Sensors for Intelligent Food Packaging

Sensors for Intelligent Food Packaging

Problem being addressed

With the increased demand for packaged food​,​ it has become vital for the food industry to increase the shelf life of food. However​,​ in recent years​,​ foodborne illnesses caused by microorganisms has become a major concern for the consumers as well as the packaging industries. Conventional packaging techniques are inadequate to address this issue.

Solution

One of the prime indicators of food spoilage in packed foods is the increased level of carbon dioxide gas. So, an intelligent packaging technique where a carbon dioxide sensor strip is placed above the food packet to monitor the level of concentration of the gas inside the package, can help the consumers in assessing the quality of the food packets.

Advantages of this solution

Such Carbon dioxide sensors are very suitable for use as food spoilage indicators and provides real time information to the consumers instead of the mere printed manufcaturing/expiry data on the packet. This is mainly advantageous in cases where the food comes from a very distant place and particularly in case of freshfood/raw items.

Possible New Application of the Work

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Agriculture Industry

Such sensors can also be used in greenhouses or in crop-storages for monitoring and maintaining the level of carbon dioxide gases.

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

Other Industry

Besides using in food packaging industries, such sensors could possibly be used in our homes/restuarants for early detection or onset of food/fruit spoilage. This would be very useful in reducing food waste having a direct imapct in reducing environmnetal pollution.

Source DOI: #############check-icon

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