Crop Sensor Calibration for Variable-Rate Nutrient Application
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Solution Overview
Problem
Conventional crop monitoring methods, such as soil sampling and satellite imaging, fail to provide accurate and consistent measurements of crop-related parameters due to variability and environmental factors, leading to overapplication or underapplication of nutrients, which are labor-intensive and costly.
Innovation Solution
A sensor system with multiple sensors, including visible light and near-infrared cameras, monitors crop parameters in real-time, determining calibration factors to adjust nutrient application plans for precise application.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional crop monitoring methods (soil sampling and satellite imaging) are used, then labor and cost are reduced, but measurement precision and reliability of crop parameter data deteriorate
Solution Approach 1:
The system divides the crop field into multiple sections and uses multiple sensors to monitor different parameters simultaneously. Each sensor targets specific crop parameters (growth stage, health, nutrient levels) to provide segmented, comprehensive monitoring data that improves overall measurement precision.
Solution Approach 2:
The patent combines multiple sensor types (visible light cameras, near-infrared cameras, multispectral sensors) into a single integrated sensor system. This merging of different sensing technologies allows simultaneous measurement of multiple crop parameters, improving reliability and precision while managing device complexity through unified data processing.
2Productivity
If uniform nutrient application is applied across the entire field, then application simplicity is maintained, but nutrient efficiency and yield optimization deteriorate
Solution Approach 1:
The system applies local quality by determining specific nutrient application rates for different sections of the field based on localized sensor measurements. Each section receives customized nutrient application according to its specific needs, optimizing yield for that local area rather than applying uniform treatment across the entire field.
Solution Approach 2:
The nutrient application system transitions from static uniform application to dynamic variable rate application. The system continuously monitors crop parameters and adjusts application rates in real-time based on current field conditions, allowing the application plan to adapt dynamically to spatial and temporal variations in crop needs.
3Reliability
If excessive nutrients are applied to ensure adequate supply, then crop nutrient adequacy is maintained, but environmental harm and cost increase
Solution Approach 1:
The system implements feedback control by continuously monitoring crop parameters and using this information to adjust nutrient application rates. The sensor data provides real-time feedback on crop nutrient status, allowing the system to apply precisely the amount of nutrients needed, ensuring adequacy while preventing excessive application that would cause environmental harm.
Solution Approach 2:
The system changes the application parameter from fixed uniform rates to variable rates based on measured crop parameters. By adjusting application rates according to actual crop needs determined through sensor measurements, the system maintains reliable nutrient supply while minimizing excess application and its associated environmental impacts.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The sensor system enables precise application of nutrients, reducing costs and environmental impact by maximizing yield and minimizing excess application.
Implementation Method 1
a third sensor (e.g., a near-infrared camera) different from the first sensor and the second sensor
Implementation Method 2
the first sensor and the second sensor may be visible light cameras
Data Source
Figure 1A
Figure 1B
Figure 2
AI summary
A method that includes determining, based on data from a first sensor (204), a first estimated value of a crop health parameter in a first section (222) of a crop (220) and determining, based on data from a second sensor (206), a second estimated value of the crop health parameter in a second section (224) of the crop (220). The method also includes measuring, using a third sensor (208), a measured value of the crop health parameter in the second section, and comparing the second estimated value and the measured value to determine a calibration factor. Additionally, the method includes determining a first product application plan for the first section based upon the first estimated value and the calibration factor.