Harvester Grain Imaging for Count, Size, and Mass Mapping
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Solution Overview
Problem
Existing methods for harvesting cereals fail to measure grain dimensions or mass, which are crucial for optimizing yield potential and resource allocation, as they only provide yield data without considering grain size or number per unit area.
Innovation Solution
A method and apparatus using a camera and image processing system on a harvesting machine to measure grain count, dimensions, and mass per unit area, generating output values for agronomic planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If yield measurement is performed using conventional measuring devices, then yield data is obtained, but grain-specific parameters (thousand kernel mass, number of grains per unit area) are not measured
Solution Approach 1:
The patent applies a camera-based image processing system that can measure multiple grain-specific parameters (thousand kernel mass, number of grains per unit area, grain dimensions) simultaneously from a single image source, making the measurement device universal for various agronomic quantities without requiring separate specialized instruments for each parameter
2Adaptability or versatility
If conventional yield measurement is used, then yield data is available, but location-specific agronomic planning cannot be optimized
Solution Approach 1:
The patent enables location-specific agronomic planning by capturing images at different locations during harvest and processing them to obtain spatially-resolved data on grain dimensions and mass. This allows farmers to identify specific areas with different grain characteristics and adjust sowing rates or resource allocation accordingly for each location
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
Enables location-specific agronomic planning by providing grain count, dimensions, and mass data, allowing for optimized sowing rates and resource allocation based on grain-specific characteristics.
Implementation Method 1
acquiring an image of the grain in the harvesting machine using a camera
Implementation Method 2
processing the image in an image processing system and generating an output value in respect of properties of the grain
Data Source
AI summary
A method for measuring grain on a harvesting machine for harvesting cereals comprising: acquiring an image of the grain in the harvesting machine using a camera; and processing the image in an image processing system and generating an output value in respect of properties of the grain, wherein the output value contains information relating to at least one of the following quantities per unit area of the field: grain count, grain dimensions, and grain mass.