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.

The disclosed apparatus, systems and methods relate to automatic calibration systems, methods and devices for use with vehicle systems such as grain cart and combine vehicle systems to calibrate the yield monitor via collected calibration load profile data that is processed and used to calibrate and recalibrate the system automatically.

A system for an agricultural harvester includes a chopper assembly configured to separate a harvested material into debris and stalk. A primary extractor is configured to remove debris from the harvester. A sensor system is configured to capture data associated with harvested material conditions downstream of the primary extractor. A computing system includes one or more processors and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, configure the computing system to perform operations. The operations include obtaining the data associated with the associated harvested material conditions downstream of the primary extractor, determining a current foliage ratio based on the data, determining an error between the current foliage ratio to a desired foliage ratio, and generating a harvest-related parameter of the primary extractor based at least in part on the error.

A computer implemented method includes receiving a map that maps values of a crop characteristic to different locations across a field; receiving harvester route data indicative of a planned route of a harvester at the field; identifying a crop characteristic threshold; identifying a material transfer end location indicative of a location, along the planned route of the harvester, at which a material transfer operation between the harvester and a receiving machine is to end, based on the map, the planned route of the harvester, and the crop characteristic threshold; identifying a material transfer start location range indicative of a geographic area, along the planned route of the harvester, at which the material transfer operation is to start based on the material transfer end location; and generating a route for the receiving machine to travel based on the material transfer end location and the material transfer start location range.

An agricultural harvesting system includes a harvesting logistics module that is configured to receive a map that maps values of a crop characteristic to different geographic locations in a field. The harvesting logistics module further configured to identify a crop characteristic threshold and to identify a mixture of crop material based on the map and based on the crop characteristic threshold. The harvesting logistics module configured to generate a route for a mobile machine, such as a receiving machine or a harvester, based on the identified mixture.

An agricultural harvester includes: a chassis; a threshing and separation system including at least one concave carried by the chassis, the threshing and separation system being configured to thresh and separate a flow of crop material; and a controller carried by the chassis. The controller is configured to: operably couple to a moisture sensor disposed upstream of the threshing and separation system, relative to the flow of crop material; determine a moisture level of crop material headed for the threshing and separation system; and output an adjustment signal to at least one component of the agricultural harvester to adjust performance of the threshing and separation system based at least partially on the determined moisture level.

A method and an apparatus for separating a crop flow on at least one conveying and cleaning unit, particularly a top sieve, of a combine harvester, wherein the conveying and cleaning unit is excited to a longitudinal oscillation and a transverse oscillation. The transverse oscillation is controlled depending on at least one state, wherein least one state for controlling the transverse oscillation is the inclination of the combine harvester, wherein at least one further state for controlling the transverse oscillation is the grain purity, particularly the grain purity of a main crop flow. The transverse oscillation is pre-controlled depending on the inclination of the combine harvester and fine-tuned depending on the grain purity.

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.

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.