The disclosure relates to a method for processing plants in a field in which a specific type of crop is planted, said method having the following steps: selecting a processing tool for processing plants; acquiring an image of the field, the image being correlated with position information; determining a position of a plant to be processed in the field using a neural network into which the acquired image is input, the neural network having a plurality of heads and in particular one of the heads being evaluated according to the processing tool and/or the type of crop grown; guiding the processing tool to the position of the plants; and processing the plants using the processing tool.

The present disclosure relates to a method for adjusting a working depth of a plough implement, the plough implement comprising a plurality of ground engaging tools for penetrating and moving soil and a depth adjustment apparatus configured to adjust a working depth of at least one of the ground engaging tools, wherein the method comprises receiving control-data indicative of at least one of an operation the plough implement or a field condition of a field across which the plough implement is moved; and automatically controlling an operation of the depth adjustment apparatus in a manner that adjusts a working depth of the at least one ground engaging tool on the basis of the control-data received.

A method and system provide the ability to manage an orchard. Sensor data that represents a first state of the orchard is captured via one or more sensors. The sensor data is captured as the one or more sensors are traveling through the orchard. An almanac is maintained. The almanac provides a state library of sequential states of a representative orchard and a task library for one or more tasks to be performed to transition between the sequential states. A task manager queries the almanac to identify a first task of the one or more tasks and allocates the first task to one or more robots that perform the first task.

A planting system includes a seed flow controller coupled to a hopper and a spreader. The seed flow controller, hopper, and spreader are transported by an unmanned aerial vehicle to spread the seeds over a geography. The seed flow controller includes several rollers having apposed outer surfaces. The rollers also include fins that extend about respective roller axes such that the fins cross at discrete contact points as the rollers rotate. The interfacing rollers break up clumps of seed material stored in the hopper and controllably convey the seed material from the hopper to the spreader. The spreader has a spinning spreader plate that flings the seed material laterally outward to spread the seed material over the ground.

A monitoring system for an agricultural sprayer includes spray nozzles, spray monitoring sensors, electromagnetic sensors, and control circuitry in electronic communication with the electromagnetic sensors. Each spray nozzle is configured to spray a fluid. Each spray monitoring sensor is disposed adjacent to a corresponding one of the spray nozzles and is configured to measure a spray parameter of that spray nozzle. The electromagnetic sensors are configured to generate signals when the electromagnetic sensors sense a magnetic field. Each electromagnetic sensor is disposed adjacent to and each of is representative of one of the spray monitoring sensors. The control circuitry is configured to receive the signals from the electromagnetic sensors in a received signal order and assign physical locations to the spray monitoring sensors based on the sequential communication order and a predetermined sequential order. Related methods and systems are also disclosed.

A method of monitoring agricultural spray performance includes spraying a fluid from spray nozzles, sensing spray parameters (e.g., droplet size, a flow rate, an application density, or a pressure of the fluid) for the spray nozzles, receiving the spray parameters, generating an average spray parameter value, determining a minimum spray parameter value and a maximum spray parameter value, and displaying the average, minimum, and maximum spray parameter values. Other methods include spraying a fluid from a spray nozzle, sensing a spray parameter for the spray nozzle, detecting that the spray parameter has exceeded a pre-defined threshold value, displaying an alarm, and ceasing spraying the fluid from the spray nozzle. A user interface continues to display the alarm after the act of ceasing spraying the fluid. Related systems and other methods are also disclosed.

An agricultural harvesting machine includes crop processing functionality configured to engage crop in a field, perform a crop processing operation on the crop, and move the processed crop to a harvested crop repository, and a control system configured to identify a weed seed area indicating presence of weed seeds, and generate a control signal associated with a pre-emergence weed seed treatment operation based on the identified weed seed area.

Described herein are systems and methods for agricultural data analysis. In one embodiment, a computer system for monitoring field operations includes a database for storing agricultural data including yield and field data and at least one processing unit that is coupled to the database. The at least one processing unit is configured to execute instructions to monitor field operations, to store agricultural data, to automatically determine whether at least one correlation between different variables or parameters of the agricultural data exceeds a threshold, and to perform analysis of the agricultural data to identify a category of man-made issues or other issues that have potentially caused the correlation when at least one correlation occurs between different variables or parameters of the agricultural data.

Described herein are implements and applicators for placement of fluid applications with respect to agricultural plants of agricultural fields. In one embodiment, a fluid applicator includes at least one applicator arm, a first nozzle disposed to apply fluid to a rhizosphere of the plants, and a second nozzle disposed to apply fluid between the row of plants.

Techniques are provided for generating a set of target hybrid seeds with optimal yield and risk performance, including a server receiving a candidate set of hybrid seeds along with probability of successful yield values, associated historical agricultural data and property information, and selecting a subset of the hybrid seeds that have probability of success values greater than a filtering threshold. The server generates representative yield values for hybrid seeds based on the historical agricultural data and risk values for each hybrid seed. The server generates a dataset of target hybrid seeds for planting based on the risk values, the yield values, and the properties for the target fields. The dataset of target hybrid seeds includes target hybrid seeds that meet a specific threshold for a range of risk values. The server causes display of the dataset of target hybrid seeds including yield values and risk values for the target fields.