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Artificial Intelligence in Food Supply Chains

Updated: Jul 18, 2023

As the FDA plans to use AI to ‘scan external information’ so it can focus its resources on areas of risk, it follows that food businesses will need do the same.

In this blog we will consider key concepts on how industry can do this and discuss how Primority used AI technology to successfully achieve much of what FDA are seeking to do.

Before considering AI and its uses in food supply chains, it is useful to understand what AI is.

What Is Artificial Intelligence?

Investopedia defines AI as “Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving.”

This definition highlights the comparison between the ‘intelligence’ of machines and humans. Specifically, how computer software can replicate and exceed the logic and processing capabilities of the human brain.

This means learning like humans is a key goal in AI. Therefore, the ability to reason and solve problems by identifying patterns in large amounts of data is important.

Several layers of disciplines within AI have evolved as the technology has developed. These are shown below:

A brief explanation of each layer of AI is given below:

Artificial Intelligence: This is the umbrella term for technologies that can learn and reason like humans. This could be as simple as logical rules, e.g., in a computer system with a camera and a temperature measuring device a camera may ‘look’ at the sky and see a predominantly blue colour while the temperature probe senses a warm temperature. In this case the system might conclude that it is a nice summer day.

Machine Learning: This is the act of teaching the system to learn and involves feeding it enough data with existing answers or results so it can learn from those results. With this knowledge the machine can go on to predict the answers to problems that it does not have the answers to in advance. In this way, it replicates the kind of repetitive, experiential learning that humans experience. For example, on Amazon’s “Products you might also like” AI is used to profile buyers based on age, location, the time of year, or even the upcoming weather pattern to sell, for example, a pair of nice warm gloves in winter.

Deep Learning: This is where a much heavier load of data is processed and typically a map of connections between the data is created by the machine, much like the neural connections in the human brain. The strength of these connections allows the machine to effectively become like a decision-making machine in the same way that humans can become highly skilled at certain tasks by massive repetition of certain behaviours, e.g., Golf professionals often take over 10,000 hours of practice to develop the necessary muscle memory get to Pro level.

AI technology can be very powerful at seeing patterns in data that humans cannot because they can work at very high speed with vast arrays of data, and they can do this 24/7 at low cost, easily outperforming humans. This makes AI a very useful productivity tool and, in the context of food safety and traceability, a potential source of intelligence on risks in food supply chains.

Existing Applications of AI in Food Supply Chains:

AI is being exploited in many ways in the food industry. Some examples include:

  • Food Authenticity – BriteScan - “uses state-of-the-art Computer Vision (CV) and Deep Machine Learning algorithms similar to fingerprint and facial recognition applications. Cloud-based AI software automatically evaluates all visual aspects of the [food product] images, including colour, texture, and size, even that which is not detectable by the human eye or even a microscope. Because it evaluates materials at a pixel level, it can authenticate species and tissue type, detect adulterants such as fillers and filth, both biological and non-biological.”

  • Crop Disease Control & Productivity – AppHarvest - “Uses camera sensing technology with AI-driven ripe detection to harvest only fruit that is ready using robotics and an indoor farming model that uses 90% less water and no pesticides. This leads to better yields, less food waste and contributes to sustainable farming to help feed a growing human population.”

  • Artificial Intelligence (AI) Imported Seafood Pilot program – FDA - “The U.S. Food and Drug Administration has launched the second phase of its Artificial Intelligence (AI) Imported Seafood Pilot program. The pilot is designed to enhance and improve the agency’s ability to quickly and efficiently identify imported seafood products that may pose a threat to public health. This is especially important since the United States imports upwards of 94 percent of its seafood supply.”

  • AI Powered Food Supply Chain Monitoring – Primority - “Primority have built an AI Powered supply chain monitoring solution called AI Scan which gathers data on food safety alerts, incidents, and regulatory compliance issues. The system risk assesses and analyses the information using a combination of algorithms, AI and a unique technology called Anomaly Detection to spot supply chain issues.”

  • IBM’s AI assisted e-tongue Could Fight Food Fraud – IBM - “IBM Research is currently working on Hypertaste, an electronic, AI-assisted tongue that, researchers say, draws inspiration from the way humans taste. Because liquids contain many different molecules, IBM said it is therefore inefficient to identify each separate component. Instead, Hypertaste uses ‘combinational sensing’ – an approach that resembles our natural senses of taste and smell. A mobile app transfers the data to a cloud server, where a trained machine learning algorithm compares the digital fingerprint just recorded to a database of known liquids. The algorithm figures out which liquids in the database are most chemically like the liquid under investigation, and reports the result back to the mobile app.”

AI technology is being deployed to help solve a diverse set of problems related to productivity, food safety and quality, authenticity, food fraud and food supply chain risk management. The total AI technology market is growing at 16.4% pa and the industry is currently worth $325bn and set to top $500bn by 2024. As food represents most of the manufacturing worldwide, a very large portion of AI technology will be employed in the food sector and generate tremendous value.

If you would like to learn more about how Artificial intelligence is revolutionising the food safety sector, please feel free to get in touch today.



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