Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
- Publication
- Publication Type
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Annual Forage Cropping-Systems For Midwestern Ruminant Livestock Production, John Ernest Mcmillan
Annual Forage Cropping-Systems For Midwestern Ruminant Livestock Production, John Ernest Mcmillan
Open Access Dissertations
Annual forage cropping systems are a vital aspect of livestock forage production. One area where this production system can be enhanced is the integration of novel annual forages into conventional cropping systems. Two separate projects were conducted to investigate alternative forage options in annual forage production. In the first discussed research trial, two sets of crops were sown following soft red winter wheat (Triticum aestivum L.) grain harvest, at two nitrogen application rates 56 and 112 kg ha-1 . The first set of crops were C4 summer annuals seeded within two weeks of wheat grain harvest and included, brown …
Residual Effects Of Nitrogen Fertilization On Soil Nitrogen Pools And Corn Growth, Meghan E. Moser
Residual Effects Of Nitrogen Fertilization On Soil Nitrogen Pools And Corn Growth, Meghan E. Moser
Open Access Theses
Given the dynamic nature of soil nitrogen (N), inorganic N fertilization to corn (Zea mays L.) has potential to alter N pool balance by creating an accumulation or depletion of soil N. Current corn N recommendations in the common corn-soybean rotation of Indiana strive to find the best N rate that maximizes producer profit. Increasing our understanding of soil N will inform producers if they should adjust fertilizer rates for corn to influence maintenance of organic N and Carbon. Our objective was to determine residual N effects from fertilized corn in a corn-soybean rotation by measuring (1) soil N …
Learning From Data: Plant Breeding Applications Of Machine Learning, Alencar Xavier
Learning From Data: Plant Breeding Applications Of Machine Learning, Alencar Xavier
Open Access Dissertations
Increasingly, new sources of data are being incorporated into plant breeding pipelines. Enormous amounts of data from field phenomics and genotyping technologies places data mining and analysis into a completely different level that is challenging from practical and theoretical standpoints. Intelligent decision-making relies on our capability of extracting from data useful information that may help us to achieve our goals more efficiently. Many plant breeders, agronomists and geneticists perform analyses without knowing relevant underlying assumptions, strengths or pitfalls of the employed methods. The study endeavors to assess statistical learning properties and plant breeding applications of supervised and unsupervised machine learning …
Developing Probability Maps For Locating And Scouting Unprotected Areas Of Gravel Hill Prairies On Rodman Soils Along The Wabash River Valley Near Lafayette, Indiana, Ryan W.R. Schroeder
Developing Probability Maps For Locating And Scouting Unprotected Areas Of Gravel Hill Prairies On Rodman Soils Along The Wabash River Valley Near Lafayette, Indiana, Ryan W.R. Schroeder
Engagement & Service-Learning Summit
No abstract provided.
Improved Prediction Of Severe Thunderstorms Over The Indian Monsoon Region Using High-Resolution Soil Moisture And Temperature Initialization, K. K. Osuri, R. Nadimpalli, U. C. Mohanty, F. Chen, M. Rajeevan, Dev Niyogi
Improved Prediction Of Severe Thunderstorms Over The Indian Monsoon Region Using High-Resolution Soil Moisture And Temperature Initialization, K. K. Osuri, R. Nadimpalli, U. C. Mohanty, F. Chen, M. Rajeevan, Dev Niyogi
Department of Earth, Atmospheric, and Planetary Sciences Faculty Publications
The hypothesis that realistic land conditions such as soil moisture/soil temperature (SM/ST) can significantly improve the modeling of mesoscale deep convection is tested over the Indian monsoon region (IMR). A high resolution (3 km foot print) SM/ST dataset prepared from a land data assimilation system, as part of a national monsoon mission project, showed close agreement with observations. Experiments are conducted with (LDAS) and without (CNTL) initialization of SM/ST dataset. Results highlight the significance of realistic land surface conditions on numerical prediction of initiation, movement and timing of severe thunderstorms as compared to that currently being initialized by climatological fields …