250 research outputs found
MULTILOCUS INTERACTIONS RESTRICT GENE INTROGRESSION IN INTERSPECIFIC POPULATIONS OF POLYPLOID GOSSYPIUM (COTTON)
Gravimetric phenotyping of whole plant transpiration responses to atmospheric vapour pressure deficit identifies genotypic variation in water use efficiency
There is increasing interest in rapidly identifying genotypes with improved water use efficiency, exemplified by the development of whole plant phenotyping platforms that automatically measure plant growth and water use. Transpirational responses to atmospheric vapour pressure deficit (VPD) and whole plant water use efficiency (WUE, defined as the accumulation of above ground biomass per unit of water used) were measured in 100 maize (Zea mays L.) genotypes. Using a glasshouse based phenotyping platform with naturally varying VPD (1.5 to 3.8 kPa), a 2-fold variation in WUE was identified in well-watered plants. Regression analysis of transpiration versus VPD under these conditions, and subsequent whole plant gas exchange at imposed VPDs (0.8 to 3.4 kPa) showed identical responses in specific genotypes. Genotype response of transpiration versus VPD fell into two categories: 1) a linear increase in transpiration rate with VPD with low (high WUE) or high (low WUE) transpiration rate at all VPDs, 2) a non-linear response with a pronounced change point at low VPD (high WUE) or high VPD (low WUE). In the latter group, high WUE genotypes required a significantly lower VPD before transpiration was restricted, and had a significantly lower rate of transpiration in response to VPD after this point, when compared to low WUE genotypes. Change point values were significantly positively correlated with stomatal sensitivity to VPD. A change point in stomatal response to VPD may explain why some genotypes show contradictory WUE rankings according to whether they are measured under glasshouse or field conditions. Furthermore, this novel use of a high throughput phenotyping platform successfully reproduced the gas exchange responses of individuals measured in whole plant chambers, accelerating the identification of plants with high WUE
Analysis of root growth from a phenotyping data set using a density-based model
Major research efforts are targeting the improved performance of root systems for more efficient use of water and nutrients by crops. However, characterizing root system architecture (RSA) is challenging, because roots are difficult objects to observe and analyse. A model-based analysis of RSA traits from phenotyping image data is presented. The model can successfully back-calculate growth parameters without the need to measure individual roots. The mathematical model uses partial differential equations to describe root system development. Methods based on kernel estimators were used to quantify root density distributions from experimental image data, and different optimization approaches to parameterize the model were tested. The model was tested on root images of a set of 89 Brassica rapa L. individuals of the same genotype grown for 14 d after sowing on blue filter paper. Optimized root growth parameters enabled the final (modelled) length of the main root axes to be matched within 1% of their mean values observed in experiments. Parameterized values for elongation rates were within ±4% of the values measured directly on images. Future work should investigate the time dependency of growth parameters using time-lapse image data. The approach is a potentially powerful quantitative technique for identifying crop genotypes with more efficient root systems, using (even incomplete) data from high-throughput phenotyping systems
Modification of the expression of the aquaporin ZmPIP2;5 affects water relations and plant growth
The maize plasma membrane PIP2;5 aquaporin plays a role in controlling root radial water movement, leaf hydraulic conductivity, and plant growth.
The plasma membrane intrinsic protein PIP2;5 is the most highly expressed aquaporin in maize (Zea mays) roots. Here, we investigated how deregulation of PIP2;5 expression affects water relations and growth using maize overexpression (OE; B104 inbred) or knockout (KO; W22 inbred) lines. The hydraulic conductivity of the cortex cells of roots grown hydroponically was higher in PIP2;5 OE and lower in pip2;5 KO lines compared with the corresponding wild-type plants. While whole-root conductivity decreased in the KO lines compared to the wild type, no difference was observed in OE plants. This paradox was interpreted using the MECHA hydraulic model, which computes the radial flow of water within root sections. The model hints that the plasma membrane permeability of the cells is not radially uniform but that PIP2;5 may be saturated in cell layers with apoplastic barriers, i.e. the endodermis and exodermis, suggesting the presence of posttranslational mechanisms controlling the abundance of PIP in the plasma membrane in these cells. At the leaf level, where the PIP2;5 gene is weakly expressed in wild-type plants, the hydraulic conductance was higher in the PIP2;5 OE lines compared with the wild-type plants, whereas no difference was observed in the pip2;5 KO lines. The temporal trend of leaf elongation rate, used as a proxy for that of xylem water potential, was faster in PIP2;5 OE plants upon mild stress, but not in well-watered conditions, demonstrating that PIP2;5 may play a beneficial role in plant growth under specific conditions
High resolution imaging of maize (Zea mays) leaf temperature in the field: the key role of the regions of interest
Abstract. The use of remote sensors (thermometers and cameras) to analyse crop water status in field conditions is fraught with several difficulties. In particular, average canopy temperature measurements are affected by the mixture of soil and green regions, the mutual shading of leaves and the variability of absorbed radiation. The aim of the study was to analyse how the selection of different 'regions of interest' (ROI) in canopy images affect the variability of the resulting temperature averages. Using automated image segmentation techniques we computed the average temperature in four nested ROI of decreasing size, from the whole image down to the sunlit fraction of a leaf located in the upper part of the canopy. The study was conducted on maize (Zea mays L.) at the flowering stage, for its large leaves and well structured canopy. Our results suggest that, under these conditions, the ROI comprising the sunlit fraction of a leaf located in the upper part of the canopy should be analogous to the single leaf approach (in controlled conditions) that allows the estimation of stomatal conductance or plant water potential
Root system markup language: toward an unified root architecture description language
The number of image analysis tools supporting the extraction of architectural features of root systems has increased over the last years. These tools offer a handy set of complementary facilities, yet it is widely accepted that none of these software tool is able to extract in an efficient way growing array of static and dynamic features for different types of images and species.
We describe the Root System Markup Language (RSML) that has been designed to overcome two major challenges: (i) to enable portability of root architecture data between different software tools in an easy and interoperable manner allowing seamless collaborative work, and (ii) to provide a standard format upon which to base central repositories which will soon arise following the expanding worldwide root phenotyping effort.
RSML follows the XML standard to store 2D or 3D image metadata, plant and root properties and geometries, continuous functions along individual root paths and a suite of annotations at the image, plant or root scales, at one or several time points. Plant ontologies are used to describe botanical entities that are relevant at the scale of root system architecture. An xml-schema describes the features and constraints of RSML and open-source packages have been developed in several languages (R, Excel, Java, Python, C#) to enable researchers to integrate RSML files into popular research workflow
Non-invasive hydrodynamic imaging in plant roots at cellular resolution
A key impediment to studying water-related mechanisms in plants is the inability to non-invasively image water fluxes in cells at high temporal and spatial resolution. Here, we report that Raman microspectroscopy, complemented by hydrodynamic modelling, can achieve this goal - monitoring hydrodynamics within living root tissues at cell- and sub-second-scale resolutions. Raman imaging of water-transporting xylem vessels in Arabidopsis thaliana mutant roots reveals faster xylem water transport in endodermal diffusion barrier mutants. Furthermore, transverse line scans across the root suggest water transported via the root xylem does not re-enter outer root tissues nor the surrounding soil when en-route to shoot tissues if endodermal diffusion barriers are intact, thereby separating ‘two water worlds’
Does root plasticity contribute to crop tolerance to abiotic stresses?
Poster that presents the experiments, the main results and take home messages
Toward Integration of Comparative Genetic, Physical, Diversity, and Cytomolecular Maps for Grasses and Grains, Using the Sorghum Genome as a Foundation
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