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Oltmans, R.R
Laboski, C.A
Qian, S
Tarkalson, D
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Authors
Dobermann, A
Ferguson, R
Hergert, G
Shapiro, C
Tarkalson, D
Walters, D
Wortmann, C
Mallarino, A.P
Clover, M.W
Oltmans, R.R
Oltmans, R.R
Mallarino, A.P
Laboski, C.A
Andraski, T.W
Qian, S
Unrine, J
Poffenbarger, H
Orjuela Diaz, D
Laboski, C.A
Arriaga, F
Orjuela Diaz, D
Laboski, C.A
Arriaga, F
Topics
State Report
Graduate Award Student Poster
General
Graduate Award Student Poster
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Oral
Poster
Year
2006
2011
2020
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2023
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1. Should We Abandon Soil Testing and Yield Goals in Estimating Nitrogen Rates for Corn

If the prices of corn and fertilizer-N and the shape of the N response function relating crop yield to the amount of fertilizer used are known, calculating an economically optimal N rate (EONR) for maximizing the net return to applied N is straightforward: the EONR is the N rate at which no firher increase in net return occurs. In most cropping systems and under common price scenarios, crop yield at the EONR is within 95 to 99% of the maximum yield obtained for the specific management package. In...

2. Identification of Reasons for High Temporal Soil-Test Potassium Variation

Extensive research has focused on potassium (K) fertlization and soil K testing during several decades in the Corn Belt. IN Iowa, more t han 200 conventional or on-farm strip trials were conducted since the iddle 1990s until the early 2000s. Results of this research were used to update Iowa State University (ISU) K recommendations in 1999 and in 2002. In spite of increasd knowledge about soil-test K calibration, K fertilizer placement meethods, and needed K fertilizer rates, this research demonstrated...

3. Phosphorus and Potassium Removal and Leaching from Residue in Corn and Soybean

Research is continually being conducted to adjust and update recomm endations for phosphorus (P) and potassium (K), and to be tter understand relationships betw een nutrient application, grain yield, nutrient removal with harvest, and soil-test values. Studies in Iowa and other states of the north central region have been used to develop guidelines about P and K removal rates in corn and soybean for use together with soil testing information to manage P and K. There is very large temporal variability...

4. Lessons learned from long-term P & K trial

This presentation will disucss corn and soybean response to P and K over 10 years in a notill system.    ... C.A. Laboski, T.W. Andraski

5. Effects of Silicon Supplementation on Growth and Silicon Accumulation in Tall Fescue (Festuca arundinacea) and Bentgrass (Agrostis stolonifera)

This study assessed the effect of silicon (Si) supplementation on biomass production and Si accumulation of tall fescue (Festuca arundinacea) and bentgrass (Agrostis stolonifera). Plants were grown in buffered Hoagland’s media (pH 6) with four Na2SiO4 treatments (0, 0.5, 1, 2, 4 mM). The two species responded differently to Si supplementation in terms of biomass. For bentgrass, biomass was enhanced by Si supplementation, but only significantly (p... S. Qian, J. Unrine, H. Poffenbarger

6. Biochemical Soil Health Indicators Related to Economic Optimum Nitrogen Rate in Corn

In corn production, nitrogen (N) fertilization is one of the main inputs to enhance yield. However, in the last few years, reducing N utilization has been a goal due to environmental concerns and production costs. Soil health tests have been studied to understand the relationship with N availability and its use to adjust N recommendation rates. The objective of this study was to evaluate the relationship of different soil tests with the economic optimum N rate (N) for corn in Wisconsin. Soil samples... D. Orjuela diaz, C.A. Laboski, F. Arriaga

7. Employing Statistical Models to Determine the Soil Tests and/or Soil Characteristics That Improved EONR Prediction in Corn

In corn production, nitrogen (N) fertilization is crucial for increasing yield. However, in the last few years, there has been a push to use less N due to environmental concerns and production costs. There has been an interest in using soil health tests to predict N mineralization potential and further understand soil N availability to adjust N recommendation rates. Different statistical models like regression or decision tree analysis have been used to determine how the Economic Optimum N Rate... D. Orjuela diaz, C.A. Laboski, F. Arriaga