2026-0935393 - Plant Phenotyping System
Awarded
The competition has ended and a winner has been selected.
- Award
- Competition Requirements 40%
- Procedure
- OpenSingle stage
- Agreement
- Buying goods
Brief
Aarhus Universitet has entered into an agreement with LemnaTec GmbH for the delivery of a plant phenotyping system, valued at 50,070 €. This system, featuring five high-resolution cameras, will be used to capture images of in vitro tissue cultures or seedlings for continuous and non-destructive monitoring of plant growth and development. The image datasets will be analyzed using machine-learning models to quantify morphological and physiological traits, accelerating the optimization of tissue-culture protocols for new species or cultivars. The award criteria emphasized acquisition price (60%) and quality (40%), including storage capacity of the database server and expedited delivery time.
Result
- LemnaTec GmbHWinner
- 1Number of bids
- €50,070Contract value
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Award Criteria
Description
Acquisition Price for the Plant Phenotyping System
Source
No source found in the documents. Check the weight against the tender documents.
Description
In the evaluation of qualitative sub-criterion, the Contracting Authority will place emphasis on the part-criteria listed below. Weight if the Plant Phenotyping System Storage capacity of database server Expedited delivery time
Sub-criteria
- Weight if the Plant Phenotyping System
Weight if the Plant Phenotyping System
- Storage capacity of database server
Storage capacity of database server
- Expedited delivery time
Expedited delivery time
Source
No source found in the documents. Check the weight against the tender documents.
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From the notice
The Department of Agroecology, Section for CropsGenetics and Biotechnology at Aarhus University puts out to tender the purchase of a phenotyping system using five high-resolution cameras to cap-ture images of in vitro tissue cultures or seedlings, enabling continuous and non-destructive moni-toring of the growth and development of regenerated plants. These image datasets will be analysed using machine-learning models to automatically quantify morphological and physiological traits that will be difficult to assess manually. By identifying patterns associated with successful growth re-sponses, the system will accelerate the optimization of tissue-culture protocols for new species or cultivars.
Contact
Ann Sophie Steffensenasst@au.dk- ResultType
- Vest- og SydsjællandLocation
- 38000000Main codeLaboratory, optical and precision equipments (excl. glasses)
- 38500000Checking and testing apparatus38650000Photographic equipment38900000Miscellaneous evaluation or testing instruments