Dr. Richard Nair

Summary

Phenology is the way living things change through the seasons. For plants, phenology affects how much CO2 they take up in photosynthesis or release as they die, so phenology affects climate change. But climate change is altering phenology, such as more growth in warm winters or less in dry summers. Hence understanding phenology is critical for climate change predictions. We can study plant phenology using cameras or satellites collecting sequences of images. However, around 1/3 of CO2 taken up is transported belowground to root systems. Roots are difficult to study as soil is opaque. Other scientists have found that roots don"t grow at the same time as leaves, but we don"t understand why in a general way that can be used in predictions. In this project, I will work in natural ecosystems and collect sequences of images of roots using buried robotic cameras to tackle this problem. Using artificial intelligence (AI) for image analysis, I will produce datasets of daily root growth. AI is necessary because counting roots is time consuming for humans but not an AI. I will use the new data to understand how roots respond to the seasons and climate. The robotic instruments will stay at long term field sites, generating datasets useful for other research. I will use the data to understand how to predict root growth patterns. I will study links between carbon uptake and release, and leaf and root phenology under field conditions. This willhelp us forecast, adapt to, and manage climate change.

Funding Agency

Science Foundation Ireland

Programme

Royal Society SFI University Research Fellowship

Project Type

Individual

Summary

Healthy plants are essential for sustainable and productive agriculture. A substantial part of all plants is below ground and health and physiology of roots may precede or not be reflected in the health status of leaves. In spite of this, methods to assess the health and physiological status of roots in field are still rudimentary. This limits the ability to manage agricultural systems in an era of increasing uncertainty. Quantitative tools to allow practitioners to measure root health properties would help deliver future agricultural production and security. In RootCheck we will develop a novel robust handheld sensor attachment to a smartphone to allow rapid assessment of root health status using multispectral imaging techniques. Over the seed and concept phases, the RootCheck team will build a database of hyperspectral images of roots of different crop species and statuses and refine this to a limited number of targeted wavelengths for a concept low-cost technical solution, supported by an smartphone app supported by a growing database of hyperspectral root imagery. RootCheck will put the ability to assess root health and physiology directly into the hands of farmers, allow rapid quantitative root health diagnosis from field-fresh samples and facilitate management of Future Food Systems.

Funding Agency

Science Foundation Ireland

Programme

National Challenge Fund

Project Type

Consortium