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.

Operating conditions corresponding to a harvesting operation being performed by a mobile harvesting machine are detected along with a priority of a first performance pillar metric relative to a second performance pillar metric. An operating characteristic of the mobile harvesting machine is detected and a performance pillar metric value is identified for the first performance pillar metric based on the detected operating characteristic. A performance limitation corresponding to the first performance pillar metric is identified based on the detected operating conditions and an aggressiveness setting is detected that is indicative of an operating settings change threshold. It is then determined whether a settings change is to be performed based on the first performance pillar metric value, the priority of the first performance pillar metric, the first performance limitation and the settings change threshold and if the settings change is to be performed, a settings change actuator is controlled to execute the settings change.

Operating conditions corresponding to a harvesting operation being performed by a mobile harvesting machine are detected along with a priority of a first performance pillar metric relative to a second performance pillar metric. An operating characteristic of the mobile harvesting machine is detected and a performance pillar metric value is identified for the first performance pillar metric based on the detected operating characteristic. A performance limitation corresponding to the first performance pillar metric is identified based on the detected operating conditions and an aggressiveness setting is detected that is indicative of an operating settings change threshold. It is then determined whether a settings change is to be performed based on the first performance pillar metric value, the priority of the first performance pillar metric, the first performance limitation and the settings change threshold and if the settings change is to be performed, a settings change actuator is controlled to execute the settings change.

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.

An agricultural vehicle including a container, which is mounted on at least one train of wheels, wherein the container rests by way of fixation brackets and load cells or weight sensors, preferably directly, i.e. without use of an intermediate chassis, on one axle or more forming the train of wheels. The vehicle container is mounted on the axle or each of the axles of the train under consideration by way of at least two pairs of load cells, wherein each pair consists of two load cells situated on opposite sides of a vertical plane parallel to the vertical planes containing the axes of the axles of a multi-axle train.

A product system for an agricultural sprayer includes a product tank configured to store a volume of an agricultural product. A fill station is configured to accept the agricultural product from an off-board source. A flow assembly is fluidly coupled with the fill station and is configured to direct the agricultural product into a product tank from the conduit. A reclaim system is configured to provide the agricultural product within the flow assembly to the product tank. A computing system is communicatively coupled to the reclaim system. The computing system is configured to receive inputs indicative of activation of a fill mode, detect termination of the fill mode, and activate a reclaim mode to move the agricultural product from at least the conduit to the product tank through activation of the reclaim system.

The disclosure discloses an apparatus for online volumetrically detecting grain yield based on weight calibration comprising left volumetric granary, right volumetric granary and push board. The left volumetric granary is provided on its bottom with first weighing sensor, and in its side with unload grain port opening and first closing door, the right volumetric granary is provided on its bottom with second weighing sensor, and in its side with unload grain port opening and second closing door, the left volumetric granary and the right volumetric granary are provided on their tops with the push board, the push board is a hollow box structure with a top side and a bottom side both opened, and is slidably mounted to a top of the left volumetric granary and the right volumetric granary through a slide driving mechanism.

The disclosure discloses an apparatus for online volumetrically detecting grain yield based on weight calibration comprising left volumetric granary, right volumetric granary and push board. The left volumetric granary is provided on its bottom with first weighing sensor, and in its side with unload grain port opening and first closing door, the right volumetric granary is provided on its bottom with second weighing sensor, and in its side with unload grain port opening and second closing door, the left volumetric granary and the right volumetric granary are provided on their tops with the push board, the push board is a hollow box structure with a top side and a bottom side both opened, and is slidably mounted to a top of the left volumetric granary and the right volumetric granary through a slide driving mechanism.

A method, using an autonomous, unmanned device and a control device, includes the steps of automatically harvesting feed crop in a part of a crop field by means of the autonomous, unmanned device; automatically loading the harvested feed crop directly into a storage space provided on the autonomous, unmanned device without said harvested feed crop contacting the soil; choosing a destination location from a feeding location and a stationary crop processing location; automatically transporting the harvested feed crop from the crop field to the chosen destination location by means of the autonomous, unmanned device; and automatically unloading harvested feed from the storage space of the autonomous, unmanned device at the chosen destination location.