SustainPlant Group, Department of Plant Sciences, NMBU
Genomics, phenotyping and AI for resilient crops and self-sufficient food and feed production
We develop genomic, gene-editing, phenotyping and AI tools for improving forage crops such as timothy, perennial ryegrass and red clover, potato, and more recently cereals such as barley.
Targets: higher yield and quality, tolerance to biotic and abiotic stresses, and lower fertiliser need, in partnership with breeders and farmers.
What we do
Five connected research areas, from genes to field to farm decisions
Genetics & Genomics
Finding the genes behind yield, quality, winter survival, disease resistance and nitrogen efficiency in forage crops and potato.
Functional Genomics
Testing what candidate genes do with CRISPR gene editing and transcriptomics.
Genomic Selection
Prediction models that let breeders pick the best plants from their DNA and shorten breeding cycles.
Phenomics
Drones, field robots and 3D scanners that measure thousands of plots through the season.
AI & Digital Twins
Models that turn field and greenhouse data into predictions and decision tools for breeders and farmers.
Projects at a glance
Six funded projects with breeders, industry and farmers
Soil2Milk
Grass and clover mixtures, nitrogen-efficient varieties and gene editing to cut nitrogen losses and cow methane in Norwegian dairy farming.
DLT-Farming
Field robots, sensors, genomics and AI evaluate 40 ryegrass cultivars to find nitrogen-efficient genes and give farmers real-time yield and quality reports.
TWIN-NUE
Daily 3D scans of ryegrass and oat in the PheNo greenhouse feed digital twins that predict how each genotype responds to nitrogen.
ProteinSense
Drone imaging and AI give farmers a 3 to 5 day harvest alert to capture peak grass protein and reduce imported concentrates.
NitroGenEdit
CRISPR editing of nitrogen transporter and metabolism genes to develop ryegrass that yields more with less fertiliser.
GE-Sustain
Precision breeding tools for potato: the genes behind late blight resistance and processing quality, and tissue-culture-free gene editing.
How we do it: from lab to field
Six steps connect gene discovery to varieties and tools on Norwegian farms
Discover genes
We scan thousands of grass and potato plants for the DNA variants behind yield, quality, winter survival and nitrogen efficiency.
Edit and validate
We edit key genes with CRISPR to test what they do, from nitrogen transporters in ryegrass to disease susceptibility genes in potato.
Predict the best plants
Statistical models rank plants from their DNA alone, so breeders can shorten breeding cycles.
Measure in the field
Drones and field robots measure every plot through the season at Ås and Hamar.
Model and decide
AI and digital twins turn the data into predictions of yield, protein and nitrogen response.
Breeders and farmers
Better varieties and decision tools for Norwegian farms, developed with Graminor, advisors and farmers.
In the field
Robots and drones measure every plot
Our field robot and drones record images, spectral data and 3D structure across thousands of forage grass plots at NMBU Ås and Graminor Hamar through the season. The data feed our genomic prediction models and the digital twins that forecast yield, protein and nitrogen response.
Autonomous robot collecting image and spectral data across forage grass field trial plots at NMBU Ås.
More about phenomicsIn silico
Digital twin: nitrogen response simulator
Move the slider to see how reducing nitrogen fertiliser changes growth in a simplified virtual grass plot. The full plot on the left keeps 100% nitrogen; the right plot gets your chosen reduction. It is an illustration of the idea behind our digital twins, not output from a research model.
More about AI and digital twinsLatest News & Updates
Stay up to date with our research activities and achievements
Congratulations Gargi Dutta: MSc thesis defended with grade A
Gargi defended her thesis on targeting susceptibility genes in potato and received the top grade. Read more →
New publication: genomic selection in timothy
Our evaluation of prediction models, multi-trait strategies and forward validation across Norwegian environments is out in Theoretical and Applied Genetics. Read the paper →
Ås Avis: gene editing for future food security
Our CRISPR work in the NitroGenEdit and GE-Sustain projects was featured in Ås Avis. Read more →
Our Team
A diverse team of researchers passionate about plant science and technology
Mallikarjuna Rao Kovi
Research Scientist at NMBU and R&D Scientist (20%) at Graminor AS. 15+ years specialising in NUE, stress tolerance, genomics, phenomics, AI/ML, and CRISPR. Supervised 16 students (6 PhD, 10 MSc).
Odd Arne Rognli
Decades of expertise in forage grass breeding and genetics.
Akhil Reddy Pashapu
Digital Twin modelling for NUE in perennial ryegrass and oats. Expertise in computational genomics and bioinformatics.
Funders and partners
Our projects are funded by these agencies and carried out with breeders, industry and research partners
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Interested in Joining Us?
We welcome inquiries about exchanges, collaborations, and future opportunities. Send us an email with your background and research interests.
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