Real-Time Food Quality Analysis Using HSI
Updated: Apr 20
With modernization in every space or industry through technology, food quality testing is not the exception. The world is rapidly evolving at a higher pace with the increasing demand for speed and innovative ways of doing things.
With a bundle of tasks required to be completed in a limited amount of time, it is always prudent to clear mental space through shifting manual and routine tasks to smart solutions.
In this blog, I will focus on one of the most challenging aspects related to food quality testing. Still, most of the food processing companies are doing quality testing using the traditional approach of laboratories, investing heavily in infrastructure and different bulky equipment. Analyst/chemist need to wait for a couple of hours to get the results as there are a lot of complex quality steps involved as below:
Lots of questions pop up such as:
Do we need to necessarily follow all the above steps in food quality testing in spite of much technological advancement?
Do we need to wait for a couple of hours to get the results?
Do we need to train the chemist or technician to carry out the task of quality testing?
Do we need to invest heavily in testing equipment?
The answer to all these questions is a big NO as food quality testing can be now done in real-time in just 40 seconds with the advent of a hyperspectral imaging solution embedded with AI.
How it is possible to test the food in just 30 seconds?
With the combination of hyperspectral Imaging solution and Artificial Intelligence, it is definitely possible to test the food quality in just 30 seconds.
For a technological expert, Hyperspectral Imaging uses an imaging spectrometer to collect spectral information. This device is called a hyperspectral camera which measures hundreds of spectra at each pixel, unlike single-point spectroscopy. The collected spectra are used to form a 3-D image of the target food called a hyperspectral cube. By analyzing this 3-D image, real-time insights can be gathered on 'what is in my food, how much and where?'
For a layman, Hyperspectral Imaging is seeing beyond what our human eye can see. In other words, the human eye is restricted to see things on the surface whereas HSI allows us to see beneath the surface
How it is beneficial to the food processing companies if they get real-time food quality analysis?
It is of immense benefit to the food processing companies to get real-time insights about the food. Today it is not the big who eat the small anymore. It is the fast who eat the slow.
Adopting a faster solution to do the things always works in favor of the companies as they can do more in a limited span of time giving them a significant competitive edge over their peers.
Isn’t it great when the food testing is possible in a fraction of a minute?
Following are the steps involved:
The user places a food sample on the system tray with no sample preparation making it hygienic, contactless, and safe.
Scans the sample:
The hyperspectral camera scans the food sample in seconds capturing full spectrum wavelength at each pixel.
ImagoAI advanced AI software gives actionable insights such as chemical composition, micro-contaminants
Why there is an urgent need for the food company to go for the Real-Time Quality Analysis
Below is the table in which you can see how Hyperspectral Imaging Solution covers all the limitation that the traditional method has :
From the above table, it is obvious that the hyperspectral imaging solution for food quality analysis is highly efficient than the traditional methods in all aspects. Now I will talk about the diverse application of the different hyperspectral cameras. In the below table you can see the classification of the hyperspectral camera on the basis of their wavelengths along with their respective applications.
Classification of the hyperspectral camera and its application
There are three types of hyperspectral cameras based on the wavelength covered.
In nutshell, I would say hyperspectral imaging offers new possibilities in the food industry to map the distribution of constituents over the surface of a sample. This capability is useful for food analysis at the laboratory research scale, plant operations, raw ingredient procurement side, and finished product stage.