Abstract: Annotations for a map of a worksite are generated by a controller. The controller receives georeferenced crop state data and georeferenced agricultural characteristic data, collectively referred to as agronomy data. The georeferenced crop state data and georeferenced agricultural characteristic data are analyzed by the controller to determine relationships therebetween. The controller generates the annotations based on the determined relationships. The controller generates explanations, which are type of annotation, based on determined relationships between current agronomy data and historical agronomy data.

Abstract: 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.

Abstract: A computer-implemented method includes obtaining a weed map of a field including a crop, the weed map representing weed plant locations on the field, identifying, based at least in part on the weed map, weed seed locations that represent presence of weed seeds on the field, and generating a control signal for a pre-emergence weed mitigation operation based on the weed seed locations.

Abstract: 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.

Abstract: One or more maps are obtained by an agricultural work machine. The one or more 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 maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An agricultural machine includes a seeding system having a seed transport mechanism configured to transport a seed along a transport route. A terahertz-based seed sensor is configured to direct terahertz electromagnetic radiation toward the seed at a sensing location along the transport route and detect terahertz electromagnetic radiation after the terahertz electromagnetic radiation interacts with the seed to provide terahertz data. An actuator is configured to selectively move the seed. A processing system is configured to receive the terahertz data and classify the seed as qualified or non-qualified and to selectively engage the actuator based on whether the seed is classified as qualified or non-qualified.

Abstract: A work vehicle configured for operating in a field for growing a crop. The work vehicle comprises an implement coupled to the work vehicle. A global positioning system is communicatively coupled to the work vehicle. The global positioning system is configured for generating a location signal indicative of a location of the work vehicle. A sensor is communicatively coupled to the work vehicle. The sensor is configured for sensing a current field characteristic and generating a current field characteristic signal indicative of the field characteristic. A control system is communicatively coupled to the work vehicle. The control system is configured to receive the location signal, receive the current field characteristic signal, determine a sentinel plant characteristic of a sentinel plant from the current field characteristic, determine an implement action based on the sentinel plant characteristic, and control the implement to execute the implement action in the field.

Abstract: A planter configured for planting a sentinel plant in a field. The planter comprises a first planting system that is coupled to the planter. The first planting system is configured for planting a first sentinel plant having a first sentinel plant characteristic. A global positioning system is communicatively coupled to the planter. The global positioning system is configured for generating a location signal indicative of a location of the planter. A control system is communicatively coupled to the planter. The control system is configured to receive the first sentinel plant characteristic, receive the location signal, receive a georeferenced field characteristic, and control the first planting system based on at least one of the first sentinel plant characteristic, the location, or the georeferenced field characteristic.

Abstract: A work vehicle includes an implement coupled to the work vehicle. A global positioning system is communicatively coupled to the work vehicle and is configured for generating a location signal indicative of a location of the work vehicle. At least one sensor is communicatively coupled to the work vehicle and configured for generating first and second sentinel plant characteristic signals indicative of first and second sentinel plant characteristics. A control system is communicatively coupled to the work vehicle and configured to receive the location signal, the first and second sentinel plant characteristic signals, determine an implement action based on a function including the first and second sentinel plant characteristics as variables, and control the implement to execute the implement action in the field.

Abstract: 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.

Abstract: 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.

Abstract: Methods and system for minimizing soil compaction relating to operations performed by agricultural machines. The agricultural machines can be guided so that at least one engagement body travels along an existing track path that was established by a prior travel of the same or different agricultural machine. Further, travel plans can determine the sequence in which the agricultural machine(s) travel in areas in the field so that travel on the track path(s) can be initiated in drier regions in the field. Operation of agricultural machines can also be adjusted to minimize deviations of other agricultural machines from existing track paths. For example, a windrower can operate a diverter to deposit a windrow at an offset location, and with a non-linear pattern, that may limit a baler from deviating from an existing track path while collecting crop material from the windrow, while also assisting in forming uniformly shaped crop bales.

Abstract: 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.

Abstract: 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.

Abstract: A method for remediating developmentally delayed plants within a field of crops using at least one work vehicle during a field operation. The method comprises identifying delayed plants within the field with a sensor on the work vehicle and generating, with a processor, location data associated with the location of the delayed plant with the field. Upon arriving at the location of the delayed plant with the work vehicle, the delayed plant is remediated.

Abstract: A computer-implemented method of controlling a mobile agricultural machine includes obtaining prior field data representing a position of plants in a field, obtaining in situ plant detection data from operation of the mobile agricultural machine in the field, determining a position error in the prior field data based on the in situ plant detection data, and generating a control signal that controls the mobile agricultural machine based on the determined position error.

Abstract: 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.