Food fraud, shortage and wastage – on the chopping block

What exactly will change in terms of technology for tech-first, transparent and sustainable food industry disruptions to take place?

Consumers have already begun paying closer attention to what they eat, especially by checking ingredient lists and preservative claims. The next shift will be about ensuring that these claims are not just stated on the pack, but are actually enforced throughout the supply chain.

Technology will increasingly move upstream—from checking finished products to controlling ingredient quality at the source. AI-based systems can help assess raw material quality at scale, including detecting contaminants such as aflatoxins in grains, which are difficult to identify reliably through manual inspection.

AI-based systems can help assess raw material quality at scale, including detecting contaminants such as aflatoxins in grains, which are difficult to identify reliably through manual inspection.

At the same time, digital systems will play a key role in establishing ingredient provenance and end-to-end traceability, from farm to final pack. Together, these technologies will help turn transparency from a marketing claim into an operational reality that can be measured and verified.

How do you cover questions like scale and affordability with traditional processing, single-source procurement, shorter shelf-lives and authenticity?

Scale and affordability become difficult when traditional processes rely on fragmented sourcing and multiple intermediaries. We address this by combining authentic sourcing with a lean, technology-enabled supply chain.

Most of our products are sourced directly from farmers through our Khetika SAATHI centres, which removes several layers of middlemen and helps us maintain better price control as well as quality consistency. While our processing methods remain traditional, the surrounding supply chain is designed for speed and efficiency.

We operate micro-manufacturing and distribution nodes that are suited to short shelf-life products and 24-hour delivery cycles. Data-driven demand forecasting further helps us avoid overproduction and stock-outs. Authenticity is reinforced through blockchain-based traceability that tracks products from farm to pack, ensuring that scale does not come at the cost of trust.

How easy and in-action are technologies like blockchain for improving traceability?

Blockchain becomes truly useful when it is embedded into day-to-day operations rather than treated as a digital database.

At Khetika, traceability begins at the farm level through our SAATHI application, where sourcing and quality data is captured and recorded on a blockchain ledger. Each batch of raw material is tagged with a unique QR code and scanned at every stage of the supply chain.

Every scan creates a time-stamped, immutable record. Because these entries cannot be altered later, traceability becomes tamper-proof by design. This makes it possible to trace any product back to its source with a high degree of confidence.

How does clean labelling work?

Clean labelling goes beyond listing ingredients correctly on a pack. It works when transparency is supported by disciplined sourcing and processing decisions.

At a basic level, clean-label products use simple, recognisable ingredients and avoid artificial colours, flavours, and preservatives. However, many products remain technically compliant while still relying on additives that may have long-term health implications.

Clean labelling goes beyond listing ingredients correctly on a pack. It works when transparency is supported by disciplined sourcing and processing decisions.

At Khetika, we focus on designing products to be preservative-free and toxin-free from the start. Technology helps us enforce this upstream—by controlling ingredient quality, monitoring processes, and ensuring that unwanted substances never enter the system. When clean labelling is backed by such controls, it builds real and lasting consumer trust.

Tell us more about AI-led quality verification. How critical is the data aspect for this to work?

AI-led quality verification is heavily dependent on both the quality and structure of data.

At Khetika, we use SuperGRT (Grain Recognition Technology), a patented system developed in-house, which uses image processing and artificial intelligence to perform rapid, grain-level quality assessments for grains and dry fruits.

Our deep-learning and machine-learning models have been trained on millions of images, but volume alone is not enough. Accurate labelling is critical. Our technology teams work closely with quality and product experts to tag detailed attributes such as insect damage, weevils, deformities, and surface defects. This collaboration allows the system to assess commodity quality objectively and consistently at scale.

Would IoT-based changes work given the complexity and fragmentation of food supply chains?

IoT works best when applied selectively to critical control points rather than attempting to digitise the entire supply chain.

At our SAATHI centres, moisture sensors and temperature monitors help maintain raw material quality before processing. For perishable products such as batters, temperature logging across storage and transportation helps preserve freshness without relying on preservatives.

We are developing tools that allow consumers to scan or photograph ingredient lists and receive clear explanations of what those ingredients mean for health.

In production environments, SCADA systems provide real-time monitoring and tighter control over manufacturing processes, improving both quality consistency and operational efficiency. Even in fragmented supply chains, such targeted use of IoT can significantly reduce variability and risk.

How can technology help in preservative-free, personalised and clean-convenience food ahead?

Regulatory frameworks like FSSAI mandate ingredient and nutrient disclosure, but labels are often difficult for consumers to interpret. Claims such as healthy or natural may be compliant, yet still misleading without proper context.

Technology has a dual role here. First, it ensures that harmful preservatives, artificial colours, and additives are systematically excluded from products at the formulation and processing stages. Second, it helps bridge the gap between disclosure and understanding.

We are developing tools that allow consumers to scan or photograph ingredient lists and receive clear explanations of what those ingredients mean for health. This helps consumers make informed choices based on substance rather than marketing claims.

What kind of use cases can you cite to illustrate what’s possible with technology?

Some practical use-cases include AI-based detection of impurities and pesticide residues in raw materials before they enter production, SAATHI farmer hubs that combine QR-based traceability (which is an industry-first and only we are doing it) with digital quality labs, and single-origin sourcing supported by SCADA-driven monitoring in spice processing.

Together, these use-cases show how technology can enable proactive quality control, improve transparency, and maintain nutritional integrity at scale.

Can technology help address food fraud, food waste, shortages and health concerns?

Yes, technology plays a critical role across all these areas. AI-driven quality verification helps identify adulterants, toxins, and chemical residues early, reducing both health risks and food fraud. Clean-

label systems combined with transparent ingredient data help consumers navigate health concerns and misinformation.

On the supply-chain side, lean, technology-enabled planning and shorter production cycles reduce overstocking and spoilage. Better demand forecasting also improves responsiveness during sudden shortages, helping the system adapt rather than relying on excess inventory.

pratimah@cybermedia.co.in