10.4231/DFB0-F030
Alison J. Eagle , Cameron M. Pittelkow , Claudia Wagner-Riddle , Craig F. Drury , David E. Pelster , Douglas R. Smith , G. Philip Robertson , Gustavo Cambareri , Martin H. Chantigny , Rex A. Omonode , Rodney T. Venterea , Sylvie M. Brouder , Timothy B. Parkin , Tony J. Vyn
09/14/2020
Dataset for meta-analysis establishing generalized relationship between N2O emissions and field-crop partial N balance. Quantifying on-farm N2O emissions for food-supply chains.
Agriculture Agronomy Greenhouse Gas Emissions Net Nitrogen Balance Nitrogen Nitrous Oxide row crops Surplus Nitrogen
10.4231/JE4B-8J88
Cheng-Hsien Lin , Cliff Johnston , Richard H Grant
09/21/2020
This file includes the data used in the figures of the manuscript entitled 'Measuring N2O Emissions from Multiple Sources Using a Backward Lagrangian Stochastic Model'.
A backward Lagrangian stochastic (bLS) dispersion model Agronomy Atmospheric measurements Greenhouse Gas Emissions Maize multiple emission sources N2O OP-FTIR
10.4231/D2JJ-Y263
Mitchell R Tuinstra , Seth A Tolley
10/12/2020
Ear photometry was used to characterize 298 ex-PVP inbred lines and 274 Drought Tolerant Maize for Africa (DTMA) inbred lines when crossed to Iodent (PHP02) and/or Stiff Stalk (2FACC) testers for 25 yield-related traits in 2017 and 2018.
Agronomy Ear photometry in maize testcrosses heat-tolerant maize Maize
10.4231/BJHE-3239
Jeffrey J. Volenec , Margaret Gitau , Nicole S. De Armond , Pauline Welikhe , Ronald F. Turco , Sylvie M. Brouder
11/24/2020
The data included here are for the WQFS tile discharge, DRP concentrations and loads for the Miscanthus x giganteus, continuous maize with residue removal, and switchgrass variety Shawnee treatments only.
Agronomy Dissolved reactive phosphorus P sink soils P source soils Phosphorus loss Tile discharge Water Quality water quality data Water Quality Field Station
10.4231/69H7-CV75
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
A pipeline to generate the XML parameter file for APSIM was developed in R. The files and R codes are reported in "R Pipeline for Calculation of APSIM Parameters and Generating the XML File".
Agronomy APSIM Crop Growth Models APSIM Pipeline Remote Sensing
10.4231/KMK0-J993
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
The model calibration step compares the APSIM simulated results with measured phenotypes in field trials. Parameter adjustments are reported in “SorghumXMLOutputUQ”.
2018 Sorghum Simulation Agronomy APSIM Crop Model Remote Sensing
10.4231/0NX5-RT34
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
The APSIM models from 2018 West Lafayette were validated by comparing simulated and observed results of experiments conducted in 2015 West Lafayette.
2015 Sorghum Crop Simulation Agronomy Biophysical crop models Remote Sensing
10.4231/6NW4-TB31
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
The calibrated APSIM models from 2018 West Lafayette were validated by comparing simulated and observed results of experiments conducted in 2017 West Lafayette.
2017 Sorghum simulation Agronomy APSIM Crop Model Remote Sensing
10.4231/PRS2-AC22
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
In the Texas scenario simulations, the physiology parameters from 2018 West Lafayette were used to run APSIM simulations in Bushland, TX using multi-year historical weather data.
Agronomy APSIM Forage sorghum crop models Texas Scenario Simulation
10.4231/63GJ-CJ23
Kai-Wei Yang , Mitchell Tuinstra , Scott Chapman
12/15/2020
In the West Lafayette scenario simulations, the physiology parameters from 2018 West Lafayette were used to run APSIM simulations in West Lafayette using multi-year historical weather data.
Agronomy APSIM Forage sorghum modelling West Lafayette Scenario Simulation
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