A detector detects yield data corresponding to a plurality of different harvesters. Detectors can also detect harvest performance data and logistics performance data for those harvesters. A control signal generator generates control signals to control the harvesters to maintain a target harvest rate, for the crop harvested by the plurality of harvesters, collectively.

A method and system for controlling the quality of harvested grains include capturing, by one or more image sensors, one or more images of material at a sampling location within a grain elevator of the combine harvester. The captured images are defined by a set of image pixels represented by image data and having a classification feature indicative of grain or non-grain material. One or more controllers receive the image data associated with the one or more images captured by the image sensor(s) and select a sample image defined by a subset of image pixels of the set of image pixels. The controller(s) apply a convolutional neural network (CNN) algorithm to the image data of the subset of image pixels of the selected sample image to determine the classification feature. The controller(s) analyze the determined classification feature to adjust an operational parameter of the combine harvester.

A grain tailings elevator for a combine harvester includes a an elevator housing having an interior containing a conveyor arrangement configured to transport grain tailings through the elevator housing to a discharge outlet. The elevator housing has a side wall with a window to the interior of the elevator housing. A camera having a camera housing containing an image sensor is mounted to the side wall of the elevator housing over the window with the image sensor in registration with the window. The image sensor is trained on the conveyor arrangement and configured to image the grain tailings transported by the conveyor arrangement through the elevator housing.

A device and a method for determining a portion of broken grain and/or non-grain components in a stream of harvested material is disclosed. The device includes a camera to generate images of the stream of harvested material and an evaluation unit to estimate the portion in an image supplied by the camera. The evaluation unit includes a first-order classifier to estimate a first parameter of the stream of harvested material, and a plurality of second-order classifiers assigned to various values of the first parameter to estimate the portion in a stream of harvested material that has the assigned parameter value. The evaluation unit, with assistance of the first-order classifier, estimates a value of the first parameter using a first number of images of the camera, and then selects the second-order classifier assigned to the value of the first parameter to estimate the portion with assistance of the selected second-order classifier.

An object of the present invention is to improve the quality level discrimination accuracy of the grain G by a grain quality level discrimination device. The device includes an optical unit 3 that emits light to the grain G, receives reflected and/or transmitted light from the grain G by a photosensor, and obtains information for discrimination of the quality level of the grain G from the upper and lower surface side of the grain G, and a quality level discrimination unit 7 that discriminates the quality level of the grain G on the basis of the information. The information on the upper and lower surface sides can be acquired by one optical unit at the same time so that the divergence therebetween due to the displacement or variation of the attitude of the grain G can be avoided. The reference plate for the correction of the information is placed outside of the moving path of the grain G to prevent it from soiling or damaging. Thus the deterioration of information can be avoided. Further, a reference plate especially for the information to be obtained from the side surface of the grain G may be provided for enhancing the accuracy of the side surface information. Thus the quality level discrimination accuracy can be improved further.

A spectrometric measuring head for forestry, agricultural and food industry applications comprises a housing having a window and a spectrometer that is arranged inside the housing and comprises a dispersive element and a sensor, a first light source for exposing a sample to light, which reaches the spectrometer through the window after having been transmitted and/or reflected by the sample, and a standard that can be exposed to light to provide a reference for the spectrometer, which standard can be exposed to light by a light source arranged in the housing.

A system and method for automated grain inspection and analysis of results during harvest, using an inspection system mounted on a combine harvester with geolocation tracking, allowing for real time analysis during harvest and tracking of grain quality by location of harvest.

A system and method for automated grain inspection and analysis of results, that inspects grains using a plurality of light spectra, analyzes the results, and produces detailed reports from the analysis.

Systems, and methods for controlling a modular system for improved real-time yield monitoring and sensor fusion of crops in an orchard are disclosed. According to some embodiments of the invention, a modular system for improved real-time yield monitoring and sensor fusion may include a collection vehicle, a modular processing unit, a volume measurement module, a three-dimensional point-cloud scanning module, an inertial navigation system, and a post-processing server. As the collection vehicle travels through an orchard, the volume measurement module calculates volume measurements of the windrow, the three-dimensional point-cloud scanning module assembles point-clouds of each plant in the orchard, and the inertial navigation system calculates geodetic positions of the collection vehicle. The modular processing unit may fuse the collected data together and transmit the fused data set to a post-processing server. The post-processing server may process the geodetic position data for errors which may be used for geo-referencing the fused data.

A work machine with a sensing assembly that identifies characteristics of an underlying surface and a distribution assembly that distributes material to the underlying surface. Wherein, the sensing assembly identifies the characteristics of the underlying surface and the distribution assembly distributes varying amounts of material based on the characteristics as the work machine moves along the underlying surface.