A&G van den Bosch, a grower of beef tomatoes in The Netherlands, has deployed a complete robotic line for automated grading, sorting, and packing of its beef tomatoes.
In the recent year, the family-owned grower worked closely together with Crux Agribotics to deploy SortiPack for beef tomatoes. In this line, advanced Robotics, Computer Vision, Data, and AI are combined to improve the grading, sorting, and packing process.
Bart van den Bosch comments: “We are very happy with the first results from the robotic system. Besides significant savings in labor costs, we see that the system grades and packs our beef tomatoes much more uniformly and consistently. The data derived from the system enables us to further improve and to differentiate on quality and service levels to our customers.”
A&G van den Bosch has deployed a SortiPack Robotic system from Crux Agribotics with 7 robots handling up to 20.000 beef tomatoes and 14 sorting classes simultaneously per hour. The system handles the product much more gently, reducing damages and extending shelf life. In addition, the system is based on machine learning, ensuring that it pro-actively provides suggestions to increase packing yields and to reduce waste.
In this video, Bart van den Bosch shares his experience with SortiPack and Crux Agribotics:
Less dependency on labor
“The results and return of the system are beyond our expectations, and we discover new possibilities together with A&G every day based on the data that our system generates. We can now record and manage the trajectory of individual tomatoes, packages, and batches, from its originating greenhouse row to the designated package to the final pallet position. In this way, we realize full track & traceability and quality assurance,” says Michel van Reenen, Sales manager at Crux Agribotics.
“We believe that, with these types of technologies, we can get much higher yields per m2 and minimize food waste. At the same time, growers and packing centers become less dependent on human labor and more flexible to scale up in capacity 24/7. The real-time data and AI algorithms can optimize processes and quality control further. Besides labor cost reduction, shelf life, and give-away weight optimization we get additional interest from growers for the track and tracing possibilities as well as from breeders for phenotyping,” says Richard Vialle CCO & Founder of Kind Technologies.
“As the SortiPack system is fully data-based, it can assess the potential savings and optimizations for a grower in advance. Based on simulations of historical sorting and packing data, the right robot configuration and business case are ensured for each grower’s situation.”