3D printed food?

8

October

2021

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How does 3D food printing work?

Exclusive 3D printing restaurants are already a thing , while consumers can buy their own 3D food printers for their home! But, first and foremost, let’s explain what 3D food printing actually means. It is defined as the automated process of manufacturing food products using a variety of additive manufacturing techniques. The most common example of this currently is food grade syringes that hold the printing material, while a food grade nozzle deposits it layer by layer, the so-called extrusion-based printing technique. Additional printing techniques include selective laser sintering, in which powdered food materials are heated and bonded together to form a solid structure and binder jetting, which is similar in nature but uses a liquid binder instead of heat to bond the materials. Sometimes there are post-processes needed such as baking or frying, before the food is safe and ready for consumption.

Which foods can be 3D printed?

Not all foods can be 3D printed of course, at least at this point in time with the currently available technologies. The reason for this is that food materials need to be in paste-like form in order to be able to go into the cartridge, thus limiting the options significantly. Consequently, the types of foods that 3D printing is focused in right now come from inputs of purées, mousses and other sugary ingredients, cheeses, mashes and raw meats. On top of these, some companies are also creating 3D printed pizzas and pasta, or even burgers and sushi.

What are the benefits of 3D printing?

One of the important benefits provided by this process is the ability to cater to people with dietary restrictions, as the ingredients can be handpicked and personalized to each person’s needs and wants. The company Barilla for example, is using 3D printing technology to experiment with gluten-free pasta options. Moreover, 3D printed food can be healthier, as it provides the option of putting a custom amount of protein, sugar, vitamins, and minerals into the foods we consume. In a similar context, 3D printing can assist in reducing food waste by utilizing otherwise “useless” food products like meat off-cuts, distorted vegetables and fruits, sea food by-products and perishables, which can all be turned into a suitable form to be used in printing. For instance, Upprinting Food, a Dutch startup, has already been blending and combining different ingredients from food waste and turning them into materials for 3D printing.

Possible uses for 3D printing in the future?

The precision that can be achieved through this technology could prove to be very beneficial to hospitals for example in the future, where restricted diets may be a necessity. Another field that can benefit greatly from 3D printed food is space travel. The compactness and ease of use, as well as the ability to fulfill all the necessary nutritional requirements of astronauts, make 3D printing the ideal solution to cover the crew’s dietary needs. Lastly, 3D printing can be used to provide a sustainable food source to the world, by assisting in the effort to cover the immense and growing need for food due to the rapid increase of the world’s population.

All in all, 3D printing food is an innovative and exciting technology that has a lot of potential to disrupt industries that span several sectors and might seem totally unrelated at first glance. In reality though, 3D printed food is still in its infancy and needs to see a lot more advancement in its field before seeing a broader adoption from professionals and consumers.

References:

Carolo, L. 3D Printed Food (2021): All You Need to Know. all3dp (2021). Available at: https://all3dp.com/2/3d-printed-food-3d-printing-food/ (Accessed: 08 October 2021).

3dsourced (2021) ‘7 Exciting 3D Printed Food Projects Changing How We Eat Forever’. Available at: https://www.3dsourced.com/guides/3d-printed-food/  (Accessed: 08 October 2021).

Tom, M. 3D Printed Pasta – Are There Limits to the Benefits of 3D Printing in the Food Sector? digital.hbs.edu (2018). Available at: https://digital.hbs.edu/platform-rctom/submission/3d-printed-pasta-are-there-limits-to-the-benefits-of-3d-printing-in-the-food-sector/ (Accessed: 08 October 2021).

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How Greece used AI to detect asymptomatic travelers infected with COVID-19

29

September

2021

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A few months after the Covid-19 outbreak, operations researcher Kimon Drakopoulos, who works in data science at the University of Southern California, offered to help the Greek government by developing a system that uses machine learning in order to determine which travelers had the most risk of being infected and thus should get tested. Greece was asked by the European Union to allow non-essential travel again, but of course the option of testing all travelers was not available. Consequently, they chose to implement a more efficient way to test incoming travelers than the usual practices of randomized sample testing or testing based on the visitor’s country of origin, by launching this system called ‘Eva’ and deploying it across all Greek borders.

Drakopoulos and his colleagues discovered that machine learning proved to be more effective at identifying asymptomatic cases than the aforementioned methods, by a factor of two to four times during peak tourist season. This was accomplished because Eva used multiple sources of data, besides just travel history, to assess and estimate the infection risk of an individual. These sources include demographic data like the age and sex of the travelers, which was then paired with the obtained data from previously tested passengers, to calculate who had the highest risk out of a group and needed to be tested. This process was also used to provide information to the border policies about real-time estimates of the prevalence of COVID-19.

When the researchers compared the performance of this model against the methods that only use epidemiological metrics, such as random testing, it was clear that it performed better in all aspects. One main reason for this was the limited predictive value that these metrics possessed in relation to asymptomatic cases. Consequently, the paper raises concern on the effectiveness of internationally proposed border policies that employ such population-level metrics.

All in all, Eva is a successful example of how the use of reinforcement learning and artificial intelligence in combination with real-time data can provide very useful assistance both in crisis situations but also in the public health sector.

References

Bastani, H., Drakopoulos, K., Gupta, V. et al. Efficient and targeted COVID-19 border testing via reinforcement learning. Nature (2021). https://doi.org/10.1038/s41586-021-04014-z

Nature (2021) ‘Greece used AI to curb COVID: what other nations can learn’, 22 September. Available at: https://www.nature.com/articles/d41586-021-02554-y  (Accessed: 29 September 2021).

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