Remote Sensing Crop Yield Loss Prediction
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Solution Overview
Problem
Current methods for determining nitrogen deficiency and yield loss in crops are inefficient and costly, relying on localized and time-consuming measurements, which limits the ability to predict nitrogen loss and apply rescue nitrogen fertilization effectively, especially due to the spatial variability of nitrogen in agricultural fields.
Innovation Solution
A method using remote sensing data from aerial photographs to estimate yield loss and determine economically optimal nitrogen fertilization rates by analyzing relative color values from red, green, and infrared reflectivity, allowing for spatially referenced yield loss and nitrogen application maps to guide nitrogen management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional localized measurement methods are used to determine nitrogen deficiency, then measurement precision may be adequate, but productivity is severely limited due to time-consuming repeated measurements across the field
Solution Approach 1:
The patent combines multiple localized measurements into a single comprehensive remote sensing assessment. By using aerial or satellite imagery to capture reflectance data across the entire field simultaneously, the system merges what would otherwise require numerous separate measurement points into one unified evaluation, thereby dramatically increasing productivity while maintaining adequate precision through spatially distributed pixel-level analysis
Solution Approach 2:
The patent transitions from ground-based point measurements to aerial/space-based areal measurements. By changing the dimension of observation from two-dimensional ground traversal to three-dimensional aerial imaging, the system can assess entire fields from above, capturing spatial variability in nitrogen status across the whole field in a single pass, thus resolving the contradiction between precision and productivity
2Reliability
If excess nitrogen fertilizer is applied at planting to compensate for anticipated losses, then yield loss due to nitrogen deficiency is prevented, but loss of substance occurs through leaching and denitrification
Solution Approach 1:
The patent applies preliminary action by using remote sensing to detect nitrogen deficiency early in the growing season, before yield impact occurs. This early detection enables timely intervention with targeted nitrogen applications, preventing the need for excessive preliminary fertilizer applications that would lead to leaching and denitrification losses
Solution Approach 2:
The patent implements local quality by providing spatially variable nitrogen management recommendations based on actual field conditions detected by remote sensing. Instead of uniform field-wide applications that cause unnecessary losses, the system identifies specific zones with nitrogen deficiency and targets applications to those locations, thereby maintaining yield protection while minimizing overall nitrogen loss through leaching and denitrification
3Reliability
If rescue nitrogen application is performed to correct nitrogen deficiency, then yield loss is reduced, but device complexity and operating costs increase due to need for specialized high-clearance equipment
Solution Approach 1:
The patent applies preliminary action by detecting nitrogen deficiency early through remote sensing, allowing farmers to plan and execute rescue nitrogen applications before yield impact occurs. This early warning system enables proactive management using standard equipment rather than emergency applications requiring specialized high-clearance equipment, thereby reducing device complexity while maintaining yield protection
Solution Approach 2:
The patent applies segmentation by dividing the field into zones based on nitrogen status and prioritizing rescue applications to the most affected areas. This targeted approach reduces the overall volume of nitrogen requiring complex application methods and allows sequential treatment of different field zones using progressively simpler equipment, thereby reducing device complexity requirements
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 approach enables accurate prediction of crop yield loss and determination of optimal nitrogen application rates, reducing economic losses by providing timely and spatially informed decisions for nitrogen supplementation, thus improving nitrogen use efficiency and reducing costs.
Implementation Method 1
based on the reflectivity of the leaf at this wavelength of light; the leaf blade nitrogen content is measured with high precision
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.