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.

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.

The apparatus (1) for agricultural crop analysis, comprises: a light source (2) for sending light radiation towards a crop; a plurality of sensors (21) for acquiring light radiation reflected by the crop and a plurality of filtering elements (22) adapted to enable complete passage only of light having frequencies within a predetermined passband. The filtering elements (22) have passbands that differ from each other and each filtering element (22) is functionally coupled with a respective sensor (21) in such a manner that the latter receives only light radiation that has traversed the former.

Systems and methods are disclosed herein for optimizing harvester yield. In an embodiment, a controller receives a pre-harvest image from a front-facing camera of a harvester. The controller inputs the pre-harvest image into a model, and receives as output from the model a predicted harvest yield. The controller receives, from an interior camera of the harvester, a post-harvest image including the plants as harvested. The controller inputs the post-harvest image into a second model and receives, as output, an actual harvest yield of the plants as-harvested. The controller determines that the predicted harvest yield does not match the actual harvest yield, and outputs a control signal.

An agricultural work machine for performing an agricultural work process is disclosed. The agricultural work machine includes working units and a driver assistance system for controlling the working units to achieve one or more quality criteria. The driver assistance system may set parameters to control the working units in order to satisfy the criteria. Further, the driver assistance system includes a graphical user interface through which an operator may change the setting of one of the quality criteria. Responsive to the change, the driver assistance system may determine the expected effects on other quality criteria. In addition, the driver assistance system may visually highlight the expected effects on the graphical user interface.

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.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.