dc.contributor.author | Schimek, Nicholas James | |
dc.description.abstract | A challenge for hard red spring wheat (HRSW) (Triticum aestivum L. emend Thell.) producers is to obtain both high yields and market-required grain protein content (GPC). The ability to accurately predict HRSW yield with the Decision Support System for Agrotechnology Transfer (DSSAT) crop model early in the growing season may help producers determine probable GPC and lead to management decisions on whether to apply supplemental nitrogen (N) to enhance protein. A management decision HRSW producers may consider in high yielding environments is a late-season foliar N application to increase GPC. A second objective of this research was to test methods to improve the efficiency of a foliar N application. Improving the efficiency of a late-season foliar N application coupled with the ability to predict high yielding environments using DSSAT, can provide producers with effective management tools to determine the optimum situation in which supplementing GPC will have the most economic success. | en_US |
dc.publisher | North Dakota State University | en_US |
dc.rights | NDSU policy 190.6.2 | |
dc.title | Developing Methodology to Predict and Increase Grain Protein Content in Spring Wheat | en_US |
dc.type | Thesis | en_US |
dc.date.accessioned | 2018-07-03T19:39:41Z | |
dc.date.available | 2018-07-03T19:39:41Z | |
dc.date.issued | 2017 | en_US |
dc.identifier.uri | https://hdl.handle.net/10365/28399 | |
dc.description.sponsorship | North Dakota State University (NDSU) | en_US |
dc.description.sponsorship | North Dakota State University. Experiment Stations | en_US |
dc.description.sponsorship | North Dakota (State) | en_US |
dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
ndsu.degree | Master of Science (MS) | en_US |
ndsu.college | Agriculture, Food Systems and Natural Resources | en_US |
ndsu.department | Plant Sciences | en_US |
ndsu.program | Plant Sciences | en_US |
ndsu.advisor | Ransom, Joel K. | |