RADIX: rhizoslide platform allowing high throughput digital image analysis of root system expansion.

BACKGROUND: Phenotyping of genotype-by-environment interactions in the root-zone is of major importance for crop improvement as the spatial distribution of a plant's root system is crucial for a plant to access water and nutrient resources of the soil. However, so far it is unclear to what extent genetic variations in root system responses to spatially varying soil resources can be utilized for breeding applications. Among others, one limiting factor is the absence of phenotyping platforms allowing the analysis of such interactions. RESULTS: We developed a system that is able to (a) monitor root and shoot growth synchronously, (b) investigate their dynamic responses and (c) analyse the effect of heterogeneous N distribution to parts of the root system in a split-nutrient setup with a throughput (200 individual maize plants at once) sufficient for mapping of quantitative trait loci or for screens of multiple environmental factors. In a test trial, 24 maize genotypes were grown under split nitrogen conditions and the response of shoot and root growth was investigated. An almost double elongation rate of crown and lateral roots was observed under high N for all genotypes. The intensity of genotype-specific responses varied strongly. For example, elongation of crown roots differed almost two times between the fastest and slowest growing genotype. A stronger selective root placement in the high-N compartment was related to an increased shoot development indicating that early vigour might be related to a more intense foraging behaviour. CONCLUSION: To our knowledge, RADIX is the only system currently existing which allows studying the differential response of crown roots to split-nutrient application to quantify foraging behaviour in genome mapping or selection experiments. In doing so, changes in root and shoot development and the connection to plant performance can be investigated.

High-resolution quantification of root dynamics in split-nutrient rhizoslides reveals rapid and strong proliferation of maize roots in response to local high nitrogen.

The plant's root system is highly plastic, and can respond to environmental stimuli such as high nitrogen (N) in patches. A root may respond to an N patch by selective placement of new lateral roots, and therewith increases root N uptake. This may be a desirable trait in breeding programmes, since it decreases NO3(-) leaching and N2O emission. Roots of maize (Zea mays L.) were grown without N in split-nutrient rhizoslides. One side of the slides was exposed to high N after 15 d of root development, and root elongation was measured for another 15 d, described in a time course model and parameterized. The elongation rates of crown axile roots on the N-treated side of the plant followed a logistic increase to a maximum of 5.3cm d(-1); 95% of the maximum were reached within 4 d. At the same time, on the untreated side, axile root elongation dropped linearly to 1.2cm d(-1) within 6.4 d and stayed constant thereafter. Twice as many lateral roots were formed on the crown axis on the N side compared to the untreated side. Most strikingly, the elongation rates of laterals of the N side increased linearly with most of the roots reaching an asymptote ~8 d after start of the N treatment. By contrast, laterals on the side without N did not show any detectable elongation beyond the first day after their emergence. We conclude that split-nutrient rhizoslides have great potential to improve our knowledge about nitrogen responsiveness and selection for contrasting genotypes.

Rhizoslides: paper-based growth system for non-destructive, high throughput phenotyping of root development by means of image analysis.

BACKGROUND: A quantitative characterization of root system architecture is currently being attempted for various reasons. Non-destructive, rapid analyses of root system architecture are difficult to perform due to the hidden nature of the root. Hence, improved methods to measure root architecture are necessary to support knowledge-based plant breeding and to analyse root growth responses to environmental changes. Here, we report on the development of a novel method to reveal growth and architecture of maize root systems. RESULTS: The method is based on the cultivation of different root types within several layers of two-dimensional, large (50 × 60 cm) plates (rhizoslides). A central plexiglass screen stabilizes the system and is covered on both sides with germination paper providing water and nutrients for the developing root, followed by a transparent cover foil to prevent the roots from falling dry and to stabilize the system. The embryonic roots grow hidden between a Plexiglas surface and paper, whereas crown roots grow visible between paper and the transparent cover. Long cultivation with good image quality up to 20 days (four fully developed leaves) was enhanced by suppressing fungi with a fungicide. Based on hyperspectral microscopy imaging, the quality of different germination papers was tested and three provided sufficient contrast to distinguish between roots and background (segmentation). Illumination, image acquisition and segmentation were optimised to facilitate efficient root image analysis. Several software packages were evaluated with regard to their precision and the time investment needed to measure root system architecture. The software 'Smart Root' allowed precise evaluation of root development but needed substantial user interference. 'GiaRoots' provided the best segmentation method for batch processing in combination with a good analysis of global root characteristics but overestimated root length due to thinning artefacts. 'WhinRhizo' offered the most rapid and precise evaluation of root lengths in diameter classes, but had weaknesses with respect to image segmentation and analysis of root system architecture. CONCLUSION: A new technique has been established for non-destructive root growth studies and quantification of architectural traits beyond seedlings stages. However, automation of the scanning process and appropriate software remains the bottleneck for high throughput analysis.