AI Streamlines Cherry Sorting at Efringen Churches: Human Labor Overshadowed by Artificial Intelligence
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Machine learning takes the cherry on top of the farm work!
Meet Kevin Brändlin, a farmer from Efringen-Kirchen, Germany, who's tapped into the future of agriculture with a little help from AI. He's equipped his cherry farm with an AI-powered sorting machine, and it's revamping the game!
Cherry picking done by AI
Brändlin's high-tech AI sorter is ruthless when it comes to producing board-worthy cherries – his investment of half a million euros was money well-spent. This machine can process a ton of cherries each hour, spotting even the littlest flaws for precise quality control. It's all thanks to more than 30 high-res photos taken of each individual fruit and an infrared camera, ensuring no soft, discolored, or damaged cherry slip through the cracks.
The game-changer that saves labor
Ten years ago, Brändlin switched from manual sorting to mechanical methods. His old machine was limited to sorting by size and color, so inspecting each fruit remained a tedious task for his team. With four employees dedicated to checking 400 tons of cherries per season, labor costs were skyrocketing, and it was increasingly difficult to find seasonal workers.
Now, with AI on board, Brändlin can do more with less. The new sorter reduces employee headcount by half, requiring only four workers for the same output, which means significant savings on labor costs.
AI: the tireless workforce
Anthony Stein, a scientist from the University of Hohenheim who specializes in AI in agricultural technology, foresees agriculture as the next big frontier for AI. He believes that the technology's potential could ease the labor crunch in farming, as it requires no breaks and can work around the clock without tiring.
The AI's eating habits: a potential pitfall?
However, the AI's appetite for data is insatiable. Machine learning systems, like the one powering Brändlin's sorter, are trained on data sets. But data evaluation and analysis by human experts can lead to errors. If data collection is restricted to lab settings instead of real-world scenarios, the risk of errors rises.
AI transforms cherry picking, eases strain on growers
With the AI sorter in place, cherry picking has become a less grueling job for Brändlin's team. Before, they spent extra time sorting cherries directly on the tree. Now, they only need to ensure ripeness, as the AI takes care of the quality sorting process.
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Anthony Stein, a scientist specializing in AI in agricultural technology, sees the potential for AI to revolutionize food-and-drink industries, particularly in labor-intensive jobs like food-and-drink sorting.
As the use of artificial-intelligence systems like the one used by Brändlin becomes more prevalent, the lifestyle of farmers is set to undergo significant changes, with technology taking over time-consuming tasks and reducing the need for manual labor, leading to improved efficiency and cost savings.
