This article has been written by Gopalakrishnan Kumar pursuing a Training program on Using AI for Business Growth from SkillArbitrage.

 This article has been edited and published by Shashwat Kaushik.

Introduction 

Food is the first and foremost basic need of all the living organisms in the world. The word safety indicates the importance of safeguarding food from waste. The wastage happens predominantly due to the effect of microorganisms on the food. There are several factors, like purchasing food from unrecognised sources, practising poor personal hygiene, cleaning and sanitation, and chemical, physical and biological factors, that are all responsible for the contamination of the food. Salmonella and E. coli are among the most common foodborne diseases that cause illness and death, along with norovirus, Clostridium perfringens, campylobacter, and listeria. Food should be biologically, chemically and physically consumable so that it does not result in food borne diseases like food poisoning after consumption. There are a number of conventional methods used to make the food free from contamination. As this is a global concern and an ongoing challenge to feed the millions of people in the world, including humans and animals, there have been a number of studies done on food safety. Though we are living in the era of artificial intelligence, the basic needs of all the living organisms in the world are food and nutrition, which cannot be compromised. A remarkable breakthrough in the twenty-first century is the application of artificial intelligence to food safety.

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Need and importance of AI in food safety

Food is the most important factor that supplies energy to our body to keep us fit and healthy. Food is in the form of solids and liquids, which are the sources of nutrients. Nutrients are components of food that provide nourishment. The nutrients are classified into macronutrients such as carbohydrates, proteins and fats and micronutrients such as vitamins and minerals, as well as dietary fibre and water. Eating the right type of food with the proper quantity of nutrients is needed for growth, development, health and the maintenance of the body. So keeping the food free from bacteria and germs is vital; – else we would be prone to various food borne diseases. Though there are conventional methods followed to ensure food safety, the advent of AI in food safety provides a very  wide scope and avenues for making the food free from contamination. The use of AI in this process is effective, efficient and economical in terms of cost and time.

Artificial intelligence (AI) offers a transformative approach to enhancing food safety and ensuring the well-being of consumers. Here’s how AI can contribute to protecting food safety:

  1. AI-powered predictive analytics:
    • AI algorithms can analyse historical data on foodborne illnesses, consumer complaints, and environmental factors to predict potential food safety risks.
    • This predictive capability enables food producers, distributors, and retailers to proactively identify high-risk food items, production lines, or geographic regions.
    • Early detection of potential outbreaks allows for timely interventions and targeted preventive measures.
  2. Real-time food quality monitoring:
    • AI-based systems can monitor food quality in real time using sensors, cameras, and other IoT devices.
    • Continuous monitoring of temperature, humidity, and other environmental parameters helps ensure optimal storage and transportation conditions.
    • AI algorithms can detect anomalies, such as sudden temperature changes or unusual patterns, indicating potential food spoilage or contamination.
  3. Automated food safety inspections:
    • AI-powered visual inspection systems can automate food safety checks, reducing the need for manual inspections.
    • These systems use computer vision algorithms to detect foreign objects, mould growth, or other defects in food products.
    • Automated inspections ensure consistency, accuracy, and speed, minimising the risk of human error.
  4. Food traceability and supply chain management:
    • AI can enhance food traceability by tracking food products throughout the supply chain, from farm to fork.
    • Blockchain technology, coupled with AI, can create a secure and transparent ledger of all transactions, ensuring the authenticity and integrity of food products.
    • Real-time tracking allows for rapid identification of contamination sources and facilitates efficient product recalls, minimising consumer exposure to unsafe food.
  5. Risk assessment and decision-making:
    • AI algorithms can analyse vast amounts of data to assess food safety risks associated with specific food products, processes, or regions.
    • This risk assessment helps food businesses prioritise their efforts and allocate resources effectively.
    • AI can also provide decision-support tools to help food regulators and policymakers make informed decisions regarding food safety standards and regulations.
  6. Personalised food safety recommendations:
    • AI can personalise food safety recommendations for consumers based on their individual preferences, dietary restrictions, and health conditions.
    • AI-powered apps can provide tailored guidance on food storage, cooking temperatures, and other safe food handling practices.
    • This personalised approach empowers consumers to make informed choices and reduces their risk of foodborne illnesses.
  7. Food fraud detection:
    • AI algorithms can analyse food product labels, ingredient lists, and consumer reviews to detect potential food fraud, such as mislabeling or adulteration.
    • By identifying fraudulent products, AI helps protect consumers from deceptive practices and ensures the authenticity of the food they consume.
  8. Collaboration and data sharing:
    • AI facilitates collaboration and data sharing among stakeholders in the food supply chain.
    • Real-time data exchange between food producers, distributors, retailers, and regulators enables a coordinated response to food safety incidents.
    • This collaborative approach enhances overall food safety management and reduces the risk of widespread outbreaks.

Early exposure to technology in food safety

We have been witnessing the application of technology in all walks of life for the past two decades in general and food safety in particular. The concepts of healthy food and nutrition have been reflected in the fields of school and higher education. Later on, there have been opportunities to become professionals in the food industry with the advent of technology such as machine learning and further advancements in artificial intelligence. There were two such experiences worth mentioning.

Detection of e coli in farm water

Before discussing the different ways in which AI can be used to protect food from contamination and make it fit for consumption, I would like to mention my project experience, as an undergraduate student in Chemical Technology to detect the E. coli present in the agricultural pond. In the project titled “Application of Novel Metal oil to convert Non Potable water to Potable water,” the main objective was to detect the count of microbes (E. coli) present in the water by using E. coli solution and Agar Agar. This laboratory method took almost fifteen days to almost a month to complete the project.

Detection of plant health

Another experience as a budding data analyst in the agribusiness sector four years ago was a kind of preparatory step towards using artificial intelligence in the field of agriculture.

Initially, my senior consultant presented me with a problem definition for detecting good, Bad and blight leaves from a file containing approximately 3000 plant images of an agricultural farm. In this project, hyperspectral image processing and analysis techniques were used to detect plant health, which helps in better agricultural produce.

Hyperspectral imaging technology 

Using image processing and analysis methods and techniques, the spatial characteristics or colour attributes of food and agricultural products and crops or plants growing in

The fields are classified. Since surface or external characteristics are important to the consumer’s perception about product quality and, in many cases, are also a good indicator of product maturity and/or internal quality, imaging technology is being widely used in inspecting, monitoring, and grading a large class of agricultural and food products based on colour, size/shape, and surface texture during postharvest handling, packing,and processing.

Procedure adopted to classify the leaves

I was given plant images quantumwise, in which each quantum consisted of approximately 300-400 images. In this manner, I received 9-10 quantums of images. The images were taken by a digital camera and coloured. Computer size resolutions of imaging sensors of 640×480 pixels were used for the images. The purpose of the project was to convert the digital camera images of leaves into visual form, which should clearly indicate the health of the leaves, leading to the classification of good, bad, and blight. I must say that I enjoyed the whole process of the project, as I was given full freedom to choose the appropriate programming language of my choice. As a first step, using Spyder-Python, the raw images were converted to EPS images.

Artificial intelligence (AI) and its application in food safety

As far as the impact of Artificial Intelligence in Food industry is concerned, it plays a significant role in food production, quality, nutrition and waste. Where ML is focused on the ability to learn and make predictions, AI encompasses the ability to sense, reason, engage and learn. Though AI tools can be used in a number of ways, it can be classified in to

  • Vision,
  • Text,
  • Interactive,
  • Analytical, and
  • Prediction. 

As far as the agriculture sector is concerned, AI and robotics, with their sensors, can monitor crops, soil condition, climate, moisture level, rainfall, temperatures and water availability, thus increasing food production. Computer Functional Solutions. These tools can be applied in the food industry sector, which includes   cultivation, quality checks, tracking the food supply chain, automated packaging, the shelf life of food industry produce, trend analysis, and predictive analysis. The revolution created by AI, machine learning and robotics is manifold, of which two important aspects are discussed below.

Artificial intelligence (AI) in agriculture

Computer Vision (CNN) as a field of artificial intelligence can analyse images, which helps in pathogen detection and identification and protects crops to give good yields. Analytical tools are very effective in the agricultural process to predict hazards, monitor and adopt better agricultural techniques. The data pertaining to the environment is processed using analytical tools such as random forest and gradient boost to predict the presence of pathogens.

Artificial intelligence (AI) in supply chain

AI applications in food safety across agri-food supply chains have the potential to support traceability, monitoring, inspection, and other purposes and processes. In the field of retail, computer vision ( CNN) is used for foreign object detection and safety practice verification. Moreover, with the help of natural language processing, outbreak tracking can be monitored, which helps to check and improve food safety.

Artificial intelligence (AI) in warehousing storage

AI helps in inventory management to avoid stock outs and overstocking, which helps very much in reducing the waste of food products. The prediction analysis helps in determining the shelf life of products, ordering new stocks, delivery time and delivery date to customers, thus helping in customer satisfaction and an efficient supply chain.

Food safety laws in India

Food safety laws in India are a complex and comprehensive set of regulations designed to protect consumers from unsafe food. These laws are enforced by the Food Safety and Standards Authority of India (FSSAI), which is an autonomous body under the Ministry of Health and Family Welfare.

The FSSAI is responsible for setting food safety standards, regulating food businesses, and monitoring food imports and exports. It also works to raise awareness of food safety issues and promote safe food practices.

The Food Safety and Standards Act, 2006, is comprehensive legislation that aims to ensure the safety and quality of food in India. It is the primary law governing food safety in the country and provides a framework for the Food Safety and Standards Authority of India (FSSAI) to regulate the food industry. The act covers a wide range of food products, including processed foods, packaged foods, and imported foods.

The Food Safety and Standards Act, 2006 seeks to achieve its objectives through a number of provisions, including:

  1. Establishing a food safety regulatory system: The Act establishes the FSSAI as the central authority responsible for regulating food safety in India. The FSSAI is responsible for developing and enforcing food safety standards, monitoring the food industry, and taking action against violators.
  2. Regulating the food industry: The Act provides a framework for regulating the food industry, including the licensing of food businesses, the registration of food products, and the inspection of food premises. It also sets out the requirements for food labelling and advertising.
  3. Ensuring food safety: The Act contains a number of provisions aimed at ensuring the safety of food, including the requirement for food businesses to follow good manufacturing practices and the prohibition of the sale of unsafe food. It also provides for the recall of unsafe food products and the imposition of penalties for violations.
  4. Promoting food safety awareness: The Act also includes provisions aimed at promoting food safety awareness among consumers. These provisions include the requirement for food businesses to provide consumers with information about food safety and the establishment of a food safety education program.
  5. Strengthening the food safety infrastructure: The Act provides for the establishment of a number of institutions and mechanisms to strengthen the food safety infrastructure in India. These include the establishment of food safety laboratories, the development of a food safety information system, and the establishment of a food safety advisory board.

The Act covers a wide range of food safety issues, including:

  • Food hygiene and sanitation
  • Food labeling and packaging
  • Food additives and contaminants
  • Food import and export regulations
  • Food recall procedures

The FSSAI has also developed a number of regulations under the Food Safety and Standards Act, 2006. These regulations provide more specific guidance on food safety requirements for specific types of food businesses.

The FSSAI is also responsible for enforcing food safety laws. It has the power to inspect food businesses, collect samples for testing, and take enforcement action against businesses that violate food safety laws.

The FSSAI also works to promote food safety awareness among consumers. It does this through a variety of channels, including public awareness campaigns, food safety education programs, and food safety information resources.

The FSSAI is committed to ensuring that food in India is safe for human consumption. It works closely with food businesses, consumers, and other stakeholders to achieve this goal.

Conclusion

The role played by artificial intelligence is so immense and indispensable that it has reached the doorsteps of all households in the world, especially in India, where online shopping portals such as Amazon, Big Basket, Jio Mart and Flipkart have been performing a vital role, especially during pandemic times.

References

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