A method and apparatus for determining a reflectance, of at least a portion of a target object, in at least one selected wavelength range of electromagnetic (EM) radiation are disclosed. The method comprises, for each selected wavelength range, providing a digital image including at least one target object and a plurality of reference objects, each reference object having respective non-identical predetermined reflectance characteristics, with a digital camera arrangement that provides output image data that comprises digital numbers that are responsive to radiation, in only a selected wavelength range, incident at a sensing plane of the digital camera arrangement. A relationship between a first set of the digital numbers is determined and a first set of the respective predetermined reflectance characteristics of the reference objects. Responsive to the relationship, a further set of digital numbers is transformed to allocate a value of reflectance for each of the digital numbers in the further set. For at least a portion of the target object, a corresponding first group of allocated values of reflectance is determined and responsive to the first group of allocated values, determining a reflectance of the portion of the target object.

A system and method for non-destructive food rapid profiling in terms of taste, variant classification, adulteration, etc., using artificial intelligence. The system includes: a receptacle configured to move a non-homogenized sample in a path to intersect a volumetric sampling space; a sensor configured to sense reflectance from at least a part of the sample in the volumetric sampling space, the sensor being configured to output a component of the reflectance as captured data, the captured data being characterised by an overtone spectrum over a range of wavelengths; and a computing device configured to apply at least one first machine learning model to the captured data to: predict at least one facet corresponding to predictively determined selected wavelengths; and provide a signature data using the at least one facet.

A sensing module for monitoring dosage delivery of a vaporized material, and a portable vaporization unit including the sensing module, include a light sensor that detects disruptions in a light path across a vapor channel, the disruptions caused by the vaporized material flowing through the vapor channel. The light sensor includes a UV light source, which may emit 370 nm wavelength light, and a UV light detector that converts intensity of incident light in the light path into a signal. A microprocessor of the sensing module compares the signal to a baseline measurement to determine the concentration of a medicament in the vapor; then, using the flow rate and activation time of the device, the microprocessor determines the dosage and can perform monitoring and reporting actions based on the dosage. A measuring circuit measures fluctuations in resistance/impedance of a vaporization element to further determine flow rate and/or dosage.

A reagent strip and a reagent analyzer for reading the reagent strip is described. The reagent strip includes a substrate, at least one reagent pad positioned on the substrate, and a photo luminescent phosphor spot positioned at a fixed location on the substrate. The photo luminescent phosphor spot is formulated to exhibit a predetermined addressable attribute.

The present invention includes an apparatus and method for detecting the location of one or more sources of one or more target molecule, the apparatus comprising: a molecule detector; and a processor connected to the molecule detector and to a global position system, wherein the processor calculates the presence of the one or more target molecules, runs a computer code that determines a dynamic reverse gas stack model for the one or more target molecules, and triangulates the possible position for a source or effluent of the one or more target molecules based on the dynamic reverse gas stack model. The determined reverse gas stack model may have a Gaussian dispersion over one or more sampled locations.

A method for sample analysis that employs a signal-amplifying nanosensor is provided. An implementation of the present method may include a) obtaining a sample, b) applying the sample to a signal-amplifying nanosensor containing a capture agent that binds to an analyte of interest, under conditions suitable for binding of the analyte in a sample to the capture agent, c) washing the signal-amplifying nanosensor, and d) reading the signal-amplifying nanosensor, thereby obtaining a measurement of the amount of the analyte in the sample. In some embodiments, the analyte may be a biomarker, an environmental marker, or a foodstuff marker. Also provided herein are kits that find use in performing the present method.

Provided herein is a sensing apparatus comprising, at least one LSPR light source, at least one detector, and at least one sensor for LSPR detection of a target chemical. The sensor comprises a substantially transparent, porous membrane having nanoparticles immobilized on the surface of its pores, the nanoparticles being functionalized with one or more capture molecules. There is further provided a self-referencing sensor for distinguishing non-specific signals from analyte binding signals. The self-referencing sensor comprising one or more nanoparticles having at least two distinct LSPR signals.

An apparatus for analyzing a plant specimen is disclosed which includes a housing assembly adapted to be in i) an open configuration adapted to receive a plant specimen, and ii) a closed configuration wherein ambient light is controlled therein, a light source disposed in or coupled to the housing assembly, the light source adapted to shine light onto or through the plant specimen when the housing assembly is in the closed configuration, and a camera assembly coupled to the housing assembly, the camera assembly having an image sensor adapted to receive light from the plant specimen in i) a transmittance mode where light transmits through the plant specimen, or ii) a reflectance mode where light is reflected from the plant specimen, the image sensor adapted to thereby capture hyperspectral images of the plant specimen.

A method of performing antimicrobial susceptibility testing (AST) on a sample uses a reader device that mounts on a mobile phone having a camera. A microtiter plate containing wells preloaded with the bacteria-containing sample, growth medium, and drugs of differing concentrations is loaded into the reader device. The wells are illuminated using an array of illumination sources contained in the reader device. Images of the wells are acquired with the camera of the mobile phone. In one embodiment, the images are transmitted to a separate computing device for processing to classify each well as turbid or not turbid and generating MIC values and a susceptibility characterization for each drug in the panel based on the turbidity classification of the array of wells. The MIC values and the susceptibility characterizations for each drug are transmitted or returned to the mobile phone for display thereon.

An infrared (IR) imaging system for determining a concentration of a target species in an object is disclosed. The imaging system can include an optical system including a focal plane array (FPA) unit behind an optical window. The optical system can have components defining at least two optical channels thereof, said at least two optical channels being spatially and spectrally different from one another. Each of the at least two optical channels can be positioned to transfer IR radiation incident on the optical system towards the optical FPA. The system can include a processing unit containing a processor that can be configured to acquire multispectral optical data representing said target species from the IR radiation received at the optical FPA. One or more of the optical channels may be used in detecting objects on or near the optical window, to avoid false detections of said target species.