Crop Constituent Sensing with Vegetative Index Mapping
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Solution Overview
Problem
Current agricultural systems lack the ability to provide precise localization of crop constituent values due to the low resolution of crop constituent sensors, which are often located at a single point on the harvester, leading to imprecise application of substances like fertilizer based on averaged crop constituent values.
Innovation Solution
Utilizing an agricultural characteristic map, such as a vegetative index map, to correlate with crop constituent values and generate weighted crop constituent values for each subregion, allowing for precise control of agricultural machinery based on localized crop characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single-point crop constituent sensor is used on the harvester, then the sensor placement is simple and the device complexity is low, but the measurement precision and localization accuracy are insufficient
Solution Approach 1:
The patent divides the field into multiple subregions based on the harvester's position and header width, assigning sensor measurements to specific spatial segments. This segmentation allows the single sensor to provide location-specific data by mathematically dividing the measurement across multiple subregions, thereby improving localization accuracy without adding multiple physical sensors.
Solution Approach 2:
The patent introduces an intermediary computational model that combines sensor data with harvester operational parameters (position, speed, header width) to calculate subregion-specific crop constituent values. This intermediary processing layer transforms the single-point measurement into multiple localized values without requiring additional sensing hardware.
2Manufacturing precision
If crop constituent values are averaged across the entire field, then the data processing is simple, but the manufacturing precision of subsequent agricultural operations is reduced
Solution Approach 1:
The patent segments the field into multiple subregions based on the harvester's real-time position and header width, calculating separate crop constituent values for each subregion rather than using a single field-wide average. This segmentation enables precise, variable-rate fertilizer application tailored to each subregion's actual crop conditions.
Solution Approach 2:
The patent dynamically adjusts the subregion boundaries and assignments based on the harvester's real-time position, speed, and header width during operation. This dynamic approach ensures that the crop constituent values are continuously updated to reflect current field conditions, enabling adaptive and precise agricultural operations.
3Loss of information
If the sensor measures crop constituents at a single point, then the measurement process is fast and simple, but the information about spatial variation is lost
Solution Approach 1:
The patent mathematically segments the single sensor measurement into multiple subregion values by dividing the total measurement across the header width and assigning portions to different spatial locations. This allows the system to recover spatial variation information from a single-point measurement without requiring multiple sensors or extended measurement time.
Solution Approach 2:
The patent uses preliminary knowledge of the harvester's position, header width, and crop flow characteristics to pre-calculate the distribution pattern of crop constituents across subregions. This preliminary modeling allows the system to rapidly allocate the single measurement to multiple locations without requiring additional real-time measurements.
Data Source
AI summary
A crop constituent value is sensed by a crop constituent sensor on an agricultural machine. The crop constituent value is distributed among subregions covered by the agricultural machine. A vegetative index-estimated crop constituent value is obtained for each of the subregions. A weighted crop constituent value is generated for each subregion based upon the distributed constituent value for each subregion and the vegetative index-estimated constituent value for that subregion. An action signal is generated based upon the weighted crop constituent value for the subregion.