Biology subjects

Smolders, E.

Publications and source records attributed to Smolders, E..

4 recordsLinked to original sources

bioRxiv2020

Millimeter-resolution mapping of citrate exuded from soil grown roots using a novel, low-invasive sampling technique

The reliable sampling of root exudates in soil grown plants is experimentally challenging. This study aimed at developing a citrate sampling and mapping technique with millimetre-resolution using DGT (diffusive gradients in thin films) ZrOH binding gels. Citrate adsorption kinetics, DGT capacity and stability of ZrOH gels were evaluated. ZrOH gels were applied to generate 2D maps of citrate exuded by white lupin roots grown in rhizotrosn in a phosphorus deficient soil. Citrate was adsorbed quantitatively and rapidly by the ZrOH gels, these gels can be stored after sampling for several weeks prior to analysis. The DGT capacity of the ZrOH gel for citrate depends on the ionic strength and the pH of the soil solution but was suitable for citrate sampling. 2D citrate maps of rhizotron grown plants have been generated for the first time at a millimetre resolution to measure an illustrated plant response to P fertilization. DGT-based citrate sampling is suitable for studying the root exudation in soil environments, at unprecedented spatial resolution. By changing binding material, the technique is also applicable to other exudate classes and might be used for the evaluation of whole root exudation crucial in specific cultivar breeding. HighlightWe present a novel, reliable, easy to use, non-destructive citrate sampling- and two-dimensional high-resolution imaging technique for soil grown plant roots.

plant biology↗

bioRxiv2020

Phenotyping Root Architecture of Soil-Grown Rice: A Robust Protocol Combining Manual Practices with Image-based Analyses.

BackgroundBreeding towards resilient rice varieties is often constrained by the limited data on root system architecture obtained from relevant agricultural environments. Knowledge on the genotypic differences and responses of root architecture to environmental factors is limited due the difficulty of analysing soil-grown rice roots. An improved method using imaging is thus needed, but the existing methods were never proven successful for rice. Here, we aimed to evaluate and improve a higher throughput method of image-based root phenotyping for rice grown under field conditions. Rice root systems from seven experiments were phenotyped based on the "shovelomics" method of root system excavation followed by manual root phenotyping and digital root analysis after root imaging. Analyzed traits were compared between manual and image-based root phenotyping systems using Spearman rank correlations to evaluate whether both methods similarly rank the phenotypes. For each trait, the relative phenotypic variation was calculated. A principal component analysis was then conducted to assess patterns in root architectural variation. ResultsSeveral manually collected and image-based root traits were identified as having a high potential of differentiating among contrasting phenotypes, while other traits are found to be inaccurate and thus unreliable for rice. The image-based traits projected area, root tip thickness, stem diameter, and root system depth successfully replace the manual determination of root characteristics, however attention should be paid to the lower accuracy of the image-based methodology, especially when working with older and larger root systems. ConclusionsThe challenges and opportunities of rice root phenotyping in field conditions are discussed for both methods. We therefore propose an integrated protocol adjusted to the complexity of the rice root structure combining image analysis in a water bath and the manual scoring of three traits (i.e. lateral density, secondary branching degree, and nodal root thickness at the root base). The proposed methodology ensures higher throughput and enhanced accuracy during root phenotyping of soil grown rice in fields or pots compared to manual scoring only, it is cheap to develop and operate, it is valid in remote environments, and it enables fast data extraction.

developmental biology↗

bioRxiv2020

Farm yard manure enhances phosphate fertilizer use efficiency in different upland rice genotypes through mitigating aluminium toxicity

Upland rice production on weathered soils is often constrained by phosphorus (P) deficiency and soil acidity. Farmyard manure application (FYM) can sharply enhance yields and agronomic P fertilizer (TSP) efficiency. We tested the hypothesis that rice genotypes differ in the extent of using organic P and offering distinct benefits under TSP-FYM combinations. Multiple field trials were conducted in the uplands of Madagascar, with factorial combinations of six genotypes, FYM, and TSP applications, with blanket N&K additions. Rice grain yields reached 6 t ha-1 after three years of TSP+FYM application, were lower when FYM or TSP were used separately, while crops failed under zero P input. Genotypic differences were inferior to the large treatment effects. Application of FYM increased soil pH and CaCl2-extractable P while decreasing CaCl2-extractable aluminium. An additional liming trial indicated that beneficial effects of FYM over TSP relate to liming effects. Genotypic ranking of yields and agronomic efficiency was inconsistent, without superior genotypes under FYM versus TSP. However, Chomrong Dhan and FOFIFA 172 showed superior yields under TSP+FYM. The FYM application lowers aluminium toxicity which overrules potential effects of organic P supply. Aluminium tolerance should be included when developing rice genotypes for low P tolerance in weathered soils.

plant biology↗

bioRxiv2020

Water and phosphorus uptake by upland rice root systems unraveled under multiple scenarios: linking a 3D soil-root model and data

Background and aimsUpland rice is often grown where water and phosphorus (P) are limited and these two factors interact on P bioavailability. To better understand this interaction, mechanistic models representing small-scale nutrient gradients and water dynamics in the rhizosphere of full-grown root systems are needed. MethodsRice was grown in large columns using a P-deficient soil at three different P supplies in the topsoil (deficient, suboptimal, non-limiting) in combination with two water regimes (field capacity versus drying periods). Root architectural parameters and P uptake were determined. Using a multiscale model of water and nutrient uptake, in-silico experiments were conducted by mimicking similar P and water treatments. First, 3D root systems were reconstructed by calibrating an architecure model with observed phenological root data, such as nodal root number, lateral types, interbranch distance, root diameters, and root biomass allocation along depth. Secondly, the multiscale model was informed with these 3D root architectures and the actual transpiration rates. Finally, water and P uptake were simulated. Key resultsThe plant P uptake increased over threefold by increasing P and water supply, and drying periods reduced P uptake at high but not at low P supply. Root architecture was significantly affected by the treatments. Without calibration, simulation results adequately predicted P uptake, including the different effects of drying periods on P uptake at different P levels. However, P uptake was underestimated under P deficiency, a process likely related to an underestimated affinity of P uptake transporters in the roots. Both types of laterals (i.e. S- and L-type) are shown to be highly important for both water and P uptake, and the relative contribution of each type depend on both soil P availability and water dynamics. Key drivers in P uptake are growing root tips and the distribution of laterals. ConclusionsThis model-data integration demonstrates how multiple co-occurring single root phene responses to environmental stressors contribute to the development of a more efficient root system. Further model improvements such as the use of Michaelis constants from buffered systems and the inclusion of mycorrhizal infections and exudates are proposed.

developmental biology↗