QR-Coded Microbial Test Kits for Early Crop Contamination Detection

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Solution Overview

Problem

The degradation of organic materials due to mold, bacteria infestations, rot, and decay leads to a decline in the commercial value and marketability of crops, necessitating critical processing steps to prevent such degradation.

Innovation Solution

A system utilizing machine-readable QR codes, sensors, and artificial intelligence to detect and analyze microbial contamination in organic materials, providing real-time monitoring, remediation recommendations, and automated reporting to mitigate infestations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If traditional processing methods are used without advanced detection systems, then device complexity is reduced, but microbial contamination and degradation occur leading to loss of organic materials

Engineering Contradiction:

Improvepreservation of organic materialsVSAvoiddetection and monitoring system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary detection of microbial contamination using QR-coded test kits before significant degradation occurs. The test kits are prepared in advance with specific media for detecting different types of microorganisms, allowing early identification and intervention to prevent crop loss.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary detection system consisting of QR-coded test kits, sensors, and imaging devices that mediate between the organic materials and the degradation process. This intermediary system enables non-intrusive monitoring and detection of contamination without directly interfering with the organic materials.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

If comprehensive microbial testing and monitoring are implemented, then detection precision is improved, but processing time and operational complexity increase

Engineering Contradiction:

Improvemicrobial contamination detectionVSAvoidtesting and processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The testing system is segmented into multiple specialized test kits, each containing media specific to different types of microorganisms (bacteria, mold, yeast). This segmentation allows for parallel testing of multiple contamination types simultaneously, improving detection precision without significantly increasing total processing time.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system uses QR codes as digital copies/representations of test kit information, enabling rapid identification and tracking of test results. The QR codes store encoded information about the test kit type, batch, and parameters, allowing quick data retrieval and analysis without manual recording time.

Inventive Principle:

Principle #26Copying

3Difficulty of detecting and measuring

If advanced sensors and AI analysis are deployed, then detection capability is improved, but device complexity and cost increase

Engineering Contradiction:

Improvemicrobial contamination detectionVSAvoidsensor and AI system

Core Design Contradiction:

Difficulty of detecting and measuringVSDevice complexity

Solution Approach 1:

The patent replaces complex manual inspection and mechanical testing methods with automated imaging sensors and AI-based image analysis. The system captures images of microbial growth on test media and uses machine learning algorithms to automatically identify and quantify contamination, reducing the need for manual expertise and simplifying operation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI-based image analysis system performs self-service by automatically analyzing images, identifying microorganisms, and generating results without requiring constant human intervention. The system self-calibrates and processes data autonomously, reducing operational complexity despite the advanced technology employed.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250347622A1Organic plant material microbial test kit devices and processing method

Publication Date: 2025.11.13 ELLINS CRAIG

AI summary

The embodiments disclose an apparatus for testing organic plant materials for microbial contamination including machine-readable QR code identifiers associated with multiple facility testing locations, samples from each location are treated with microorganism-specific growth stimulator solutions and incubated locally in a portable incubator to accelerate microbial growth, a plurality of sensors and a camera, wirelessly coupled to a remote server, capture environmental data and images of the incubated samples, an artificial intelligence (AI) engine on the server analyzes the images and sensor data, correlates them to respective QR code identifiers, and compares them against a pattern recognition database to identify microbial contaminants, a mobile application displays AI-generated contamination reports, remediation recommendations, and a facility heat map identifying locations of recurrent infestations, a machine learning system continuously updates remediation determinations based on sensor feedback, an AI-enabled contamination prediction module models the spread of contamination and generates preventative recommendations to aid in eradication.