Abstract: There is provided a system and method for determining external and/or internal attributes of an object using hyperspectral imaging, while taking into consideration changes in the spectral emission profile of the light source used for the imaging.

Abstract: A method and system for monitoring invasive species in an algal bioreactor utilizes a low resolution Raman spectrometer (LRRS) system and signal processing methods based upon Support Vector Machine (SVM) models. A spectrum preprocessing algorithm transforms LRRS spectra into normalized spectral data vectors. An ex-situ method is used to analyze a calibration set of known samples of a suspension containing a desired biomass, such as spirolina, together with various concentrations of invasive algal or cyanobacterial species. The ex-situ method generates SVM models and their associated SVM support vectors for classification modeling. An in-situ method uses the SVM models to provide an output vector of probability values corresponding to the presence of invasive species in an unknown sample, and optionally to provide an additional output vector of probability values corresponding to concentrations of the invasive species in the unknown sample.

Abstract: System and method for imaging-based quality assessment of raw produce loads, including an imaging structure comprising a mounting beam, light sources; optical sensors, and additional sensors; wherein the mounting beam is configured to allow vertical, lateral and/or longitudinal and movement of the measurement chamber. The system also includes a processing unit configured to control the vertical, lateral and/or longitudinal movement of the measurement chamber relative to the mounting beam, control opto-mechanical parameters of the optical sensors, control the position, orientation, light projection and/or light intensity of the light sources; trigger signal acquisition, receiving and fusing spectral data from the optical sensors with data from the additional sensors; and feeding the fused data into machine learning algorithm and/or big-data analytics model, to derive internal and/or external quality attributes of the produce.

Abstract: A fruit flesh extracting machine for extracting a flesh of a fruit is provided. The machine includes a conveyor configured for, carrying and displacing the fruit; an edge removing station configured for slicing at least one edge of the fruit; and a flesh extracting station having a first scoop slidabley and transversely mounted with respect to the conveyor and being configured for scooping out the flesh of the fruit. The conveyor is configured to displace the fruit between the edge removing station and the flesh extracting station.