A system and computer-implemented method for assessing an amount of ash includes an agricultural implement and an ash assessment system. The implement includes a crop processing portion configured to move a cut organic material in a field. The ash assessment system includes an ash sensor configured to determine a measured ash contamination value, a GNSS receiver configured to determine a geolocation, and a processor programmed to perform an ash assessment process. The process includes receiving the measured ash contamination value from the ash sensor and receiving the geolocation data from the GNSS receiver. The geolocation data corresponds to a geolocation of the measured ash contamination value. The process also includes correlating the measured ash contamination value and the geolocation data to one another and storing the measured ash contamination value and the geolocation data in a memory device that is coupled in communication with said processor.

Systems and methods for controlling formation of a windrow in response to a single control input are disclosed. The single control input represents a desired windrow width. The single control input is used to determine positions of components of a cutter implement, such as side shields and a swath flap, that are used to form a windrow having the desired windrow width represented or that is otherwise associated with the single control input.

A method for shadow and cloud masking for remote sensing images of an agricultural field using multi-layer perceptrons includes electronically receiving an observed image, performing using at least one processor an image segmentation of the observed image to divide the observed image into a plurality of image segments or superpixels, extracting features for each of the image segments using the at least one processor, and determining by a cloud mask generation module executing on the at least one processor a classification for each of the image segments using the features extracted for each of the image segments, wherein the cloud mask generation module applies a classification model including an ensemble of multilayer perceptrons to generate a cloud mask for the observed image such that each pixel within the observed image has a corresponding classification.

Method and apparatus for presenting information associated with a multi-segment header of an agricultural harvester. The operational states of the segments are monitored and used to present information. Examples of presented information include graphics depicting which segments are operational and which segments are non-operational, crop coverage maps, and crop yield maps.

A crop residue monitoring system may include a harvester, a camera to capture an image of crop residue generated by the harvester, an analytical unit to derive a value for a crop residue parameter of the crop residue based upon an optical analysis of the image and a control unit to adjust a subsequent field operation based upon the value of the crop residue parameter.

Systems and methods for monitoring the distribution of residue material from a spreader tool of an agricultural machine including a sensor, preferably a LIDAR or other scanning transceiver-type sensor mounted or otherwise coupled to the machine and orientated with a sensing region pointing rearwards of the agricultural machine, where operational data indicative of an operational parameter of the spreader tool is obtained and used to control operation of the sensor.

Methods and apparatus to identify headlands are disclosed. A disclosed example apparatus to identify a headland of a field includes an image analyzer to generate an image from data corresponding to path information of at least one field operation performed on the field, a mask generator to generate a mask of the image based on the image, and a headland identifier to identify the headland in the field based on the mask.

Disclosed herein is an apparatus for facilitating managing cultivation of crops based on monitoring the crops. Further, the apparatus comprises an apparatus body, cameras, light sensors, a processing unit, and a communication interface. Further, the cameras generate a measurement of a crop and a field portion. Further, the light sensors generate an environment measurement of an environment of the apparatus. Further, the processing unit analyzes the environment measurement, determines a factor affecting the measurement, and generates a calibrating factor for the cameras. Further, the calibrating factor facilitates compensating the affecting of the factor in the measurement. Further, the cameras calibrate a camera parameter of the cameras based on the calibrating factor to generate the measurement. Further, the processing unit analyzes the measurement and generates a status of the crop. Further, the communication interface transmits the status to a device.

A field map generating system includes: a crop data obtaining unit that obtains crop data over time; a position information obtaining unit that obtains position information, indicating a harvesting position of the crop, over time; polygon constructing units that construct a polygon on the basis of a work width and speed of a harvester, for each piece of crop data obtained by the crop data obtaining unit; data assigning units that assign crop data or crop information based on the crop data to the constructed polygons; a position information assigning unit that assigns position information to the constructed polygons; and field map generating units that generate a field polygon map, which is an aggregate of the polygons, by aggregating the polygons.

A map generator generates a replanting map designating a particular area in a field in which it is recommended to add additional seeds. A function of the agricultural machine is then controlled based at least in part on the replanting map so as to facilitate planting additional seeds in the designated particular area.