DeepWheat: Estimating Phenotypic Traits from Crop Images with Deep Learning

In this paper, we investigate estimating emergence and biomass traits from color images and elevation maps of wheat field plots. We employ a state-of-the-art deconvolutional network for segmentation and convolutional architectures, with residual and Inception-like layers, to estimate traits via high dimensional nonlinear regression. Evaluation was performed on two different species of wheat, grown in field plots for an experimental plant breeding study. Our framework achieves satisfactory performance with mean and standard deviation of absolute difference of 1.05 and 1.40 counts for emergence and 1.45 and 2.05 for biomass estimation. Our results for counting wheat plants from field images are better than the accuracy reported for the similar, but arguably less difficult, task of counting leaves from indoor images of rosette plants. Our results for biomass estimation, even with a very small dataset, improve upon all previously proposed approaches in the literature.Comment: WACV 2018 (Code repository: https://github.com/p2irc/deepwheat_WACV-2018

Pressure tuning of charge ordering in iron oxide

A Verwey-type charge-ordering transition in magnetite at 120 K leads to the formation of linear units of three iron ions with one shared electron, called trimerons. The recently-discovered iron pentoxide (Fe$_4$O$_5$) comprising mixed-valent iron cations at octahedral chains, demonstrates another unusual charge-ordering transition at 150 K involving competing formation of iron trimerons and dimerons. Here, we experimentally show that applied pressure can tune the charge-ordering pattern in Fe$_4$O$_5$ and strongly affect the ordering temperature. We report two charge-ordered phases, the first of which may comprise both dimeron and trimeron units, whereas, the second exhibits an overall dimerization involving both the octahedral and trigonal-prismatic chains of iron in the crystal structure. We link the dramatic change in the charge-ordering pattern in the second phase to redistribution of electrons between the octahedral and prismatic iron chains, and propose that the average oxidation state of the iron cations can pre-determine a charge-ordering pattern

GrowPro: a flexible and high-resolution imaging tool for high-throughput plant phenotyping in the field

Various remote sensing platforms are being used in agriculture research, but their capability and exibility may not be enough for carrying out e cient computer analysis. Low-quality data can a ect the accuracy of methods and techniques used for high-throughput phenotyping in plant breeding. Despite the fact that there are many available remote sensing tools, researchers are seeking new platforms with superior features and performance over already proven systems. In this thesis, we describe a novel approach for remote sensing for eld-based phenotyping called the GrowPro. This thesis presents an overview of related work and commonly available approaches to remote sensing, description of the designed system, data gathering procedure, post-processing pipeline and best practice for capturing plants. We show the ease of use of the GrowPro, simplicity of data gathering and qualify the accuracy of the stitching process. We proved that by using this novel approach, high-resolution RGB stitched images of regions of interests (e.g., an individual plot or range of plots) can be obtained. This method appeared to be stable over time, di erent trials and weather conditions. Examples of RGB stitched images of a variety of crops at various stages of growth have been described

Discovery of Elgoresyite, (Mg,Fe)5Si2O9: Implications for Novel Iron Magnesium Silicates in Rocky Planetary Interiors

International audienceAs the most abundant material of rocky Planets, alhigh-pressure PolYmorPhs of iron- andinum. bearingmagnesium silicates have long been soughtbybuoth observations and experiments. Meanwhile, it wasrecently revealed that iron oxides form (Fe0.)m (Fe203),, bomologous series above -'10 GPa according to laboratory high-pressureexperiments. Here, we report a new high-pressure iron-magnesium silicate, recently approved by the International Mineralogical Association as a new mineral (No. 2020-086) and named elgoresy,ite,in a shock-induced melt vein ot., the Suizhou L6 chondrite with a chemistry of (mg,Fe) ironi209. The crystal structure of this new silicate is the same as the oxide Fe709, strongly suggesting that silicates also form ((Mg,Fe)) (SiO2), series that are isostructural to iron oxides via0,m +Si(Mg2+,Fe') 2Fe3' substitution. To test this hypothesis, the phase relationships of the silicates and iron oxides should further investigated at higher temperature conditions. Newly found iron -magnesium silicate is a potential constituent mineral rocky planets with relatively high Mg0 + Fe0 content