Datasets

date: 2023

Total is 119 Results
mHealth hyperspectral learning for hemodynamics

10.4231/VAFP-DW68

Young L Kim ORCID logo

03/27/2023

A small sampling of hyperspectral data enables spectrally informed learning to recover a hypercube from a red-green-blue (RGB) image without complete hyperspectral measurements. Hyperspectral learning is capable of recovering full spectroscopic resolution

Biomedical Engineering hemodynamics Matlab mHealth spectral learning

Source Data for Organic Optoelectronic Synapse

10.4231/K3D7-2698

Ashkan Abtahi , Habtom B Gobeze , Hang Hu , Inho Song , Jianguo Mei , Ke Chen ORCID logo , Kirk S. Schanze , Won-June Lee

06/23/2023

Source data for manuscript 'Organic Optoelectronic Synapse Based on Photon-Modulated Electrochemical Doping ' ( 10.1038/s41566-023-01232-x)

Chemistry electrochemical device image memorization and recognition organic optoelectronic synapse

COVID impacts on human-animal relationship and mental health

10.4231/B5TQ-5Z89

Hsin-Yi Weng ORCID logo , Niwako Ogata

03/29/2023

Trend in human-animal relationship, stress and loneliness during COVID pandemic

COVID-19 human-animal bond human-animal interaction Mental Health stress

Ovacık (Aphrodisias) Archaeological Survey: Processed Ceramics, 2017 through 2019

10.4231/0EAN-DE59

Günder Varinlioglu ORCID logo , Nicholas Kregotis Rauh ORCID logo , Noah Kaye ORCID logo , Stanislav Pejša ORCID logo

09/08/2023

This dataset contains the processed ceramics of the pedestrian survey conducted at Ovacık - Aphrodisias by the Boğsak Archaeological Survey Project, 2017-2019.

Ancient Greece Archaeological Survey Boğsak Ceramics Classical Studies geoarchaeology Late Roman Amphoras pottery Rough Cilicia Turkey

Row Selection in Remote Sensing for Maize and Sorghum

10.4231/PF9S-4G38

Mitchell R Tuinstra ORCID logo , Seth A Tolley ORCID logo

07/26/2023

Remote sensing data evaluates all row segments of a plot, but the repeatability of traits from different row segments has not been evaluated. We evaluated which row segments provide the best repeatability and yield prediction of remote sensing traits.

Border effect High-throughput Phenotyping hyperspectral LiDAR Maize Plot trimming Predictive modelling Remote Sensing RGB Sorghum UAV

Code and Model results for Soil organic carbon is a key determinant of CH4 sink in global forest soils

10.4231/8K7W-NF84

Hojeong Kang , Jaehyun Lee ORCID logo , Qianlai Zhuang ORCID logo , Youmi Oh ORCID logo

05/09/2023

This dataset contains code and model results for the paper 'Soil organic carbon is a key determinant of CH4 sink in global forest soils' by Lee et al. (2023).

Biogeochemistry EAPS global forest soils Methane Dynamics Model (MDM) soil methane oxidation

Genetic and environmental variation in alfalfa forage yield from variety testing experiments conducted in North America between 1986 to 1999

10.4231/QS1J-6J77

Daniel Wiersma , Jeffrey Volenec ORCID logo , Stanislav Pejša ORCID logo , Sylvie Brouder ORCID logo , Wayne G. Hartman

05/25/2023

The dataset contains data used to analyze genetic and environmental effects on alfalfa yield and agronomic performance. Data were compiled from alfalfa variety tests conducted by University researchers in the US and Canada from 1986 through 1999.

Agriculture Agronomy Alfalfa alfalfa_db Forage yield Genetic improvement Genotype x environment Germplasm Lucerne Medicago Variety testing

Investigating the Genomic Background and Predictive Ability of Genotype-by-environment Interactions in Maize Grain Yield Based on Reaction Norm Models

10.4231/0C1Q-2G44

Mitchell R Tuinstra ORCID logo , Seth A Tolley ORCID logo

05/12/2023

Genotype-by-environment interaction (GEI) is among the greatest challenges for maize breeding programs. The main objectives of this study were to evaluate genetic parameters and perform genomic prediction using a reaction norm model.

Agronomy G2F Genome-Wide Association Study Genomes 2 Fields Genomic Prediction Genotype-by-environment Interaction Grain Yield GxE Maize Multi-environment Trial Reaction Norm Model

Genetic Parameters and Multi-trait Genomic Prediction of Grain Yield on a Plot and Ear Basis in Temperate and Tropical Maize

10.4231/PQFT-7G59

Mitchell R Tuinstra ORCID logo , Seth A Tolley ORCID logo

05/02/2023

The objective of this study was to assess genetic parameters and perform single- and multi-trait genomic prediction of grain yield and yield components assessed through ear photometry in three testcross populations of either temperate or tropical descent.

Ear Photometry Ear photometry in maize testcrosses Genomic Prediction Grain Yield Maize Multi-Trait Genomic Prediction Single-Trait Genomic Prediction Temperate Germplasm Tropical Germplasm Yield components

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