with Auto-Grooming Behavior between Apis cerana and Apis mellifera Infested by Varroa destructor.

The grooming behavior of honeybees serves as a crucial auto-protective mechanism against Varroa mite infestations. Compared to Apis mellifera, Apis cerana demonstrates more effective grooming behavior in removing Varroa mites from the bodies of infested bees. However, the underlying mechanisms regulating grooming behavior remain elusive. In this study, we evaluated the efficacy of the auto-grooming behavior between A. cerana and A. mellifera and employed RNA-sequencing technology to identify differentially expressed genes (DEGs) in bee brains with varying degrees of grooming behavior intensity. We observed that A. cerana exhibited a higher frequency of mite removal between day 5 and day 15 compared to A. mellifera, with day-9 bees showing the highest frequency of mite removal in A. cerana. RNA-sequencing results revealed the differential expression of the HTR2A and SLC17A8 genes in A. cerana and the CCKAR and TpnC47D genes in A. mellifera. Subsequent homology analysis identified the HTR2A gene and SLC17A8 gene of A. cerana as homologous to the HTR2A gene and SLC17A7 gene of A. mellifera. These DEGs are annotated in the neuroactive ligand-receptor interaction pathway, the glutamatergic synaptic pathway, and the calcium signaling pathway. Moreover, CCKAR, TpnC47D, HTR2A, and SLC17A7 may be closely related to the auto-grooming behavior of A. mellifera, conferring resistance against Varroa infestation. Our results further explain the relationship between honeybee grooming behavior and brain function at the molecular level and provide a reference basis for further studies of the mechanism of honeybee grooming behavior.

High Rates of Honey Bee Colony Losses and Regional Variability in Ethiopia Based on the Standardised COLOSS 2023 Survey.

The COLOSS research association has been assessing honey bee colony losses, associated risk factors and management, focusing on Western countries but with a progressive international expansion. Here, we report the first survey on the loss rates of colonies in 2022/2023 in Ethiopia using COLOSS monitoring survey tools. A face-to-face interview questionnaire survey was conducted on 64 beekeepers selected from Oromia and Tigray regions. This covered 1713 honey bee colonies distributed in 68 apiaries. The percentages of colonies lost were significantly different between Oromia (24.1%) and Tigray (66.4%) regions. Colony losses were attributed as unsolvable queen problems (8% in Oromia; 10% in Tigray), natural disaster (32%; 82%), and empty hives or dead colonies (60%; 8%). The loss rate was significantly affected by queen replacement (p < 0.0001), use of natural comb (p < 0.0001), feed supplementation (p < 0.0001), region (p < 0.0001), varroa treatment (p < 0.0001), colony splitting (p < 0.01), and merging (p < 0.01). Beekeepers in Oromia managed more colonies and implemented improved practices compared to those in Tigray. However, all beekeepers in Oromia detected at least some bees with signs of deformed wing virus, compared to 76% of beekeepers in Tigray. In conclusion, the colony loss rate was significantly different between Oromia and Tigray regions due to differences in natural disasters, management, environment and health factors.

Amitraz Resistance in French Varroa Mite Populations-More Complex Than a Single-Nucleotide Polymorphism.

Resistance against amitraz in Varroa mite populations has become a subject of interest in recent years due to the increasing reports of the reduced field efficacy of amitraz treatments, especially from some beekeepers in France and the United States. The loss of amitraz as a reliable tool to effectively reduce Varroa mite infestation in the field could severely worsen the position of beekeepers in the fight to keep Varroa infestation rates in their colonies at low levels. In this publication, we present data from French apiaries, collected in the years 2020 and 2021. These data include the field efficacy of an authorized amitraz-based Varroa treatment (Apivar® ,Véto-pharma, France) and the results of laboratory sensitivity assays of Varroa mites exposed to the reference LC90 concentration of amitraz. In addition, a total of 240 Varroa mites from Eastern, Central, and Southern regions in France that were previously classified as either "sensitive" or "resistant" to amitraz in a laboratory sensitivity assay were genotyped. The genetic analyses of mite samples are focused on the ß-adrenergic-like octopamine receptor, which is considered as the main target site for amitraz in Varroa mites. Special attention was paid to a single-nucleotide polymorphism (SNP) at position 260 of the ORß-2R-L gene that was previously associated to amitraz resistance in French Varroa mites, Varroa. Our findings confirm that amitraz resistance occurs in patches or "islands of resistance", with a less severe reduction in treatment efficacy compared to pyrethroid resistance or coumaphos resistance in Varroa mites. The results of our genetic analyses of Varroa mites call into question the hypothesis of the SNP at position 260 of the ORß-2R-L gene being directly responsible for amitraz resistance development.

Comprehensive Approach to Phenotype Varroa destructor Reproduction in Honey Bee Drone Brood and Its Correlation with Decreased Mite Reproduction (DMR).

The mechanisms of action behind decreased mite reproduction (DMR) are still unknown, but current hypotheses state that DMR is the result of brood-intrinsic and/or external disturbances in the V. destructor-honey bee pupa signal interactions. For accurate and precise DMR phenotyping, sufficient single infested honey bee brood cells are required (e.g., 35), which requires extensive labor and time and may exclude many samples not reaching the threshold. We defined a new comprehensive trait called the 'mean V. destructor reproduction rate' (mVR), which describes the mean number of offspring mites per infested cell in the sample while compensating for the reduced number of offspring with increasing multiple infested cells. We found a significant correlation between mVR and DMR, allowing for an estimation of DMR based on the mVR only. When the mVR was calculated with 10 infested cells, we found an average variation in mVR of 16.8%. For the same variation in DMR determination, 40 single infested cells are required. This broader look at V. destructor resistance phenotyping can improve the applicability and effectiveness of traits related to V. destructor reproduction in honey bee breeding programs.

Oxalic Acid Treatment: Short-Term Effects on Enzyme Activities, Vitellogenin Content, and Residual Oxalic Acid Content in House Bees, Apis mellifera L.

Honeybees (Apis mellifera L.) have to face many challenges, including Varroa destructor infestation, associated with viral transmission. Oxalic acid is one of the most common treatments against Varroa. Little is known about the physiological effects of oxalic acid, especially those on honeybees' immune systems. In this study, the short-term effects (0-96 h) of oxalic acid treatment on the immune system components (i.e., glucose oxidase, phenoloxidase, glutathione S-transferase, catalase activities, and vitellogenin contents) of house bees were preliminarily investigated. Oxalic acid contents of bee bodies and haemolymphs were also measured. The results confirm that oxalic acid is constitutively present in bee haemolymphs and its concentration is not affected by treatment. At 6 h after the treatment, a maximum peak of oxalic acid content was detected on bees' bodies, which gradually decreased after that until physiological levels were reached at 48 h. In the immune system, the oxalic acid treatment determined a peak in glucose oxidase activity at 48 h, indicating a potential defence response and an increase in vitellogenin content at 24 h. No significant changes were recorded in phenoloxidase, glutathione S-transferase, and catalase activities. These results suggest a time-dependent response to oxalic acid, with potential immune system activation in treated bees.

Allele Frequencies of Genetic Variants Associated with Varroa Drone Brood Resistance (DBR) in Apis mellifera Subspecies across the European Continent.

Implementation of marker-assisted selection (MAS) in modern beekeeping would improve sustainability, especially in breeding programs aiming for resilience against the parasitic mite Varroa destructor. Selecting honey bee colonies for natural resistance traits, such as brood-intrinsic suppression of varroa mite reproduction, reduces the use of chemical acaricides while respecting local adaptation. In 2019, eight genomic variants associated with varroa non-reproduction in drone brood were discovered in a single colony from the Amsterdam Water Dune population in the Netherlands. Recently, a new study tested the applicability of these eight genetic variants for the same phenotype on a population-wide scale in Flanders, Belgium. As the properties of some variants varied between the two studies, one hypothesized that the difference in genetic ancestry of the sampled colonies may underly these contribution shifts. In order to frame this, we determined the allele frequencies of the eight genetic variants in more than 360 Apis mellifera colonies across the European continent and found that variant type allele frequencies of these variants are primarily related to the A. mellifera subspecies or phylogenetic honey bee lineage. Our results confirm that population-specific genetic markers should always be evaluated in a new population prior to using them in MAS programs.

Mite non-reproduction is not a consequence of the brood removal behavior of varroa sensitive hygiene honey bee colonies (Apis mellifera).

A sustainable solution to the global threat of the Varroa destructor mite is the selection of varroa-resistant honey bee (Apis mellifera) colonies. Both "mite non-reproduction" (MNR) and "varroa sensitive hygiene" (VSH) appear to be promising selection traits for achieving the goal of a resistant honey bee. MNR describes colonies that have a high number of non-reproductive mites (no offspring, no males, or delayed development of mite offspring). High numbers of non-reproductive mites have been observed in selected colonies, but the mechanism behind this trait has not yet been identified. The specialized hygienic behavior of selected honey bees, called VSH, is the removal of varroa-infested brood. These traits were thought to be linked by VSH bees preferentially removing reproductive varroa females leaving only non-reproductive mites behind in cells and thus creating colonies with high levels of MNR. To further investigate this link, we used an experimental setup and data sets from a four-year selection project designed to breed for MNR and VSH colonies. In addition, we sought to answer the question of whether non-reproductive mites are a direct consequence of worker removal behavior. To test this, we artificially induced removal behavior, and after providing the mite with enough time to re-enter another cell, we opened all capped cells, relocated the mites, and evaluated their reproduction. As shown in previous studies and in this study, VSH had no effect on MNR levels. Also, the induced removal behavior did not lead to non-reproduction in the subsequent reproductive cycle post interruption. We thus concluded that breeding for non-reproductive mites does not automatically breed for VSH behavior and worker removal behavior does not cause subsequent reproductive failure of the mites forced to flee and find a new cell for reproduction.

Large cells suppress the reproduction of Varroa destructor.

BACKGROUND: The parasitic mite, Varroa destructor has posed a threat to the health and survival of European honey bees, Apis mellifera worldwide. There is a prevailing belief that small comb cells could provide a management tool against Varroa mites. However, the hypothesis that smaller cells can impede Varroa reproduction has not been fully tested. Here, we tested this hypothesis under laboratory conditions by using two distinct Varroa in vitro rearing systems: one involved gelatin capsules of different sizes, specifically size 00 (0.95 mL) versus size 1 (0.48 mL), and the second consisted of brood comb cells drawn on 3D printed foundations with varying cell sizes, ranging from 5.0 mm to 7.0 mm at 0.5 mm intervals. RESULTS: The results showed that mother mites in size 00 cells had significantly lower fecundity and fertility compared to those in size 1 cells. Interestingly, the reproductive suppression in larger cells could be reversed by adding an extra worker larva. Similarly, gonopore size of mother mites was smaller in size 00 cells, but restored with another host larva. Furthermore, both the fecundity and fertility of mother mites decreased linearly with the size of brood comb cells. CONCLUSIONS: Our results suggest that the reproduction of V. destructor is hindered by larger cells, possibly because larger brood cells disperse or weaken host volatile chemical cues that are crucial for Varroa reproduction. The insights derived from this study are expected to hold significant implications for the implementation of Varroa management programs. © 2024 Society of Chemical Industry.

Caught in the act: the invasion of a viral vector changes viral prevalence and titre in native honeybees and bumblebees.

Novel transmission routes change pathogen landscapes and may facilitate disease emergence. The varroa mite is a virus vector that switched to western honeybees at the beginning of the last century, leading to hive mortality, particularly in combination with RNA viruses. A recent invasion of varroa on the French island of Ushant introduced vector-mediated transmission to one of the last varroa-naive native honeybee populations and caused rapid changes in the honeybee viral community. These changes were characterized by a drastic increase in deformed wing virus type B prevalence and titre in honeybees, as well as knock-on effects in bumblebees, particularly in the year following the invasion. Slow bee paralysis virus also appeared in honeybees and bumblebees, with a 1 year delay, while black queen cell virus declined in honeybees. This study highlights the rapid and far-reaching effects of vector-borne transmission that can extend beyond the directly affected host species, and that the direction of the effect depends on the pathogen's virulence.

RNA interference as a next-generation control method for suppressing Varroa destructor reproduction in honey bee (Apis mellifera) hives.

BACKGROUND: The Varroa mite (Varroa destructor) is considered to be the greatest threat to apiculture worldwide. RNA interference (RNAi) using double-stranded RNA (dsRNA) as a gene silencing mechanism has emerged as a next-generation strategy for mite control. RESULTS: We explored the impact of a dsRNA biopesticide, named vadescana, designed to silence the calmodulin gene in Varroa, on mite fitness in mini-hives housed in a laboratory. Two dosages were tested: 2 g/L dsRNA and 8 g/L dsRNA. Vadescana appeared to have no effect on mite survival, however, mite fertility was substantially reduced. The majority of foundress mites exposed to vadescana failed to produce any offspring. No dose-dependent effect of vadescana was observed, as both the low and high doses inhibited mite reproduction equally well in the mini-hives and neither dose impacted pupal survival of the honey bee. Approximately 95% of bee pupae were alive at uncapping across all treatment groups. CONCLUSION: These findings suggest that vadescana has significant potential as an effective alternative to conventional methods for Varroa control, with broader implications for the utilization of RNAi as a next-generation tool in the management of pest species. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Winter Hive Debris Analysis Is Significant for Assessing the Health Status of Honeybee Colonies (Apis mellifera).

Honeybee diseases are one of the most significant and most common causes of honeybee colonies' weakness and death. An early diagnosis of subclinical infections is necessary to implement precautionary and control measures. Sampling debris from hive bottom boards is simple, non-invasive, and cheap. In this study, we collected winter debris samples in apiaries located in the continental part of Croatia. We used molecular methods, PCR and qPCR, for the first time to analyze those samples. Laboratory results were compared with the health condition and strength of honeybee colonies at an apiary in spring. Our study successfully identified the presence and quantity of various pathogens, including the presence of Vairimorpha spp. (Nosema spp.), quintefied Paenibacillus larvae, Acute Bee Paralysis Virus (ABPV), Black Queen Cell Virus (BQCV), Deformed Wing Virus (DWV), and Sacbrood Virus (SBV). However, our analysis did not detect Melissococcus plutonius, Crithidia mellificae, Lotmaria passim, and Aethina tumida. Samples of winter debris were also examined for the presence and quantification of the V. destructor mites, and their natural mite fall was observed in spring. Honeybee colonies were simultaneously infected by an average of four to six pathogens. Some observed honeybee colonies developed characteristic symptoms, while others did not survive the winter.