How Does Hyperspectral Imaging Ensure Food Safety in 30 Seconds?

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As the mycotoxin landscape continues to evolve, traditional testing methods are increasingly facing significant challenges. 

According to a 2023 North American mycotoxin survey, 89% of grain samples that were analyzed contained at least one mycotoxin, while 65% of samples had more than one mycotoxin present in the same sample. For farmers, grain processors, and food safety experts, the high prevalence of multiple co-occurring mycotoxins presents a serious challenge, as this can increase toxicity levels and make testing more difficult.

Since traditional test kits like ELISA and Lateral Flow are only meant to identify the presence of one mycotoxin at a time, they are unable to keep up with these new problems. They are also time-consuming, labor-intensive, and require consumables, making large-scale testing inefficient and introducing high degrees of variability in the test results. 

Therefore, the need of the hour is a faster, more comprehensive solution that eliminates test kit-related supply chain issues. This is where Hyperspectral Imaging (HSI) comes in. HSI offers an advanced alternative to traditional test methods, streamlining testing processes and enhancing food safety.   

What is Hyperspectral Imaging?

Hyperspectral imaging (HSI) is a breakthrough technology that analyzes materials based on their unique chemical signatures.  Unlike traditional imaging, which captures only three color bands (Red, Green, and Blue), hyperspectral imaging cameras collect and process information from hundreds or thousands of narrow spectral bands across the electromagnetic spectrum. By combining spectroscopy principles with digital imaging technology, hyperspectral imaging cameras can detect subtle variations even in the infrared and ultraviolet regions. This helps reveal chemical variations and physical properties invisible to the human eye.

The technology structures the collected data in three dimensions (spatial information along x and y coordinates and spectral information such as wavelength or frequency along the z coordinate), providing a comprehensive analysis of the spatial and spectral characteristics of the scanned material. Since no two materials reflect light the same way, hyperspectral imaging cameras capture the light intensity of each pixel across many bands, creating a unique “fingerprint” for precise material identification.

How Does Hyperspectral Imaging Work In Food Testing?

Here are the steps involved:

  1. Illumination: The food sample is illuminated with controlled light, and the reflected light is captured by a hyperspectral camera.
  2. Spectral Analysis: The system analyzes the unique spectral fingerprint of each sample.
  3. AI Technology: Advanced machine learning algorithms analyze the spectral data to compare fingerprints and identify contaminated samples.

This high-speed, non-invasive method allows large-scale screening, ensuring more comprehensive and accurate testing.

Why is HSI a game-changer in testing for mycotoxins?

  • Rapid Testing: Results are available within seconds, compared to several minutes or hours with traditional tests.
  • Chemical-Free: Eliminates the need for consumables, reducing costs and environmental impact.
  • Zero Test Kit Supply Chain Issues: No more test kits. No more operational delays.
  • Increased Testing Capacity: Can scan more number of food samples at scale without disrupting operations.
  • Early Detection & Prevention: Identifies contamination before food processing or distribution, minimizing risk.
  • Seamless Integration: Easily incorporated into existing processing and quality control workflows.

Why choose ImagoAI’s Galaxy to test for mycotoxins?

ImagoAI’s Galaxy is an AOAC PTM-certified mycotoxin test that has pioneered the use of hyperspectral imaging technology and AI to enhance food safety.

It is at the forefront of hyperspectral imaging technology, delivering:

  • Myctoxin test results in less than 30 seconds: It is the world’s fastest mycotoxin testing method.
  • 4 Mycotoxin tests at once: Galaxy runs tests for aflatoxins, fumonisin, zearalenone, and DON simultaneously in corn, DDGS, wheat, and Corn Gluten Meal (CGM).
  • Easy-to-use test method: The test is completed with a single-step scan.
  • Reduced variability in test results: Galaxy eliminates manual errors that multiply through each step of the test kit-based testing process. 
  • Freedom from test kit supply chain issues: It prevents last-minute surprises due to test kit shortages.

Galaxy is fast gaining recognition as the “30-Second Mycotoxin Test” across the US and has helped leading grain elevators, animal feed mills, and ethanol plants transform their operations like never before. 

Here's a quick video of how Galaxy works:

Real-World Impact: A Case Study

A major player in the U.S. mycotoxin testing landscape recently adopted ImagoAI’s Galaxy after the organization suffered from processing delays and operational inefficiencies with traditional test kits. Their technicians also had to undergo significant physical strain when the test sample load was high. 

With ImagoAI’s Galaxy, the results were clear:

  • 95% Faster Testing – Reduced analysis time from 10 minutes to under 30 seconds per test, minimizing customer waiting time and enhancing operational efficiency.
  • Simultaneous Multi-Toxin Testing – It enabled multiple tests at once, significantly increasing throughput and reducing bottlenecks.
  • Zero Chemical Exposure - The elimination of hazardous chemicals and manual sample mixing significantly improved workplace safety for technicians.
  • Increased Productivity - With reduced physical strain on technicians, the lab was able to handle a higher volume of samples, streamlining overall operations.
  • 100% Digital Record-Keeping – Cloud integration ensured seamless data storage and eliminated delays in data retrieval and running additional tests.

With ImagoAI’s Galaxy, the future of mycotoxin testing is already here!  

Book a free demo today and discover how Galaxy can be your organization’s next big breakthrough.