Book Description
Until recently, a majority of the applications of X-ray computed tomography (CT) scanning in plant sciences remained descriptive; some included a quantification of the plant materials when the root-soil isolation or branch-leaf separation was satisfactory; and a few involved the modeling of plant biology processes or the assessment of treatment or disease effects on plant biomass and structures during growth. In the last decade, repeated CT scanning of the same plants was reported in an increasing number of studies in which moderate doses of X-rays had been used. Besides the general objectives of Frontiers in Plant Science research topics, “Branching and Rooting Out with a CT Scanner” was proposed to meet specific objectives: (i) providing a non-technical update on knowledge about the application of CT scanning technology to plants, starting with the type of CT scanning data collected (CT images vs. CT numbers) and their processing in the graphical and numerical approaches; (ii) drawing the limits of the CT scanning approach, which because it is based on material density can distinguish materials with contrasting or moderately overlapping densities (e.g., branches vs. leaves, roots vs. non-organic soils) but not the others (e.g., roots vs. organic soils); (iii) explaining with a sufficient level of detail the main procedures used for graphical, quantitative and statistical analyses of plant CT scanning data, including fractal complexity measures and statistics appropriate for repeated plant CT scanning, in experiments where the research hypotheses are about biological processes such as light interception by canopies, root disease development and plant growth under stress conditions; (iv) comparing plant CT scanning with an alternative technology that applies to plants, such as the phenomics platforms which target leaf canopies; and (v) providing current and potential users of plant CT scanning with up-to-date information and exhaustive documentation, including clear perspectives and well-defined goals for the future, for them to be even more efficient or most efficient from start in their research work.
