A planting system (100) for arrangement on a vehicle (110) comprises at least one plant arm (130) comprising a plant head (140) configured to penetrate ground and a plant feeding device (120) configured to feed plant seedlings (125) to the plant arm by dropping the plant seedlings from the plant feeding device. The plant arm comprises at least one articulation (180) and is configured to receive plant seedlings (125) and to guide the plant seedlings to the plant head. The planting system is configured to operate the plant arm by penetrating the ground and release the plant seedlings from the plant head into the ground while the plant system (100) is in motion and the plant head has a fixed position relative the ground. The plant seedlings fall from the plant feeding device (120) to the plant head (140) while the plant arm (130) is in motion.

A method of improving agricultural treatment includes identifying a mineralogical feature based on a collected soil sample, generating a soil clay characterization based on the mineralogical feature, and generating an agricultural prescription. A system includes a processor and a memory storing instructions that, when executed by the processor, cause the system to identify a mineralogical feature based on a collected soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription. A non-transitory computer readable medium containing program instructions that, when executed, cause a computer to identify a mineralogical feature based on a soil sample, generate a soil clay characterization based on the mineralogical feature, and generate an agricultural prescription.

A ponding monitoring and detection system monitors, detects, and predicts ponding in an irrigated field in essentially real-time. The ponding monitoring and detection system also monitors and records locations of detected and predicted ponding.

In one aspect, a system for determining subsurface soil layer characteristics as an agricultural implement is towed across a field by a work vehicle may include a RADAR sensor configured to capture data indicative of a subsurface soil layer characteristic of the field. Furthermore, the system may include a load sensor configured to capture data indicative of a load applied to the agricultural implement by soil within the field, with the load being indicative of the subsurface soil layer characteristic. Additionally, a controller of the system may be configured to determine a first value of the subsurface soil layer characteristic based on the data received from the RADAR and a second value of the subsurface soil layer characteristic based on the data received from the load sensor. Moreover, the controller may be configured to determine a differential between the first value and the second value.

This invention shows a system and method for phenotype characterization of agricultural crops, comprising at least one support device which can be reconfigured in an autonomous or controlled remote manner. It includes a central embedded microcontroller connected to atmospheric sensors located in the upper body, a microcontroller connected to a multi-spectral camera located at the distal end of the arm. The central microcontroller is connected to a base microcontroller that receives signals from soil sensors. A solar panel provides the energy source to a regulating unit that powers the microcontrollers. The system contains a communication unit that includes a router wirelessly connected to Internet.

A soil or plant analysis apparatus to perform low and high frequency measurements is described herein. In one embodiment, the soil analysis apparatus comprises a first sub-system to perform low frequency soil measurements and a second sub-system to perform high frequency soil measurements. The high frequency measurements of the second sub-system are at least 1.25 times the low frequency measurements of the first sub-system.

Methods, apparatus, systems, and articles of manufacture to select track paths for one or more vehicles in a field are disclosed. An example apparatus includes input interface circuitry to obtain a request for a first track path for a first vehicle, path instruction generation circuitry to, in response to the request, obtain information defining a plurality of track paths in a field, and select, based on the request, the first track path from the plurality of track paths, and update circuitry to update the information to indicate that the first track path is claimed by the first vehicle.

Systems, methods, and storage mediums storing methods of natural capital measurement are described. A region of influence for the area whose natural capital is to be measured is determined and segmented into a plurality of segments. A land assessment model, including a system dynamics model and a spatially explicit model, is generated for the region of influence by training one or more machine learning algorithms to classify land use categories for the segments and to determine statistical relationships between state variables and properties of the segment. A flow sequence for simulating a transport of materials between the plurality of segments is executed to update the land assessment model. Health indicators for the natural capital of the area are generated using the updated land assessment model.

An agricultural harvester includes a frame configured to support a crop processing system and a sensor supported on the frame, with the sensor configured to capture data indicative of one or more subsurface soil layers present within the field across which the agricultural harvester is traveling. Furthermore, the agricultural harvester includes a computing system communicatively coupled to the sensor. The computing system is configured to identify the one or more subsurface soil layers within the field based on the data captured by the sensor and generate a tillage prescription map for use during a subsequent tillage operation based on the identified one or more subsurface soil layers. The tillage prescription map, in turn, prescribes a penetration depth for a tillage tool at a plurality of locations within the field.

Implementations are disclosed for automatic commissioning, configuring, calibrating, and/or coordinating sensor-equipped modular edge computing devices that are mountable on agricultural vehicles. In various implementations, neighbor modular edge computing device(s) that are mounted on a vehicle nearest a given modular edge computing device may be detected based on sensor signal(s) generated by contactless sensor(s) of the given modular edge computing device. Based on the detected neighbor modular edge computing device(s), an ordinal position of the given modular edge computing device may be determined relative to a plurality of modular edge computing devices mounted on the agricultural vehicle. Based on the sensor signal(s), distance(s) to the neighbor modular edge computing device(s) may be determined. Extrinsic parameters of the given modular edge computing device may be determined based on the ordinal position of the given modular edge computing device and the distance(s).