NIT Rourkela unveils AI-based tech for instant spice adulteration detection

NIT Rourkela researchers develop FTIR and AI-based system to detect and quantify spice adulteration within seconds, offering faster and cost-effective food safety monitoring

Adulteration in spices can now be detected in seconds. In a significant innovation, researchers at the National Institute of Technology (NIT), Rourkela, have developed and patented a rapid technology that can detect and quantify adulteration in spices and food products within seconds.

 

This new technology comes at a time when food adulteration drew national scrutiny following the tragic death of four members of a family in Mumbai after allegedly consuming watermelon. The Mumbai incident, which took place on Sunday, has raised fresh concerns over food contamination and unsafe practices in the supply chain.

 

Although authorities have sent watermelon samples for forensic examination to determine whether toxic chemicals or adulterants were involved, this has reignited debate over India’s food safety monitoring systems and the urgent need for faster, more reliable screening technologies.

 

The NIT researchers have secured a patent for a system that combines Fourier Transform Infrared (FTIR) spectroscopy with advanced machine learning models to rapidly identify and measure adulteration levels in spices and other food products.

 

Unlike conventional laboratory methods that often take hours or even days and require expensive chemicals, trained personnel, and elaborate sample preparation, the newly developed technology can deliver highly accurate results in a matter of seconds.

 

The patented technology, titled “Method and System for Detecting and Quantifying Adulteration in Food Stuff” (Patent number: 581403), has been developed by Sushil Kumar Singh, assistant professor in the Department of Food Process Engineering, Late Prof Poonam Singha, and an MTech graduate, Rishabh Goyal.

 

Food adulteration remains a persistent challenge in India, especially in spices, edible oils, milk, fruits, and processed foods. Adulteration is often driven by profit motives, where inferior, artificial, or harmful materials are mixed with genuine products to increase volume or improve appearance. Such practices compromise quality, cheat consumers, and can pose severe health hazards ranging from digestive illness to organ damage and even death.

 

The new system addresses these limitations with a rapid, non-destructive, and cost-effective alternative suitable for real-time deployment in quality control laboratories and industrial processing units. The FTIR spectroscopy technique used in the system helps identify organic and some inorganic materials by measuring how they absorb infrared light.

 

"Every substance creates a unique spectral fingerprint based on its chemical composition. The NIT system captures these fingerprints from food samples and feeds the data into machine learning algorithms trained to identify patterns associated with adulteration," said Singh.

 

Unlike conventional methods that only show whether the food product is adulterated or not, he said, the new technology measures the level of adulteration of food within seconds. This capability is essential for food processing industries and regulatory bodies that require precise measurements to ensure compliance and maintain product quality, he maintained.

 

According to the researchers, powdered spices such as turmeric, chilli, coriander, and cumin are frequently mixed with fillers, synthetic colours, brick powder, starch, husk, or industrial waste. Since adulterants are often visually difficult to detect, many consumers unknowingly consume contaminated products.

 

Traditional detection methods such as chromatography, chemical assays, and molecular diagnostics are scientifically robust but expensive, time-consuming, and largely confined to specialised laboratories. This limits their use for routine inspections, especially in small industries and price-sensitive markets.

 

As part of a study, published in the Food Chemistry journal, the researchers have tested the system on coriander powder adulterated with sawdust, a known malpractice in spice markets. Using FTIR spectroscopy integrated with machine learning models, the system achieved around 92 per cent accuracy in detecting the adulteration.

 

"The study also establishes a broader framework that can be adapted for multiple adulterants across different food products, opening the door for large-scale commercial use," said Goyal.

 

Researchers said the innovation could significantly improve food safety compliance while strengthening consumer trust across supply chains. On commercial use, Singh said any food company handling spices — from raw material procurement to packaging of final products — requires rapid testing tools.

 

“Our developed system can seamlessly integrate into their existing quality control workflows and allow real-time decision-making, which is highly suitable for routine screening. With its scalability and cost-effectiveness, the system has strong potential for adoption by both large industries and SMEs,” he said.

 

India is one of the largest producers and exporters of several spices, including turmeric, chilli, cumin, and coriander. Maintaining quality standards is crucial not only for domestic consumers but also for exports, where contamination can trigger international recalls, shipment rejections, and reputational damage.

 

"The NIT Rourkela system could help companies carry out frequent batch screening without slowing production by reducing testing time, manpower needs, and reagent costs," Singh added.