X-ray backscatter crop mass estimation
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Solution Overview
Problem
Current methods for estimating crop yields in agriculture, particularly for specialty crops like fruits and vegetables, are labor-intensive, inaccurate, and inefficient due to reliance on manual sampling and visual imaging, which struggles with variable illumination and foliage occlusion.
Innovation Solution
The use of X-ray backscatter imaging to irradiate crops from multiple sides, process scan images through contrast enhancement, de-noising, registration, and segmentation, and calibrate distance to estimate crop weight and yield, allowing for precise measurement of fruit and plant health.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual sampling and visual imaging methods are used for crop yield estimation, then the equipment and operational complexity remain low, but the measurement precision and productivity are poor
Solution Approach 1:
The patent replaces manual mechanical sampling with X-ray backscatter imaging systems that automatically detect and measure crop characteristics. The system uses electromagnetic radiation (X-rays) to penetrate and image crops, substituting human labor with automated detection technology that provides both high precision and productivity simultaneously
Solution Approach 2:
The system changes the detection parameter from visual light reflection to X-ray backscatter intensity. By measuring the backscatter intensity of X-rays at different energies, the system can distinguish between different crop types and conditions, enabling accurate yield estimation without manual intervention
2Measurement precision
If visual imaging is used for crop assessment, then the device complexity remains low, but the measurement precision deteriorates due to variable illumination and foliage occlusion
Solution Approach 1:
The patent substitutes visible light imaging with X-ray backscatter imaging. X-rays penetrate foliage and are not affected by illumination conditions, allowing accurate detection of crop characteristics through the canopy without the limitations of visual imaging
Solution Approach 2:
The system transitions from two-dimensional visual surface imaging to three-dimensional volumetric imaging using X-ray backscatter. This enables detection of crop characteristics throughout the entire plant volume, not just the visible surface, improving measurement precision
3Productivity
If statistical sampling with manual counting is used, then the device complexity remains low, but the loss of time and productivity increase significantly
Solution Approach 1:
The patent replaces manual counting and sampling with automated X-ray imaging and digital image processing. The system captures images of entire crop areas and uses computer algorithms to automatically count and measure crops, eliminating time-consuming manual operations
Solution Approach 2:
The system enables continuous yield assessment by continuously capturing X-ray images as crops grow. Unlike discrete manual sampling, the automated system can monitor crop development continuously, providing ongoing productivity data without interrupting agricultural operations
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 provides accurate, automated, and efficient crop yield estimation and health assessment, reducing labor and improving decision-making in agriculture by penetrating foliage and providing detailed, systematic data on crop conditions.
Implementation Method 1
determining a crop characteristic by detecting Compton backscatter signal from the crop
Data Source
AI summary
Systems and methods for determining a mass of a crop by using at least one X-ray scanner is provided. The method includes obtaining at least two scan images of the crop, where a first of the at least two images is obtained along a first plane relative to the crop and a second of the at least two images is obtained along a second plane relative to the crop, and where the first plane is angularly displaced relative to the second plane, registering the first image and the second image, correcting the registered first and second images, and determining the mass of the crop from the corrected first and second images.