Automated Seed Sampler with Imaging Orientation
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Solution Overview
Problem
In plant development, existing methods for sampling seeds are inefficient and time-consuming, as not all seeds express desired traits, requiring manual sorting and testing to cull undesirable seeds from large populations.
Innovation Solution
An automated system for seed sampling and sorting that includes a seed loading station, imaging station, seed orientation station, and sample and sort station, which uses image data to orient and extract tissue samples from seeds, sorting them into trays for efficient testing and tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual sorting and testing methods are used to cull undesirable seeds, then seed trait evaluation can be performed, but the process is inefficient and time-consuming
Solution Approach 1:
The patent replaces manual mechanical sorting and testing with an automated system that uses imaging technology to capture seed images, computer vision algorithms to analyze trait expression, and robotic mechanisms to sort seeds. This substitution of mechanical/manual operations with automated optical and computational systems directly resolves the contradiction by dramatically increasing productivity while reducing the time required for seed evaluation.
Solution Approach 2:
The system enables seeds to be automatically evaluated and sorted based on their own visual characteristics captured by imaging stations. The seeds themselves provide the information needed for sorting through their phenotypic expression of desired traits, which is captured and analyzed automatically without human intervention, thus achieving both high efficiency and rapid processing.
2Productivity
If statistical samples are taken from large seed populations to hasten the bulking process, then breeding efficiency improves, but manual sampling and tracking becomes increasingly complex
Solution Approach 1:
The system creates digital copies of seeds through high-resolution imaging that captures phenotypic traits. These image copies are then analyzed by computer vision algorithms to evaluate trait expression and determine sorting decisions. This copying approach allows for rapid evaluation of large seed populations without physical manipulation complexity, as the digital representations can be processed automatically and tracked through the system.
Solution Approach 2:
The automated system performs multiple functions within a single integrated platform: imaging seeds, analyzing phenotypic traits, making sorting decisions, and tracking seed identities. This multi-functional approach handles the complexity of sampling and tracking large populations uniformly, eliminating the need for separate manual processes for each function and thereby reducing overall system complexity despite the high throughput requirements.
3Productivity
If rapid seed processing is implemented to increase throughput, then breeding efficiency increases, but seed damage and loss of germination viability may occur
Solution Approach 1:
The system replaces mechanical handling and physical sorting methods with automated imaging and non-contact analysis. Seeds are imaged and evaluated based on their visual phenotypic expression without requiring physical manipulation that could cause damage. The sorting mechanism is precisely controlled to minimize mechanical stress, thereby maintaining germination viability while achieving high processing throughput.
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
The system significantly increases sampling and sorting efficiency and throughput, allowing for rapid identification and culling of seeds that do not express desired traits, preserving germination viability and facilitating high-throughput genetic analysis.
Implementation Method 1
an imaging station for collecting image data of the at least one seed
Implementation Method 2
a seed orientation station for independently positioning and retaining each seed in a desired orientation based on the collected image data
Implementation Method 3
a seed sample and sort station for extracting a tissue sample from each seed, sorting each tissue sample to a sample tray and sorting each sampled seed to a seed tray
Data Source
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Figure 3A
AI summary
In various embodiments, the present disclosure provides an automated seed sampling and sorting system. The system includes an imaging station for collecting image data of a set of seeds and a seed orientation station for independently positioning each seed in the set in a desired orientation based on the collected image data. The system further includes a seed sample and sort station for extracting a sample from each seed in the set, sorting each sample to a sample tray and sorting each sampled seed to a seed tray.