Lawrence Berkeley National Laboratory (LBNL)

Plants capture atmospheric carbon dioxide (CO2) using photosynthesis, and transfer the carbon to the soil through their roots. Soil organic matter, which is primarily composed of carbon, is a key determinant of soil’s overall quality. Even though crop productivity has increased significantly over the past century, soil quality and levels of topsoil have declined during this period. Low levels of soil organic matter affect a plant’s productivity, leading to increased fertilizer and water use. Automated tools and methods to accelerate the process of measuring root and soil characteristics and the creation of advanced algorithms for analyzing data can accelerate the development of field crops with deeper and more extensive root systems. Crops with these root systems could increase the amount of carbon stored in soils, leading to improved soil structure, fertilizer use efficiency, water productivity, and crop yield, as well as reduced topsoil erosion. If deployed at scale, these improved crops could passively sequester significant quantities of CO2 from the atmosphere that otherwise cannot be economically captured.

Lawrence Berkeley National Laboratory (LBNL) will develop an imaging-modeling toolbox to aid in the development of more efficient crops at field scales. The approach is based on a root phenotyping method called Tomographic Electrical Rhizosphere Imaging (TERI). TERI works by applying a small electrical signal to a plant, then measuring the impedance responses through the roots and correlating those responses to root and soil properties. Key target traits of the LBNL project include root mass, root surface area, rooting depth, root distribution in soil, and soil moisture content and texture. The TERI technology will be sensitive enough to distinguish between various plant varieties. The process is minimally invasive, and by doing repeated TERI measurements over the growing season, critical root architectural traits and their dynamic changes over time can be quantified for a range of soil conditions. From laboratory studies, LBNL and its partners will integrate hardware and software tools to develop a field deployable instrument based on the TERI technology. LBNL is partnered with the Noble Foundation to apply the TERI technology to wheat breeding and identify wheat varieties with improved root characteristics, and also link visible above-ground phenotypes with the desired root characteristics. The team will utilize the TERI technology to characterize plants in both controlled laboratory and field studies, and use the data generated to improve ecological models predicting plant performance in the environment.