Proceedings :: International Society of Precision Agriculture

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Laboski, C.A

Hannah, L

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Authors

Bean, G.M

Kitchen, N.R

Camberato, J.J

Ferguson, R.B

Fernandez, F.G

Franzen, D.W

Laboski, C.A

Nafziger, E.D

Sawyer, J.E

Scharf, P.C

KC, K

Hannah, L

Roehrdanz, P

Donatti, C

Fraser, E

Berg, A

Saenz, L

Wright, T.M

Hijmans, R.J

Mulligan, M

Topics

In-Season Nitrogen Management

Geospatial Data

Type

Oral

Year

2018

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Filter results2 paper(s) found.
1. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf Download paper
2. Using Geospatial Data to Assess How Climate Change May Affect Land Suitability for Agriculture Production Finding solutions to the challenge of sustainably feeding the world’s growing population is a pressing research need that cuts across many disciplines including using geospatial data. One possible area could be developing agricultural frontiers. Frontiers are defined as land that is currently not cultivated but that may become suitable for agriculture under climate change. Climate change may drive large-scale geographic shifts in agriculture, including expansion in cultivation at the thermal... K. Kc, L. Hannah, P. Roehrdanz, C. Donatti, E. Fraser, A. Berg, L. Saenz, T.M. Wright, R.J. Hijmans, M. Mulligan

Filter results2 paper(s) found.

1. Corn Nitrogen Fertilizer Recommendation Models Based on Soil Hydrologic Groups Aid in Predicting Economically Optimal Nitrogen Rates

Nitrogen (N) fertilizer recommendations that match corn (Zea mays L.) N needs maximize grower profits and minimize water quality consequences. However, spatial and temporal variability makes determining future N requirements difficult. Studies have shown no single soil or weather measurement is consistently increases accuracy, especially when applied over a regional scale, in predicting economically optimal N rate (EONR). Basing site N response on soil hydrological group could help account for... G.M. Bean, N.R. Kitchen, J.J. Camberato, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J.E. Sawyer, P.C. Scharf

Download paper

2. Using Geospatial Data to Assess How Climate Change May Affect Land Suitability for Agriculture Production

Finding solutions to the challenge of sustainably feeding the world’s growing population is a pressing research need that cuts across many disciplines including using geospatial data. One possible area could be developing agricultural frontiers. Frontiers are defined as land that is currently not cultivated but that may become suitable for agriculture under climate change. Climate change may drive large-scale geographic shifts in agriculture, including expansion in cultivation at the thermal... K. Kc, L. Hannah, P. Roehrdanz, C. Donatti, E. Fraser, A. Berg, L. Saenz, T.M. Wright, R.J. Hijmans, M. Mulligan