AI AND ML ARE HAVING A DRAMATIC IMPACT ON EVERY ASPECT OF FOOD MANUFACTURE
When foodtech is mentioned, most people will immediately think of the science involved in food production, the proteins, microorganisms, and fermentation processes.
Alternatively, you might jump to production, packaging and delivery processes or the increasing part robotics, drones, and 3D printing now play in the food industry.
The aspects of technology that might not feature in your thinking are Artificial Intelligence (AI) and Machine Learning (ML).
However, AI and ML are having a dramatic impact on every aspect of food manufacture. They help drive efficiencies. They support the formation of new ideas and new recipes. They encourage increased use of automation. They reduce human error which is critical when you are producing products that humans are about to ingest. Most importantly in these difficult times, they reduce waste, reduce the use of chemicals (both pesticides and fertilizers) in the fields and increase productivity and profitability.
In this special report we will examine which areas of food manufacture are benefiting from the introduction of AI and ML and look at the key considerations for maximising the value of the underlying innovation.
WHICH AREAS OF FOOD PRODUCTION CAN BENEFIT FROM AI?
AI innovations are starting to lay the foundations for a better future for the food industry. It has introduced sophisticated data science solutions to tackle some of the key issues the food industry faces including:
- IMPROVING FOOD SAFETY
Arguably the most important application of AI in the food industry is in food safety.
There are two potentially ground-breaking uses of AI that are widely tipped to come into widespread use very soon:
- NEXT GENERATION SEQUENCING (NGS)
NGS could eventually replace DNA in food safety testing. It can capture data and prepare lab samples more quickly and more precisely. It can also be used to highlight potentially dangerous trends and even prevent the outbreak of some diseases.
- ELECTRIC NOSES
These are electronic chemical sensors that can accurately identify a variety of odours and discern whether the odours they pick up could be signs of pollution or infection.
- NEXT GENERATION SEQUENCING (NGS)
- SUPPLY CHAIN OPTIMISATION
Food manufacture is rightly highly regulated to protect consumers. Part of this responsibility is to make sure the way a food product travels through its supply chain is transparent. AI can play a huge part in this. It can automate the tracking of goods from where they are grown or made all the way to the consumer's table.
However, as well as offering greater transparency in the providence of a foodstuff, AI can also reduce waste. By making more informed decisions on price, inventory and transportation, AI can prevent manufacturers form ending up with a surplus of goods at any stage of the supply chain, a surplus that would otherwise end up being wasted.
- IMPROVING PRODUCTION LINE PERFORMANCE
Most food production lines are made up of a series of highly complex machines. It is easy for these to go wrong from time to time. Repair is not only expensive in itself, the resultant delays in production will also be costly. AI can be used to predict when and where maintenance is needed based on past performance amongst other criteria.
AI can also identify what is/is likely to cause problems so you can act before they become issues to maintain the highest levels of overall equipment effectiveness on your production lines.
These are probably the highest-level applications for AI in food manufacture. However, as we've already said, a lot of food production is science and today, a lot of science is data. The real strength of AI and ML is they can keep you at the cutting edge of data science by using what you know to keep your business moving forward by:
- DRIVING THE USE OF NUTRACEUTICALS
The recent pandemic has sharpened our focus on healthy eating. This in turn has sent nutraceuticals back to the top of the food industry's list of priorities, particularly as the benefits of nutraceuticals extend to reducing our susceptibility to allergies, diabetes and disease.
- OPTIMIZING FOR FERMENTATION PROCESSES
If a drink producer or someone looking to develop a dairy or meat alternative wants a specific combination of taste, texture and nutrition, AI can make calculated predictions as to which microbial strains are most likely to work well together.
In the case of fermented dairy products in particular, as they have their own very specific characteristics, AI's predictions will not only inform potential combinations of ingredients but also identify the levels of nutrients the final product will offer. These properties are crucial to the development of products that are genuinely healthy as well as great tasting.
- ACCELERATING THE PRODUCTION OF ALTERNATIVE
PROTEINS
Cultured meats and plants are the primary sources of alternative proteins. Advancements in the use of AI in fermentation and molecular biology have empowered manufacturers to find more efficient and more sustainable alternate protein discovery and production solutions.
- GREATER PRECISION
AI has become increasingly important to improving the overall harvest quality and accuracy. AI can assist in detecting disease in plants, pests and nutrition levels in the soil and AI sensors can detect different diseases in agricultural crops and decide which and how much of a particular pesticides or combination of pesticides should be applied.
- OPTIMISING PLANT BREEDING
AI is increasingly being used to shape modern crop breeding.
Improvements in crop phenomics and enviromics (in addition to many other 'omics') is helping researchers understand the complex relationship between genes and agronomic traits. AI injects huge additional computational power and many new tools and strategies that will improve future breeding further still over the coming years.
- WIDENING THE POTENTIAL OF 3D PRINTING
3D food printers are now producing nutritious personalised diets and alternative protein-based meals. Some manufacturers are even experimenting with laser and inkjet food printing and bioprinting methods to develop new food products that meet personal nutrition demands and reduce food waste.
- IMPROVING FOOD-WASTE TRACKING
Far too much of the food produced around the world is still lost or wasted. AI can track food wastage so that trends can be capitalised on to minimise waste in shops, restaurants, hotels, and smart cities and is helping food manufacturers realise their aim of achieving zero waste.
- IMPROVING FOOD SORTING
Historically manufacturers would have to employ a large amount of low skilled workers to sort through fruit and vegetables to separate them for different purposes or to discard them entirely if unsaleable. Today AI can do all of this by size, purpose or even colour.
This doesn't only make the process more efficient and more cost-effective for producers, it also increases food quality and safety for the consumer.
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