An agricultural distribution machine for spreading liquid and/or solid plant protection products by means of a distribution apparatus which is height-adjustably arranged on a frame of the distribution machine having a plurality of nozzle holders with spray nozzles mounted thereon arranged spaced apart from each other for the purpose of distributing the plant protection product to be spread. Activation of the distribution apparatus is carried out based on at 10 least two spray profiles stored in a computer unit, each spray profile composed of a plurality of parameters. In order to achieve a consistent distribution quality of the plant protection product, different spray profiles can be stored in a computer unit and, in the instance of a deviation of the parameters of a spray profile, an automated activation of the distribution machine or of the distribution 15 apparatus to the parameters of a second spray profile is carried out.

A farming system includes a field engagement unit. The field engagement unit includes a support assembly. The support assembly includes one or more work tool rail assemblies. The field engagement unit additionally includes one or more propulsion units which provide omnidirectional control of the field engagement unit. The field engagement unit additionally includes one or more work tool assemblies. The one or more work tool assemblies are actuatable along the one or more work tool rail assemblies. The farming system additionally includes a local controller. The local controller includes one or more processors configured to execute a set of program instructions stored in memory. The program instructions are configured to cause the one or more processors to control one or more components of the field engagement unit.

Subfield moisture model improvement in generating overland flow modeling using shallow water calculations and kinematic wave calculations is disclosed. In an embodiment, a computer-implemented data processing method comprises: receiving precipitation data and infiltration data for an agricultural field; obtaining surface water depth data, surface water velocity data, and surface water discharge data for the same agricultural field; determining subfield geometry data for the agricultural field; executing a plurality of water calculations and wave calculations using the subfield geometry data to generate an overland flow model that includes moisture levels for the agricultural field; based on, at least in part, the overland flow model, generating and causing displaying a visual graphical image of the agricultural field comprising a plurality of color pixels having color values corresponding to the moisture levels determined for the agricultural field. Output of the overland flow model is provided to control computers of seeders, planters, fertilizer spreaders, harvesters, or combines to control seeding, planting, fertilizing or irrigation activities in the field.

Apparatuses, systems, and techniques to generate one or more confidence values associated with one or more objects identified by one or more neural networks. In at least one embodiment, one or more confidence values associated with one or more objects identified by one or more neural networks are generated based on, for example, one or more neural network outputs.

The present disclosure provides jewelry that can instruct farmers on methods for planting a variety of crops in standard conditions and in drought conditions. The utilization of the described jewelry will enable small-scale producers to more efficiently and sustainably grow food. The jewelry taught herein can also be utilized to spread awareness about global hunger.

Display of graphical maps of agricultural fields, coded with color or other indicators of values of data pertaining to agronomy at high resolution, and updated on a daily basis or on demand by recalculating agronomy models with the high-resolution data, is disclosed. Map displays may include multiple layers that relate to different agronomy metrics, and GUI widgets that are programmed to receive selection of values indicating different field properties or layers to display. In an embodiment, a computer-implemented data processing method providing an improvement in efficient calculation of digital data representing physical properties of agricultural fields, the method comprising receiving digital input specifying a request to display a map image of a specified agricultural field for a particular day; in response to receiving the input, calculating an interpolated digital image of the specified agricultural field with a plurality of different field properties, by: dividing a digital map of the specified field into a plurality of grids each having a same size and a same area; obtaining, from digital storage, a plurality of data for the different field properties and assigning the data as covariates; grouping the grids into a specified number of clusters based on values of the covariates; pseudo-randomly selecting a specified number of one or more sample values in each of the clusters; evaluating a digital fertility model using the sample values and storing a plurality of output values from the digital fertility model; interpolating a plurality of model values for the grids; generating and causing displaying a visual graphical image of the specified agricultural field including color pixels corresponding to each of the model values.

Provided is a method for planting a mixed forest of yew trees and fig trees. Yew trees and fig trees are interplanted based on characteristics of yew trees and fig trees. A seedling bed method is used in the plain zones, and a terrace field method is used in mountain zones in order to improve land utilization rate and make full use of complementary advantages of ecological niches. In the present disclosure, ground and underground spaces on tree growing site are fully used. Fig trees grow fast and have large leaves, thus shading part of sunlight for yew trees and savings costs required for building shade shelters for yew trees. By using the method for constructing a mixed forest in the present disclosure, the constructed mixed forest not only allows for increase of biomass, but also provides higher paclitaxel content in yew trees than that in pure forest.

A soil analysis system is provided for an agricultural vehicle and includes a sensor apparatus, a controller, and a display device. The sensor apparatus includes a location sensor configured to determine a location of the agricultural vehicle; and an infrared sensor configured to collect infrared spectra from soil at the location. The controller is configured to determine a soil type based on the location; select at least one nutrient calibration curve based on the soil type at the location; analyze the infrared spectra according to the at least one nutrient calibration curve to generate at least one estimated nutrient value for the soil at the location; and generate display commands representing the at least one estimated nutrient value. The display device is configured to generate a first display representing the at least one estimated nutrient value based on the display commands.

A method for adjusting operating parameters of an agricultural implement during a product-dispensing operation may include monitoring a location of the agricultural implement while performing a product-dispensing pass across a field. The method may further include determining that the agricultural implement will encounter an operating parameter boundary prescribing a change in an operating parameter of the agricultural implement. Moreover, the method may include determining a transition boundary along the product-dispensing pass based at least in part on a propagation delay for the prescribed change, where the agricultural implement will cross the transition boundary before the operating parameter boundary. Additionally, the method may include initiating the change in the operating parameter when the agricultural implement reaches the transition boundary such that the prescribed change in the operating parameter is complete when the agricultural implement reaches the operating parameter boundary.

A method including: recording a first image of a first field region; automatically treating a plant within the first region in-situ based on the first image; automatically verifying the plant treatment with a second image of the first region; and automatically treating a second region concurrently with treatment verification.