Abstract: Disclosed a crop yield prediction method and system based on low-altitude remote sensing information from an unmanned aerial vehicle (UAV). Obtaining a plurality of images taken by the UAV; stitching the plurality of images to obtain a stitched image; performing spectral calibration on the stitched image to obtain the reflectivity of each pixel in the stitched image; using a threshold segmentation method to segment the stitched image, to obtain a target area for crop yield prediction; using a Pearson correlation analysis method to analyze a correlation between the reflectivity of each band and the growth status and yield of the crop to obtain feature bands; constructing yield prediction factors based on the feature bands; and determining a predicted crop yield value of the target area for crop yield prediction based on the yield prediction factors and a crop planting area of the target area for crop yield prediction.

Abstract: An open microfocus X-ray source and a control method thereof are provided. The open microfocus X-ray source includes: an open X-ray tube, a high voltage power supply (HVPS) system, a vacuum system and a control system. The open X-ray tube includes a cathode system, a deflection system and a focusing system. The HVPS system is configured to provide an emission current I0, an accelerating high voltage U0 and a grid voltage UG for an electron beam. The vacuum system is configured to perform vacuumization. The control system is configured to control, according to a spot size of an electron beam for bombarding an anode target, the HVPS system to adjust the emission current I0, the accelerating high voltage U0, a deflection coil current IXY of the deflection system, and a focusing coil current IF of the focusing system, such that the spot size meets a preset requirement.

Abstract: A whole-process automatic soil tabletting machine is provided, which relates to the technical field of soil tabletting. The machine includes a device body. A tabletting platform is arranged at a bottom of the device body, a first station on which a heating device is arranged, second and third stations are arranged on the tabletting platform. A top plate is arranged at a top of the device body. A soil crushing cutter and a punch head are installed on the top plate. The soil crushing cutter and the punch head are arranged above the first and second stations respectively. The tabletting platform is installed with a groove disc where sample preparation grooves and a cleaning groove are formed. The sample preparation grooves and the cleaning groove correspond to the first station, the second station or the third station. The cleaning groove and each sample preparation groove are for placing a cleaning container and a soil sample container, respectively.

Abstract: The present disclosure provides a gas mixture-based laser-induced breakdown spectroscopy (LIBS) signal enhancement apparatus and a heavy metal detection method. The apparatus includes a pulsed solid-state laser 1, an optical path system 2, a spherical gas mixing chamber 3, a fiber-optic receiver 4, a spectrometer 5, and a controller 8. The optical path system 2 is connected to the pulsed solid-state laser 1. The spherical gas mixing chamber 3 is disposed opposite to the optical path system 2. The fiber-optic receiver 4 is disposed opposite to the spherical gas mixing chamber 3. The spectrometer 5 is connected to the fiber-optic receiver 4. The controller 8 is connected to the spectrometer 5 and the pulsed solid-state laser 1. The spectrometer 5 determines LIBS information based on an optical signal received by the fiber-optic receiver 4. The controller 8 determines a LIBS spectrogram based on the LIBS information.

Abstract: The invention relates to a method and device for predicting a volume median diameter (VMD) in an overlapped spray area of twin nozzles. Placing a single nozzle at different heights to determine a spray area; measuring all VMDs in the spray area to obtain first true measured values; dividing the first true measured values to construct a first calibration set and a first prediction set; establishing a polynomial fitting formula by a REGRESS function; placing twin nozzles at different heights and different nozzle spacing, and measuring VMDs in the overlapped spray area to obtain second true measured values; determining simulated values of the VMDs of first and second nozzles; dividing the simulated values of the VMDs and the second true measured values to construct a second calibration set and a second prediction set; quantitatively calibrating by using a radial basis function neural network (RBFNN) to obtain a prediction model; determining a VMD in the overlapped spray area of twin nozzles.

Abstract: Disclosed a crop yield prediction method and system based on low-altitude remote sensing information from an unmanned aerial vehicle (UAV). Obtaining a plurality of images taken by the UAV; stitching the plurality of images to obtain a stitched image; performing spectral calibration on the stitched image to obtain the reflectivity of each pixel in the stitched image; using a threshold segmentation method to segment the stitched image, to obtain a target area for crop yield prediction; using a Pearson correlation analysis method to analyze a correlation between the reflectivity of each band and the growth status and yield of the crop to obtain feature bands; constructing yield prediction factors based on the feature bands; and determining a predicted crop yield value of the target area for crop yield prediction based on the yield prediction factors and a crop planting area of the target area for crop yield prediction.

Abstract: The invention relates to a method and device for predicting a volume median diameter (VIVID) in an overlapped spray area of twin nozzles. Placing a single nozzle at different heights to determine a spray area; measuring all VMDs in the spray area to obtain first true measured values; dividing the first true measured values to construct a first calibration set and a first prediction set; establishing a polynomial fitting formula by a REGRESS function; placing twin nozzles at different heights and different nozzle spacing, and measuring VMDs in the overlapped spray area to obtain second true measured values; determining simulated values of the VMDs of first and second nozzles; dividing the simulated values of the VMDs and the second true measured values to construct a second calibration set and a second prediction set; quantitatively calibrating by using a radial basis function neural network (RBFNN) to obtain a prediction model; determining a VIVID in the overlapped spray area of twin nozzles.