IIT-G's Paper Sensor Can Assess Quality Of Milk In Minutes

Researchers at the Indian Institute of Technology (IIT) Guwahati have developed a paper-based sensor that can accurately assess the quality and freshness of milk within minutes by changing its colour.

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Krishnendu Chatterjee
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IIT-G's Paper Sensor Can Assess Quality Of Milk In Minutes

IIT-G's Paper Sensor Can Assess Quality Of Milk In Minutes( Photo Credit : File Photo)

Researchers at the Indian Institute of Technology (IIT) Guwahati have developed a paper-based sensor that can accurately assess the quality and freshness of milk within minutes by changing its colour. The quality and freshness of milk are decided by the invasion and presence of microbes in the milk, the researchers explained in the study published in the journal Biosensors, and Bioelectronics.

They noted that bacteria and other microbes that grow in milk can not only affect its taste and freshness, but also result in health issues. Pasteurisation is commonly used to kill the microbes in milk and various tests are used to ensure the effectiveness of the process, according to the researchers led by Pranjal Chandra, an assistant professor at IIT Guwahati. Commonly used tests such as the methylene blue test, are time consuming, and could take many hours for colour changes to indicate the presence and absence of microbes.

Commercial phenol-based tests require sophisticated spectrophotometers and involve multi-step procedures, which necessitates dedicated testing centres and skilled personnel. The team, including scholar Kuldeep Mahato, developed the simple visual detection technique to assess the quality of milk, without the need for special equipment and instruments.

"It would be useful if the quality of milk can be tested at the point of collection of milk or even in the home kitchen," Chandra said in a statement, adding that such testing requires easy-to-operate and portable detection kits.

Chandra explained that Alkaline Phosphatase (ALP) is a metalloprotein found naturally in raw milk samples, and is considered an important biomarker in the quality control of milk.

It is found in raw milk and is destroyed during pasteurisation.  ALP is also found in higher amounts in the case of milk derived from animals with infection in the mammary glands, he noted. Detection of ALP in milk can thus point to inadequate pasteurisation and perhaps contamination.

"Despite ALP's recognisable detection potential in native milk, the multi-step nature, and requirement of sophisticated bulky analytical instruments and trained personnel, to detect ALP, limit their use as a sensor of milk quality in remote settings and in-home kitchens," added Chandra.

The researchers used simple filter paper, chemically modified it, and loaded it with a recognition element -- anti-ALP -- which captures the ALP present in the milk.

Upon treatment with the colour-forming compound 'BCIP', the captured complex of ALP forms a blue-green coloured precipitate, that otherwise does not give any colour in the absence of ALP. The intensity of the colour indicates the amount of ALP present. The researchers used a smartphone to capture the image of the colour.

They used the RGB (Red Green Blue) filter in the phone to profile the colour obtained, which could be co-related to the concentration of ALP present in the test sample. "Our sensor takes merely 13? minutes to detect ALP, and hence it can be applied for quick onsite analysis," said Chandra.

The researchers successfully tested milk obtained from villages and commercially available milk samples using their paper-based sensor kit, and found that they could detect down to 0.87 units of ALP per millilitre of milk to about 91 to 100 per cent accuracy.

This detection limit and accuracy make it possible to discriminate raw milk from pasteurised or boiled milk which contains ALP in ultra-trace amounts, the researchers said. Based on the detection principle, the team has also developed a miniaturised detection kit and demonstrated the instrument-free, in-kitchen applicability of the kit for milk monitoring, they said.

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