Field Management Zone Clustering for Variable-Rate Planting
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Solution Overview
Problem
Current agricultural management systems lack efficient methods to identify and manage management zones within fields, leading to suboptimal crop yields and resource allocation due to uniform management practices across varying field regions.
Innovation Solution
A computer-based system that utilizes digital map data and pipelined data processing to determine management zones by clustering yield and field characteristic data, generating graphical representations and recommendations for customized agricultural practices such as seeding, irrigation, and fertilizer application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If uniform management practices are applied across the entire field, then operational simplicity is maintained, but crop yields and resource allocation efficiency deteriorate due to ignoring field variability
Solution Approach 1:
The patent divides the agricultural field into multiple management zones based on spatial variability of soil properties, topography, and historical yield data. Each zone is then managed separately with customized practices, transforming a single uniform management approach into segmented zone-specific management. This segmentation enables tailored agricultural practices that address local conditions, thereby improving crop yields while maintaining operational simplicity through automated zone identification and management recommendation generation.
2Productivity
If detailed field analysis and customization are implemented, then agricultural productivity and yield are improved, but computational resources and processing time increase
Solution Approach 1:
The patent performs preliminary analysis of field characteristics, soil properties, topography, and historical yield data to pre-identify management zones before the actual agricultural operations. This preliminary zone delineation and characterization work is completed in advance, allowing subsequent agricultural operations to proceed with predefined management recommendations for each zone. By performing the computationally intensive analysis beforehand, the system reduces real-time computational resource consumption during field operations while still enabling detailed customization for improved productivity.
Data Source
AI summary
In an embodiment, yield data representing yields of crops that have been harvested from an agricultural field and field characteristics data representing characteristics of the agricultural field is received and used to determine a plurality of management zone delineation options. Each option, of the plurality of management zone delineation options, comprises zone layout data for an option. The plurality of management zone delineation options is determined by: determining a plurality of count values for a management class count; generating, for each count value, a management delineation option by clustering the yield data from and the field characteristics data, assigning zones to clusters, and including the zones in a management zone delineation option. One or more options from the plurality of management zone delineation options are selected and used to determine one or more planting plans. A graphical representation of the options and the planting plans is displayed for a user.