Feldklasse Zurama: accurate hoeing technology for arable crops and mulch seeding or regenerative agriculture
It's never too early – neither for good hoeing nor for good news.
The machine has successfully chopped the first fields. Test machines for interested customers are available in 2023, feel free to get in touch!
Excellent advantages in field cultivation
- Ingenious tools for a very precise first chopping run
- Blockage-free operation even in mulch and no-till stocks
- Hoeing of strip till and targeted removal of undersown crops in developed stock
- Powerful hoeing between and in the crop row
- AI-based camera system recognises crops and differentiates them from weeds
- Selective knives remove the weeds between the crops
- Very low residual weed coverage due to almost full-surface weed control
- Flexibly adjustable to all row spacings
- The hoe that grows with the crop: tools are adjusted to the crop's growing stage
- Ideal hoe for regenerative agriculture, hybrid agriculture or fusion farming
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Ideally suited for the following plants and stages:
- Sugar beet and maize: From cotyledon until last weeding pass
- Cabbage: One week after planting until last weeding pass
- Lettuce: One week after planting until shortly before harvesting
- Annual or perennial herbs (e.g. balm, chervil, parsley, coriander, dandelion, foxglove): from sprouting until last weeding pass
Ideally suited for the following plants and stages:
- Sugar beet and maize: From cotyledon until last weeding pass
- Cabbage: One week after planting until last weeding pass
- Lettuce: One week after planting until shortly before harvesting
- Annual or perennial herbs (e.g. balm, chervil, parsley, coriander, dandelion, foxglove): from sprouting until last weeding pass
Plant regocnition based on AI
The Zurama works with optical plant recognition, which was developed in collaboration with the Czech tech start-up Ullmanna. Ullmanna is a specialist in the development of image recognition software.
The image-processing software is based on artificial intelligence (AI) and was trained in advance with images of sugar beet as well as other crops in different stages of development. In this way, the system has learned to distinguish the crops from weeds, similar to us humans, on the basis of special features such as leaf shape, plant colour and number of leaves. This works very precisely in sugar beet from the 2nd leaf stage onwards, even when the beet is surrounded by significantly larger weeds.
The system is programmed in such a way that the plant recognition can constantly adapt to the current conditions through the images taken during hoeing. For precise work by day and night, each camera is supported by four powerful LED lights.
You want to bring a breath of fresh air into your machinery?
If you want to revolutionise your weed control, feel free to contact us.
Funding
The project is supported by funds of the German Government’s Special Purpose Fund held at Landwirtschaftliche Rentenbank.
