Proceedings :: International Society of Precision Agriculture

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Whelan, B.M

Delgado, J.A

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Authors

Delgado, J.A

Ascough II, J.C

Delgado, J.A

Sauer, B

Guppy, C.N

Trotter, M.G

Lamb, D.W

Delgado, J.A

Filippi, P

Jones, E.J

Fajardo, M

Whelan, B.M

Bishop, T.F

Topics

Precision Conservation and Carbon Management

Precision Conservation

Precision Nutrient Management

Big Data, Data Mining and Deep Learning

Type

Poster

Oral

Year

2012

2010

2018

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Filter results4 paper(s) found.
1. A New Version of the Nitrogen Trading Tool (NTT) To Assess Nitrogen Management across the USA A recent study from the USDA Economic Research Service (September 2011) reported that about one-third of U.S. cropland was found to meet the requirements for nutrient... J.A. Delgado, J.C. Ascough ii
2. A New GIS Approach To Assess Nitrogen Management Across The USA Nitrogen is one of the elements that are essential to maximizing agricultural productivity and economic returns for farmers. Its management is difficult because this element is very dynamic and mobile, characteristics that can contribute to significant losses via atmospheric, surface and/or leaching pathways. The magnitude of these losses can be affected by site-specific physical and chemical factors. These physical and chemical factors can vary significantly across the landscape, adding to the... J. Delgado Download paper
3. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol Soil Crop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado
4. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine Learning The ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop Download paper

Filter results4 paper(s) found.

1. A New Version of the Nitrogen Trading Tool (NTT) To Assess Nitrogen Management across the USA

A recent study from the USDA Economic Research Service (September 2011) reported that about one-third of U.S. cropland was found to meet the requirements for nutrient... J.A. Delgado, J.C. Ascough ii

2. A New GIS Approach To Assess Nitrogen Management Across The USA

Nitrogen is one of the elements that are essential to maximizing agricultural productivity and economic returns for farmers. Its management is difficult because this element is very dynamic and mobile, characteristics that can contribute to significant losses via atmospheric, surface and/or leaching pathways. The magnitude of these losses can be affected by site-specific physical and chemical factors. These physical and chemical factors can vary significantly across the landscape, adding to the... J. Delgado

Download paper

3. Matching Nitrogen To Plant Available Water For Malting Barley On Highly Constrained Vertosol Soil

Crop yield monitoring, high resolution aerial imagery and electromagnetic induction (EMI) soil sensing are three widely used techniques in precision agriculture (PA). Yield maps provide an indication of the crop’s response to a particular management regime in light of spatially-variable constraints. Aerial imagery provides timely and accurate information about photosynthetically-active biomass during crop growth and EMI indicates spatial variability in soil texture, salinity and/or... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado

4. Forecasting Crop Yield Using Multi-Layered, Whole-Farm Data Sets and Machine Learning

The ultimate goal of Precision Agriculture is to improve decision making in the business of farming. Many broadacre farmers now have a number of years of crop yield data for their fields which are often augmented with additional spatial data, such as apparent soil electrical conductivity (ECa), soil gamma radiometrics, terrain attributes and soil sample information. In addition there are now freely available public datasets, such as rainfall, digital soil maps and archives of satellite remote... P. Filippi, E.J. Jones, M. Fajardo, B.M. Whelan, T.F. Bishop

Download paper