Described are various embodiments of a crop phenology characterisation method, and system using same. One embodiment relates to a method of monitoring a crop phenology, the method comprising acquiring a size measurement of a crop in a crop location over time, monitoring a first parameter calculated based at least in part on to a periodic recovery value of the size measurement, and a second parameter calculated at least in part based on a periodic growth value of the size measurement. In some embodiments, one or more of the first parameter and the second parameter are indicative of a crop characteristic. In some embodiments, an indication related to the crop characteristic may be provided in response to one or more of the first parameter and the second parameter.

A seed depth device for an agricultural planter includes an electric motor. The seed depth device also includes an actuator driven by the electric motor and arranged to move to a home position. The seed depth device further includes a first stop proximate to the actuator when in the home position. The seed depth device yet further includes at least one controller including a computing processor and a computer readable storage medium configured to control the electric motor. The seed depth device also includes a seed depth auto-learn system at least in-part stored and executed by the at least one controller, the seed depth auto-learn system configured to learn the home position based at least in-part on the actuator stalling upon the first stop, wherein the seed depth auto-learn system is configured to move the actuator a prescribed distance away from the first stop to establish the home position.

A seed depth device for an agricultural planter includes an electric motor. The seed depth device also includes an actuator driven by the electric motor and arranged to move to a home position. The seed depth device further includes a first stop proximate to the actuator when in the home position. The seed depth device yet further includes at least one controller including a computing processor and a computer readable storage medium configured to control the electric motor. The seed depth device also includes a seed depth auto-learn system at least in-part stored and executed by the at least one controller, the seed depth auto-learn system configured to learn the home position based at least in-part on the actuator stalling upon the first stop, wherein the seed depth auto-learn system is configured to move the actuator a prescribed distance away from the first stop to establish the home position.

A yield estimation system comprising a harvester. The harvester comprising a plurality of row units, one or more stalk sensors on each of the plurality of row units, and a yield monitor in communication with the plurality of row units. The system also comprising a processor configured to correlate data from the one or more stalk sensors to data from the yield monitor on a row-by-row basis and a display configured to display the correlated data to a user.

A working vehicle includes a vehicle body to be coupled to a working device, a communication controller to obtain first operation information relating to operation of the working device, the communication controller being electrically connected to the working device to communicate bi-directionally with the working device, an applicability judging device to judge applicability of the working device to the operation based on the first operation information obtained by the communication controller, and a display device to display the applicability judged by the applicability judging part.

A computer-implemented data processing method providing an improvement in executing machine learning processes on digital data representing physical properties related to agriculture is described. In an embodiment, the method comprises: receiving, from a computing device, a request to browse machine learning models stored in a digital model repository; retrieving, from the digital model repository and transmitting to the computing device, information about the machine learning models stored in the digital model repository; receiving, from the computing device, a selection, from the machine learning models, of a particular model and receiving particular input for the particular model; using resources available in a model execution infrastructure platform, executing the particular model on the particular input to generate particular outputs; transmitting the particular output to a computer configured on an agricultural machine to control the agricultural machine as the agricultural machine performs agricultural tasks in an agricultural field.

An agricultural machine includes a set of ground engaging elements that perform a ground engaging operation. The agricultural machine includes a rearward sensor mounted to the agricultural machine to sense an area of ground behind the agricultural machine and generate a rearward sensor signal. The agricultural machine includes rearward zone generator logic that determines a first zone and a second zone, wherein the first zone and the second zone represent portions of the area of ground behind the agricultural machine. The agricultural machine includes rearward residue generator logic configured to receive the rearward sensor signal and determine a first residue metric indicative of the amount of residue in the first zone. The agricultural machine includes control logic that controls one or more aspects of the ground engaging operation on the area of ground based on the first residue metric.

A depth-adjustment assembly for ground openers of an agricultural implement. The ground openers each include an opening disc, a gauge wheel, and a support assembly securing the ground opener to the agricultural implement. The support assembly is configured to raise and lower the ground opener with respect to the ground and/or to adjust a down-pressure of the ground opener. The depth-adjustment assembly comprises for each of the ground openers, a linkage assembly and a depth-adjustment arm configured to adjust a relative position between the opening disc and the gauge wheel. At least a portion of the linkage extends in parallel relationship with the support assembly. The depth-adjustment assembly further comprises a laterally-extending common pivot bar. Each linkage assembly is secured to the common pivot bar, such that rotation of said common pivot bar is configured to simultaneously adjust the relative position between the opening disc and the gauge wheel of each of the ground openers.

A depth-adjustment assembly for ground openers of an agricultural implement. The ground openers each include an opening disc, a gauge wheel, and a support assembly securing the ground opener to the agricultural implement. The support assembly is configured to raise and lower the ground opener with respect to the ground and/or to adjust a down-pressure of the ground opener. The depth-adjustment assembly comprises for each of the ground openers, a linkage assembly and a depth-adjustment arm configured to adjust a relative position between the opening disc and the gauge wheel. At least a portion of the linkage extends in parallel relationship with the support assembly. The depth-adjustment assembly further comprises a laterally-extending common pivot bar. Each linkage assembly is secured to the common pivot bar, such that rotation of said common pivot bar is configured to simultaneously adjust the relative position between the opening disc and the gauge wheel of each of the ground openers.

An agricultural assistance system including a driver assistance system for controlling one or both of a prime mover and an attachment of an agricultural combination is disclosed. The agricultural assistance system generates control parameters for one or both of the prime mover and the attachment, has a rule interpreter that generates the control parameters by processing rules from sets of rules, and has a rule generator that provides a plurality of sets of rules. The agricultural assistance system executes the rule interpreter as needed on control hardware that is part of one or both of the prime mover or the attachment, and on control hardware that is disposed remote from the combination. The agricultural assistance system has a coordination module for this which, independent of the site at which the rule interpreter is run, coordinates the rule interpreter with the control generator and the driver assistance system.