A farming machine moves through a field and performs one or more farming actions (e.g., treating one or more plants) in the field. Portions of the field may include moisture, such as puddles or mud patches. A control system associated with the farming machine may include a traversability model and/or a moisture model to help the farming machine operate in the field with the moisture. In particular, the control system may employ the traversability model to reduce the likelihood of the farming machine attempting to traverse an untraversable portion of the field, and the control system may employ the moisture model to reduce the likelihood of the farming machine performing an action that will damage a portion of the field.

In order to predict plant stresses at a localized level, data feeds from many sensor types can be fused and analyzed to create a synthetic sensor estimating plant water stress, predicting microclimatic conditions, and performing localized plant disease and pest modeling. To make this affordable, an array of low-cost, lower precision sensors can be used. Sensor fusion is used to improve the accuracy of each sensing element by using machine learning to fuse data from the other sensing elements in the array. Additionally, machine learning can create a “synthetic sensor” replicating the output of high-cost and maintenance intensive sensing devices by using machine learning to replicate their output.

A soil measure, such as a soil cone index, and a vehicle index indicating the amount of force the vehicle exerts on the ground as it travels over the ground, are obtained and compared to identify a soil damage score. The soil damage score can be mapped over a field and an agricultural vehicle can be controlled based upon the soil damage score.

A soil measure, such as a soil cone index, and a vehicle index indicating the amount of force the vehicle exerts on the ground as it travels over the ground, are obtained and compared to identify a soil damage score. The soil damage score can be mapped over a field and an agricultural vehicle can be controlled based upon the soil damage score. In another example, a detector detects a fill level of a material storage compartment on an agricultural vehicle. The inflation pressure of tires on the agricultural vehicle is controlled based upon the detected fill level.

There are provided an optical probe and method for analysing a soil located in an underground area. The optical probe includes a probe head insertable into the underground area to contact the soil, the probe head including a waveguide having opposite first and second ends both optically shielded from the soil; a light source configured to generate a multiwavelength interrogating beam and optically coupled to the first end of the waveguide so that the multiwavelength interrogation beam is inputted in the waveguide to propagate towards the second end; and a detector optically coupled to the second end of the waveguide to detect said multiwavelength interrogation beam. The waveguide includes an unshielded interaction zone extending between the first and second ends providing a wavelength-dependent attenuation of the multiwavelength interrogation beam through interaction with the soil.

The invention relates to an isotopic identification method making 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. The invention also relates to a method which makes it possible to impose a unique code on the animals of a farm or on the plants of a farm, a computer making it possible to store the unique codes generated in memory, to generate unique codes for new farms and to perform comparisons.

The invention includes a device for determining the moisture or conductivity of a medium in a container. A measurement probe is plunged into the medium and consists of a conductive material, a conductive rod, and a first feed-through component designed such that the conductive rod can be fastened to an electrically conductive wall or holder. A rod of a non-conductive material and a second feed-through component are provided, where the non-conductive rod can be fastened to the wall, the conductive rod and the non-conductive rod are dimensioned and oriented that the measurement probe is oriented parallel to the longitudinal axis of the container and a signal-processing unit designed such that high-frequency measurement signals are conducted via the measurement line to the measurement probe and that the moisture or the conductivity of the medium is determined by means of a TDR method.

A system and method for visualizing one or more crop response surfaces. The system includes a geospatial database associated with a crop prediction engine. The geospatial database receives soil composition information for plots of land. The crop prediction engine identifies covariates from the soil composition information, which has a feature matrix. The crop prediction engine generates a multi-dimensional covariate training data set from the covariates. The crop prediction engine then applies the multi-dimensional covariate training data set to a machine learning training model to generate at least one predictive crop-yield predictive model. The crop prediction engine ranks covariates having feature set interactions. Subsequently, the crop prediction engine determines a dominant crop-yield feature set interaction from the ranked covariates having feature set interactions. The crop prediction engine generates a crop response surface from the dominant crop-yield feature set interaction. The crop prediction engine then visualizes the crop response surface.

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.

An agricultural implement wear monitoring system that monitors a first component of an agricultural implement. A sensor detects and emits a signal indicative of a first geometric dimension of the first component and/or a second geometric dimension of the first component relative to a second component. A controller couples to the sensor. The controller monitors the first geometric dimension and/or the second geometric dimension, and in response to a detected change in the first geometric dimension and/or the second geometric dimension determines a remaining service life of the first component.