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Chapman, Scott

Publications and source records attributed to Chapman, Scott.

Automated Sorghum Phenotyping and Trait Development Platform

There is an urgent need to accelerate energy crop development for the production of renewable transportation fuels from biomass. Our interdisciplinary team developed mobile, ground-based and aerial phenotyping platforms and advanced remote sensing data analysis tools to acquire and process imagery from different types of cameras (e.g. RGB, multispectral, hyperspectral, and thermal sensors) and LiDAR point cloud data in large-scale sorghum field trials during phase 1 of the project. Phase 2 focused on Technology to Market activities to deliver these systems to the market place coupled with targeted research programs to address specific limitations or challenges for these systems.

09 BIOMASS FUELS↗

Snowmass 2021 CMB-S4 White Paper

This Snowmass 2021 White Paper describes the Cosmic Microwave Background Stage 4 project CMB-S4, which is designed to cross critical thresholds in our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. We provide an overview of the science case, the technical design, and project plan.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Uncovering fossils of the distant Milky Way with UNIONS: NGC 5466 and its stellar stream

ABSTRACT We examine the spatial clustering of blue horizontal branch (BHB) stars from the u-band of the Canada–France Imaging Survey (CFIS, a component of the Ultraviolet Near-Infrared Optical Northern Survey, or UNIONS). All major groupings of stars are associated with previously known satellites, and among these is NGC 5466, a distant (16 kpc) globular cluster. NGC 5466 reportedly possesses a long stellar stream, although no individual members of the stream have previously been identified. Using both BHBs and more numerous red giant branch stars cross-matched to Gaia Data Release 2, we identify extended tidal tails from NGC 5466 that are both spatially and kinematically coherent. Interestingly, we find that this stream does not follow the same path as the previous detection at large distances from the cluster. We trace the stream across 31° of sky and show that it exhibits a very strong distance gradient in the range 10 < Rhelio < 30 kpc. We compare our observations to simple dynamical models of the stream and find that they are able to broadly reproduce the overall path and kinematics. The fact that NGC 5466 is so distant, traces a wide range of Galactic distances, has an identified progenitor, and appears to have recently had an interaction with the Galaxy’s disc makes it a unique test-case for dynamical modelling of the Milky Way.

Jensen, Jaclyn↗

Integrating crop growth models with remote sensing for predicting biomass yield of sorghum

Abstract Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programmes to develop varieties aimed at performance in the target environments. Crop models can improve this testing regime by providing a predictive framework to (i) augment field phenotyping data and derive hard-to-measure phenotypes and (ii) estimate performance across geographical regions using historical weather data. The goal of this study was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits in 18 commercial grain and biomass sorghum hybrids. Genotype parameters for each hybrid were estimated using remote-sensing measurements combined with manual phenotyping in West Lafayette, IN, in 2018. The models were validated in hybrid performance trials in two additional seasons at that site and against yield trials conducted in Bushland, TX, between 2001 and 2018. These trials demonstrated that (i) maximum plant height, final dry biomass and radiation use efficiency (RUE) of photoperiod-sensitive and -insensitive forage sorghum hybrids tended to be higher than observed in grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass production in longer growing environments and (iii) the parameterized and validated models perform well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize larger plant breeding populations.

Yang, Kai-Wei↗