Proceedings :: International Society of Precision Agriculture

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2022

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Authors

Abbas, F

Abdala, M

Abenina, M

Abukmeil, R

Adamchuk, V

Adedeji, O

Adedeji, O.I

Adhikari, K

Adu-Gyamfi, Y

Aggarwal, V

Agneroh, T

Ahmad, A

Ahrends, H.E

Aikes Junior, J

Al Amin, A

Al-Gaadi, K

Alchanati, V

Alchanatis, V

Alderman, P.D

Aldridge, K

Ali, A

Ali, U

Allegro, G

Almallahi, A

Amaral, L.R

Ameglio, L

Amin, S

Amouzou, K.A

Ampatzidis, Y

Anaba, C.I

Andersen, P

Anderson, S.H

Andvaag, E

Antunes, J.F

Archontoulis, S

Arias, A

Arias, A.C

Ashworth, A

Attanayake, A

Attanayake, A.U

Balboa, G

Balla, I

Balzarini, M

Bareth, G

Barker, D

Baumbauer, C

Bautista, F

Bazzi, C

Bazzi, C.L

Bean, G.M

Bede, L

Bedwell, E

Beeri, O

Behrendt, K

Bekkerman, A

Ben-Gal, A

Benke, S

Berger, A

Bergheim, R

Berzins, R

Best, S

Betzek, N

Bhandari, S

Bier, J

Biswas, A

Boejer, O

Bolfe, E

Bolton, C

Bongiovanni, M

Bongiovanni, R

Bonnardel, B

Brazda, D

Brinkhoff, J

Brorsen, W

Butts, C

Bückmann, H

Cabrera Dengra, M

Camberato, J.J

Cambouris, A

Cambouris, A.N

Cammarano, D

Canavari, M

Capolicchio, J

Carlier, A

Carneiro, F.M

Carter, P.R

Cerliani, C

Cesario Pereira Pinto, J

Charvat Jr., K

Charvat, K

Cheema, S.J

Chen, Z

Christensen, A

Ciampitti, I

Cohen, Y

Conway, L.S

Coulter, J.A

Csenki, S

Custer, S

Cutulle, M

DUMONT, B

Dafnaki, D

Dandrifosse, S

Das, A

Das, A.K

Dash, M

Davadant, P

De Neve, S

De Poorter, E

De Waele, T

DeBruin, J

Degioanni, A

Denton, A.M

Dhal, S

Dillen, J

Dong, R

Dos Reis, A.A

Dos Santos, R.S

Dreyer, J.G

DuPont, E.M

Duarte de Val, M

Duchemin, M

Duddu, H

Duddu, H.U

Duff, H

Duff, H.D

Dufrasne, I

Dumont, B

Dutilleul, P

Eberle, D

El Gamal, A

El-Mejjaouy, Y

Elsen, A

Elvir Flores, A

Emmi, L

Enger, B.D

Ennadifi, E

Erickson, B.J

Esau, T

Esau, T.J

Esposito, G

Evers, B

Eyster, R

Farooque, A

Farooque, A.A

Ferguson, R.B

Fernández, F.G

Ferraz Pueyo, C

Ferreyra, R

Figueiredo, G.K

Filippetti, I

Fleming, K

Flint, E.A

Flores, P

Flores, P.J

Floyd, W

Fortes, R

Fortunato, M

Franklin, K

Franklin, K.F

Franz, F

Franzen, D.W

Freitas, R.G

Friell, J

Frimpong, K.A

Friskop, A

Fritz, A

Fulton, J.P

Gallios, I

Gamble, A

Ganascini, D

Garza, C

Gauci, A

Gavioli, A

Gebler, L

Ghimire, B.P

Ghimire, D

Gill, N

Gips, A

Gnatowski, T

Gobezie, T.B

Goldshtein, E

Goldwasser, Y

Gonzalez, J

Goodrich, P

Goodrich, P.J

Gosselin, B

Graff, N

Grewal, K

Gu, H

Gumero, J

Gunther, D

Gunzenhauser, B

Gunzenhauser, R

Guo, W

Gupta, S

Gutteridge, M

Ha, T

Hachisuca, A

Hachisuca, A.

Hachisuca, A.M

Hajda, C

Hammond, J

Hammond, K

Hansel, D

Hansen, N

Harkin, S.J

Harris, G

Harsha Chepally, R

Hartmann, B

Hartschuh, J

Hartschuh, J.M

Hatfield, J.L

Hawkins, E

He, Z

Hegedus, P

Hegedus, P.D

Heggemann, T.W

Hejl, R

Hennessy, P.J

Hensley, R

Hernandez, C

Hettiarachchi, G

Hoffmann Silva Karp, F

Hokanson, G.E

Hong, S

Hongo, C

Hopkins, B

Hopkins, B.G

Horakova, S

Hu, Q

Hüging, H

Ingram, B

Inunciaga Leston, G

Isono, S

Jalem, R.S

Jansky, T

Jasper, J

Jenal, A

Jensen, N

Jensen, R

Jia, M

Jimenez, A

Johal, G

Johnson, E

Johnson, E.U

Johnson, R.M

Jones, J

Jorgensen, R

Kalafatis, S

Kang, C

Karam, A

Karampoiki, M

Karkee, M

Karn, R

Kashetri, S

Katz, L

Kazula, M

Keller, M

Kelley, A

Kepka, M

Kerry, R

Khan, H

Kharel, T

Khosla, R

Kitchen, N.R

Klopfenstein, A

Koch, G

Kolar, P.R

Krishnaswamy, K

Krmenec, A

Krys, K

Kshetri, S

Kubickova, H

Kuehner, K

Kukal, S

Kulmany, I.M

Kumpatla, S

Kyveryga, P

LENOIR, A

Laboski, C.A

Lacerda, L

Lacerda, L.N

Lajunen, A

Lamb, D.W

Lamichhane, R

Lamparelli, R.A

Lang, V

Langovskis, D

Lare, M

Lattanzi, P

Lebeau, F

Leduc, M

Lee, J

Lee, K

Lee, W

Lehmann, J

Lena, B.P

Lessl, J

Leszczyńska, R

Levi, M

Li, D

Li, Y

Liburd, O.E

Lima, J.P

Lin, Z

Lindsey, A

Litaor, I

Liu, H

Loewen, S

Loewen, S.D

Longchamps, L

Lotsi, A.K

Louis, J

Lowenberg-DeBoer, J

Lowenberg‑DeBoer, J

Lu, J

Lund, E

Lund, T

Lusher, J

MacEachern, C

Macura, J

Madugundu, R

Magalhães, P.S

Magyar, F

Mahanta, S

Maharjan, B

Mahmood, S

Mahmoudi, S

Maja, J

Maja, J.J

Mandal, D

Manoj, K

Martelli, R

Martins, M.R

Massey, R

Mathew, J

Mathew, J.J

Maxton, C

Maxwell, B

Maxwell, B.D

Mayer, J

Mazzoleni, R

McArthor, B

McArtor, B

Medici, M

Melchiori, R

Melgar, J

Melnitchouck, A

Mendes, I

Mennuti, D

Mercante, E

Mercatoris, B

Miao, Y

Mieno, T

Milani, I

Milics, G

Miranda, C

Mizuta, K

Molin, J.P

Montull, J.M

Morales Luna, G.L

Morales, A.C

Morales, G

Morales, G.L

Morata, G

Morata, G.T

Moreira, W

Moreno Heras, L

Morlin, F

Moro, E

Mouazen, A.M

Mueller, N

Mulla, D.J

Munnaf, M.A

Murdoch, A

Musil, M

Myers, D

Nadav, I

Nafziger, E.D

Nagel, P

Nambi, E

Naor, A

Nascimento-Silva, K

Nielsen, M.B

Nielsen, R.L

Nišavić, N

Norquest, S

Nze Memiaghe, J

Nze Memiaghe, J.D

O'Sullivan, N

Oh, S

Oliveira, L.P

Oliveira, M.F

Oliveira, S.R

Orellana, M.C

Ortega, A.F

Ortega, R

Ortega, R.A

Ortiz, B

Ortiz, B.V

Otto, R

Oukarroum, A

Owens, P

Owens, P.R

Owusu Ansah, E

Pajuelo Madrigal, V

Palacios, D

Paraforos, D

Parkash, V

Pasquel, D

Pastore, C

Paz, L

Pecze, R

Peerlinck, A

Peerlinck, A.D

Peeters, A

Pelta, R

Peralta, D

Pereira, F.R

Pereira, J.C

Pereira, N.D

Petix, R

Pezzi, F

Peña, J

Plum, J

Poblete, H.P

Pokhrel, A

Poland, J

Portz, G

Postelmans, A

Pourreza, A

Poursina, D

Prasad, R

Prestholt, A

Prostko, E.P

Puntel, L

PÄTZOLD, S

Quanbeck, J

Quinn, D.

Quoitin, B

Raheja, A

Rahman, M.M

Rai, N

Ramachandran, B

Ranieri, E

Ransom, C.

Ransom, C.J

Rathee, G

Rekhi, M

Reusch, S

Reyes Gonzalez, J

Robson, A

Rodrigues, M

Roel, A

Rosen, C

Rossetti, G

Roux, S

Ruma, F.Y

Rutter, M.S

Rydahl, P

Ryu, S

SVIERCOSKI, R

Sade, Z

Saeys, W

Saifuzzaman, M

Samborski, S.M

Sampath, N

Sanches, G.M

Sanz-Saez, A

Saraswat, D

Saurette, D

Sawyer, J.E

Saxena, A

Scaramuzza, F

Schaefer, M.T

Schenatto, K

Schepters, J.S

Schill, S

Schottle, N

Schueller, J.K

Schuenemann, G.M

Schumann, A.W

Sela, S

Shafian, S

Shahid, A

Shanahan, J.F

Sharda, A

Sharma, A

Sharma, V

Shcherbatyuk, N

Shearer, S

Shearer, S.A

Sheppard, J

Sheppard, J.W

Shilo, T

Shirtliffe, S

Shirtliffe, S.J

Shirtliffe, S.U

Shorkey, R

Shumate, S

Siegfried, J

Sielenkemper, M

Sigit, G

Silva, F.V

Silva, R.P

Siqueira, R.D

Smith, A.P

Smith, D.R

Snevajs, H

Snider, J.L

Sobjak, R

Soerensen, M

Soetan, M

Sogbedji, J.M

Sornapudi, S

Souza, E.G

Sparrow, R

Squires, T

Sridharan, S

Stavness, I

Stelford, M

Stenger, J

Stettler, E

Straw, C

Stueve, K

Sudduth, K

Sudduth, K.A

Suh, C

Sun, C

Sun, X

Sunkevic, M

Szatylowicz, J

TORGBOR, B.A

Taberner, A

Takahashi, T

Tamura, E

Tarshish, R

Tavares, T.R

Taylor, J

Taylor, J.A

Tedesco, D

Thompson, L

Thornton, M

Thurmond, M

Tiscornia, G

Tisseyre, B

Todman, L

Tola, E

Torresen, K

Tsibart, A

Tucker, M.W

Turner, I

Tóth, G

Underwood, H

Upadhyaya, P

Utoyo, B

VANDOORNE, B

Valentini, G

Van de Ven, G

Varga, P.M

Vellidis, G

Verma, A.P

Vermeulen, P

Verschwele, A

Vetch, J.M

Veum, K

Veum, K.S

Videla, H

Virk, S

Virk, S.S

Vitali, G

Vona, V

Vong, C

Vories, E

Wakahara, S

Walsh, O

Walsh, O.S

Wang, X

Watkins, E

Watkins, K

Wehrle, R

Welch, S

White, S.N

Wieland, S

Williams, D

Woolley, E

Wyatt, B

Xiong, X

Xu, Z

Yang, C

Ye, D

Yilma, W

Yilma, W.A

Yost, M

Young, J

Zadrazil, F

Zaman, Q

Zaman, Q.U

Zhang, J

Zhang, Q

Zhang, X

Zhang, Y

Zhang, Z

Zhao, H

Zhao, X

Zhou, C

Zhou, J

Ziadi, N

Zuniga-Ramirez, G

da Silva, T.R

de Carvalho, H.W

de Castro, A

del Val, M.D

song, S

Topics

Geospatial Data

Drainage Optimization and Variable Rate Irrigation

On Farm Experimentation with Site-Specific Technologies

Decision Support Systems

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Robotics, Guidance and Automation

Precision Crop Protection

In-Season Nitrogen Management

Education and Outreach in Precision Agriculture

Applications of Unmanned Aerial Systems

Wireless Sensor Networks

Factors Driving Adoption

Precision Horticulture

Land Improvement and Conservation Practices

Smart Weather for Precision Agriculture

Site-Specific Nutrient, Lime and Seed Management

Big Data, Data Mining and Deep Learning

ISPA Community: Economics

Farm Animals Health and Welfare Monitoring

Site-Specific Pasture Management

Profitability and Success Stories in Precision Agriculture

ISPA Community: Latin America

Precision Agriculture and Global Food Security

ISPA Community: Nitrogen

Small Holders and Precision Agriculture

Precision Dairy and Livestock Management

Plenary

Industry Sponsors

Type

Poster

Oral

Year

2022

Home » Year » Results

Year

Filter results4 paper(s) found.
1. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processi... F. Hoffmann Silva Karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul Download paper
2. Predicting Corn Emergence Uniformity with On-the-go Furrow Sensing Technology Integration of proximal soil sensors into commercial row-crop planter components have allowed for a dense quantification of within-field soil spatial variability. These technologies have potential to guide real-time management decisions, such as on-the-go variable seeding rate or depth. However, little is known about the performance of these systems. Therefore, research was conducted in central Missouri, USA to determine the relationship between planter sensor metrics, and corn (Zea mays ... L.S. Conway, C. Vong, N.R. Kitchen, K.A. Sudduth, S.H. Anderson Download paper
3. Soil, Landscape, and Weather Affect Spatial Distributions of Corn Population and Yield As more planters are equipped with the technology to vary seeding rate, evaluation of the within-field relationships between plant stand density (or population) and yield is needed. One aspect of this evaluation is determining how stand loss and yield are related to soil and landscape factors, and how these relationships vary with different weather conditions. Therefore, this research examined nine site-years of mapped corn yield, harvest population, and soil and landscape data obtained for a... K.A. Sudduth, N.R. Kitchen, L.S. Conway Download paper
4. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use Efficiency Current tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR). Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmenta... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey Download paper

Filter results4 paper(s) found.

1. Optimization of Batch Processing of High-density Anisotropic Distributed Proximal Soil Sensing Data for Precision Agriculture Purposes

The amount of spatial data collected in agricultural fields has been increasing over the last decade. Advances in computer processing capacity have resulted in data analytics and artificial intelligence becoming hot topics in agriculture. Nevertheless, the proper processing of spatial data is often neglected, and the evaluation of methods that efficiently process agricultural spatial data remains limited. Yield monitor data is a good example of a well-established methodology for data processi... F. Hoffmann Silva Karp, V. Adamchuk, A. Melnitchouck, P. Dutilleul

Download paper

2. Predicting Corn Emergence Uniformity with On-the-go Furrow Sensing Technology

Integration of proximal soil sensors into commercial row-crop planter components have allowed for a dense quantification of within-field soil spatial variability. These technologies have potential to guide real-time management decisions, such as on-the-go variable seeding rate or depth. However, little is known about the performance of these systems. Therefore, research was conducted in central Missouri, USA to determine the relationship between planter sensor metrics, and corn (Zea mays ... L.S. Conway, C. Vong, N.R. Kitchen, K.A. Sudduth, S.H. Anderson

Download paper

3. Soil, Landscape, and Weather Affect Spatial Distributions of Corn Population and Yield

As more planters are equipped with the technology to vary seeding rate, evaluation of the within-field relationships between plant stand density (or population) and yield is needed. One aspect of this evaluation is determining how stand loss and yield are related to soil and landscape factors, and how these relationships vary with different weather conditions. Therefore, this research examined nine site-years of mapped corn yield, harvest population, and soil and landscape data obtained for a... K.A. Sudduth, N.R. Kitchen, L.S. Conway

Download paper

4. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use Efficiency

Current tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR). Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmenta... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey

Download paper