Abstract: The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

Abstract: The present invention provides a system, method and apparatus for providing variable rate application of applicants to discrete field locations. According to a first preferred embodiment, the present invention includes a control device having software modules to allow for the execution of irrigation and chemical spray patterns according to specific prescriptions for each crop being sprayed. According to further preferred embodiments, the control device may use data from a variety of image sensors to create a selective, variable rate application of applicants. Using the imaging data, the system of the present invention may use a primary applicant system to broadly deliver a first selected application (e.g. water or the like) and use a separate system to deliver targeted applicants for specific plants or areas of a given field.

Abstract: The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

Abstract: The present invention provides a system, method and apparatus for providing variable rate application of applicants to discrete field locations. According to a first preferred embodiment, the present invention includes a control device having software modules to allow for the execution of irrigation and chemical spray patterns according to specific prescriptions for each crop being sprayed. According to further preferred embodiments, the control device may use data from a variety of image sensors to create a selective, variable rate application of applicants. Using the imaging data, the system of the present invention may use a primary applicant system to broadly deliver a first selected application (e.g. water or the like) and use a separate system to deliver targeted applicants for specific plants or areas of a given field.

Abstract: The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

Abstract: A system and method for determining specific prescriptions for targeted areas/plants within given irrigation areas. According to preferred embodiments, the system may use imaging data in combination with other sensors and analysis modules to identify selected pests and diseases affecting given crops. Preferably, the system may use machine learning/AI modules to analyze the data and to provide targeted prescriptions for targeted groups of identified crops based on identified conditions of infestation and/or disease within the identified crops.

Abstract: The present invention provides a system and method which includes a machine learning module which analyzes data collected from one or more sources such as UAVs, satellites, span mounted crop sensors, direct soil sensors and climate sensors. According to a further preferred embodiment, the machine learning module preferably creates sets of field objects from within a given field and uses the received data to create a predictive model for each defined field object based on detected characteristics from each field object within the field.

Abstract: The present invention provides an irrigation system that includes a control system for determining whether to apply an applicant to an agricultural field. In an implementation, the control system includes memory operable to store one or more modules and a processor coupled to the memory. The processor is operable to execute the one or more modules to cause the processor to receive one or more signals representing a microbe characteristic from a soil sensor. The processor is also operable to determine whether to apply an applicant (i.e., water having a concentration of a biological or a microbe therein) to a soil based upon the microbe characteristics and to initiate operation of the irrigation assembly to apply the applicant to the soil in response when the soil requires the applicant.

Abstract: The present invention provides a system, method and apparatus for providing an irrigation scheduling module including a graphical user interface for providing irrigation scheduling data for a given field location. According to a preferred embodiment, the irrigation scheduling module is configured to calculate and display an irrigation recommendation for a given set of forecast data. According to a further preferred embodiment, the irrigation recommendation includes a representative shape in the form of a circle which changes from a full circle to a crescent-shaped percentage of the full circle based on the field moisture status.

Abstract: The present invention provides a system, method and apparatus for spraying the leaf and root areas of plants. According to an exemplary preferred embodiment, the present invention provides a foliar chemical application package which is designed specifically to deliver a chemical solution to the leaf area of plants in which the chemical will primary enter the plant through the foliar area rather than the root zone. According to a further preferred embodiment, the present invention teaches a system, method and apparatus for providing a specialized foliage spraying application in which water supply lines and chemical supply lines are individually controlled so that applicants, such as different chemicals received from different chemical tanks, may be simultaneously applied to a given crop.

Abstract: The present invention provides a system, method and apparatus for providing an irrigation scheduling module including a graphical user interface for providing irrigation scheduling data for a given field location. According to a preferred embodiment, the irrigation scheduling module is configured to calculate and display an irrigation recommendation for a given set of forecast data. According to a further preferred embodiment, the irrigation recommendation includes a representative shape in the form of a circle which changes from a full circle to a crescent-shaped percentage of the full circle based on the field moisture status.

Abstract: The present invention provides a system for combining the use of near real-time and/or real-time data acquired from an array of single purpose or integrated sensors mounted on a mechanized irrigation machine. According to a preferred embodiment, the integrated sensor of the present invention preferably provides for the collection of a variety data. According to a further preferred embodiment, the integrated sensor suite of the present invention may preferably include internally mounted sensors within a common housing which preferably includes a spectrometer, a radiometer and sensors to measure temperature, rainfall, relative humidity and barometric pressure. According to a further preferred embodiment, the number of integrated sensors mounted on a mechanized irrigation machine may preferably be determined based on a detected number of management zones and/or a detected location.

Abstract: To address the shortcomings presented in the prior art, the present invention provides a system and method to provide improved irrigation management through the detection of fast neutrons. According to a preferred embodiment, the fast neutron detector of the present invention includes a 4-He based noble gas detector, a power source, a signal processing circuit, and a resistor in series with a preamplifier and a shaping amplifier to produce a processed signal. According to a further preferred embodiment, the present invention preferably further includes a signal channel analyzer and a pulse counter/rate meter. According to a further preferred embodiment, the present invention includes a controller which receives a count of detected fast neutrons and translates the detected number of fast neutrons into an irrigation map indicating the required levels of irrigation needed for selected areas of a given field based on the detected moisture levels.

Abstract: The present invention provides a system, method and apparatus for providing variable rate application of applicants to discrete field locations. According to a first preferred embodiment, the present invention includes a control device having software modules to allow for the execution of irrigation and chemical spray patterns according to specific prescriptions for each crop being sprayed. According to further preferred embodiments, the control device may use data from a variety of image sensors to create a selective, variable rate application of applicants. Using the imaging data, the system of the present invention may use a primary applicant system to broadly deliver a first selected application (e.g. water or the like) and use a separate system to deliver targeted applicants for specific plants or areas of a given field.

Abstract: The present invention provides a system and method which includes a crop/soil analysis module which analyzes data collected and feeds the machine learning module, from one or more sources including imaging data from UAVs, satellites, span mounted crop sensors, in situ field and weather sensors. According to a further preferred embodiment, aerial data is combined and overlaid with span mounted sensor data in near real-time to generate irrigation management recommendations. According to a further preferred embodiment, the span mounted sensors may preferably provide field specific data of current field conditions and may preferably use the system's analytics to calculate crop water use and crop water stress index. According to a further preferred embodiment, vegetation indexes may preferably be calculated as checks against the values calculated from the aerial data and to provide information if cloud cover or other atmospheric interference is present.

Abstract: The present invention provides a system, method and apparatus for spraying the leaf and root areas of plants. According to an exemplary preferred embodiment, the present invention provides a foliar chemical application package which is designed specifically to deliver a chemical solution to the leaf area of plants in which the chemical will primary enter the plant through the foliar area rather than the root zone. According to a further preferred embodiment, the present invention teaches a system, method and apparatus for providing a specialized foliage spraying application in which water supply lines and chemical supply lines are individually controlled so that applicants, such as different chemicals received from different chemical tanks, may be simultaneously applied to a given crop.

Abstract: The present invention provides an irrigation system that includes a control system for determining whether to apply an applicant to an agricultural field. In an implementation, the control system includes memory operable to store one or more modules and a processor coupled to the memory. The processor is operable to execute the one or more modules to cause the processor to receive one or more signals representing a microbe characteristic from a soil sensor. The processor is also operable to determine whether to apply an applicant (i.e., water having a concentration of a biological or a microbe therein) to a soil based upon the microbe characteristics and to initiate operation of the irrigation assembly to apply the applicant to the soil in response when the soil requires the applicant.