The safety and or security of drinking water can be threatened by natural disasters, accidents or malevolent attacks. The European FP7 project SAFEWATER aims at developing a comprehensive event detection and event management solution for drinking water security management and mitigation against major deliberate, accidental or natural CBRN related contaminations. New cost-effective C, B, and RN sensors will be developed. An innovative concept with a broad network of low-cost sensors - "domestic sensors" (complementary to a set of sensors in strategic locations) will be developed. A technology platform will be provide which is able to capture and analyze the data collected by the sensors and from other information systems and give a full overview of the crisis to the responders by means of online look-ahead simulations to efficiently manage potential crises. For testing the SAFEWATER solution it will be integrated with on utility-partners' information systems.

We developed a novel biodetection method for influenza virus based on AC magnetic susceptibility measurement techniques (the DynoMag induction technique) together with functionalized multi-core magnetic nanoparticles. The sample consisting of an incubated mixture of magnetic nanoparticles and rolling circle amplified DNA coils is injected into a tube by a peristaltic pump. The sample is moved as a plug to the two well-balanced detection coils and the dynamic magnetic moment in each position is read over a range of excitation frequencies. The time for making a complete frequency sweep over the relaxation peak is about 5 minutes (10 Hz–10 kHz with 20 data points). The obtained standard deviation of the magnetic signal at the relaxation frequency (around 100 Hz) is equal to about 10−5 (volume susceptibility SI units), which is in the same range obtained with the DynoMag system. The limit of detection with this method is found to be in the range of 1 pM.

We developed nanoparticles with tailored magnetic properties for direct and sensitive detection of biomolecules in biological samples in a single step. Thermally blocked nanoparticles obtained by thermal hydrolysis, functionalized with specific ligands, are mixed with sample solutions, and the variation of the magnetic relaxation due to surface binding is used to detect the presence of biomolecules. The binding significantly increases the hydrodynamic volume of nanoparticles, thus changing their Brownian relaxation frequency which is measured by a specifically developed AC susceptometer. The system was tested for the presence of Brucella antibodies, a dangerous pathogen causing brucellosis with severe effects both on humans and animals, in serum samples from infected cows and the surface of the nanoparticles was functionalized with lipopolysaccarides (LPS) from Brucella abortus. The hydrodynamic volume of LPS-functionalized particles increased by 25-35% as a result of the binding of the antibodies, measured by changes in the susceptibility in an alternating magnetic field. The method has shown high sensitivity, with detection limit of 0.05 μgmL-1 of antibody in the biological samples without any pretreatment. This magnetic- based assay is very sensitive, cost-efficient, and versatile, giving a direct indication whether the animal is infected or not, making it suitable for point-of-care applications. The functionalization of tailored magnetic nanoparticles can be modified to suit numerous homogeneous assays for a wide range of applications.

Flow cytometry is a laser-based technology that rapidly detects and analyzes the chemical and physical characteristics of single cells or particles and is already well established in environmental and toxicological studies for microalgae and bacterial quantification. This study introduces an imaging Flow Cytometer (FC) system, designed specifically for the enhanced analysis of microalgae biomass populations and aggregate groups through Artificial Intelligence (AI) integration. The FC incorporates a single flow line, critical hardware components, and a trifurcated software setup. The system employs a multi-step process for counting algae units and an Artificial Neural Network (ANN) for classifying them in groups of two or four. To demonstrate its capabilities, the system was tested on its ability to capture, count, and categorize algal units, specifically the Desmodesmus sp. morphotype with high accuracy. Furthermore, the FC’s capabilities were contrasted with traditional counting methods, validating its enhanced precision and efficiency against a hematocytometer. With its capability to provide rapid, accurate, and high-throughput analyses, this innovative FC paves the way for a revolutionary approach to cellular research. 

The aim of this project is to investigate a new method for fast detectionof fecal contamination in water resources by using E. coli as indicator bacteria. Online measurement of raw water quality is important in order toavoid outbreaks of waterborne diseases and therefor very interesting for thewater producers for society in general. The method is based on fluorescently labelled antibodies which specific binds to the indicator bacteria andan instrument was developed to count individual bacteria in a continuously sample flow. The system was designed to be more robust to match theindustrial environment to a lower cost than a conventional flow cytometer.The fluorescent markers was at first chosen in the visible region of thelight spectrum, but early tests showed a high level of interfering fluorescent background signal in this region, arising from the chlorophyll in algaeand cyanobacteria in raw water. Hence a decision was made to change themeasurement to near-infrared (NIR) wavelengths, in order to reduce thebackground signal. The change of measurement region solved the problem with background fluorescence which is an important step towards aworking product. The required adjustments of the optics in the instrumentintroduced new challenges, especially on the detector side.Field trials performed at Överby Water treatment plant in Trollhättanshowed that the instrument was working fine in the industrial environmentand connection to the raw water pipe was tested. Laboratory measurementsshowed that the instrument clearly could measure difference between rawwater samples and treated sewage water, but the estimated differences inconcentration were lower than expected.The greatest challenge with this technique is probably to achieve a sufficient sample flow through the instrument in order to get a good estimationof the E. coli concentration within reasonable time (minutes). However, itis possible to increase the throughput flow by increasing the size of the flowchannel, but this will probably lower the sensitivity of the system and this isan important trade-off for future development.The evaluation done in this project shows that the instrument has greatpotential for online measurement of E.coli content in raw water, whichmakes it suitable as an early warning system. To invest in further development can be well motivated.

Projektet har utvärderat olika onlinesensorer för att upptäcka föroreningar från avloppsvatten i dricksvattennätet. Flera kommersiella sensorer kunde detektera inläckage vid koncentrationer av avloppsvatten på cirka 0,7 procent, men bäst var den nyutvecklade sensor som kallas elektronisk tunga. Den kunde med låg sannolikhet för falsklarm detektera ner till åtminstone 0,05 procent avloppsvatten. Vanliga problem som kan ge upphov till smitta via dricksvatten är gamla och läckande ledningsnät som ger tryckfall, eller felaktiga kopplingar som gör att ytvatten och avloppsvatten kan förorena dricksvattnet. Risken för inläckage av avloppsvatten ansågs i projektet vara det högst prioriterade scenariot. Med ett nätverk av sensorer i dricksvattennätet och ett effektivt övervakningssystem skulle man kunna upptäcka och lokalisera föroreningskällan och ingripa med nödvändiga åtgärder innan det förorenade vattnet når kunderna.

Projektet utfördes av Tekniska verken i Linköping i samverkan med Totalförsvarets forskningsinstitut (FOI) och ett stort antal andra aktörer. I en referensgrupp ingick ett antal svenska dricksvattenproducenter som ställde upp viktiga kriterier för onlinesensorer i dricksvattennätet. Sensorerna ska vara billiga, robusta, driftsäkra, anpassade för driftmiljön och kräva lite underhåll. De ska inte behöva förbehandling eller reagenser och bör helst mäta direkt på det trycksatta nätet. De bör helst vara generella, det vill säga upptäcka alla typer av föroreningar, men det är ett stort mervärde om de kan klassificera typen av förorening. Den elektroniska tungan har vidareutvecklats inom Vinnovaprojektet Sensation III. Även de nya sensorerna flödescytometer och elektronisk näsa testades i projektet, liksom standardsensorer för konduktivitet, pH och kloröverskott, samt en avancerad sensor baserad på optisk absorbans. Testerna skedde i en rigg på avloppsreningsverket i Linköping under ett par månader då olika koncentrationer av avloppsvatten tillfördes. Även syntetiskt avloppsvatten och råvatten tillfördes vid några tillfällen. Två elektroniska tungor testades även vid en tryckstegringsstation respektive vid vattentornet under cirka ett år. Olika typer av signalbehandling undersöktes för att optimera larmalgoritmerna.

Resultaten visar att det är möjligt att upptäcka inläckage av avloppsvatten i dricksvattnet med hjälp av onlinesensorer. Även standardsensorer för konduktivitet och pH kunde detektera inläckage av avloppsvatten, men bäst resultat gav den elektroniska tungan. Sensorn för optisk absorbans hade en detektionsgräns mellan den elektroniska tungan och standardsensorerna. I anläggningar med större utspädning av avloppsvattnet än i Linköping kommer sensorerna förmodligen att ha en högre detektionsgräns.

För att det ska bli möjligt att övervaka dricksvattenkvaliteten med hjälp av onlinesensorer krävs det nära samverkan mellan sensortillverkare, dricksvattenproducenter och -distributörer, eftersom det behövs fortsatta tester och är så svårt att kravställa och bestämma prestandan för sensorerna för alla tänkbara vatten.

A plant phenotyping approach was applied to evaluate growth rate of containerized tree seedlings during the precultivation phase following seed germination. A simple and affordable stereo optical system was used to collect stereoscopic red-green-blue (RGB) images of seedlings at regular intervals of time. Comparative analysis of these images by means of a newly developed software enabled us to calculate (a) the increments of seedlings height and (b) the percentage greenness of seedling leaves. Comparison of these parameters with destructive biomass measurements showed that the height traits can be used to estimate seedling growth for needle-leaved plant species whereas the greenness trait can be used for broad-leaved plant species. Despite the need to adjust for plant type, growth stage and light conditions this new, cheap, rapid, and sustainable phenotyping approach can be used to study large-scale phenome variations due to genome variability and interaction with environmental factors.

In order to detect fast changes of the Brownian relaxation time due to reaction kinetics on the surface of magnetic particles or particle-clustering processes, we have developed a method that uses pulsed magnetic fields and detects the relaxation of the magnetic response on the time scale of milliseconds. We compared measurements in the frequency domain with the time domain measurement using particle suspensions with three different median sizes. The results obtained with the two methods agreed well. Time domain determination of Brownian relaxation was then used to study the reaction kinetics of the clustering process when sodium chloride solution was added to a magnetic nanoparticle suspension.

Obtaining more data for the research/studies of plants growing may be easier realized when suitable non-destructive detection methods are available. We are here presenting the development of a miniaturised, low-power, real-time, multi-parameter and cost-effective sensor for measurements in mini plugs (growth of seedling). The detection technique is based on measurement of electrical impedance at two frequencies for sensing two soil parameters, water content and water conductivity (dependent on e.g. total ions concentration). Electrical models were developed and comply with data at two frequencies. An easy and efficient calibration method for the sensor is established by using known liquids’ properties instead of various soil types. The measurements show a good correlation between the sensor's readings and the traditional soil testing. This soil sensor can easily send data wirelessly allowing for spot checks of substrate moisture levels throughout a greenhouse/field, and/or enable sensors to be buried inside the soil/substrate for long-term consecutive measurements.

We describe a sensing system that is able to measure pH in-vivo, in the rumen of a cow, in real time. The sensing principle is based on gravimetric transduction using a magnetoelastic ribbon functionalized by pH-sensitive nanobeads that is placed in the rumen where it is actuated and read-out wirelessly. We describe a generic procedure that enables one to deposit monolayers or multilayers of nano- and micro beads onto virtually any substrate. The topography of the resulting layers as well as interlayer coverages were characterised using optical microscopy and scanning profilometry. First we determined performance of the system in-vitro, in phosphate-buffered saline, in McDougall's buffer and in a rumen fluid. Thereafter we also performed in-vivo measurements. Using buffers we determined pH response in the liquids both at the fundamental frequency of the functionalised foils, and at the 1st overtone. We argue that observed frequency changes vs pH are mainly due to changes of trapped liquid when the bead layers shrink or expand as a response to changed pH. The data obtained from the pH response of magnetoelastic foils at different bead coverages was modelled by a simple two-parameter model that corroborates this assumption.