The invention relates to an adjustable hoeing device (10) for removing weeds situated on a ground surface, the hoeing device (10) having a supporting frame (50), on which there is arranged at least one hoeing unit (100), which hoeing unit comprises the following:—at least one main bar (200) and at least two transverse bars (250) arranged parallel to one another, which transverse bars (250) are each mounted rotatably on the at least one main bar (200);—at least two connection bars (300), which run parallel to the at least one main bar (200) and which mechanically connect the at least two transverse bars (250) to one another;—at least two blades (500), wherein the blades (500) are arranged on the at least two transverse bars (250) at a normal distance from the main bar (200); and—at least one actuation device (400), which acts on at least two transverse bars (250) or a transverse bar (250) and the main bar (200) in order to rotate same by means of a linearly displaceable actuation arm.

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.

An agricultural method includes providing a positive air pressure chamber to prevent outside contaminants from entering the chamber; growing crops in a plurality of cells in the chamber, each cell having multi-grow benches or levels, each cell further having connectors to vertical hoists for vertical movements in the chamber; maintaining pre-set temperature, humidity, carbon dioxide, watering and lighting levels to achieve predetermined plant growth; using motorized transport rails to deliver benches for operations including seeding, harvesting, grow media recovery, and bench wash; dispensing seeds in the cell with a mechanical seeder coupled to the transport rails; growing the crops with computer controlled nutrients, light and air level; and harvesting the crops and delivering the harvested crop at a selected outlet of the chamber.

Novel, universal, in-field/in-orchard, well-controlled, scalable, easy-to-use, and cost-effective management systems and methods for artificial pollination of agricultural areas such as orchards and fields are provided.

A system for automatically determining a trip magnitude of a ground engaging tool of an agricultural implement includes a ground-engaging system having an attachment structure coupled to a frame of an agricultural implement, a ground-engaging tool rotatably coupled to the attachment structure at a joint, and a biasing element configured to bias the ground-engaging tool towards a predetermined ground-engaging position. The system further includes a trip sensor configured to generate data indicative of a magnitude of rotation of the ground-engaging tool, the trip sensor being at least partially received within the biasing element. Additionally, the system includes a computing system communicatively coupled to the trip sensor, the computing system being configured to determine the magnitude of rotation of the ground-engaging tool based at least in part on the data generated by the trip sensor.

Described herein are methods and systems for generating shared collaborative maps for planting or harvesting operations. A method of generating a collaborative shared map between machines includes generating a first map for a first machine based on a first set of data and generating a second map for a second machine based on a second set of data. The method further includes generating at least one shared collaborative map for at least one of the first and second machines based on the first and second maps.

An irrigation method for coastal regions. The method includes: selecting coastal region and collecting natural and environmental data of the coastal region; building a basic database of the coastal region based on high-precision map of the coastal region; establishing a water demand calculation model for coastal crops and a multi-source water supply model, where the multi-source water supply model includes a multi-source water of mixed salt-fresh water calculation model and a freshwater source calculation model; calculating water demand Q.sub.demand during a forecast period according to the water demand calculation model for coastal crops; clarifying salt content S.sub.limit of the water demand during the forecast period; calculating the water supply amount Q.sub.supply in the coastal region during the forecast period according to the multi-source water of mixed salt-fresh water calculation model; and comparing the Q.sub.demand and the Q.sub.supply to accordingly regulate irrigation operation.

A monitoring system and a monitoring method for a planter includes a computer having an unit speed fusion module, a seeding flow rate monitoring module, and a decision module for theoretical rotation speed of a drive motor, a rotation speed deviation inference module, a controlling parameter tuning module, an adjusting module for rotation speed of a seeding shaft, a controlling module for rotation speed of seeding shaft and a positioning signal receiver fixed on a top of a cab for receiving a geographic position signal. The system monitors operating state parameters of the planter and accurately controls seed amount.

Systems, devices, and methods for performing autonomous agricultural operations are described herein. An exemplary device may include a toolbar to which a plurality of implements may be interchangeably coupled, and a pair of parallel chassis beams mounted perpendicularly on the toolbar. At least a portion of each of the chassis beams may be telescopic and configured to be extended outward from, and retracted inward towards, the toolbar. The device may also include a plurality of drive assemblies each mounted on one of the chassis beams, and a plurality of motors corresponding to the drive assemblies and configured to drive the drive assemblies in accordance with one or more drive parameters to move the device throughout a site. The device may further include a computing device configured to automatically determine the drive parameters, and cause the plurality of motors to drive the corresponding drive assemblies in accordance with the drive parameters.

In an embodiment, a computer-implemented method for predicting subfield soil properties for an agricultural field comprises: receiving satellite remote sensing data that includes a plurality of images capturing imagery of an agricultural field in a plurality of optical domains; receiving a plurality of environmental characteristics for the agricultural field; generating a plurality of preprocessed images based on the plurality of satellite remote sensing data and the plurality of environmental characteristics; identifying, based on the plurality preprocessed images, a plurality of features of the agricultural field; generating a subfield soil property prediction for the agricultural field by executing one or more machine learning models on the plurality of features; transmitting the subfield soil property prediction to an agricultural computer system.