In one example, a system for evaluating an agricultural material is provided. The system comprising: a housing having a passage in or through an interior of the housing with an inlet for receiving agricultural material and an outlet for outputting the agricultural material; a wall opening in a wall of the passage; and an imaging device having a window located within a border, the imaging device having a removable portion with at least one of a moisture absorbing material, a heat source, and an anti-fog agent within the removable portion.

A terahertz frequency-based sensing system for an agricultural harvester is provided. The system includes a terahertz sensor mounted to the agricultural harvester. The terahertz sensor at least one a terahertz source disposed to direct electromagnetic radiation toward a harvest material of the agricultural harvester. At least one terahertz detector is disposed to detect the terahertz electromagnetic radiation after the terahertz electromagnetic radiation interacts with the harvest material. A controller is operably coupled to the at least one terahertz detector and is configured to detect at least one harvest-related parameter based on a signal from the at least one terahertz detector and to perform an action based on the at least one detected parameter.

The height of a header of a self-propelled harvesting machine is controlled by a closed loop header position control system. A sensitivity control system receives parameters related to header position error (e.g., an accuracy parameter) and machine stability (e.g., a stability parameter) and automatically identifies a sensitivity metric indicative of a sensitivity with which the header position control system controls the header height, based upon the received parameters. The sensitivity metric is provided to the header position control system. The header position control system performs closed loop header position control with a sensitivity level based upon the sensitivity metric provided by the sensitivity control system.

An apparatus is presented that receives first and second parameters including first parameters from plural harvesting machines, determines a batch unload for a specified quantity of material to unload from each of the harvesting machines, requests permission to receive the batch unload from one of the harvesting machines, and communicates a control signal to trigger the requested batch unload from the one of the harvesting machines.

An apparatus is presented that receives first and second parameters including first parameters from plural harvesting machines, determines a batch unload for a specified quantity of material to unload from each of the harvesting machines, requests permission to receive the batch unload from one of the harvesting machines, and communicates a control signal to trigger the requested batch unload from the one of the harvesting machines.

Methods for autonomous operation of harvesters use header drive pump displacement, header speed, harvester ground speed, engine load and engine speed to control and maximize harvester operation under varying conditions such as crop type, crop condition and terrain. Adaptive learning processes within the methods relate the parameters of pump displacement with header speed and engine speed during harvester operation to permit the control system to establish combinations of related control parameters which are used by a control system to control harvester operation.

A cutting system includes knives attached to a continuously moving belt-type carrier. The carrier motion moves the knives past stationary counterknife fingers which are attached to or uniform with a cutterbar, as the cutting system is driven through a field of crop stalks, which are cut by the interaction between the knives and counterknives. One or more sensing devices produce signals or images related to the condition of the knives when the knives are moving past the sensing devices. A processing unit processes the signals or images and derives therefrom one or more parameters representative of the condition of the knives, and compares the parameters to a reference, to thereby monitor the condition. An agricultural implement such as a combine harvester, can be equipped with the cutting system.

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.

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.

A harvester monitoring system configured to determine one or more parameters associated with harvested items, the system comprising: a camera module having a field of view and configured to generate image data associated with the harvested items; a mounting bracket configured to secure the camera module to a harvester such that a conveyor of the harvester is within the field of view of the camera module; a location sub-system configured to determine and output location data representative of a geographical location of the harvester monitoring system; and a processing unit configured to receive the image data and the location data, to determine one or more parameters associated with the harvested items, and to record the one or more parameters in association with the location data on a computer readable medium.