Research | Digital AgroEcosystems

Current Research Projects

The Digital AgroEcosystems Lab (DALab) at the University of Manitoba develops innovative technologies that advance the digital transformation of agriculture and natural ecosystems. Our research integrates remote sensing, artificial intelligence, spectroscopy, machine learning, environmental modeling, and geospatial analytics to address some of the most pressing challenges facing food production and environmental sustainability.

From soil health and crop productivity to grassland conservation and plant disease detection, our projects aim to convert environmental data into actionable intelligence that supports producers, policymakers, industry, and society. Through interdisciplinary collaborations and cutting-edge technologies, we are building the foundations for resilient and sustainable agroecosystems.

Digital Soil Mapping

Discover how digital soil mapping revolutionizes farming by delivering precise information about soil health, fertility, and carbon storage. Using hyperspectral imaging, machine learning, and advanced geospatial analysis,

Monitoring Land Degradation

Protecting our soils starts with understanding them. We monitor soil salinity and erosion to combat land degradation. Our research delivers the most accurate actionable insights for sustainable land management planning.

Soil Spectral Library

Explore our Soil Spectral Library, a transformative tool for precision agriculture. By integrating hyperspectral data and machine learning, we provide accurate data on soil properties like organic carbon and fertility.

Crop Yield Prediction

Enhance farming decisions with state-of-the-art crop modeling. By integrating climate data, soil properties, and machine learning algorithms, our research delivers accurate predictions of crop yields and growth patterns.

Mapping Canada's Grassland

Uncover the power of AI and big data in preserving Canada’s grasslands. Our research uses remote sensing and machine learning to map and monitor vital ecosystems, supporting biodiversity and sustainable land use.

Plant Health Detection

Stay ahead of crop challenges with innovative plant health detection tools. Our research combines remote sensing, machine learning, and geospatial data to identify stress factors like pests, diseases, and nutrient deficiencies early.

Looking Ahead

The future of agriculture lies at the intersection of environmental science and digital technologies. Beyond our current projects, DALab is actively expanding into emerging research areas that will define the next generation of agroecosystem intelligence.

These include Earth observation foundation models, geospatial artificial intelligence, digital twins of agroecosystems, climate-smart agriculture, biodiversity monitoring, carbon assessment, explainable AI, and decision-support systems for sustainable land management.

Our long-term vision is to develop integrated digital ecosystems capable of connecting soils, vegetation, climate, and management information into intelligent platforms that support adaptive and resilient agricultural systems.