Proceedings

Find matching any: Reset
Hawkins, E
Murphy, L
Kovac, P
Add filter to result:
Authors
Murphy, L
Kovac, P
Van Scoyoc, G.E
Doerge, T.A
Camberato, J.J
Vyn, T.J
Matcham, E
Subburayalu, S
Fulton, J
Hawkins, E
Paul, P
Lindsey, L
Topics
Type
Oral
Poster
Year
1992
2012
2018
Home » Authors » Results

Authors

Filter results3 paper(s) found.

1. Importance of Subsoil Potassium

Recent information has emphasized the importance of nutrient distribution by depth in soils. Information from across the Cotton Belt in the U.S. has demonstrated that cotton yields have been affected by accumulation of potassium (K) near the soil surface with subsequent depletion of subsoil K. This condition combined with changes in K demand by new, high-yielding cotton varieties has led to a change in cotton K deficiency symptoms and delayed diagnosis of the actual problem. Recent studies have emphasized...

2. Consequences Of Shallow NH3 Placement And Timing On N Use Efficiencies In Corn Production

A field study in west-central Indiana was conducted to investigate the effects of shallow anhydrous ammonia (NH 3) placement and timing on N use efficiencies in a conventionally tilled corn production system following soybean crop. The spring NH 3 was applied either pre-plant (6- inches offset from future corn row) or side-dress (at mid-row position) at different rates (0, 80, 130 or 180 lbs N acre -1). Aboveground biomass harvest and combine harvested yield were used to determine N recovery, N internal...

3. Grid Soil Sample Interpolation Using Geographicaly Weighted Regression and Random Forest

Soil sampling is useful in agriculture for setting fertilizer application rates. High density soil samples can also be used for variable rate seeding and other precision agriculture applications. Half-acre grid soil samples were collected from 6 soybean fields, and phosphorous (P), potassium (K), and organic matter (OM) were measured. Each soil parameter was interpolated for each field, with terrain attributes as covariates, using two different methods: geographically weighted regression (GWR)... E. Matcham, S. Subburayalu, J. Fulton, E. Hawkins, P. Paul, L. Lindsey