lettuce harvesting

How computer vision helps automate lettuce harvesting

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lettuce harvest

The prototype of a lettuce harvesting robot | Source: IDS imaging

Lettuce is a valuable crop in Europe and the United States, but labor shortages make harvesting this valuable field vegetable difficult, as sourcing enough seasonal labor to meet harvesting commitments is one of the industry’s biggest challenges. . Furthermore, with wage inflation rising faster than producer prices, the margins are very tight.

In England, technology and agricultural machinery experts are working with IDS Imaging Development Systems GmbH, based in Obersulm, Germany, to develop a robotic solution to automate lettuce harvesting. The team is working on a project funded by Innovate UK and includes experts from the Grimme agricultural machinery factory, the Agri-EPI Center in Edinburgh, UK, Harper Adams University in Newport, UK, the Center for Machine Vision of University of the West of England in Bristol and two of the UK’s largest salad producers, G’s Fresh and PDM Produce.

As part of the project, existing leek harvesting machinery is adapted to lift the lettuce off the ground and grab it between the grab straps. The outer leaves, or “shell”, of the lettuce will be mechanically removed to expose the stem. Machine vision and artificial intelligence are then used to identify a precise cut point on the stem to neatly separate the lettuce head.

“The iceberg cutting process is the most technically complicated step in the automation process, according to teammates at subsidiary G Salad Harvesting Services Ltd.,” said Rob Webb, IDS product sales specialist. “The harvesting robot prototype under construction incorporates a GigE Vision camera from the uEye FA family. It is considered to be particularly robust and is therefore ideal for demanding environments. “As this is an outdoor application, an IP65 / 67 enclosure is required here.”

lettuce harvest

Machine vision and artificial intelligence are used to determine the point of intersection on the stem. | Source: IDS imaging

The choice fell on the GV-5280FA-C-HQ model with Sony’s compact 2/3 ″ global shutter CMOS sensor IMX264.

“The sensor was chosen primarily for its versatility. We don’t need full resolution for AI processing, so sensitivity can be increased with binning. The larger sensor format means you don’t even need wide-angle lenses, “said Rob Webb.

The robotic lawnmower prototype will be used for field trials in England towards the end of the 2021 season.

“We are delighted to be involved in the project and look forward to seeing the results. We are convinced of its potential to automate and increase the efficiency of lettuce harvesting, not just in terms of compensating for the lack of seasonal workers, “said Jan Hartmann, managing director of IDS Imaging Development Systems GmbH.

The challenges facing the agricultural sector are truly complex. According to a forecast from the United Nations Food and Agriculture Organization (FAO), agricultural productivity will have to increase by almost 50% by 2050 compared to 2012 due to the dramatic increase in population. This yield expectation represents a huge challenge for the agricultural industry, which is still in its infancy in terms of digitization compared to other sectors and is already under severe pressure to innovate in the light of climate change and labor shortages.

The agriculture of the future is based on networked devices and automation. Cameras are a cornerstone, and AI is a core technology here. Smart applications such as harvesting robots can make a significant contribution in this regard.

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