Proceedings :: International Society of Precision Agriculture

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Du, X

Welp, G

Villodre, J

Armstrong, S

Weist, D

Das, A.K

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Authors

Sun, C

Ji, Z

Qian, J

Li, M

Zhao, L

Li, W

Zhou, C

Du, X

Xie, J

Wu, T

Qu, L

Hao, L

Yang, X

Schulthess, R

Schelling, K

Weist, D

Gebbers, R

Dworak, V

Mahns, B

Weltzien, C

Büchele, D

Gornushkin, I

Mailwald, M

Ostermann, M

Rühlmann, M

Schmid, T

Maiwald, M

Sumpf, B

Rühlmann, J

Bourouah, M

Scheithauer, H

Heil, K

Heggemann, T

Leenen, M

Pätzold, S

Welp, G

Chudy, T

Mizgirev, A

Wagner, P

Beitz, T

Kumke, M

Riebe, D

Kersebaum, C

Wallor, E

Osann, A

Campos, I

Calera, M

Plaza, C

Bodas, V

Calera, A

Villodre, J

Campoy, J

Sanchez, S

Jimenez, N

Lopez, H

Mathew, J.J

Flores, P.J

Stenger, J

Miranda, C

Zhang, Z

Das, A.K

Topics

Information Management and Traceability

Precision A-Z for Practitioners

Precision Nutrient Management

In-Season Nitrogen Management

Precision Agriculture and Global Food Security

Type

Poster

Oral

Year

2012

2010

2016

2018

2022

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Filter results5 paper(s) found.
1. Towards a Multi-Source Record Keeping System for Agricultural Product Traceability Agricultural production record keeping is the basis of traceability system. To resolve the problem including single method of information acquisition, weak ability of real-time monitoring and low credibility of history information in agricultural production process, the... C. Sun, Z. Ji, J. Qian, M. Li, L. Zhao, W. Li, C. Zhou, X. Du, J. Xie, T. Wu, L. Qu, L. Hao, X. Yang Download paper
2. From Rapideye's Spad In The Sky To N Application Maps ... R. Schulthess, K. Schelling, D. Weist
3. Integrated Approach to Site-specific Soil Fertility Management In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor Download paper
4. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez Download paper
5. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision Applications Crop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation tools,... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das Download paper

Filter results5 paper(s) found.

1. Towards a Multi-Source Record Keeping System for Agricultural Product Traceability

Agricultural production record keeping is the basis of traceability system. To resolve the problem including single method of information acquisition, weak ability of real-time monitoring and low credibility of history information in agricultural production process, the... C. Sun, Z. Ji, J. Qian, M. Li, L. Zhao, W. Li, C. Zhou, X. Du, J. Xie, T. Wu, L. Qu, L. Hao, X. Yang

Download paper

2. From Rapideye's Spad In The Sky To N Application Maps

... R. Schulthess, K. Schelling, D. Weist

3. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a fundamental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

Download paper

4. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez

Download paper

5. Comparative Analysis of Light-weight Deep Learning Architectures for Soybean Yield Estimation Based on Pod Count from Proximal Sensing Data for Mobile and Embedded Vision Applications

Crop yield prediction is an important aspect of farming and food-production. Therefore, estimating yield is important for crop breeders, seed-companies, and farmers to make informed real-time financial decisions. In-field soybean (Glycine max L.(Merr.)) yield estimation can be of great value to plant breeders as they screen thousands of plots to identify better yielding genotypes that ultimately will strengthen national food security. Existing soybean yield estimation tools,... J.J. Mathew, P.J. Flores, J. Stenger, C. Miranda, Z. Zhang, A.K. Das

Download paper