Agronomic Performance Zone Mapping for Site-Specific Crop Treatment
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Solution Overview
Problem
Conventional agricultural practices face challenges in maximizing crop yields due to variations in soil conditions and topography across fields, leading to inefficient use of inputs and unrealized yield potential, as they typically apply inputs based on averaged soil requirements rather than site-specific needs.
Innovation Solution
A system and method for aggregating enhanced learning blocks by performance zone, which involves collecting data from randomized replicated treatments in test plots and classifying similar agronomic environments to provide personalized treatment recommendations for specific areas within a field, optimizing agronomic responses based on factors like weather and management practices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If agricultural inputs are applied based on averaged soil requirements for the entire field, then the implementation is simple and uniform, but this results in significant waste of inputs in areas that do not need them and unrealized yield potential in deficient areas
Solution Approach 1:
The field is divided into multiple performance zones based on agronomic environment characteristics such as soil type, topography, and historical yield data. Each zone is then treated independently with customized input rates, allowing precise application where needed and avoiding waste in areas with sufficient nutrients.
Solution Approach 2:
Different portions of the field receive different treatment levels tailored to their specific agronomic needs. High-deficiency areas receive higher input rates while adequate areas receive reduced rates, optimizing both yield potential and input efficiency across the entire field.
2Measurement precision
If conventional small plot testing is used to determine treatment levels, then the research model is simple to conduct, but the results cannot be accurately translated to production fields with different soil and management conditions
Solution Approach 1:
Enhanced test plots serve as an intermediary between conventional small plot research and actual production fields. These test plots are established within the farmer's own field, replicating local soil, topography, and management conditions, thereby providing agronomic response data that is directly applicable to commercial production while maintaining research rigor.
Solution Approach 2:
Enhanced test plots are established and monitored in advance of the growing season, allowing agronomic responses to be measured and analyzed before full-scale production planting. This preliminary data collection enables optimization of input rates for the entire field based on site-specific responses to various treatment levels.
Data Source
AI summary
A system to receive data representing agronomic responses based on randomized replicated treatments conducted in test plots of agronomic environments, aggregate the data representing the agronomic responses into subsets of the data representing the agronomic responses, each subset of the data representing the agronomic responses associated with one of a number of performance zones, receive characteristics associated with a portion of a field and determine that the portion of the field represents a particular performance zone of the number of performance zones based on the characteristics associated with the portion of the field, recommend a particularized treatment level for a crop located in the portion of the field based on the particular performance zone, and communicate the particularized treatment level to a machine, the particularized treatment level to be applied to the portion of the field by the machine to optimize an agronomic response based on the particular performance zone.