Automated Plant Contamination Detection Using Sensor-Based Bonitur
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Solution Overview
Problem
Current methods for inspecting plant tissue cultures for contamination are time-consuming and costly, relying on manual visual inspection, which is prone to errors and inefficiencies.
Innovation Solution
An automated system using a sensor unit and evaluation instrument, potentially with neural networks, to rapidly and reliably identify contaminations in plants and nutrient media by comparing images and samples, reducing the need for human intervention and enhancing processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual visual inspection is used to detect contamination, then the inspection can be performed with simple equipment, but the process is time-consuming and costly
Solution Approach 1:
The patent replaces manual visual inspection with an automated sensor-based inspection system. Sensors capture images or spectral data of plant tissue cultures, and an evaluation instrument automatically analyzes this data to detect contamination. This substitution of mechanical/manual inspection with automated sensing and evaluation systems directly resolves the contradiction by maintaining simplicity while dramatically improving inspection speed and productivity.
2Device complexity
If manual visual inspection is used, then the equipment requirements are minimal, but the inspection accuracy and reliability are reduced due to human error
Solution Approach 1:
The patent replaces human visual inspection with automated sensor-based detection and electronic evaluation. The sensor unit captures data from plant tissue cultures, and the evaluation instrument objectively analyzes this data to detect contamination without human error. This substitution maintains relatively simple device complexity while dramatically improving reliability and inspection accuracy through automated, consistent evaluation.
3Productivity
If automated sensor-based inspection is implemented, then inspection speed and productivity are improved, but the device complexity increases
Solution Approach 1:
The patent implements automated sensor-based inspection where sensors capture images or spectral data and an evaluation instrument automatically analyzes the data to detect contamination. This automation dramatically improves inspection speed and productivity by eliminating manual inspection processes while managing device complexity through integrated sensor and evaluation systems.
Solution Approach 2:
The patent creates digital copies (images or spectral data) of plant tissue cultures using sensors, and then evaluates these copies to detect contamination. This copying approach allows rapid, automated inspection without physically handling or disturbing the original samples, improving productivity while keeping the physical inspection system relatively simple.
4Ease of manufacture
If manual inspection is used, then the cost of implementation is low, but the cost per inspection increases due to labor requirements
Solution Approach 1:
The patent replaces manual inspection with automated sensor-based detection and electronic evaluation. The sensor unit captures data from plant tissue cultures, and the evaluation instrument automatically analyzes this data to detect contamination. This substitution eliminates labor-intensive manual inspection processes, reducing the time per inspection from minutes to seconds while the initial implementation cost remains manageable through the use of standard sensor and computing components.
Data Source
AI summary
A method and a device with which the processing of plants can be made more efficient. This is achieved by the plants and in particular plant-based and synthetic nutrient media or substrates being subjected to an automated bonitur. For this purpose, a sample and/or an image of at least one plant or of at least one nutrient medium or of the substrate is taken automatically by a sensor unit from the plant or from the nutrient medium or the substrate. This sample and/or this image are then compared by an evaluation instrument with known samples and/or recordings of plants and/or nutrient media/substrate, which have a contamination.