An automated computer-controlled sampling system and related methods for collecting, processing, and analyzing agricultural samples for various chemical properties such as plant available nutrients. The sampling system allows multiple samples to be processed and analyzed for different analytes or chemical properties in a simultaneous concurrent or semi-concurrent manner. Advantageously, the system can process soil samples in the “as collected” condition without drying or grinding. The system generally includes a sample preparation sub-system which receives soil samples collected by a probe collection sub-system and produces a slurry (i.e. mixture of soil, vegetation, and/or manure and water), and a chemical analysis sub-system which processes the prepared slurry samples for quantifying multiple analytes and/or chemical properties of the sample. The sample preparation and chemical analysis sub-systems can be used to analyze soil, vegetation, and/or manure samples. A soil collection system is disclosed which captures and directs samples to the sampling system for processing.

Apparatus, system, and method are provided herein for causing and controlling the injection of fertilizer into an irrigation of an irrigation system. The fertigation system comprises a fertigation supply unit including at least one storage container containing at least one of a fertilizer component, a herbicide, and an insecticide coupled to a irrigation of the irrigation system. A fertigation control unit is coupled to the fertigation supply unit. The fertigation control unit is configured to cause the fertigation supply unit to inject at least some of the fertilizer component, herbicide, and/or insecticide into the irrigation. The fertigation control unit can cause the fertigation supply unit to inject the fertilizer component, herbicide, and/or insecticide in response to at least air temperature data and/or soil temperature data received from a sensor unit, or in response to user input at the fertigation control unit.

An automated farming system includes a frame. The frame includes a fixed base, a beam, and a support. A farming implement support extends from the beam and moves up and down in relation to the beam. The farming implement support moves along a length of the beam. The movable support includes a propulsion system and is configured to rotate around the fixed base. Movement of the farming implement support and the movable support allows for high density planting of crops in hexagonal patterns and/or a continuous spiral pattern.

Various embodiments relate generally to computer vision and automation to autonomously identify and deliver for application a treatment to an object among other objects, data science and data analysis, including machine learning, deep learning, and other disciplines of computer-based artificial intelligence to facilitate identification and treatment of objects, and robotics and mobility technologies to navigate a delivery system, more specifically, to an agricultural delivery system configured to identify and apply, for example, an agricultural treatment to an identified agricultural object. In some examples, a method may include, receiving data representing a policy specifying a type of action for an agricultural object, selecting an emitter with which to perform a type of action for the agricultural object as one of one or more classified subsets, and configuring the agricultural projectile delivery system to activate an emitter to propel an agricultural projectile to intercept the agricultural object.

In an embodiment, agricultural intelligence computer system stores a digital model of nutrient content in soil which includes a plurality of values and expressions that define transformations of or relationships between the values and produce estimates of nutrient content values in soil. The agricultural intelligence computer receives nutrient content measurement values for a particular field at a particular time. The agricultural intelligence computer system uses the digital model of nutrient content to compute a nutrient content value for the particular field at the particular time. The agricultural intelligence computer system identifies a modeling uncertainty corresponding to the computed nutrient content value and a measurement uncertainty corresponding to the received measurement values. Based on the identified uncertainties, the modeled nutrient content value, and the received measurement values, the agricultural intelligence computer system computes an assimilated nutrient content value.

Engineered food to promote health and maintain homeostasis in a subject and methods of producing the food.

Some example embodiments may provide a capability for intelligent control or management of a number of assets in connection with yard maintenance with the assistance or inclusion of a management unit having distributed properties. Thus, for example, sensor equipment and task performance equipment operation may be coordinated between local management and remote management entities for efficient monitoring and maintaining of lawn wellness.

In one aspect, a crop input applicator is provided. In one aspect, the applicator comprises a valve (e.g., voice coil valve) disposed to deposit liquid on or near a seed furrow and/or on or near a seed. In one aspect, the applicator includes one or more seed sensors disposed to detect passage of seeds.

An agricultural material application management system includes an automated agricultural data collection vehicle including a location sensor. The automated agricultural data collection vehicle includes a receiver that receives sensor data including crop information, a memory that stores the plurality of locations and the sensor data, and a processor that generates a mapping correlating the crop information with the plurality of locations in the agricultural area, and generates an agricultural material application recommendation for each of the plurality of locations based on the mapping. The agricultural material application management system includes an agricultural vehicle including an interface unit that interfaces with the automated agricultural data collection vehicle and receives the agricultural material application recommendations from the agricultural data collection vehicle. An agricultural material applicator applies an agricultural material to at least some of the plurality of locations, and a display provides the recommendations to a driver of the agricultural vehicle.

A soil mapping system for collecting and mapping soil reflectance data in a field includes an implement having a furrow opener for creating a furrow and an optical module. The optical module is arranged to collect soil reflectance data at a predetermined depth within the furrow as the implement traverses a field. The optical module includes two monochromatic light sources, a window arranged to press against the soil, and a photodiode for receiving light reflected back from the soil through the window. The two light sources have different wavelengths and are modulated at different frequencies. The photodiode provides a modulated voltage output signal that contains reflectance data from both of the light sources. Additional measurement devices are carried by the implement for collecting additional soil property data, such as electrical conductivity, pH, and elevation, which can be used together with the optical data to determine variations in soil organic matter.