EAMR: Enhanced Minirhizotron and Image Analysis System

The single most critical value in any terrestrial carbon (C) sequestration budget is the net primary production. The biggest unknown in determining C sequestration is the allocation, production, respiration, mortality and decomposition of soil organisms. We developed and are refining a new observation/sensor platform, the enhanced automated minirhizotron (EAMR) which, when coupled to a soil sensor network, provides detailed data on soil C budgets, for studying terrestrial ecosystems. We designed and built an in situ, automated minirhizotron (AMR) system around USB-port microscopes, which we could network to allow for high-resolution imagery, high repeatability, and continuous observations that could be integrated with networked sensor data. We propose to make design improvements that will provide for greater flexibility for an individual PI in the types of imaging that can be undertaken. Our objectives in Phase I are to (1) Explore alternative potential filters to vary the light source, including fluorescence capability and an 880nm wavelength that would eliminate algal growth on the tube surface; (2) Determine the feasibility of 3-D imaging of soil processes to improve the identification ability from images; (3) Further develop, code and integrate root analysis into our already existing RootView web-based software. (4) Complete Cost Reduction alterations and other enhancements that will result in a commercially workable soil observing system. The Phase I (and Phase II goals) are to complete both hardware and software AMR systems that can obtain observing and sensing system-based data for tracking the dynamics of soil organism (fine roots, fungi, soil animals) and determining terrestrial C budgets. Commercial Applications and Other Benefits: We designed the worlds first automated minirhizotron for continuously observing roots and microorganisms at microscopic levels, that we coupled to arrayed rhizosphere soil sensor systems that continuously measures soil conditions (http://ccb.ucr.edu/amarss.html, http://www.rhizosystems.com/). Using this system, we are able to observe the infection process of symbiotic mycorrhizal and parasite infection in roots in the field. These same technologies can be readily applied to understanding disease progression and control by biological control products, by monitoring disease fungal growth and infection of test plants. This technology can be used by researchers in agriculture, forestry, and wildland management.