The present disclosure describes a system, method, and non-transitory computer readable medium for analyzing soil samples. Accordingly, soil sample units may be obtained and provided to a server that generates raw data. The raw data is subsequently organized into a sub-report for each nutrient or variable contained in the raw data. An average for each nutrient in the raw data and a number of additional factors related to the raw data may be calculated. The average and additional factors are used to determine bulk recommendations by comparing target data to an exchangeable measured value. Additionally, the factors are also used to determine challenges and solutions by comparing the average data to the target data for each nutrient. The system compares the raw data to the measured values an mathematically adjusts the compared values to compute an optimal treatment algorithm.

An environment information collecting system collects environment information on a surface of the earth or a surface layer of the earth. The environment information collecting system includes a sensor element which is scattered in a target region where the environment information is collected, of which at least one of reflection properties, transmission properties, absorption properties, or luminescence properties with respective to an electromagnetic wave with a specific wavelength, or light emitting properties changes in accordance with an environment, and an aircraft configured to receive the electromagnetic wave obtained from the sensor element and configured to collect the environment information in the target region.

A vegetative health mapping system which creates two- or three-dimensional maps and associates moisture content, soil density, ambient light, surface temperature, and/or additional indications of vegetative health with the map. Moisture content is inferred using radar return signals of near-field and/or far-field radar. By tuning various parameters of the one or more radar (e.g. frequency, focus, power), additional data may be associated with the map from subterranean features (such as rocks, soil density, sprinklers, etc.). Additional sensors (camera(s), lidar, IMU, GPS, etc.) may be fused with radar returns to generate maps having associated moisture content, surface temperature, ambient light levels, additional indications of vegetative health (as may be determined by machine learned algorithms), etc. Such vegetative health maps may be provided to a user who, in turn, may indicate additional areas for the vegetative health device to scan or otherwise used to recommend and/or perform treatments.

A method of using an unmanned agricultural robot to generate an anticipatory geospatial data map of the positions of annual crop rows planted within a perimeter of an agricultural field, the method including the step of creating a geospatial data map of an agricultural field by plotting actual annual crop row positions in a portion of the geospatial data map that corresponds to a starting point observation window, and filling in a remainder of the geospatial data map with anticipated annual crop row positions corresponding to the annual crop rows outside of the starting point observation window, and refining the geospatial data map by replacing the anticipated annual crop row positions with measured actual annual crop row positions when an unexpected obstacle is encountered.

Various methods and systems are provided for monitoring and control of soil conditions. In one example, among others, a method includes obtaining one or more aqueous sample from at least one suction probe within a soil substrate and analyzing the one or more aqueous sample to determine a chemical composition of the soil substrate. Amounts of an additive may be determined to adjust the chemical composition of the soil substrate. In another example, a method includes installing at least one suction probe within a soil substrate; drawing a vacuum to induce hydraulic conduction of at least one aqueous solution from the soil substrate; extracting one or more aqueous sample; and analyzing the one or more aqueous sample to determine a chemical composition.

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.

The present invention relates to methods and vehicles for separately applying a solid fertilizer and a liquid fertilizer additive to a working area of a field.

A system and method for evaluating soil characteristics. The system and method includes providing one or more soil test kits to a user. The soil tests kits may include ion-exchange resins and may instruct the user to collect a soil sample from his/her growing area, to combine the soil sample with the ion-exchange resins, and to provide the combination to the system for analysis. Other test kits may not include ion-exchange resins and may instruct the user to provide a soil sample from his/her growing area to the system for analysis. The system evaluates the ion-exchange resins and/or the soil samples to identify nutrient levels, pH levels, and other characteristics of the soil. Using the evaluation results, the system provides feedback, recommendations and/or products to the user to improve the soil conditions and to ensure a successful crop, yield, quality, and nutrient density. The system and method also may include providing a second soil test kit to the user at a predetermined time after the first, to evaluate a second soil sample, and to compare the second evaluation results with the first to assess the improvement of the soil conditions.

A trailer mounted soil sampler including one or more soil sampling assemblies mounted thereon. Each of the soil sampler assemblies being selectively pivotally movable between horizontally disposed and vertically disposed positions. Each of the soil sampling assemblies includes an elongated hollow soil probe which is driven into the ground to collect a soil sample therein. The soil sampler includes a soil cleaning and oiler mechanism. The soil sampler also includes a trash cleaner for cleaning trash from the area where the soil probe is to be driven into the ground. Further, the soil sampler includes a soil sample collection apparatus for collecting the soil samples in bags.

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.