Automated Maize Haploid Identification via Microscope Imaging
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Solution Overview
Problem
Current methods for identifying maize haploids are inefficient, requiring skilled technicians, causing irreversible damage to plants, and are not suitable for large-scale identification due to their slow pace and high resource consumption.
Innovation Solution
A high-power-microscope-assisted identification method using a device with a high power microscope, computer, and automated actuators to input sample information, automatically test and analyze samples in batches, and generate data results, enabling accurate and rapid determination of chromosome numbers in maize seedlings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If morphological identification is used, then identification can be performed by technicians, but it requires skilled technicians and is not efficient
Solution Approach 1:
The system performs automatic identification of maize haploids through automated image capture, chromosome counting, and analysis. The device captures images of root tip cells, automatically counts chromosomes using image processing algorithms, and identifies haploids without requiring skilled technicians to manually examine and count chromosomes, thereby achieving self-service operation while dramatically improving identification efficiency
Solution Approach 2:
The patent replaces the manual mechanical process of chromosome counting by skilled technicians with an automated optical-mechanical system. The device uses a microscope to capture cell images, a computer system to process images and count chromosomes automatically, eliminating the need for human operators while maintaining high accuracy in haploid identification
2Measurement precision
If cytological identification or anatomical identification is used, then identification accuracy is high, but the process is slow and not suitable for large quantities of materials
Solution Approach 1:
The system enables continuous automated identification by capturing multiple images of root tip cells in sequence, automatically processing each image to count chromosomes, and continuously generating identification results. This continuous automated process maintains high accuracy through consistent image processing while dramatically increasing throughput compared to manual methods that must be performed sequentially on each sample
Solution Approach 2:
The device creates digital copies (images) of root tip cells under the microscope and performs chromosome counting on these copies using image processing algorithms. This allows multiple copies to be processed simultaneously or in rapid succession, maintaining the accuracy of cytological analysis while enabling high-speed automated identification of large quantities of materials
3Productivity
If radiological identification is used, then identification is fast, but it causes irreversible damage to maize plants and requires a large amount of work
Solution Approach 1:
The system creates optical copies (digital images) of root tip cells through microscopy and performs all analysis on these copies rather than using radiological methods that expose living plants to radiation. This allows fast automated identification while completely avoiding the harmful effects of radiation on the maize plants
Solution Approach 2:
The patent introduces an optical intermediary (microscope imaging system) that allows non-invasive observation and counting of chromosomes in living or fixed root tip cells. This intermediary method provides fast automated identification without the harmful effects of radiological techniques, as the light-based imaging process does not damage the plant material
4Adaptability or versatility
If genetic marker identification or molecular marker identification is used, then identification can be performed, but it requires a lot of manpower and materials and is not suitable for maize materials without color development
Solution Approach 1:
The patent replaces complex biochemical marker identification systems with a simpler optical-mechanical image analysis system. Instead of requiring genetic markers, molecular reagents, and extensive manual processing, the device uses microscope imaging combined with automated chromosome counting algorithms, eliminating the need for special maize varieties with color markers and dramatically reducing manpower and material requirements
Solution Approach 2:
The system performs autonomous identification by automatically capturing images of root tip cells, processing the images through chromosome counting algorithms, and generating identification results without requiring manual intervention. This self-service approach eliminates the need for skilled technicians to interpret genetic or molecular markers, making the method universally applicable to all maize materials regardless of whether they exhibit color development
Data Source
AI summary
A high-power-microscope-assisted identification method of maize haploid plants is provided, the method is implemented by a device including a high power microscope, a main frame disposed on an objective table of the high power microscope and a computer and includes four procedures of sample information input, automatic testing of a batch of samples, automatic analysis and comparison, and automatic generation of data results. Vertical sliding grooves are symmetrically formed in the main frame, and a vertical supporting plate is disposed at an upper end of the main frame. Horizontal sliding grooves are symmetrically formed in the vertical supporting plate, and a horizontal supporting plate is disposed on the vertical supporting plate.