At least some aspects of the present disclosure are directed to systems and methods of an agronomic condition prediction and alerts engine. In some cases, the engine receives a set of field data and the set of field data includes one or more of geospatial data, crop data, user data, agronomic data, and weather data. In some cases, the engine retrieves a set of agronomic profile data from an agronomic data repository, where each of the set of agronomic profile data representing an agronomic condition and comprising one or more of geospatial profile, crop profile, pest profile, agronomic profile, user data profile, and weather profile corresponding to the agronomic condition. In some embodiments, the engine applies a multivariable processing to the set of field data using the set of agronomic profile data and generates an agronomic condition indicator indicative of one or more agronomic conditions.

Methods, systems, and computer program products for customizing agricultural practices to maximize crop yield are provided herein. A computer-implemented method includes obtaining data pertaining to (i) a geographical area comprising a plurality of regions and (ii) one or more agricultural practices applied to the geographical area; assigning each of the plurality of regions to a respective cluster of a set clusters, based at least in part on comparing features identified in the data, wherein similar ones of said regions are assigned to the same cluster; generating instructions that are specific to a given cluster in the set, wherein the instructions relate to agricultural tasks to be performed on the regions assigned to the given cluster; and triggering, based on said instructions, one or more automated farming processing devices, thereby carrying out at least a portion of said agricultural tasks.

A method for agronomic and agricultural monitoring includes designating an area for imaging, determining a flight path above the designated area, operating an unmanned aerial vehicle (UAV) along the flight path, acquiring images of the area using a camera system attached to the UAV, and processing the acquired images.

An agricultural implement comprising: a ground engaging tool; and an actuator mechanism (366; 466; 566). The actuator mechanism is configured to provide a bias force to the ground engaging tool such that it is biased towards a working position. The agricultural implement also includes a controller that is configured to automatically set the level of the bias force that is provided by the actuator mechanism based on control-data.

A method for estimating precipitation distribution for a geographical region comprising the steps of: providing precipitation data (S10) for the geographical region with a first spatial resolution for a predetermined period of time (t.sub.1, t.sub.2); providing first soil moisture data (S20) for the geographical region for a first point in time (t.sub.3) with a second spatial resolution, wherein the second spatial resolution is higher than the first spatial resolution, and wherein the first point in time (t.sub.3) is within the predetermined period of time (t.sub.1, t.sub.2); providing second soil moisture data (S30) for the geographical region for a second point in time (t.sub.4) with a third spatial resolution, wherein the third spatial resolution is higher than the first spatial resolution, and wherein the second point in time (t.sub.4) is within the predetermined period of time (t.sub.1, t.sub.2); calculating soil moisture difference data (S40) between the first soil moisture data and the second soil moisture data; calculating precipitation distribution data (S50) for the geographical region for the predetermined period of time (t.sub.1, t.sub.2) based on the precipitation data and the soil moisture difference data with a spatial resolution higher than the first spatial resolution.

A system for implementing a trial in one or more fields is provided. In an embodiment, a agricultural intelligence computing system receives field data for a plurality of agricultural fields. Based, at least in part, on the field data for the plurality of agricultural fields, the agricultural intelligence computing system identifies one or more target agricultural fields. The agricultural intelligence computing system sends, to a field manager computing device associated with the one or more target agricultural fields, a trial participation request. The server receives data indicating acceptance of the trial participation request from the field manager computing device. The server determines one or more locations on the one or more target agricultural fields for implementing a trial and sends data identifying the one or more locations to the field manager computing device.

The present invention relates to a method for treatment of an agricultural field, the method comprising the steps: 1) receiving (S10) a parametrization (10) for controlling a treatment device (200) by the treatment device (200) from a field manager system (100); 2) receiving (S20) from at least one soil sensor (400) real-time soil information on the real-world situation of the geographical location G1 in the agricultural field; 3) processing (S30) the real-time soil information to generate processed information (30), 4) determining (S40) a control signal (50) for controlling a treatment arrangement (270) of the treatment device (200) based on the received parametrization (10) and the processed information (30), 5) executing (S50) a treatment on the geographical location G2 in the agricultural field, wherein the treatment is executed based on the control signal (50) real-time after receiving the real-time soil information in such a way that the distance between location G1 and location G2 does not exceed 100 meters.

An agricultural monitoring system, the agricultural monitoring system comprising: an imaging sensor, configured and operable to acquire image data at submillimetric image resolution of parts of an agricultural area in which crops grow, when the imaging sensor is airborne; a communication module, configured and operable to transmit to an external system image data content which is based on the image data acquired by the airborne imaging sensor; and a connector operable to connect the imaging sensor and the communication module to an airborne platform.

Embodiments relate to a system that generates a crop yield component map for a field. The system determines amounts of nitrogen applied to each portion of the field by a set of nitrogen applicator farming machines. The system accesses crop yield data associated with a crop that was grown in the field. The crop yield data was generated by a set of harvester farming machines that travelled through the field and harvested plant parts of the crop. The system determines, by analyzing the crop yield data, plant part metrics for the harvested plant parts in each field portion. The system generates a crop yield component map that maps, for each field portion, a plant part metric associated with the field portion and an amount of nitrogen applied to the field portion. The component map may then be provided for display.

A methods for soil clod detection within a field is provided herein and can include receiving, with a computing system, data indicative of terrain variations within a region of an agricultural field. The region of the field is comprised of one or more adjacently positioned segments. The method can also include generating, with the computing system, a mean reference line. The method can further include calculating, with the computing system, a segment height for each of the one or more adjacently positioned segments. The method can also include determining, with the computing system, a presence of an object based on a deviation of one of the one or more segment heights being greater than a threshold height from the reference line.