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Fernandez, F.G
Rupe, J.C
Li, X
Llorens, J
Randhawa , R
Jimenez, A
Rodrigues Jr, F
Ransom, C
Lejealle, S
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Authors
Randhawa , R
Bourgain, O
Duval, C
Llorens, J
kulkarni, S.S
Doubledee, M
Bajwa, S.G
Rupe, J.C
Lejealle, S
Rodrigues Jr, F
Maglh, P.S
Cerri, D.G
Duval, C
Llorens, J
Duval, C
Duval, C
Ta, S
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
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
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
Li, X
Coble, K
Oliveira, M.F
Morata, G.T
Ortiz, B
Silva, R.P
Jimenez, A
Li, X
Topics
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability, and Adoption
Remote Sensing Applications in Precision Agriculture
Precision A-Z for Practitioners
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Precision Nutrient Management
In-Season Nitrogen Management
Profitability and Success Stories in Precision Agriculture
Big Data, Data Mining and Deep Learning
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2010
2016
2018
2022
2024
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Filter results12 paper(s) found.

1. Economic Profitability Of Site-specific Pesticide Management At The Farm Scale For Crop Systems In Haute-Normandie (France)

 Modern agriculture requires decision making criteria applicable to different scales of territory in order to reconcile productivity and respect of the environment, particularly for pest management. Taking into account the recent environmental... O. Bourgain, C. Duval, J. Llorens

2. Soybean Canopy Response To Charcoal Rot In Arkansas: Observations Using Crop Circletm (ACS-470).

Charcoal Rot caused by Macrophomina phaseolina is a problem to soybean production, especially in hot and dry areas of southern US. As an approach to develop a fast assessment method of this soil-borne disease, soybean canopy reflectance was recorded with an active optical sensor, the Crop CircleTM ACS-470 in 2009 from a microplot field in Fayetteville, Arkansas. The microplot experiment was designed as a completely randomized factorial experiment with four cultivars, two inoculum... S.S. Kulkarni, M. Doubledee, S.G. Bajwa, J.C. Rupe

3. Multiplex : A New Diagnostic Tool For Management Of Nitrogen Fertilization Of Turfgrass

Multiplex is a fluorescence-based optical sensor that measures in real time and in vivo the leaf content of compounds such as chlorophyll and several families of polyphenols (anthocyanins, flavonoïds, hydroxycinnamic acids). We propose here to show that the measurement of leaf chlorophyll and flavonoïd content permits us to evaluate nitrogen status of turfgrass. Actually, experiments have shown that chlorophyll content increases whereas flavonoïd content decreases with increased... S. Lejealle

4. Spatial Variability Analyse And Correlation Between Physical Chemical Soil Attributes And Sugarcane Quality Parameters

With the high increment in the ethanol demand, the trend is that the planted area with sugar cane in Brazil will increase from the actual 7 million ha up to 12 million ha in 15 years. The sugar cane expansion demands, beyond the enlargement of the boundaries with the installation of new industrial units, better use of the production areas and improvement of the yield and quality, together with production costs reduction. In such a way, the adoption of Precision Agriculture... F. Rodrigues jr, P.S. Maglh, D.G. Cerri

5. Site-specific Fertilization Management: Influence Of The Past History Of The Addition Of Fertilizers On The Intra Field Variability Of The Rate Of P And K In The Soil.

 Site specific crop management adapts the fertilizer amount applied in relation to the intra field crop needs. In this context, tries were carried out under field conditions. The aim of the trials was to develop technico-economic baseline data and methodology of soil sampling for precision agriculture in Upper-Normandy. ... C. Duval, J. Llorens, C. Duval, C. Duval, S. Ta

6. Spectral Characterization to Discriminate Grass Weeds from Wheat Crop Using Remote Sensing and GIS for Precision Agriculture and Environmental Sustainability

Kaur, Ramanjit, Mahey RK, Mahal JS, Kingra PK and Kaur Pukhraj ... R. Randhawa

7. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

8. 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

9. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

 Improving corn (Zea maysL,) nitrogen (N) fertilizer rate recommendation tools can improve farmer’s profits and help mitigate N pollution. One way to improve N recommendation methods is to not rely on a single tool, but to employ two or more tools. Thiscould be thoughtof as “tool fusion”.The objective of this analysis was to improve N management by combining N recommendation tools used for guiding rates for an in-seasonN application. This evaluation was... C.J. Ransom, N.R. Kitchen, J.J. Camberato, P.R. Carter, R.B. Ferguson, F.G. Fernandez, D.W. Franzen, C.A. Laboski, E.D. Nafziger, J. Shanahan, J.E. Sawyer

10. Using Profitability Map to Make Precision Farming Decisions: A Case Study in Mississippi

Recent development in precision agriculture technologies have generated massive amount of geospatial data of farming, such as yield mapping, seeding rates, input applications, and so on. However, producers are still struggling to convert those precision data into farm management decisions to improve productivity and profitability of farming.  Indeed, deriving accurate decisions at each site of the field requires complex and comprehensive modeling of crop yield responses to various... X. Li, K. Coble

11. Coupling Machine Learning Algorithms and GIS for Crop Yield Predictions Based on Remote Sensing Imagery and Topographic Indices

In-season yield prediction can support crop management decisions helping farmers achieve their yield goals. The use of remote sensing to predict yield it is an alternative for non-destructive yield assessment but coupling auxiliary data such as topography features could help increase the accuracy of yield estimation. Predictive algorithms that can effectively identify, process and predict yield at field scale base on remote sensing and topography still needed. Machine learning could be an alternative... M.F. Oliveira, G.T. Morata, B. Ortiz, R.P. Silva, A. Jimenez

12. All for One and One for All: a Simulation Assessment of the Economic Value of Large-scale On-farm Experiment Network

While on-farm experiments offer invaluable insights for precision management decisions, their scope is usually confined to the specific conditions of individual farms and years, which limits the derivation of more broad and reliable decisions. To address this limitation, aggregating data from numerous farms of various crop growth conditions into a comprehensive dataset appears promising. However, the quantifiable value of this experiment network remains elusive, despite the common agreement of... X. Li