A method of predicting crop yield includes generating, via a processor, a plurality of vectors representative of growing conditions for a current time period and a plurality of vectors representative of growing conditions for a previous time period. The processor compares the plurality of vectors for the current time to the vectors of the previous time periods for corresponding growing conditions and determines which previous vectors are closest to the current vectors. The plurality of previous time periods are each associated with crop yields. Thus, the processor can determine a crop yield for the current time period for a selected crop producing field and crop type based on crop yields for the closest previous time periods.

An agricultural sprayer includes a nozzle assembly having a nozzle body, a valve moveably positioned within the nozzle body, and an actuator configured to move the valve within the nozzle body. Additionally, the agricultural sprayer includes a computing system having a spray controller positioned outside of the nozzle body and a nozzle controller positioned within the nozzle body. The spray controller is communicatively coupled to the nozzle controller such that the spray controller is configured to transmit control signals to the nozzle controller via a first communicative link, with the nozzle being controller configured to control an operation of the actuator based on the control signals received from the spray controller. Moreover, the spray controller is communicatively coupled to the actuator such that the spray controller is configured to directly control the operation of the actuator via a second communicative link independently of the nozzle controller.

A system (100), method and computer program product for optimization of crop protection. A generator module (120) accesses one or more configuration data structures (220) wherein the one or more configuration data structures include data fields to store crop data (221), advice data (222) related to respective crop data, and crop protection product data (223) related to respective advice. Further, it accesses a plurality of code snippets (230) wherein each code snippet (231, 232, 233) has a condition which relates either to at least one property field of the one or more data structures (220) or to a result of another code snippet, and further includes generic program logic associated with the condition, and wherein each property field is used in the condition of at least one code snippet. The plurality of code snippets is applied to the one or more configuration data structures to generate an advice logic program.

A computer-implemented method of targeting grower fields for crop yield lift is disclosed. The method comprises receiving, by a processor, crop seeding rate data and corresponding crop yield data over a period of time regarding a group of fields associated with a plurality of grower devices; receiving, by the processor, a current seeding rate for a grower's field associated with one of a plurality of grower devices; determining, whether the grower's field will be responsive to increasing a crop seeding rate for the grower's field from the current seeding rate to a target seeding rate based on the crop seeding rate data and corresponding crop yield data; preparing, in response to determining that the grower's field will be responsive, a prescription including a new crop seeding rate and a specific hybrid to be implemented in the grower's field.

Described herein are systems and methods for agricultural data analysis. In one embodiment, a computer system for monitoring field operations includes a database for storing agricultural data including yield and field data and at least one processing unit that is coupled to the database. The at least one processing unit is configured to execute instructions to monitor field operations, to store agricultural data, to automatically determine whether at least one correlation between different variables or parameters of the agricultural data exceeds a threshold, and to perform analysis of the agricultural data to identify a category of man-made issues or other issues that have potentially caused the correlation when at least one correlation occurs between different variables or parameters of the agricultural data.

Automated fertigation systems and methods determine crop N status from a vegetation index calculated from acquired image data of indicator blocks having at least two plots, one with a reduced N application rate (canary) and one with an increased N application rate (reference) versus a bulk area N application rate. In a preferred method, sub-regions are defined in a field being managed. In each sub-region, N (nitrogen) is applied to create adjacent canary and reference plots, wherein a canary plot is given less than a designated N amount and a reference plot. The sub-regions are subsequently imaged. A fertigation decision is made for each sub-region based upon automatic analysis of the vegetation indices of the canary and reference plots in each sub-region.

A system for measuring moisture in soil below the ground surface comprises at least one passive microwave sensor device configured to measure natural thermal emissions from the soil and output a data signal and a processing circuit operably coupled to the at least one passive microwave sensor wherein the processing circuit is configured to receive the data signal and compile a soil moisture profile. The system further comprises a wide-band antenna wherein the at least one passive microwave sensor is located therein and an elongate horizontal mounting frame extending between first and second ends wherein the first end is securable to a mobile agricultural device and wherein the wide-band antenna is secured to the second end so as to position the wide-band antenna at a distance above the ground surface.

A process for batch processing by-product water to obtain a batch of beneficial use water for application to an targeted area of soil with determined moisture and chemical characteristic to change that soil characteristic to a desired soil characteristic includes the steps of measuring the moisture and chemical composition of the targeted area of soil; determining a desired soil characteristic that will grow selected vegetation; defining a chemical composition of a batch water to be applied to the soil to obtain the desired composition; processing a batch of by-product water in accordance with the defined composition; applying the batch of processed water to the targeted area of soil; measuring the moisture and chemical composition of the soil after application; repeating the process until desired composition is achieved or the vegetation growth is completed.

A harvester monitoring system configured to determine one or more parameters associated with harvested items, the system comprising: a camera module having a field of view and configured to generate image data associated with the harvested items; a mounting bracket configured to secure the camera module to a harvester such that a conveyor of the harvester is within the field of view of the camera module; a location sub-system configured to determine and output location data representative of a geographical location of the harvester monitoring system; and a processing unit configured to receive the image data and the location data, to determine one or more parameters associated with the harvested items, and to record the one or more parameters in association with the location data on a computer readable medium.

Implementations are described herein for localizing individual plants by aligning high-elevation images using invariant anchor points while disregarding variant feature points, such as deformable plants. High-elevation images that capture the plurality of plants at a resolution at which wind-triggered deformation of individual plants is perceptible between the high-elevation images may be obtained. First regions of the high-elevation images that depict the plurality of plants may be classified as variant features that are unusable as invariant anchor points. Second regions of the high-elevation images that are disjoint from the first set of regions may be classified as invariant anchor points. The high-elevation images may be aligned based on invariant anchor point(s) that are common among at least some of the high-elevation images. Based on the aligned high-elevation images, individual plant(s) may be localized within one of the high-elevation images for performance of one or more agricultural tasks.