A system comprised of an apparatus and a test device is described. The test device and the apparatus are designed to interact to determine the presence or absence of an analyte of interest in a sample placed on the test device.

A swept frequency fluorometer having a signal processor or processing module configured to: receive signaling containing information about reflected light off one or more fluorescence species-of-interest in a liquid sample that is swept with light having a variable frequency range, the information including a characteristic optical frequency corresponding to a fluorescence species-of-interest in the liquid, and a characteristic/lifetime optical frequency corresponding to a distinct fluorescence lifetime in which the fluorescence species-of-interest remains in an excited state; and provide corresponding signaling containing information about an identity of the fluorescence species-of-interest detected and distinguished from overlapping fluorescence species in the liquid using the characteristic/lifetime optical frequency, based upon the signaling received.

Technology is provided for an aqueous solution constituent analyzer. The analyzer includes an ultraviolet light emitting diode (LED) with a current source providing variable current thereto. A spectrometer is positioned for receiving light from the LED transmitted through an aqueous solution. A controller receives radiant flux data for a plurality of wavelengths and determines, based on the radiant flux data, a usable number of the plurality of wavelengths that satisfies a relative uncertainty threshold. The controller can increase the current to the LED if the usable number of wavelengths is less than a minimum threshold and calculate a concentration of a constituent of interest in the solution. The controller can also determine a peak wavelength of the plurality of wavelengths having the greatest intensity value, and decrease the current level to the LED if the peak wavelength has an intensity value greater than a saturation value for the spectrometer.

Devices, systems and methods for sorting and labeling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labeling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labeled according to the at least one of the one or more food parameters.

Devices, systems and methods for sorting and labelling food products are provided. Respective spectra of food products for a plurality of segments of a line are received at a controller from at least one line-scan dispersive spectrometer configured to acquire respective spectra of the food products for the plurality of segments of the line. The controller applies one or more machine learning algorithms to the respective spectra to classify the plurality of segments according to at least one of one or more food parameters. The controller controls one or more of a sorting device and a labelling device according to classifying the plurality of segments to cause the food products to be one or more of sorted and labelled according to the at least one of the one or more food parameters.

An automatic analytical apparatus includes a reaction container for mixing a sample with a reagent to react the sample to the reagent, a measurement unit that irradiates a reaction solution in the reaction container with light and measures the intensity of transmitted light or scattered light, a control unit that processes time-series light intensity data obtained through the measurement in the measurement unit, a storage unit that stores one or more approximation functions each approximating to a time-series change in the light intensity data, and an output unit that outputs a processing result of the control unit. The control unit selects any one of the approximation functions stored in the storage unit, calculates an approximate curve indicating a time-series change in the light intensity data using the selected approximation function, calculates deviation feature information based on deviation information between the light intensity data and the approximate curve, and detects and classifies an abnormality included in the light intensity data using the deviation feature information.

An optical analysis system and an optical analysis method, which simply change driving electric currents of light-emitting units via using a control and process unit, so that a wavelength range and a peak wavelength of an irradiated light generated by each light-emitting unit may be fine-tuned. A plurality of irradiating lights with different wavelength ranges and peak wavelengths are irradiated to the object to be tested in different times, so that merely fewer light-emitting units may be used to improve a detection resolution and a detection accuracy of a spectrum of the object to be tested.