Corn Kernel Orientation Imaging for Haploid Diploid Sorting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for sorting corn kernels based on their ploidy level, particularly distinguishing between haploid and diploid kernels, face challenges in accuracy and throughput, especially for flint varieties with round shapes, due to difficulties in consistent and accurate kernel orientation and embryo position identification.
Innovation Solution
A method involving an orientation imaging system to determine the orientation of corn kernels using structural features, followed by a coloration imaging system to identify the embryo and endosperm characteristics, allowing for accurate sorting of kernels based on their ploidy level by determining the orientation and coloration patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional sorting methods are used for corn kernels, then the sorting process is simple, but the accuracy in identifying haploid and diploid kernels is low
Solution Approach 1:
The patent segments the sorting process into distinct functional modules: an orientation imaging system to determine kernel orientation, a coloration imaging system to identify embryo and endosperm characteristics, and a sorting mechanism. This segmentation allows each module to specialize in a specific task, improving overall identification accuracy while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent introduces an intermediary processing step that determines kernel orientation before performing coloration analysis. This intermediary orientation determination acts as a mediator that enables the coloration imaging system to correctly interpret embryo and endosperm characteristics, thereby improving identification accuracy without requiring the coloration system to handle orientation variability directly.
2Productivity
If manual identification methods are used, then the system complexity is low, but the throughput of kernel sorting is reduced
Solution Approach 1:
The patent replaces manual mechanical identification with automated imaging systems. The orientation imaging system and coloration imaging system use optical fields and image processing algorithms to automatically determine kernel orientation and identify ploidy levels, dramatically increasing throughput while the complexity is managed through software-based analysis rather than complex mechanical mechanisms.
Solution Approach 2:
The imaging systems are designed to automatically capture, process, and analyze kernel images without human intervention. The systems self-calibrate and self-process the identification of haploid and diploid kernels based on the captured orientation and coloration data, enabling high-throughput automated sorting while minimizing the need for operator intervention and reducing operational complexity.
3Measurement precision
If kernels are sorted without orientation determination, then the processing speed is high, but the accuracy of embryo position identification is poor
Solution Approach 1:
The patent performs preliminary orientation determination using the orientation imaging system before the coloration imaging system analyzes embryo and endosperm characteristics. This preliminary action of establishing kernel orientation enables subsequent accurate identification of embryo position and ploidy level, ensuring measurement precision while the entire process is optimized to minimize time loss through automated sequential processing.
Data Source
AI summary
Method for sorting corn kernels of a batch of corn kernels, the method comprising the steps of:laying the corn kernel on a support surface, the corn kernel having a resting surface in contact with the support surface, and an upper surface opposite the resting surface,acquiring at least one orientation image of the corn kernel with an orientation imaging system, the orientation imaging system having a modality adapted to enable structural features of the corn kernel to be measured,determining an orientation of the corn kernel with respect to the support surface based on the structural features of the corn kernel measured on the orientation image,sorting the corn kernel as a function of the orientation.