Aerial Crop Nitrogen Deficiency Prediction Using Reflectivity
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Solution Overview
Problem
Current methods for predicting nitrogen loss and yield loss in crops due to nitrogen deficiency are inefficient and costly, as they rely on localized and time-consuming measurements, limiting the ability to apply rescue nitrogen fertilization effectively.
Innovation Solution
A method using aerial photographs and positional data to determine nitrogen deficiency and yield loss, calculating Relative Green values and constructing yield loss maps to estimate optimal rescue nitrogen fertilization rates, thereby providing an economically informed approach to nitrogen management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional localized measurements are used to predict nitrogen loss and yield loss, then measurement precision may be adequate, but productivity is severely limited due to time-consuming and labor-intensive processes
Solution Approach 1:
The patent transitions from ground-based localized measurements to aerial photography, adding a vertical dimension to the measurement approach. This allows simultaneous observation of entire fields from above, converting a one-dimensional ground traversal problem into a two-dimensional aerial survey solution that captures spatial variability across the entire field in a single pass.
Solution Approach 2:
The patent creates a visual copy of the field's nitrogen status through aerial photographs. Instead of physically measuring each location, the system captures an optical copy of the entire field and analyzes it to determine nitrogen deficiency patterns, enabling rapid assessment without physical contact with the crops.
2Reliability
If excess nitrogen fertilizer is applied at planting to compensate for anticipated losses, then yield security is improved, but nitrogen use efficiency deteriorates and operating costs increase
Solution Approach 1:
The patent performs preliminary diagnosis of nitrogen status using aerial photography during the growing season, allowing proactive identification of deficiency areas before they cause significant yield loss. This early detection enables targeted intervention rather than reactive over-fertilization.
Solution Approach 2:
The patent identifies and treats only the specific areas of the field that exhibit nitrogen deficiency symptoms visible in aerial photographs. Instead of uniform field-wide application, nitrogen fertilizer is applied locally to deficient zones, maintaining yield security in affected areas while avoiding unnecessary application in sufficient areas, thus improving overall nitrogen use efficiency.
3Reliability
If rescue nitrogen application is performed using high-clearance equipment or aerial applications, then yield loss prevention is improved, but device complexity and operating costs increase
Solution Approach 1:
The patent uses aerial photography to identify specific locations within the field that require rescue nitrogen application. By mapping nitrogen deficiency patterns spatially, the system enables targeted application using standard equipment rather than requiring specialized high-clearance equipment for entire fields, reducing device complexity while maintaining yield protection in deficient areas.
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
This method allows for accurate prediction of yield loss and determination of economically optimal nitrogen fertilization rates, reducing costs and improving nitrogen use efficiency by providing timely and spatially variable nitrogen application decisions.
Implementation Method 1
aerial photographs... reveal spatial variation in crop nitrogen status
Data Source
AI summary
A method for determining the yield loss of a crop using remote sensor data is described. The yield loss is determined using the reflectivity of green light by the crop canopy measured from remote sensor data such as an aerial photograph that is digitized and spatially referenced to the field's longitude and latitude. Green pixel values from the aerial photograph, expressed relative to green pixel values from well-fertilized areas of the field, are transformed to yield losses using a linear transformation that was developed using empirical data. A similar method is described to determine recommended nitrogen fertilization rates for the crop fields. The yield loss data is useful for nitrogen fertilization management, as it allows a producer of crops to weigh the expense of fertilization against the loss of revenue due to yield loss.