In an agricultural field having first regions with current soil test values known from actual tests and second regions having unknown soil test values, nutrient levels are predicted using a soil test model which defines a statistical relationship between (i) nutrient levels for a given region of a training field for a given season and (ii) field specific characteristics for the given region in a previous growing season and nutrient levels in the given region or proximate regions from the given growing season. Acquired known field specific characteristics and current soil test values from the first regions are then applied to the soil test model to calculate the predicted nutrient level the second regions. This can reduce the cost of soil sampling by using actual soil test results from one management zone as a predictor when modeling other zones' properties.

An isotopic identification method is provide that makes it possible, where appropriate, to link a livestock animal or animal product to a specific farm, or a plant or a plant product to a farm, by analyzing the concentration of ratios or stable isotopes, and comparing with isotopic codes previously generated in a unique fashion for a set of frames. A method is also provided that makes it possible to impose a unique code on the animals of a farm or on the plants of a farm, and a computer making it possible to store the unique codes generated in memory is provided to generate unique codes for new farms and to perform comparisons.

Implementations generally relate to a system for sequestering carbon. In some implementations, a system includes a carbon source, where the carbon source causes soil chemical reactions that enhance nutrient uptake of at least one plant and that increase above and below ground biomass production, and where the carbon source further increases carbon sequestration in soil surrounding roots of the at least one plant. The system also includes a membrane structure configured to expose the roots of the at least one plant to the carbon source.

A solution for evaluating a medium using electrical signals is described. A plurality of electrical signals having different frequencies are transmitted through the medium and signal data corresponding to the electrical signals after having traveled through the medium is acquired. A complex impedance and a complex permittivity and/or complex conductivity can be calculated for the medium. A set of characteristics of the medium can be computed using mixing models and/or known information of the medium. A level of one or more attributes of the medium can be determined from the characteristics using nonparametric Bayesian inference. One particular application is directed to determining a nitrate level of soil.

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 batteryless, chipless, sensor is disclosed which includes a substrate, at least two conductive strips disposed on the substrate, a passivation layer encasing the substrate and the at least two conductive strips, wherein the conductive strips are adapted to respond to an interrogation signal from a reader having a first polarization, with a response signal at a second polarization different than the first polarization.

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.

Systems and methods for providing irrigation water to a soil depth of a crop rootzone in a plurality of crop fields using a sensor network and soil moisture modeling are provided. In various embodiments methods include receiving data from a sensor network in a first crop field and determining a soil moisture model using data from the sensor network in the first field. Various embodiments further include determining a first field irrigation time using the soil moisture model, the first field irrigation time providing irrigation water to a soil depth of the crop rootzone above a Wilting Point (WP) and below a Field Capacity (FC) of soil in the first field, and applying the soil moisture model to a second field.

Described herein is environmental sensors, sensor units, sensor systems and/or sensing methods. In particular, an agricultural or horticultural environment multi-sensor unit comprising a plurality of environmental sensors, including at least: an incident light sensor, a temperature sensor, a carbon dioxide sensor and a relative humidity sensor. The sensor unit may also comprise a wireless communication interface, the multi-sensor unit being configured to transmit data from the environmental sensors via the wireless communications interface.