SustainPlant: Agronomy, Genetics/Genomics & AI for Sustainable Feed Systems

Integrating multiscale agronomy, genomics, high-throughput phenomics, and Digital Twin modeling to optimize nitrogen use efficiency, yield, and quality in forage crops.

Genetics & Genomics Genomic Selection Phenomics ML / AI Functional Genomics
Our Research Meet the Team
10+ Team Members 5 Research Areas 6 Active Projects
44+ MNOK Funding ▾

From Lab to Field

Our integrated research pipeline connects molecular discovery to on-farm impact

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Gene Discovery

GWAS & RNA-seq identify NUE candidate genes in forage grasses and potato

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CRISPR Editing

Precision gene editing of nitrogen transporter & metabolism genes (GS1, NRT1.1)

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Genomic Selection

Predictive models select top genotypes without extensive field testing

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Field Phenomics

Drones & robots capture high-throughput trait data across trial sites

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AI & Digital Twins

Virtual plant models simulate N scenarios & optimize management decisions

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Farmer Impact

N-smart varieties & decision tools for sustainable feed production

Research Focus Areas

Our interdisciplinary research spans from molecular genomics to Digital Twin modeling for sustainable feed systems

Digital Twin Hub showing how all 6 projects — CRISPR, DLT-Farming, Soil2Milk, Twin-NUE, NitroSense — are linked to NUE studies
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Genetics & Genomics

Mapping the blueprints of Nitrogen Use Efficiency and climate resilience in forage grasses and potato.

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Genomic Selection

Accelerating breeding cycles through advanced predictive algorithms for sustainable agriculture.

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Functional Genomics

Utilizing CRISPR/Cas9 and transcriptomics to validate genes that drive yield, quality, and stress response.

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Phenomics

Deploying drone and robot-based sensors to capture real-time physiological data across field scales.

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Autonomous robot collecting image and spectral data across forage grass field trial plots at NMBU Ås.

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AI & Digital Twins

Creating virtual plant models to simulate nitrogen dynamics and optimize management for sustainable feed systems.

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0% (full N) -50% (severe)
100% N (Control)
Reduced N (Treatment)
Soil Nitrogen
Root System

Latest News & Updates

Stay up to date with our research activities and achievements

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Welcome
February 2026

Welcome Akhil Reddy Pashapu!

Akhil Reddy Pashapu started his PostDoc with our group in the TWIN-NUE project, developing digital twin models for Nitrogen Use Efficiency in perennial ryegrass and oats. Welcome Akhil!

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Welcome
February 2026

New Master Students Join the Lab

We welcome our new cohort of master students working on exciting projects in genomics and phenomics.

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Grant
January 2026

ProteinSense Project Funded!

ProteinSense: More protein from forage grass and less concentrates has been funded. We will be developing prediction models for tracking protein content in grass.

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Our Team

A diverse team of researchers passionate about plant science and technology

Mallikarjuna Rao Kovi

Mallikarjuna Rao Kovi

Research Scientist / Group Leader / Principal Investigator (PI)

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

Odd Arne Rognli

Professor Emeritus

Decades of expertise in forage grass breeding and genetics.

Akhil Reddy Pashapu

Akhil Reddy Pashapu

Postdoctoral Researcher

Digital Twin modelling for NUE in perennial ryegrass and oats. Expertise in computational genomics and bioinformatics.

PG

Precious Guevarra

PhD Student

Doctoral research focused on genetics and functional genomics (CRISPR-Cas9) studies in Nitrogen Use Efficiency (NUE) for sustainable forage grass improvement.

Meet Everyone