1. Corn Algorithm Comparisons, NUE Workshop
CIMMYT University of Nebraska University of Missouri University of Minnesota Kansas State University LSU Iowa State University Ohio State University Virginia Tech

2. Variables Employed √ √ 168 √250 √220 √200 td √ 170, 220 Variable 56 50
Predicted yield √
SI or RI
RI adjustment
N rate based on projected yield increase
GDD’s, days
N rate function of expected NUE
Max N Rate
√ 168
√250
√220
√200 td
Max Yield
Farmer specified
300
Lim. Pre N, lowest N rate
Farmer Practice 56
½ of Total N Rate 50
Pivotal N rate
√ 170, 220
CV of plant stand
Soil moisture at sensing

3. Data compiled by Dr. Robert Mullen, The Ohio State University

4. Data compiled by Dr. Robert Mullen, The Ohio State University

5. Check yield * RI Difference in N uptake (optimum N rate observed – check yield N uptake)/0.5

7. SBNRC (YP0*RI = YPN) 100 Pre (100 lbs N/ac applied preplant)
Difference, 12.7±7.2 bu/ac
Range 36 to 73 7

9. Conclusions Soil moisture at sensing Soil temperature
Climatological probability
Combining components
Predicting mid-season NUE