TOMRA Food presents its new organisation and its new AI-based solutions 

TOMRA Food presents its new organisation and its new AI-based solutions 

At Fruit Logística Berlin, industry leader TOMRA Food unveils its new organisational structure for the future and presents its latest innovations using Deep Learning technology.

TOMRA Food has unveiled its new, leaner and more agile organisational structure, presented its sorting, grading and packaging solutions, and launched three new AI-based sorting and grading solutions in Berlin.

The announcements were made yesterday at a press conference held at the Fruit Logistica exhibition in Berlin (Germany) by Harald Henriksen, Executive Vice President and Managing Director of TOMRA Food, and Karel Strubbe, Director of the EMEA region of TOMRA Food.

In the afternoon, Sebastian Stoof, Vice President and Head of Customer Value Chain at TOMRA Food, gave a presentation on the event’s Tech Stage. There he talked about how sorting and grading solutions in the food industry have evolved thanks to AI.

Fruit Logistica Berlin, held from 7 to 9 February at Berlin's ExpoCenter City, is the world's leading event for the fresh produce industry, attracting visitors from 140 countries.

Closer to the customer with the new organizational structure

TOMRA Food's new structure creates an organization that is more customer-centric, more agile and responsive, and more innovative in order to deliver effective solutions to the market. To achieve this, it has adopted a new regional structure consisting of 3 regions: EMEA, Americas and APAC. 

Within each region, the company has merged its TOMRA Processed Food and TOMRA Fresh Food business areas into a single TOMRA Food team. In addition, and as a key part of the new structure, a new TOMRA Food team has been created. Hub central office that brings together R&D, product development and operations tasks in order to increase TOMRA Food's operational efficiency and its agility in terms of innovation. 

Mr Henriksen explained at the event: “Throughout its history, TOMRA Food has demonstrated its ability to adapt and innovate in order to deliver the solutions our customers need at any given time. That is what we are doing with our new organisation. This change will benefit our customers in a number of ways. The regional approach will enable us to operate as their local partner, maintaining a more direct dialogue with our customers and responding quickly to their specific requirements. The unification of our two business areas into one TOMRA Food team will enable us to leverage best practices from each, work more effectively and deliver world-class solutions and services. Finally, the centralisation of our R&D and operations will enable us to leverage the collective experience and efforts of our entire team, promote our ability to innovate and deliver better solutions to our customers to lead the resource revolution with them.”

Part of TOMRA Food’s commitment to meeting the real needs of its global customers is its excellent collaboration with its partners. This is the case of ICOEL, the Italian manufacturer of fruit handling, processing and packaging equipment, whose stand at Fruit Logística shares the reception area with TOMRA Food.

New AI-based grading and sorting solutions

TOMRA Food presented three solutions that demonstrate how artificial intelligence is changing food sorting and grading. The first is TOMRA Neon, a new blueberry pre-sorter that incorporates AI to detect bunches with unprecedented accuracy. The compact, durable and easy-to-clean machine brings value to downstream blueberry sorting and packing operations. Extensive validation testing has shown that the TOMRA Neon removes over 95 % from bunches and over 90 % from unwanted red and green blueberries to optimise the efficiency of the optical sorter. With its entry into the market, TOMRA now offers a suite of solutions comprising its Harvest Cleaner, Small Fruit Eliminator, TOMRA Neon and KATO260. All of these form a complete end-to-end solution for simple and effective processing of mechanically harvested blueberries.

The calibration platform was also presented at Fruit Logística Next-generation Spectrim X for apples with LUCAi® technology based on Deep Learning. This intelligent optical sorting and grading solution is equipped with LUCAi® software, computing hardware and pre-trained models that meet today's customer demand for increased plant productivity. Spectrim X achieves unprecedented grading accuracy, high productivity, minimized fruit waste and optimized operating costs. 

Finally, TOMRA Food unveiled the software TOMRA LUCAi® for its InVision calibration platform2 for cherries. D technologyeep Learning TOMRA’s new cherries improve packaging and minimise fruit waste. It can detect, with millimetre accuracy, all types of edge cracks; pacman cherries (half cherries); damage from impacts in the suture area, as well as cosmetic defects and browning of the stem. In addition, it guarantees better detection of rotten, split or defective cherries, especially in the stem area. With this launch, customers will benefit from improved quality and consistency of their final product, while reducing product waste and maximising their production.

Three-dimensional hologram of sorting, grading and packaging solutions

A wide range of TOMRA Food solutions were on display at the hologram. It featured 3D animations and videos of the well-known TOMRA 3A, TOMRA 5A, TOMRA 5C and TOMRA 5SA sorting machines; the CURO-16 small fruit packaging system; the KATO precision grading system for blueberries; the Spectrim grading platform with UltraView inspection module; the Inspectra internal inspection system; and the TOMRA Food 3A hologram.2; and TOMRA Neon’s new pre-sorting technology for mechanically harvested blueberries destined for the fresh food market.

Presentation on the new evolution of AI-based classification and calibration

Sebastian Stoof, Vice President and Head of Customer Value Chain at TOMRA Food, gave a presentation at the Tech-Stage at Fruit Logística. He talked about AI developments and how AI is being used to solve complex problems in food sorting. Sebastian explained that in order to successfully apply AI to food sorting, several essential conditions must be met: high-quality images for training and operations, extensive experience and knowledge of the industry and the technology. Deep Learning, as well as an ideal organizational structure that allows for the company's expansion.

Sebastian also highlighted how the introduction of AI into food sorting is changing customer expectations regarding sorting accuracy, technology adaptability, operator skills and the support they receive from their technology providers.

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