Row-Level Yield Estimation for Data-Limited Agricultural Control
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Solution Overview
Problem
Existing methods for estimating crop yield in agricultural fields face challenges due to large data sets from plant-by-plant data collection, exceeding data processing budgets and capacity, particularly with crops like corn, maize, wheat, and soybeans, which require efficient methods to support position-specific control of agricultural machines without relying on extensive big data processing resources.
Innovation Solution
A method utilizing multiple data layers, including moisture data, planting date data, seeding rate, seeding depth, and seedbed/furrow quality, collected through sensors and image processing systems, is transmitted to a central server for estimating crop yield at a row position basis, conserving data processing resources by selecting data spear zones throughout the field.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plant-by-plant data collection is used to estimate crop yield, then measurement precision is improved, but data processing capacity is exceeded
Solution Approach 1:
The patent segments the field into multiple zones and selects representative data spear zones within each zone for detailed data collection. This segmentation approach maintains measurement precision by ensuring adequate sampling coverage across the entire field while reducing the total data volume to manageable levels for processing.
Solution Approach 2:
The patent applies local quality by collecting detailed plant-by-plant data only in selected data spear zones rather than uniformly across the entire field. This allows high measurement precision in representative locations while reducing overall data processing requirements by not collecting exhaustive data in every location.
2Measurement precision
If comprehensive data layers are collected for all field positions, then yield estimation accuracy is improved, but data processing resources are exceeded
Solution Approach 1:
The patent extracts and collects only the necessary data layers (moisture, planting date, seeding rate, seeding depth, and seedbed quality) in selected data spear zones rather than collecting all possible data for all field positions. This extraction approach maintains estimation accuracy by capturing key variables while dramatically reducing data volume.
Solution Approach 2:
The patent applies partial action by collecting comprehensive data layers but only in a partial set of locations (data spear zones) rather than in every field position. This partial collection strategy provides sufficient information for accurate yield estimation without the excessive data burden of universal coverage.
3Manufacturing precision
If data is collected at every row position throughout the field, then position-specific control precision is improved, but data processing budget is exceeded
Solution Approach 1:
The patent segments the field into zones and selects specific data spear zones for detailed data collection. This segmentation enables position-specific control by providing detailed data for representative locations while reducing overall data processing requirements, allowing precise control strategies to be developed without exhausting processing budgets.
Data Source
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AI summary
In one embodiment, obtained moisture data, planting data, seeding rate and seeding depth, and planted seedbed/furrow quality (e.g., first through fourth data layers associated with select data spear zones distributed throughout the field to conserve data processing resources) are applied, inputted or transmitted wirelessly to a central server, with an electronic data processing device that is configured to estimate a yield of the crop at a row position basis throughout the field.