Measurement of plant growth in view of an integrative analysis of regulatory networks

As the regulatory networks of growth at the cellular level are elucidated at a fast pace, their complexity is not reduced; on the contrary, the tissue, organ and even whole-plant level affect cell proliferation and expansion by means of development-induced and environment-induced signaling events in growth regulatory processes. Measurement of growth across different levels aids in gaining a mechanistic understanding of growth, and in defining the spatial and temporal resolution of sampling strategies for molecular analyses in the model Arabidopsis thaliana and increasingly also in crop species. The latter claim their place at the forefront of plant research, since global issues and future needs drive the translation from laboratory model-acquired knowledge of growth processes to improvements in crop productivity in field conditions

Structure and dynamics of high-z galaxies

HST and integral-field spectroscopic observations of star-forming galaxies at cosmic noon provide a view on the spatial distribution of stars, gas and dust, and probe gaseous motions revealing the central gravitational potential and local feedback processes at play. In this paper, we review recent insights gained from such observations, with an emphasis on results obtained through near-infrared imaging spectroscopy. Their context and implications are documented more fully in a forthcoming review article by Förster Schreiber &amp; Wuyts (in prep).</p

Resolved views on early galaxy evolution

Resolved observations of star-forming galaxies at cosmic noon with the Hubble Space Telescope and large ground-based facilities provide a view on the spatial distribution of stars, gas and dust, and probe gaseous motions revealing the central gravitational potential and local feedback processes at play. In this paper, we review recent insights gained from such observations, with an emphasis on results obtained through optical/near-infrared imaging and imaging spectroscopy. Their context and implications are documented more fully in a forthcoming review article by Förster Schreiber & Wuyts (in prep)

3D reconstruction of maize plants in the phenoVision system

In order to efficiently study the impact of environmental changes, or the differences between various genotypes, large numbers of plants need to be measured. At the VIB, a system named \emph{PhenoVision} was built to automatically image plants during their growth. This system is used to evaluate the impact of drought on different maize genotypes. To this end, we require 3D reconstructions of the maize plants, which we obtain from voxel carving

MOONS:The New Multi-Object Spectrograph for the VLT

MOONS is the new Multi-Object Optical and Near-infrared Spectrograph currently under construction for the Very Large Telescope (VLT) at ESO. This remarkable instrument combines, for the first time, the collecting power of an 8-m telescope, 1000 fibres with individual robotic positioners, and both low- and high-resolution simultaneous spectral coverage across the 0.64-1.8 micron wavelength range. This facility will provide the astronomical community with a powerful, world-leading instrument able to serve a wide range of Galactic, extragalactic and cosmological studies. Construction is now proceeding full steam ahead and this overview article presents some of the science goals and the technical description of the MOONS instrument. More detailed information on the MOONS surveys is provided in the other dedicated articles in this Messenger issue

GPU-based maize plant analysis: accelerating CNN segmentation and voxel carving

PHENOVISION is a high-throughput plant phenotyping system for crop plants in greenhouse conditions. A conveyor belt transports plants between automated irrigation stations and imaging cabins. The aim is to phenotype maize varieties grown under different conditions. To this end we model the plants in 3D and automate the measuring of the plants

Machine learning for maize plant segmentation

High-throughput plant phenotyping platforms produce immense volumes of image data. Here, a binary segmentation of maize colour images is required for 3D reconstruction of plant structure and measurement of growth traits. To this end, we employ a convolutional neural network (CNN) to perform this segmentation successfully

Optimal metallicity diagnostics for MUSE observations of low-z galaxies

© 2023 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/The relatively red wavelength range (4800-9300 Å) of the VLT Multi Unit Spectroscopic Explorer (MUSE) limits which metallicity diagnostics can be used; in particular excluding those requiring the []λλ3726,29 doublet. We assess various strong line diagnostics by comparing to sulphur -based metallicity measurements for a sample of 671 H ii regions from 36 nearby galaxies from the MUSE Atlas of Disks (MAD) survey. We find that the O3N2 and N2 diagnostics return a narrower range of metallicities that lie up to ∼0.3 dex below -based measurements, with a clear dependence on both metallicity and ionization parameter. The N2S2H α diagnostic shows a near-linear relation with the -based metallicities, although with a systematic downward offset of ∼0.2 dex, but no clear dependence on ionization parameter. These results imply that the N2S2H α diagnostic produces the most reliable results when studying the distribution of metals within galaxies with MUSE. On sub-H ii region scales, the O3N2 and N2 diagnostics measure metallicity decreasing towards the centres of H ii regions, contrary to expectations. The S-calibration and N2S2H α diagnostics show no evidence of this, and show a positive relationship between ionization parameter and metallicity at > 8.4, implying the relationship between ionization parameter and metallicity differs on local and global scales. We also present hiidentify, a python tool developed to identify H ii regions within galaxies from H α emission maps. All segmentation maps and measured emission line strengths for the 4408 H ii regions identified within the MAD sample are available to download.Peer reviewe

Investigating the Origin of Observed Central Dips in Radial Metallicity Profiles

Radial metallicity trends provide a key indicator of physical processes such as star formation and radial gas migration within a galaxy. Large IFU surveys allow for detailed studies of these radial variations, with recent observations detecting central dips in the metallicity, which may trace the impact of various evolutionary processes. However, the origin of these dips has not been conclusively determined, with suggestions that they may be diagnostic dependent. In this paper, we use the SDSS-IV MaNGA survey to investigate whether the observed dips represent genuine decreases in the central metallicity, or if they could be an artefact of the diagnostic used. Using a sub-sample of 758 local star-forming galaxies at low inclinations, we investigate in detail the impact of using different strong line diagnostics on the shapes of the returned profiles, and the prevalence of dips. We find no clear evidence of the dips being caused by changing values of the ionisation parameter within galaxies. To investigate physical causes, we explore both global and spatially-resolved parameters, finding that galaxies exhibiting central dips in the O3N2 metallicity profile have on average lower H$\alpha$EW values out to R/R_\rm{e} \sim 1.5, and higher values of D$_N$(4000) in the central regions. We additionally find a higher prevalence of dips in galaxies with high stellar mass, and lower values of global specific star formation rate, suggesting a possible link to central quenching. Nevertheless, these results are dependent on the diagnostic used, suggesting caution should be taken when interpreting observed features in galaxy metallicity gradients.Comment: Accepted for publication in MNRAS. 23 pages; 21 figure