Preconcentration techniques for trace explosive sensing

This project has received funding from NATO Science for Peace & Security under grant agreement MYP G5355, the European Union’s Seventh Framework Programme for research, technological development and demonstration under agreement no 284747, and the EPSRC under EP/K503940/1.Trace sensing of explosive vapours is a method in humanitarian demining and Improvised Explosives Device (IED) detection that has received increasing attention recently, since accurate, fast, and reliable chemical detection is highly important for threat identification. However, trace molecule sampling in the field can be extremely difficult due to factors including weather, locale, and very low vapour pressure of the explosive. Preconcentration of target molecules onto a substrate can provide a method to collect higher amounts of analyte for analysis. We used the commercial fluoropolymer Aflas as a preconcentrator material to sorb explosive molecules to the surface, allowing subsequent detection of the explosives via the luminescence quenching response from the organic polymer Super Yellow. The preconcentration effect of Aflas was confirmed and characterised with 2,4-DNT, prior to field sampling being conducted at a test minefield in Croatia by placing preconcentration strips in the entrance of the hives, where honeybees have collected explosive materials during free-flying. In this work we show for the first time a method for confirmation of landmines combining honeybee colonies containing a preconcentration material and subsequent monitoring of luminescence quenching.PostprintPeer reviewe

Estimating the density of honeybee colonies across their natural range to fill the gap in pollinator decline censuses

Although pollinator declines are a global biodiversity threat, the demography of the western honeybee (Apis mellifera) has not been considered by conservationists because it is biased by the activity of beekeepers. To fill this gap in pollinator decline censuses and to provide a broad picture of the current status of honeybees across their natural range, we used microsatellite genetic markers to estimate colony densities and genetic diversity at different locations in Europe, Africa, and central Asia that had different patterns of land use. Genetic diversity and colony densities were highest in South Africa and lowest in Northern Europe and were correlated with mean annual temperature. Confounding factors not related to climate, however, are also likely to influence genetic diversity and colony densities in honeybee populations. Land use showed a significantly negative influence over genetic diversity and the density of honeybee colonies over all sampling locations. In Europe honeybees sampled in nature reserves had genetic diversity and colony densities similar to those sampled in agricultural landscapes, which suggests that the former are not wild but may have come from managed hives. Other results also support this idea: putative wild bees were rare in our European samples, and the mean estimated density of honeybee colonies on the continent closely resembled the reported mean number of managed hives. Current densities of European honeybee populations are in the same range as those found in the adverse climatic conditions of the Kalahari and Saharan deserts, which suggests that beekeeping activities do not compensate for the loss of wild colonies. Our findings highlight the importance of reconsidering the conservation status of honeybees in Europe and of regarding beekeeping not only as a profitable business for producing honey, but also as an essential component of biodiversity conservation.This project was funded by the BEESHOP European network (FOOD-CT-2006-022568) and the National Research Foundation of South Africa

Authoritative subspecies diagnosis tool for European honey bees based on ancestryinformative SNPs

Background With numerous endemic subspecies representing four of its five evolutionary lineages, Europe holds a large fraction of Apis mellifera genetic diversity. This diversity and the natural distribution range have been altered by anthropogenic factors. The conservation of this natural heritage relies on the availability of accurate tools for subspecies diagnosis. Based on pool-sequence data from 2145 worker bees representing 22 populations sampled across Europe, we employed two highly discriminative approaches (PCA and F-ST) to select the most informative SNPs for ancestry inference. Results Using a supervised machine learning (ML) approach and a set of 3896 genotyped individuals, we could show that the 4094 selected single nucleotide polymorphisms (SNPs) provide an accurate prediction of ancestry inference in European honey bees. The best ML model was Linear Support Vector Classifier (Linear SVC) which correctly assigned most individuals to one of the 14 subspecies or different genetic origins with a mean accuracy of 96.2% +/- 0.8 SD. A total of 3.8% of test individuals were misclassified, most probably due to limited differentiation between the subspecies caused by close geographical proximity, or human interference of genetic integrity of reference subspecies, or a combination thereof. Conclusions The diagnostic tool presented here will contribute to a sustainable conservation and support breeding activities in order to preserve the genetic heritage of European honey bees.The SmartBees project was funded by the European Commission under its FP7 KBBE programme (2013.1.3-02, SmartBees Grant Agreement number 613960) https://ec.europa.eu/research/fp7.MP was supported by a Basque Government grant (IT1233-19). The funders provided the financial support to the research, but had no role in the design of the study, analysis, interpretations of data and in writing the manuscript

Queen rearing and selection practices and their impact on the genetic diversity and fitness of honey bee colonies

The Apimondia working group on honey bee diversity and fitness (AWG 7) was created on October 25, 2010 as a Scientific Working Group of Apimondia. The aim of this AWG is to collect information on honey bee queen rearing practices, and examine their impact on the genetic variability and general health of honey bee colonies. The AWG consists of 23 members from 16 different countries. The world wide survey being conducted by this AWG is focused on gathering information on how selection methods, instrumental insemination, disease management procedures, introduction of exotic bee lines, queen replacement strategies, and loss of local colony populations due to introduced parasites and pathogens, affect the ability of our bees to survive and reproduce. The information collected will contribute on an international level to our understanding of how apiculture practices affect honey bee genetics, health and productivity

Fluorescence-based sensors and preconcentration techniques for buried explosives detection

Trace detection of explosives is an important challenge in both humanitarian landmine clearance and in homeland security scenarios. The ability to detect the presence of explosives across an area of interest would be of particular use in technical surveys of suspected minefields. In this paper we present the development and application of fluorescence-based trace-explosives sensors based on organic semiconductor thin films. We show that these can be used to detect nano-gram level quantities of nitroaromatic (TNT-like) molecules, and combine them for the first time with a novel preconcentration approach to detect buried explosives. Initial field trials on a test minefield will also be presented, in which the sensors are used to detect trace explosives collected by colonies of foraging honeybees.</p

Preconcentration Techniques for Trace Explosive Sensing (dataset)

Science of the Total Environment datase

Ongoing evaluations of the Coloss WG 4 genotype-environment interaction experiment

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The influence of genetic origin and its interaction with environmental effects on the survival of Apis mellifera L. colonies in Europe

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