Crop Sensor Calibration for Variable Nutrient Application
Find Innovative SolutionsGenerate Solutions
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 throughout the growing season due to variability in sensor visibility and crop conditions, leading to overapplication or underapplication of nutrients and other products.
Innovation Solution
A sensor system using multiple sensors, including visible light and near-infrared cameras, to monitor crop health parameters in real-time, determine calibration factors, and adjust product application rates accordingly to ensure precise application of fertilizers, pesticides, and other nutrients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional crop monitoring methods (soil sampling, satellite imaging) are used, then measurement coverage is achieved, but measurement precision and reliability are insufficient due to variability in sensor visibility and crop conditions
Solution Approach 1:
The patent combines multiple sensor types (visible light cameras, near-infrared cameras, and other spectral sensors) into an integrated sensor system. This merging of different sensing modalities allows the system to capture complementary information about crop health and environmental conditions, thereby improving both measurement precision and reliability by compensating for the limitations of individual sensor types
Solution Approach 2:
The system dynamically adjusts sensor operation based on real-time conditions. Sensors are activated or deactivated depending on environmental factors such as lighting conditions, crop density, and atmospheric conditions. This dynamic adaptation ensures optimal measurement quality across varying operational conditions, maintaining high precision and reliability
2Quantity of substance
If uniform nutrient application is applied across the entire field, then application simplicity is maintained, but nutrient efficiency deteriorates leading to overapplication or underapplication in different sections
Solution Approach 1:
The system divides the field into multiple management zones or sections based on real-time sensor data about crop health, nutrient status, and environmental conditions. Each section receives customized nutrient application rates tailored to its specific needs, optimizing nutrient efficiency while preventing overapplication in healthy areas and underapplication in deficient areas
Solution Approach 2:
The system implements spatially variable nutrient application where different sections of the field receive different nutrient types and quantities based on local conditions detected by sensors. This localized approach ensures that each area receives the precise nutrients it needs, improving overall nutrient efficiency and crop response
3Measurement precision
If real-time crop monitoring is implemented, then application precision is improved, but system complexity increases
Solution Approach 1:
The sensor system is designed with multi-functional sensors that can detect multiple crop parameters (nutrient status, health indicators, environmental conditions) simultaneously. This universality reduces the number of separate sensing systems needed, managing complexity while maintaining high measurement precision for application decisions
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 and cost-effective application of agricultural products, maximizing yield and minimizing environmental impact by accurately monitoring crop conditions and adjusting application rates in real-time.
Implementation Method 1
a third sensor (e.g., a near-infrared camera) different from the first sensor and the second sensor
Data Source
AI summary
A method that includes determining, based on data from a first sensor, a first estimated value of a crop health parameter in a first section of a crop and determining, based on data from a second sensor, a second estimated value of the crop health parameter in a second section of the crop. The method also includes measuring, using a third sensor, 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.