An optical sorter includes an intermittent light source configured to intermittently emit light toward a plurality of sorting targets in transit, an optical sensor configured to detect the light associated with one sorting target among the plurality of sorting targets in transit during a plurality of intermittent light scan periods, a determination part configured to determine a foreign object and/or a defective product with respect to the one sorting target based on a signal acquired by the optical sensor, and a light source control part configured to control the intermittent light source. The light source control part is configured to control the intermittent light source in such a manner that, in a case where the intermittent light source is turned on during at least one intermittent light scan period among the plurality of intermittent light scan periods, a lighting period during which the intermittent light source is on and a non-lighting period during which the intermittent light source is off are provided and the lighting period is started at a timing delayed behind a start of the at least one intermittent light scan period in each of the at least one intermittent light scan period.

A seamless fumed silica monolithic integrating cavity device tailored to analyzing a flowed sample. The device is configured to facilitate optical measurements taken from a sample flowed through a cavity of the device. The cavity is defined by a fumed silica monolith with the added feature of a fused quartz lining on the surface of the monolith. This provides an intermediate surface that allows for cleaning and reuse of the highly effective diffuse light scattering fumed silica monolith. The lining may be placed under pressure or vacuum to structurally enhance mechanical integrity of the underlying monolith. Thus, continued or reliably repeated use of the device may be appreciated as well as use in more industrial environments that are prone to vibration. Additionally, while well suited for flow-based sample analysis, a valve of the cavity may be utilized for holding a sample in a temporarily static state for measurement.

A fine ratio measuring device that measures a ratio of fines adhering to the surface of a material in the form of lumps, the fine ratio measuring device includes: an illumination unit that illuminates the material in the form of lumps; a spectrometer that performs spectral analysis on light reflected from the material in the form of lumps to measure spectral reflectance; and an arithmetic device that extracts at least one feature quantity from the spectral reflectance measured by the spectrometer and computes the fine ratio from the extracted at least one feature quantity.

A seed sampling system is provided comprising an automated seed loading assembly operable to singulate seeds from a plurality of seeds or enable loading of individually stored seeds and an automated seed sampling assembly comprising at least one sampling module operable to remove tissue samples from one of the singulated seeds. The system also includes an automated seed transport assembly comprising at least one retention member operable to transfer the singulated seeds from at least one elevator unit of the seed loading assembly to the at least one sampling module of the seed sampling assembly. In connection therewith, the at least one sampling module includes multiple sampling locations, each associated with a sampler, where the at least one sampling module is operable to remove tissue samples from seeds at one of sampling locations while another one of the sampling locations is cleaned to remove residual seed tissue therefrom.

A radio frequency (RF) grain mass and constituent measurement system utilized onboard a combine harvester includes an RF sensor subsystem for capturing RF sensor readings of a harvested grain within an area of the combine harvester. A memory stores an RF characteristic database, which contains RF characteristic testing data collected for tested grain samples over one or more tested frequency ranges. A controller, operably coupled to the RF sensor subsystem and to the memory, is configured to: (i) receive the RF sensor readings from the RF sensor subsystem; (ii) determine grain mass and a first constituent content of the currently-harvested grain based, at least in part, on an analytical comparison between the RF sensor readings and the RF characteristic testing data; and (iii) perform at least one action in response to determining the grain mass and the first constituent content of the harvested grain.

An apparatus for detecting matter including: a light source arrangement adapted to emit a first and a second set of light beams towards a first detection zone through which the matter is provided. A spectroscopy system adapted to receive and analyse light which is reflected and/or scattered by matter in the first detection zone. A laser triangulation system including, a laser arrangement adapted to emit a line of laser light towards a second detection zone. A camera-based sensor arrangement configured to receive and analyse light which is reflected and/or scattered by matter in the second detection zone. The received light of the spectroscopy system completely or partially intersects the received light of the camera-based sensor arrangement and/or the line of laser light.

Method for sorting corn kernels of a batch of corn kernels, the method comprising the steps of: laying the corn kernel on a support surface, the corn kernel having a resting surface in contact with the support surface, and an upper surface opposite the resting surface, acquiring at least one orientation image of the corn kernel with an orientation imaging system, the orientation imaging system having a modality adapted to enable structural features of the corn kernel to be measured, determining an orientation of the corn kernel with respect to the support surface based on the structural features of the corn kernel measured on the orientation image, sorting the corn kernel as a function of the orientation.

A method and system for detecting an aflatoxin on a grain, seed or nut which includes sorting a plurality of the grain seeds in single file, capturing a plurality of shortwave infrared images of each seed, comparing the wavelengths from the captured image with the wavelengths indicative of an aflatoxin presence at a predetermined concentration, and ejecting from a group of the seeds those seeds that have an aflatoxin concentration greater than the predetermined concentration as indicated by the wavelengths from the captured images.

Described herein is a device (1) for measuring parameters of a material (3) flowing along a passage (5), the passage having two longitudinally spaced apart ends and transverse sides defined by one or more sidewalls (7, 9). The device (1) includes a laser source (15) positioned at a first location within or adjacent a side of the passage (5) and configured to generate a laser beam (17) at one or more predetermined frequencies. A beam projection element (21, 27) projects the laser beam (17) transversely across the passage (5) to irradiate the material (3) within a measuring zone (19). The measuring zone (19) includes a transverse region extending greater than 50% of the width of the passage (5). An optical imaging device (29) is positioned at a second location within or adjacent the passage (5) and configured to capture images of backscattered light from material (3) within the measuring zone (19). A processor (41) is in communication with the optical imaging device (29) and is configured to process the captured images and perform a scattering analysis to determine parameters of the material (3) through the passage (5).

A method and a system for determining an indicator of processing quality of an agricultural harvested material using a mobile device is disclosed. A computing unit analyzes image data of a prepared sample of harvested material containing grain components and non-grain components in an analytical routine to determine the indicator of the processing quality of the agricultural harvested material. Further, the computing unit uses a trained machine learning model in the analytical routine to perform at least one step of determining the indicator of the processing quality of the agricultural harvested material and that the computing unit adjusts at least one machine parameter of the forage harvester based on the indicator of processing quality.