The chef behind Wales' only two-Michelin-star restaurant has said he is not embarrassed after it was awarded a one-star hygiene rating. Ynyshir Restaurant and Rooms, near Machynlleth in Ceredigion, which charges nearly £500 per head, received the rating after a visit by food safety officers on 5 November. According to the Food Standards Agency (FSA), a score of one out of five means major improvement is necessary. But chef patron Gareth Ward, a contestant on MasterChef The Professionals, said the restaurant was working at the highest standard in the world and doing something different with how it approaches raw ingredients and techniques. Ynyshir offers a high-end dining experience starting at £468 per person, including a 30-course tasting menu and an in-house DJ.

Mycotoxins are a group of naturally occurring, toxic chemical compounds produced by certain species of moulds (fungi), during growth on various crops and foodstuffs, including cereals, nuts, spices and dairy products (The World Health Organization (WHO), 2023). The ingestion of certain mycotoxins has been linked to a range of harmful health impacts on both humans and animals, from short-term poisoning to long-term consequences such as liver cancer, and in some cases, death (Mavrommatis et al., 2021; Marroquín-Cardona et al., 2014; Liu and Wu, 2010). Mycotoxins are secondary metabolites (that is, compounds produced by an organism that are not essential for its primary life processes) and are often produced during the pre-harvest, harvest, and storage phases under favourable conditions of humidity and temperature (Marroquín-Cardona et al., 2014; Van der Fels-Klerx et al., 2022). The most prevalent mycotoxins include aflatoxins, tricothecenes, fumonisins, zearalenones, ochratoxins and patulin, and are produced by certain plant-pathogenic species of Aspergillus, Fusarium, and Penicillium (Tola and Kebede, 2016). Mycotoxin contamination in crop products has been found to vary significantly across different geographical locations and is influenced by annual weather conditions (Logrieco et al., 2021; Leggieri et al., 2020).

Food recalls could be a thing of the past if artificial intelligence (AI) is utilized in food production, according to a recent study from UBC and the University of Guelph. The average cost of a food recall due to bacterial or microbial contamination, like E. coli, is US$10 million according to study co-author Dr. Rickey Yada, a professor and the dean of the UBC faculty of land and food systems. We spoke with Dr. Yada about how AI can help optimize the current systems used in the food processing industry, and how it can help make our food supply safer. What are some of the current limitations when it comes to food processing? The current challenge is that food safety problems tend to show up after the fact once the products have been shipped, sold, or in some cases already consumed.

On July 14, Key Technology debuted its new FM Alert software driven by artificial intelligence (AI). The new AI alert system can help processors control foreign materials entering product streams, as well as improving documentation and overall food safety. It will be a part of the company's exhibit at Pack Expo in October at booth S-3547. The AI system captures and saves images of foreign materials (FMs) that a sorter detects and rejects from its stream, with data available immediately to alert operators. "Thanks to the application of advanced artificial intelligence, our new FM Alert software achieves uniquely accurate results -- identifying, recording and acting on true FM findings on the line," said Marco Azzaretti, director of marketing at Key. "The food processing industry continues to focus more and more on elevating food safety. By making product safer, this effective FM-fighting tool helps customers protect their brand's reputation and avoid costly recalls. Every food processor wants to prevent contamination, making FM Alert universally beneficial across all applications."

Key Technology introduces AI-driven FM alert software for its digital sorting systems. This powerful tool captures and saves digital images of critical foreign material (FM) contaminants that the sorter detects and rejects from the product stream. Data outputs from the software can be utilized to immediately alert operators and/or signal a downstream device. AI-enhanced FM Alert helps processors better control FM and improve documentation to protect food safety. "Thanks to the application of advanced artificial intelligence, our new FM Alert software achieves uniquely accurate results – identifying, recording, and acting on true FM findings on the line," said Marco Azzaretti, director of marketing at Key. "The food processing industry continues to focus more and more on elevating food safety. By making product safer, this effective FM-fighting tool helps customers protect their brand's reputation and avoid costly recalls. Every food processor wants to prevent contamination, making FM Alert universally beneficial across all applications."

Many of these challenges are caused by inefficiencies in the food processing and distribution supply chain, which is a vital value-added step in our food system. The pieces of the puzzle are all there: ubiquitous sensors and devices that generate data with unprecedented volume, velocity and veracity; mature computational methods to make use of them; connected markets that can take advantage of these innovations at a global scale; and a need to transform antiquated, obsolete components of the current system, whether because of consumer demand for personalization and empowerment, or the need for global food safety and sustainability. Millions are spent every year in both the private and public sector to bring forth innovative solutions in capturing market preference, food safety, food security, provenance and traceability, all the while creating superior products that taste good, are good for your health and don't break the bank.

The vast body of scientific publications presents an increasing challenge of finding those that are relevant to a given research question, and making informed decisions on their basis. This becomes extremely difficult without the use of automated tools. Here, one possible area for improvement is automatic classification of publication abstracts according to their topic. This work introduces a novel, knowledge base-oriented publication classifier. The proposed method focuses on achieving scalability and easy adaptability to other domains. Classification speed and accuracy are shown to be satisfactory, in the very demanding field of food safety. Further development and evaluation of the method is needed, as the proposed approach shows much potential.

To understand the promise and peril of artificial intelligence for food safety, consider the story of Larry Brilliant. Brilliant is a self-described "spiritual seeker," "social change addict," and "rock doc." During his medical internship in 1969, he responded to a San Francisco Chronicle columnist's call for medical help to Native Americans then occupying Alcatraz. Then came Warner Bros.' call to have him join the cast of Medicine Ball Caravan, a sort-of sequel to Woodstock Nation. That caravan ultimately led to a detour to India, where Brilliant spent 2 years studying at the foot of the Himalayas in a monastery under guru Neem Karoli Baba. Toward the end of the stay, Karoli Baba informed Brilliant of his calling: join the World Health Organization (WHO) and eradicate smallpox. He joined the WHO as a medical health officer, as a part of a team making over 1 billion house calls collectively. In 1977, he observed the last human with smallpox, leading WHO to declare the disease eradicated. After a decade battling smallpox, Brilliant went on to establish and lead foundations and start-up companies, and serve as a professor of international health at the University of Michigan. As one corporate brand manager wrote, "There are stories that are so incredible that not even the creative minds that fuel Hollywood could write them with a straight face."[1]

Machine vision has long found a place in food safety, working 24/7 without fatigue. But as data access increases and processing power improves, machine vision is finding even more opportunities through the added capabilities of artificial intelligence (AI). To take one example, traditional machine vision tends to struggle to inspect for contamination in sun-dried tomatoes. But it's an application that's well suited to AI. "Similar to a human, AI is very good at dealing with a lot of variations in whatever's being looked at," says Quinn Killough, senior business development manager for Landing AI, a company that provides end-to-end AI platforms for manufacturing. "That type of application, because there's so much variability in what a tomato could look like or what kind of contamination could be on it, it was a pretty tough machine vision problem in general. A human can do it easily. And it turns out AI can do it fairly easily as well. Being able to deal with all that variation in what you're looking at, it makes it very well suited for AI."

Landing AI is helping food producers overcome not only the limitations of their human workforce but of traditional machine vision as well, using machine …