Proceedings

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Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Food Security and Precision Agriculture
Education and Outreach in Precision Agriculture
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Site-Specific Nutrient, Lime and Seed Management
Precision Nutrient Management
Modeling and Geo-statistics
Profitability, Sustainability, and Adoption
Precision Nutrient Management
Agricultural Education
Big Data Mining & Statistical Issues in Precision Agriculture
Farm Animals Health and Welfare Monitoring
Remote Sensing Application / Sensor Technology
Precision Dairy and Livestock Management
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Education and Outreach in Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Spatial Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Decision Support Systems
Precision Horticulture
Precision Weed Management
Decision Support Systems in Precision Agriculture
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Authors
Abonyi, J
Acuna, T
Adamchuk, V
Adamchuk, V.I
Adamchuk, V.I
Adamchuk, V.I
Adamchuk, V.I
Adamchuk, V.I
Ahmed, M
Aizpurua, A
Akune, V.S
Al-Busaidi, A
Al-Gaadi, K.A
Alabi, T
Alchnatis, V
Alheit, K.V
Allphin, E
Amaral, L.R
Amaral, L.R
Amaral, L.R
Amaral, L.R
Amaral, L.R
Amin, S
Ampatzidis, Y.G
An, X
Anastasiou, E
Anderson, W
Andersson, K
Andrade, R.G
Anselmi, A.A
Araujo, R
Archontoulis, S
Arvidsson, J
Asgedom, H
Ashraf, E
Astillo, P
B K, A
Bölenius, E
B, K
Bae, K
Baghernejad, M
Bajwa, S
Balafoutis, A
Balboa, G
Balboa, G
Balboa, G
Balmos, A
Balzarini, M
Banerjee, M
Bareth, G
Barlage, M
Barros, M.F
Basso, B
Basso, B
Batchelor, W.D
Bauer, P.J
Bauer, P.J
Bazzi, C
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Bazzi, C.L
Beasley, D
Been, T
Beeri, O
Belford, R
Belsky, C
Benavente, J.C
Beneduzzi, H.M
Benez, S.H
Benjamin, M
Bennett, S
Benő, A
Berdugo, C
Berglund, &.E
Bernardi, A.C
Berti, M
Besga, G
Betzek, N.M
Betzek, N.M
Betzek, N.M
Bhansali, S
Bhattarai, B
Bhuiya, G
Bishop, T.F
Biswas, A
Biswas, A
Boardman, D.L
Bodson, B
Bodson, B
Bodson, B
Boini, A
Bongiovanni, M
Bongiovanni, R
Borůvka, L
Bourgain, O
Bouroubi, Y
Bouroubi, Y
Bradford, J
Brasco, T
Brasco, T.L
Brasco, T.L
Braunbeck, O
Braunbeck, O.A
Braunbeck, O.A
Bresilla, K
Brian, S
Bronson, K
Buckmaster, D
Bugnet, P
Burris, E
Burton, L
Busemeyer, L
Busscher, W.J
Bélec, C
Callegari, D
Cammarano, D
Campos, L.B
Cao, Q
Cao, Q
Carroll, S
Casanova, J.L
Castell, A
Castro, S.G
Castro, S.G
Castro, S.G
Cerliani, C
Chae, Y
Charvat, K
Charvat, K
Chau, M
Chen, F
Chen, L
Chen, L
Chen, M
Chen, T
Chen, T
Chen, T
Chen, X
Chen, X
Chiang, R.C
Chim, B
Cho, Y
Choo, Y
Choudhari, D.D
Christiaens, R
Chung, S
Chung, S
Chung, S
Ciampitti, I
Citon, L.C
Claassen, A
Clarke-Hill, W
Clay, D.E
Clay, S.A
Coelho, A
Cohen, Y
Cointault, F
Colaço, A.F
Colaço, A.F
Colley III, R
Colley III, R
Colley, T
Cooper, J
Cosby, A
Cosby, A.M
Coulter, J.A
Craker, B.E
Cugnasca, C.E
Cugnasca, C.E
Cugnasca, C.E
Cui, Z
Cunha, T.F
Cunha, T.F
Cushnahan, M.Z
Danford, D.D
Dao, T.H
Dao, T.H
Davis, J
DeFauw, S.L
Degioanni, A
Dehne, H
Delgado, J.A
Demattê, J.M
Dennis, S.J
Derdall, E
Destain, J
Destain, J
Destain, M
Destain, M
Destain, M
Devakumar, N
Dhawale, N
Diaz-Zorita, M
Dimos, N.F
Dokoozlian, N
Dong, J
Dong, R
Dong, Y
Dongare, M.L
Dota, M.A
Douridas, N
Draye, X
Drexler, D
Driemeier, C
Drummond, S.T
Drummond, S.T
Duddu, H
Duft, D.G
Duft, D.G
Dumont, B
Dumont, B
Duncan, E
Duncan, S
Dutilleul, P
Dutta, S
Duval, C
Duval, C
Duval, C
Duval, C
Duval, C
Dynes, R
Ehsani, R
Eitelwein, M.T
Eitelwein, M.T
Emadi, M.M
Enger, B.D
English, B.C
English, B.C
English, B.C
English, P.J
Erbe, A
Erickson, B
Erickson, B
Esau, K
Esposito, G
Esquivel, W
Evans, D.E
Fajardo, M
Fajardo, M
Farooque, A
Fasso, W
Fausti, S
Feher, T
Feng, G
Fergugson, R.B
Fergugson, R.B
Ferguson, R.B
Ferraz, M.N
Ferraz, M.N
Ferreyra, R
Filippi, P
Finegan, M
Fiorese, D.A
Fisher, D.K
Fixen, P
Fleming, K
Folle, S
Fontenelli, J.V
Foster, P.N
Fountas, S
Fountas, S
Fraile, S
France, W
Franco, H.C
Franco, H.C
Franco, H.C
Franco, H.C
Franco, H.C
Fraser, E
Frimpong, K.A
Fritz, B.K
Frizzel, L
Fu, W
Fulton, J
Fulton, J
Fulton, J.P
Fulton, J.P
Fulton, J.P
Fulton, J.P
Fumery, J
Gan, H
Gao, X
Gardezi, M
Gavioli, A
Gavioli, A
Gavioli, A
Gavioli, A
Ge, Y
George, D
Gerighausen, H
Ghinassi, G.P
Gholizadeh, A
Gillingham, V
Giriyappa, M
Glewen, K
Gnip, P
Gnip, P
Gnyp, M.L
Gochis, D
Goffart, J
Gonzalez, J
Gore, A.K
Gosselin, C
Grafton, M.Q
Grappadelli, L.C
Graziano Magalhães, P.S
Graziano Magalhães, P.S
Green, S
Greene, J
Grego, C.R
Gregory, S
Gritten, F
Grocholski, P
Grove, J
Gu, X
Guerra, S.S
Guo, J
Guppy, C.N
Gupta, M
Haak, D
Hamann, H.F
Hand, K.J
Hanks, J.E
Hanumanthappa, D
Harper, D.C
Harper, J
Harris, G
Hartschuh, J.M
Hatfield, J
Hauser, J.S
Hehar, G
Helga, W
Herold, L
Hertzberg, J
Hillnhuetter, C
Hinds, N
Hinsinger, P
Hirai, Y
Hoffmann, C
Hoffmann, W.C
Hoffmann, W.C
Holland, K.H
Hong, S
Hongo, C
Huang, H
Huang, S
Huang, W
Huang, Y
Huh, Y
Huh, Y
Hunsche, M
Hur, S
Ikpi, A.E
Inamasu, R
Inamasu, R.Y
Inamasu, R.Y
Inoue, E
Islam, M
Jadhav, B.T
Jang, S
Jangandi, S
Jarolimek, J
Jasper, J
Jasse, E.P
Jayachandran, K
Jayasuriya, H
Jezek, J
Jha, S
Ji, W
Jiang, R
Johnson, R.M
Jones, E.J
Joshi, N
Journaux, L
Jowett, T
Jukema, J.N
Jung, K
Kaiser, D
Kallithraka, S
Kamerer, C
Kantipudi, K
Karppinen, E
Kaul, A
Kaur, G
Kechadi, M
Kechchour, A
Kempenaar, C
Kempenaar, C
Khakbazan, M
Khanal, S
Khosla, R
Khosla, R
Khosla, R
Khosla, R
Khosla, R
Khosro Anjom, F
Khot, L
Kim, D
Kim, D
Kim, H
Kim, S
Kim, S
Kim, Y
Kindred, D
Kitchen, N
Kitchen, N
Kitchen, N.R
Kitchen, N.R
Kitchen, N.R
Kitchen, N.R
Kitchen, N.R
Kitchen, N.R
Kizer, E
Klein, L.J
Klose, R
Knight, C.W
Ko-Madden, C
Koch, J.K
Kocks, C
Kocks, C
Kocsis, M
Kodaira, M
Kolln, O.T
Kolln, O.T
Kolln, O.T
Kolln, O.T
Kong, J
Kotseridis, Y
Koundouras, S
Kovács, A.J
Krivanek, Z
Krogmeier, J
Kross, A
Krueger Shvetsova, E
Krueger, E
Kulczycki, G
Kumar, R
Kumari, S
Kurtener, D
Kurtener, D
Kurtener, D
Kurtener, D
Kyraleou, M
L, M
LAK, M
LAWAL, J
LAWAL, J
Laacouri, A
Lacey, R
Lacroix, R
Lai, C
Lai, C
Lamb, D.W
Lamb, D.W
Lambert, D.M
Lambert, D.M
Lampinen, B
Lan, Y
Lan, Y
Lan, Y
Lancas, K.P
Lapen, D
Larbi, P.A
Larkin, S.L
Larkin, S.L
Larson, J.A
Larson, J.A
Larson, J.A
Lauzon‎, S
Lavagnino, M
Le-Khac, N
Lebeau, F
Lee, D
Lee, J
Lee, J
Leemans, V
Leiva, J.N
Lemke, R
Leonard, B.J
Leroux, G.D
Lew, D
Li, B
Li, C
Li, F
Li, F
Li, M
Li, Q
Li, W
Li, Y
Liakos, V
Liakos, V
Liang, X
Lianqing, Z
Lilienthal, H
Lilienthal, H
Lindblom, J
Linz, A
Linz, A
Liu, B
Liu, K
Liu, Y
Llorens, J
Llorens, J
Longchamps, L
Longchamps, L
Longchamps, L
Lowenberg-DeBoer, J
Lowrance, C
López, J.D
Lu, Y
Luck, J
Luck, J.D
Lund, E
Lund, E
Lund, T
Lund, T
Lundström, C
Madugundu, R
Magalhães, P.S
Magalhaes, P.G
Magalhaes, P.S
Magalhaes, P.S
Magalhaes, P.S
Magalhães, P.G
Magalhães, P.S
Maharlooei, M
Mahlein, A
Mahmood, S.A
Mahoney, W
Maiti, D
Maja, J
Majumdar, K
Makkar, M.S
Malagi, M.T
Malik, G
Mallikaarjuna, G
Manfield, A
Manfrini, L
Marasca, I
Marchant, B.P
Marey, S
Mariano, E
Marin, A
Marjerison, R
Marlier, G
Marra, M.C
Martello, M
Martin, D.E
Martin, D.L
Martin, R
Martin, S.W
Martinon, V
Martre, P
Masiero, F.C
Maxton, C
Maxton, C.R
Maxwell, T
May-tal, S
Mbakwe, I
McCarter, K.S
McEntee, P
McIntyre, J
McLendon, A
McNairn, H
McVeagh, P.J
Mclure, B
Meitalovs, J
Mekonnen, Y
Melchiori, R
Melnitchouck, A
Melnitchouck, A
Melnitchouck, A
Melo, D.D
Melo, D.D
Mendez-Costabel, M
Meng, Z
Mercatoris, B
Mercuri, P
Meron, M
Mhlongo, N
Miao, Y
Miao, Y
Miao, Y
Miao, Y
Miao, Y
Miao, Y
Michalski, A
Michelon, G.K
Michelon, G.K
Milics, G
Millen, J.A
Min, C
Mireei, S.A
Mishra, A
Miteran, J
Mitra, S
Mitsuoka, M
Mizuta, K
Mizuta, K
Moclán, C
Moebiu-Clune, B
Moebius-Clune, D
Moeller, K
Molin, J
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Molin, J.P
Mooleki, P
Moon, J
Moon, J
Mooney, D.F
Mooney, D.F
Mooney, D.F
Morandi, B
Morgan, A
Morris, D
Moshia, M.E
Mostaço, G.M
Mouazen, A.M
Mouazen, D
Moulin, A
Mueller, N
Mulla, D
Mulla, D.J
Mulla, D.J
Mullenix, D
Murdoch, A.J
Murrell, S
Musil, M
Myers, D.B
Nabizadeh, E
Nagel, P
Nakao, H.S
Nakazawa, P.H
Nawar, S.M
Nayse, S.P
Negrini, R.P
Nelson, K.J
Neményi, M
Neupane, D
Neupane, J
Ngo, V.M
Nguyen-Xuan, T
Nigon, T
Nobakhti, A
Noga, G
Norquest, S
Norwood, S.H
Nowatzki, J
Nyéki, A
Nysten, S
O'Neill, K
Oerke, E
Oerke, E
Ogasawara, C
Okayasu, T
Okoruwa, V.O
Oksanen, T
Olayide, O.E
Oldoni, H
Omodele, T
Orellana, J
Orlov, V
Ortega, R.A
Otto, R
Owen, J
Ozmen, S
P.W Clevers, J.G
POLEPOLE, S.J
Pagani, A
Pagni, P
Pampolino, M
Pan, L
Pandey, A
Panneton, B
Panneton, B
Pannu, C.S
Parajulee, M
Parashuramegowda, C.C
Patil, V
Pawar, S.N
Paxton, K.W
Pecchioni, N
Pena-Yewtukhiw, E.M
Pendke, M.S
Perez-Parmo, R
Perry, C
Perulli, G
Pgowda, C.C
Phillips, S
Pinkston, P
Pitla, S.K
Pitrat, T
Pl, L
Poelling, B
Poncet, A
Port, K
Port, K
Porter, W
Porto, A.J
Portz, G
Pourshamsaei, H
Prostko, E.P
Pullanagari, R.R
Puntel, L
Puntel, L
Qian, J
Quirós, J.J
R, C
Rabe, N
Rabello, L.M
Ragab, R
Rahe, F
Rainbow, R
Raju, N
Rasheed, R
Rathore, J
Raz, J
Reeves, J.M
Rejesus, R
Reyes, J.F
Rhea, S.T
Roa Acosta, G
Robbins, J
Roberts, D.F
Roberts, J
Roberts, R.K
Roberts, R.K
Roberts, R.K
Roger, T
Rojo, F
Rojo, F
Romanelli, T.L
Romo, A
Ross, J
Rossi Neto, J
Ruckelshausen, A
Ruckelshausen, A
Rud, R
Rudolph, S
Rudramuni, T
Rudy, H
Ruiz Diaz, D
Ruiz, M
Rumpf, T
Rund, Q
Rund, Q
SVIERCOSKI, R
Saberioon, M
Saifuzzaman, M
Salimath, S.B
Samborski, S.M
Sams, B
Sanches, G
Sanches, G.M
Sanches, G.M
Sanches, G.M
Sanches, G.M
Sanches, G.M
Sanches, G.M
Sanchez, L.A
Santana Neto, A.J
Santos, C
Santos, H.P
Sanz, J
Sapkota, T.B
Saraswat, D
Sarwat, A
Sauer, B
Scaramuzza, F
Schenatto, K
Schenatto, K
Schenatto, K
Schenatto, K
Schenatto, K
Schenatto, K
Schepers, J.S
Schepers, J.S
Schindelbeck, R
Schneider, D
Schneider, D
Schneider, S
Schnug, E
Schnug, E
Schoenau, J
Schroeder, M.A
Schuenemann, G.M
Schumacher, L
Schumann, A
Segarra, E
Sekhon, B.S
Sela, S
Sessitsch, A
Shaligram, A.D
Shanahan, J.F
Shanahan, J.F
Shang, J
Shankar, M
Shannon, K
Sharda, A
Sharda, A
Sharma, A
Sharma, A
Shaver, T
She, Y
Shearer, S.A
Shearer, S.A
Sheridan, A
Sheshadri, T
Shi, Y
Shibusawa, S
Shibusawa, S
Shinde, G.U
Shinde, S
Shiratsuchi, L
Shirzadi, A
Shoups, D
Shrestha, R
Shurjeel, H.K
Sigdel, U
Sigit, G
Sikora, R.A
Simard, M
Simard, M
Simek, P
Singh, G
Singh, M
Sisák, I
Sivarajan, S
Skouby, D
Slater, G
Slaughter, D
Song, X
Songchao, C
Sousa, R.V
Souza, E
Souza, E.G
Souza, E.G
Souza, E.G
Souza, E.G
Souza, E.G
Souza, I.R
Souza, W.J
Spekken, M
Spekken, M
Stalidzans, E
Steiner, U
Stelford, M.W
Stepien, P
Stiehl, D
Stoces, M
Stone, K
Strickland, E.E
Stueve, K
Suddth, K.S
Sudduth, K
Sudduth, K.A
Sudduth, K.A
Sudduth, K.A
Sudduth, K.A
Sudduth, K.A
Suh, C
Sulik, J
Sun, X
Sun, Z
Sunohara, M
Swain, D
Swanson, G
Sylvester-Bradley, R
Szabó, K
Ta, S
Tamura, E
Tang, L
Tangerino, G.T
Tatge, J
Taylor, A
Taylor, R.K
Theriault, R
Theriault, R
Thiel, M
Thompson, A
Thompson, L
Thompson, L
Thomson, S.J
Tola, E
Toledo, O.M
Torbert, H
Trautz, D
Tremblay, N
Trevisan, R.G
Trevisan, R.G
Trindall, J
Troesch, A.M
Trotter, M
Trotter, M
Trotter, M
Trotter, M
Trotter, M.G
Trotter, M.G
Trotter, T
Tsipris, J
Tucker, M
Udompetaikul, V
Ulman, M
Umeda, H
Unamunzaga, O
Upadhyaya, S
Upadhyaya, S
Upadhyaya, S.K
Upadhyaya, S.K
Uribe-Opazo, M.A
Usui, K
V.M., A.H
Valente, I.Q
Van Langevelde, F
Vancutsem, F
Varela, S
Vargas, M.R
Vaz, C.M
Velandia, M
Velandia, M
Vellidis, G
Vellidis, G
Veum, K
Viator, B.J
Videla, H
Vieri, M.P
Vigil, M
Vigneault, P
Virk, S
Virk, S.S
Voicu, A
WORTH, S.H
Wadhai, V.M
Wagner, P
Waine, D
Wallace, D
Walsh, O
Walsh, O.S
Walthall, C
Wang, C
Wang, C
Wang, C
Wang, J
Wang, N
Wang, X
Wang, Y
Wang, Y
Wang, Y
Wang, Y
Wang, Z
Ward, M.D
Weiss, U
Welch, M
Werner, A
Weschter, E.O
Westbrook, J
Westbrook, J
Westerdijk, K
Westerdijk, K
Westfall, D
Westfall, D
Whattoff, D
Whelan, B
Whelan, B.M
Whiting, M.D
Wijewardane, N
Wijnholds, K.H
Wilde, P
Williams, E
Williams, R
Williams, R
Willness, C
Wilson, J.A
Wilson, R
Winstead, A.T
Wood, B.A
Wu, B
Wu, G
Wunder, E
Wurbs, A
Xu, K
Yafei, Y
Yamakawa, T
Yan, N
Yang, C
Yang, W
Yang, W
Yang, X
Yao, Y
Yida, D
Yoder, J
Yoo, H
Yost, M
You Fu, E
Yule, I.J
Yule, I.J
Zacepins, A
Zaller, M
Zaman, Q
Zeng, H
Zhang, H
Zhang, Q
Zhang, R
Zhang, X
Zhang, Y
Zhang, Y
Zhao, C
Zhao, C
Zhou, S
Zikan, A
Zimba, P.V
Zotarelli, L
da Cunha, I.A
da Cunha, I.A
de Boer, W.F
de Menezes, P.L
de Souza, E.G
de knegt, H
http://icons.paqinteractive.com/16x16/ac, G
http://icons.paqinteractive.com/16x16/ac, G
http://icons.paqinteractive.com/16x16/ac, G
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kaboodi, S
nabizadeh, E
van Es, H
van Evert, F
van Vliet, L
wang, X
Topics
Sensor Application in Managing In-season Crop Variability
Precision Nutrient Management
Modeling and Geo-statistics
Precision Weed Management
Site-Specific Nutrient, Lime and Seed Management
Proximal Sensing in Precision Agriculture
Decision Support Systems
Agricultural Education
Big Data Mining & Statistical Issues in Precision Agriculture
Big Data, Data Mining and Deep Learning
Decision Support Systems in Precision Agriculture
Precision Nutrient Management
Remote Sensing Application / Sensor Technology
Spatial Variability in Crop, Soil and Natural Resources
Education and Outreach in Precision Agriculture
Precision Horticulture
Education and Outreach in Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Profitability, Sustainability, and Adoption
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change, Standards)
Farm Animals Health and Welfare Monitoring
Precision Dairy and Livestock Management
Food Security and Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Type
Oral
Poster
Year
2010
2024
2016
2018
2014
2008
2022
2012
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1. Saltmed Model As An Integrated Management Tool For Precision Management Of Water, Crop, Soil, And Fertilizers

                 SALTMED-2009: A modelling tool for Precision Agriculture                                                    R. Ragab Centre for Ecology and H... R. Ragab

2. Nugis: The Development Of A Nutrient Use Geographic Information System

NuGIS is a project of the International Plant Nutrition Institute (IPNI). The goal was to examine sources of nutrients (fertilizers and manure) and compare this to crop removal. The project used GIS and database analysis to create maps at the state and county level and then used GIS to migrate the budget analysis to the local watershed and regional watershed levels. This paper will cover the sources of data used, how the data was processed to generate county level numbers, and how GIS was use... Q. Rund, R. Williams

3. A Crop And Soil Strategy For Sensor-based Variable-rate Nitrogen Management

Crop-based active canopy sensors and soil-based management zones (MZ) are currently being studied as tools to direct in-season variable-rate N application. Some have suggested the integration of these tools as a more robust decision tool for guiding spatially variable N rates. The objectives of this study were to identify (1) soil variables useful for MZ delineation and (2) determine if MZ could be useful in identifying field areas wi... D.F. Roberts, J.F. Shanahan, R.B. Fergugson, V.I. Adamchuk, N.R. Kitchen

4. Hyperspectral Imaging Of Sugar Beet Symptoms Caused By Soil-borne Organisms

The soil-borne pathogen Rhizoctonia solani and the plant parasitic nematode Heterodera schachtii are the most important constraints in sugar beet production worldwide. Symptoms caused by fungal infection are yellowing of leaves and rotting of the beet tuber late in the cropping season. Nematode afflicted plants show stunted growth early in the cropping season and also leaf wilting late in the season when water stress often sets in. Due to the low mobility of soil-borne organisms, they are ide... C. Hillnhuetter, A. Mahlein, R.A. Sikora, E. Oerke

5. Using An Active Crop Sensor To Detect Variability Of Nitrogen Supply On Sugar Cane Fields

Nitrogen management has been intensively studied on several crops and recently associated with variable rate application on-the-go based on crop sensors. On sugar cane those studies are yet scarce and as a biofuel crop the input of energy matters, looking for a high positive balance of biofuel production and low carbon emission on the whole production system. This paper shows the first results obtained using a nitrogen and biomass sensor (N-SensorTM ALS, Yara International ASA) aiming to indi... J. Molin, G. Portz, J. Jasper

6. Comparative Analysis Of Different Approaches

The efficiency of variable rate seeding (VRS) was confirmed in various crops. It is proven that corn requires increasing seeding rates in high-yielding zones, whereas soybeans need lower rates. However, the data for wheat appeared to be controversial. The aim of our experiment was to determine the most efficient strategy for variable rate fertilization and seeding in spring wheat in the conditions of Canadian Prairies. Two approaches were tested: based on Normalize Difference Vegetation Index... A. Melnitchouck

7. Primary Framework Of Diagnosis And Management For Wheat Production Based On The Online Telemonitoring Networks

  PRIMARY FRAMEWORK OF DIAGNOSIS AND MANAGEMENT FOR WHEAT PRODUCTION BASED ON THE ONLINE TELEMONITORING NETWORKS   Sun Zhong-fu, Du Ke-ming, Zhang Yan, Liang Ju-bao   Inst. of Environ. & Sustainable Develop. in Agriculture£¨IEDA£© Chinese... Z. Sun, ,

8. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain

... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen

9. Precision Manure Management: It Matters Where You Put Your Manure

“Precision fertilizer management” has been around for more than a decade and is practiced widely in Colorado and elsewhere. By precision, we mean application of fertilizer at the right time, in the right place, and in the right amount. However, “Precision Manure Management” is a relatively new concept that converge the best manure management practices with precision nutrient management practices, such as variable rate nutrient application across site-specific managemen... M.E. Moshia, R. Khosla, J. Davis, D. Westfall

10. Smoothness Index Of Thematic Maps

A thematic map shows the spatial distribution of one or more specific data themes for standard geographic areas. The thematic maps are generated to represent the studied variables, so interpolators are used to determine their values in places not sampled. It is usuall... C.L. Bazzi, E.G. Souza, D. Stiehl

11. Thematic And Profitability Maps For Precision Agriculture

Yield maps became economically feasible to farmers with the technological advances in precision agriculture. The evidence of its profitability, however, is still unknown and, rarely, yield variability has been correlated to profitable variability. Differently ... E.G. Souza, C.L. Bazzi, M.A. Uribe-opazo

12. Developing An Active Crop Sensor-based In-season Nitrogen Management Strategy For Rice In Northeast China

  Crop sensor-based in-season N management strategies have been successfully developed and evaluated for winter wheat around the world, but little has been reported for rice. The objective of this study was to develop an active crop sensor-based in-season N management strategy for upland rice in ... Y. Yao, Y. Miao, S. Huang, M.L. Gnyp, R. Jiang, X. Chen, G. Bareth

13. 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 ... O. Bourgain, C. Duval, J. Llorens

14. Application Of Algebra Hyper-curve Neural Network In Soil Nutrient Spatial Interpolation

Study on spatial variability of soil nutrient is the basis of soil nutrient management in precision agriculture. For study on application potential and characteristics of algebra hyper-curve neural network(AHNN) in delineating soil properties spatial variability and interpolation, total 956 soil samples were taken for alkaline hydrolytic nitrogen measurement from a 50 hectares field using 20m*20m grid sampling. The test data set consisted of 100 random samples extracti... L. Chen, C. Zhao, W. Huang, T. Chen, J. Wang

15. Canopy Reflectance Sensing As Impacted By Corn Hybrid Growth

  Detection of physical and chemical properties within the growing season could help predict the overall health and yield of a corn crop. Little research has been done to show differences of corn hybrids on canopy reflectance sensing. This study was conducted to examine these potential differences during the early- to mid-vegetative growth stages of corn on three different soil types in Missouri. Canopy sensing (Crop Circle) and SPAD chlorophyll met... A. Sheridan, K.A. Sudduth, N.R. Kitchen

16. Is A Nitrogen-rich Reference Needed For Canopy Sensor-based Corn Nitrogen Applications?

The nitrogen (N) supplying capacity of the soil available to support corn (Zea mays L.) production can be highly variable both among and within fields. In recent years, canopy reflectance sensing has been investigated for in-season assessment of crop N health and fertilization. Typically the procedure followed compares the crop in an area known to be non-limiting in N (called a N-rich area) to the crop in areas inadequately fertilized. Measurements from the two areas are used to ... N.R. Kitchen, K.S. Suddth, S.T. Drummond

17. Innovative Optical Sensors For Diagnosis, Mapping And Real-time Management Of Row Crops: The Use Of Polyphenolics And Fluorescence

Force-A’s Dualex® leaf-clips and Multiplex® proximal optical sensors give rapid and quantitative estimations of chlorophyll and polyphenolics of crops by measuring the fluorescence and absorption properties of these molecules. The in vivo and real-time assessments of these plant compounds allow us to define new indicators of crop nitrogen status, health and quality. The measurements of these indicators allow consultants and farmers to monitor the nitrogen status of row crop... V. Martinon, , C. Duval, J. Fumery

18. Variability In Wheat Crop Production Based On Management Zones In Humid Pampas Region, Argentina

Crop productivity within fields is heterogeneous and it responds to the variation in crop management patterns, and in previous, random, and natural crop management factors. The methodologies for the delimitation of management zones (MZ) within production fields differ based on their application objectives. The ... M. L, M. Diaz-zorita, P. Mercuri

19. Timeliness In Agricultural Credit Delivery: A Precision Tool For Improved Farm Output And Income For Cocoa Farmers In Nigeria

The agricultural sector in Nigeria is still dominated by peasant farmers’ characterized by low level of income and saving capacity. One way to improve their farm capital investment is by providing them with timely and targeted accessible credit to enhance their production outputs and income because of the clear knowledge of the time specific nature of some farm operations. Then, how timely is the agricultural credit in Nigeria? This study determined the time-lag of credit facility disbu... J. Lawal

20. Analysis Of Water Use Efficiency Using On-the-go Soil Sensing And A Wireless Network

An efficient irrigation system should meet the demands of the growing crops. While limited water supply may result in yield reduction, excess irrigation is a waste of resources. To investigate water use efficiency, on-the-go sensing technology was used to reveal soil spatial variability relevant to water holding capacity (in this example, field elevation and apparent electrical conductivity). These high-density data layers were used to identify strategic sites where monitoring water availabil... L. Pan, V.I. Adamchuk, D.L. Martin, M.A. Schroeder, R.B. Fergugson

21. Sensing The Inter-row For Real-time Weed Spot Spraying In Conventionally Tilled Corn Fields

The spatial distribution of weeds is aggregated most of the time in crop fields. Site-specific management of weeds could result in economical and environmental benefits due to he... L. Longchamps, B. Panneton, M. Simard, R. Theriault, T. Roger

22. Partial Weed Scouting For Exhaustive Real-time Spot Spraying Of Herbicides In Corn

Real-time spot spraying of weeds implies the use of plant detectors ahead of a sprayer. The range of weed spatial autocorrelation perpendicularly to crop rows is often greater than the space between the corn rows. To assess the possibility of using less than one plant detector scouting each inter-row, a one hectare field was entirely sampled with ground pictures at the appropriate timing for weed spraying. Different ways of disposing the detectors ahead of the sprayer were virtually tested. S... L. Longchamps, B. Panneton, G.D. Leroux, M. Simard, R. Theriault

23. Evaluation Of Different N Management Strategies Using A Tool For Fuzzy Multi Attributive Comparison Of Alternatives

Application of precision agriculture is related with choosing of optimal agrotechnilogy and, in particular, with definition of the best alternative of N management strategy. A potential satisfactory solution of this decision analysis problem could be the uses of multi attribute decision-making analysis based on fuzzy set theory and fuzzy logic (FMADA). This technique provides a means to achieve an optimal decision for real world problems which involve multiple alternatives and criteri... E. Krueger, D. Kurtener, D. Kurtener, R. Khosla

24. Evaluation Of Yield Maps Using Fuzzy Indicators

  The ultimate goal of application of yield maps is profitable crop output in many farming systems. Yield maps are the starting point in the precision farming system, and provide the final record indicating the effectiveness of any management changes. Researches on yield mapping shown, that positions and boundaries of zones with different levels ... E. Krueger shvetsova, D. Kurtener, D. Kurtener, H. Torbert

25. Ultra Low Level Aircraft (ULLA) As A Platform For Active Optical Sensing Of Crop Biomass

Crop producers requiring crop biomass maps to support timely application of in-season fertilisers, pesticides or growth regulators rely on either on-ground active sensors or airborne/satellite imagery. Active crop sensing (for example using Yara N-SensorTM, GreenseekerTM or CropcircleTM) can only be used when the crop is accessible by person or vehicle, and extensive, high-resolution coverage is time consuming. On the other hand, airborne or satellite imaging ... D.W. Lamb, M.G. Trotter, D. Schneider

26. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor Data

Cotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) da... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey

27. Precision Farm Labour Supply For Effective Cocoa Production In Nigeria

In Nigeria, labour is an essential factor in farming. In view of the importance of labour in agriculture, this study was carried out to investigate the sources of labour used in cocoa production. Multi-stage sampling technique was used to select 100 cocoa farming households. The first stage was a random selection of two Local Government Areas (LGAs), the second stage was the selection of two communities from each of the LGAs while the third stage involved the random selection of twenty five c... J. Lawal

28. Mepiquat Chloride Application On Cotton At Variable Rate

Mepiquat chloride (1,1-dimethylpiperidinium chloride) are used to control excessive vegetative growth in cotton (Gossypium hirsutum L.) broadcast sprayed by ground or air. As proven by previous researches the variability of the cotton plants height in the field is large enough to justify the application of Mepiquat at variable rate. The major advantages of it are: (i) yield increase; (ii) economy of the applied input; (iii) reducing the potential of environmental pollution. The main objective... P.S. Magalhaes, ,

29. Typology Of Farms And Regions In EU States Assessing The Impacts Of Precision Farming-technologies

A typology is developed describing the typical farms and the agricultural regions in Europe which presumably would apply Precision Farming technologies (PFT) and how. The typology focuses on the potential agronomic (cropping practices) benefits of PFT in crop production. Precision Farming covers a wide range of technologies for different sectors in agriculture. They differ in techniques, equipment and procedures and form core elements of information oriented production of various cr... L. Herold, B. Poelling, A. Wurbs, A. Werner

30. Assessment Of Climate Variability On Optimal Nitrogen Fertilizer Rates For Precision Agriculture

 Yield response functions... B. Basso, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac, G. Http://icons.paqinteractive.com/16x16/ac

31. Mapping The Effect Of Food Prices, Productivity And Poverty In The Development Domains Of Nigeria

  Poverty remains the major obstacle to economic emancipation and achievement of development agenda in Nigeria. Worse still, rising food prices pose a major threat to feeding the teeming population in Nigeria. Declining food production, high population growth, and negative food trade balance combine to worsen the food and poverty situations in Nigeria. We stand on the premise that surging and volatile food prices could have a hardest hit on those who could not afford it –... O.E. Olayide, A.E. Ikpi, V.O. Okoruwa, , T. Alabi, T. Omodele

32. Variable-rate Irrigation Management For Peanut Using Irrigator Pro

  Variable-rate irrigation has the potential to save substantial water. These water savings will become more important as urban, industrial, and environmental sectors compete with agriculture for available water. However, methodologies to precision-apply water for maximum agronomic and economic utility are needed.  Information is needed to optimally management variable-rate irrigation systems. In this study, we conducted irrigation experiments on peanut to c... K. Stone, P.J. Bauer, W.J. Busscher, J.A. Millen, D.E. Evans, E.E. Strickland

33. Performance Evaluation Of Off-shelf Range Sensors For In-field Crop Height Measurement

Abstract: In-season plant height is a good predictor of yield potential, which needs to be measured with techniques of high spatial resolution and accuracy. In this study, systematic performance evaluations were conducted on three types of commercial range sensors, an ultrasonic sensor, a laser range finder and a range camera on plant height measurement, under laboratory and field conditions. Results showed that the average errors between the measured heigh... N. Wang, Y. Shi, R.K. Taylor

34. Economic Analysis Of Auto-swath Control For Alabama Crop Production

With the rising costs of fertilizer and pesticides and a push towards increasing environmental stewardship, farmers are seeking means to save money while preserving the environment and wildlife habitat. One technology that aids in remedying these concerns is auto-swath control. This investigation evaluates overlap savings using this technology on different application equipment and resulting in economic savings for those adopting it. Several field boundaries were obtained from across the stat... D. Mullenix, A.M. Troesch, J.P. Fulton, A.T. Winstead, S.H. Norwood

35. A Model For Wheat Yield Prediction Based On Real-time Monitoring Of Environmental Factors

... B. Dumont, F. Vancutsem, J. Destain, B. Bodson, F. Lebeau, M. Destain

36. Early Identification Of Leaf Rust On Wheat Leaves With Robust Fitting Of Hyperspectral Signatures

Early recognition of pathogen infection is of great relevance in precision plant protection. Disease detection before the occurrence of visual symptoms is of particular interest. By use of a laserfluoroscope, UV-light induced fluorescence data were collected from healthy and with leaf rust infected wheat leaves of the susceptible cv. Ritmo 2-4 days after inoculation under controlled conditions. In order to evaluate disease impact on spectral characteristics 215 wavelengths in the range of 370... C. R, T. Rumpf, K. B, M. Hunsche, L. Pl, G. Noga

37. Real-time Calibration Of Active Crop Sensor System For Making In-season N Applications

... K.H. Holland, J.S. Schepers

38. Comparison Of Three Canopy Reflectance Sensors For Variable-rate Nitrogen Application In Corn

In recent years, canopy reflectance sensing has been investigated for in-season assessment of crop nitrogen (N) health and subsequent control of N fertilization. The several sensor systems that are now commercially available have design and operational differences. One difference is the sensed wavelengths, although these typically include wavelengths in both the visible and near-infrared ranges. Another difference is orientation – the sensors most commonly used in the US are designed to... K.A. Sudduth, N.R. Kitchen, S.T. Drummond

39. Changes Of Data Sampling Procedure To Avoid Energy And Data Losses During Microclimates Monitoring With Wireless Sensor Networks

... J.C. Benavente, C.E. Cugnasca, M.F. Barros, H.P. Santos, G. Http://icons.paqinteractive.com/16x16/ac

40. Decision Making And Operational Planning

In order to automatize crop farming and its processes, a number of technological and other problems have to be solved. Agricultural field robots are in our vision to fulfill operations in fields. Robots involve number of technological challenges in order to be functional and reliable, but also systems controlling these robots are to be developed. In this paper automatic crop farming is the vision, and decision making models and operational planning is discussed. Study is carried out with simu... T. Oksanen, ,

41. 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

42. Development Of A Nitrogen Requirement Algorithm Using Ground-based Active Remote Sensors In Irrigated Maize

Studies have shown that normalized difference vegetation index (NDVI) from ground-based active remote sensors is highly related with leaf N content in maize (Zea mays). Remotely sensed NDVI imagery can provide valuable information about in-field N variability in maize and significant linear relationships between sensor NDVI and maize grain yield have been found suggesting that an N recommendation algorithm based on NDVI could optimize N application. Therefore, a study was conducted using the ... T. Shaver, R. Khosla, D. Westfall

43. Wheat Growth Stages Discrimination Using Generalized Fourier Descriptors In Pattern Recognition Context

... F. Cointault, A. Marin, L. Journaux, J. Miteran, R. Martin

44. Cotton NDVIResponse To Applied N At Different Soil EC Levels

  Spatial variability for crop productivity in the southeastern US Coastal Plain is often due to differences in soil water holding capacity. An experiment was conducted to investigate the use of soil EC as an aid in the site-specific application of sidedress N to cotton. Treatments in the study consisted of three N rates (0, 34, and 112 kg N ha-1). Each treatment was replicated four times in plots that were 4 m wide (four cotton rows) and 350 m long. Soil EC was meas... P.J. Bauer

45. Spatial Variability Of Crop And Soil Properties In A Crop-livestock Integrated System

The knowledge of spatial variability soil properties is useful in the rational use of inputs, as in the site specific application of lime and fertilizer. The objective of this work was to map and evaluate the spatial variability of the crop, soil chemical and physical properties. The study was conducted in 2 areas of 6.9 and 11.7 ha of a Typic Haplustox in Sao Carlos, SP, Brazil. The summer crops corn and sorghum were sowed together to the forage crop Brachiaria brizantha in the system of cro... A.C. Bernardi, C.R. Grego, R.G. Andrade, C.M. Vaz, L.M. Rabello, R.Y. Inamasu

46. Comparison Of Spectral Indices Derived From Active Crop Canopy Sensors For Assessing Nitrogen And Water Status

... L. Shiratsuchi, R.B. Ferguson, J.F. Shanahan, V.I. Adamchuk, G. Slater

47. Embedded Sensing System To Control Variable Rate Agricultural Inputs

 This paper presents an embedded sensing system for agricultural machines to collect information about plants and also to control the application of fertilizer with variable rate in corn crop. The Crop Circle reflectance sensor was used with the aim to explore the spe... G.T. Tangerino, R.V. Sousa, A.J. Porto, R. . Inamasu, P. Pinkston

48. Economics Of Precision Agriculture For Wheat And Barley Cultivation In Hamedan, Western Iran

    Precision agriculture can influence agricultural operation economics. In this study, minimum economical farm sizes for producing irrigated/dry wheat and barley in... M. Lak, F. Khosro anjom, J. Tatge

49. The Effect Of Variable-Rate Fertilizer Nitrogen Decision-Making On Winter Wheat

... J. Guo, L. Chen, X. Wang, R. Zhang, L. Zotarelli

50. 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/o... B. Sauer, C.N. Guppy, M.G. Trotter, D.W. Lamb, J.A. Delgado

51. Development Of Batch Type Yield Monitor For Small Fields

 Abstract The yield monitor is intended to give the user an accurate assessment of yield variations y within a field. A yield monitor can assist grain producers in many aspects of crop management. A yield monitor by itself can provide useful information and enhance on-farm research. Yield data c... M. Singh, A. Sharma, G. Singh, P. Fixen

52. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton Production

  Crop models simulate growth and development, and provide relevant information for the routine management of the crop.  The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global p... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller

53. Mapping Soil Salinity Using Cokriging Method In Arsanjan Plain, Southern Iran

  Salt-affected landscapes are highly sensitive to changes in climatic, edaphic and hydrological conditions in time and space in semi-arid regions such as Arsanjan plain, southern Iran. The objective of this study was to combine digital satellite data with ground based measurements of ECe by cokriging method to possibility improve the soil salinity maps of study area. Soil samples in the 85 sampling site (10187 ha)were collected from 0-30 cm depths, georefrenced using GPS recei... M.P. Baghernejad, M.M. Emadi

54. Assessment Of Physiological Effects Of Fungicides In Wheat

The use of fungicides is one of the most widespread methods implemented in intensive crop production focused in solving phytosanitary problems. The use of fungicides belonging to groups such as strobilurins has been associated with positive physiological effects such as increased tolerance against abiotic stresses, changes in plant growth regulator activities and delayed leaf senescence. The use of thermography is a non- destructive method which permits to distinguish physiological changes ca... C. Berdugo, U. Steiner, E. Oerke, H. Dehne

55. Development Of A Sensor Suite To Determine Plant Water Potential

The goal of this research was to develop a mobile sensor suite to determine plant water status in almonds and walnuts. The sensor suite consisted of an infrared thermometer to measure leaf temperature and additional sensors to measure relevant ambient conditions such as light intensity, air temperature, air humidity, and wind speed. In the Summer of 2009, the system was used to study the relationship between leaf temperature, plant water status, and relevant microclimatic information in an al... V. Udompetaikul, S. Upadhyaya, B. Lampinen, D. Slaughter

56. Accounting For Spatial Correlation Using Radial Smoothers In Statistical Models Used For Developing Variable-rate Treatment Prescriptions

Variable-rate treatment prescriptions for use on commercial farms can be developed from embedded field trials on those farms. Such embedded trials typically involve non-random, high-density sampling schemes that result in large datasets and response variables exhibiting spatial correlation. In order to accurately evaluate the significance of the effects of the applied treatments and the measured field characteristics on the response of interest, this spatial correlation must be accounted for ... K.S. Mccarter, E. Burris

57. Sensor And System Technology For Individual Plant Crop Scouting

Sensor and system technologies are key components for automatic treatment of individual plants as well as for plant phenotyping in field trials. Based on experiences in research and application of sensors in agriculture the authors have developed phenotyping platforms for field applications including sensors, system and software development and application-specific mountings.   Sensor and data fusion have a high potential by compensating varying s... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss

58. Vision Of Farm Of Tomorrow

... K. Charvat, P. Gnip

59. Vlite Node – New Sensor Technology For Precision Farming

... K. Charvat, J. Jezek, M. Musil, Z. Krivanek, P. Gnip

60. Spatial And Vertical Distribution Of Soil P, K, And Mg Content In A Vineyard Of The Do Ca Rioja Using Grid And Target Sampling Methods

  Knowledge of spatial variability of soil nutrient contents is very important to design a fertilization strategy based on the needs of the vine. Matching fertilization and nutritional plant needs is very important due to the influence of nutritional status of vineyards on productive and qualitative factors. The aim of this work was to study the spatial and vertical variability of P, K and Mg in a vineyard soil by two methods: (i) the grid sampling at three depth ranges (... O. Unamunzaga, A. Castell, G. Besga, R. Perez-parmo, A. Aizpurua

61. A Computer Decision Aid For The Cotton Precision Agriculture Investment Decision

This article introduces the Cotton Precision Agriculture Investment Decision Aid (CPAIDA), a software decision tool for analyzing the precision agriculture investment decision. CPAIDA was developed to provide improved educational information about precision farming equipment ownership costs, and the required returns to pay for their investment. The partial budgeting and breakeven analysis framework is documented along with use of the decision aid. With care in specifying values, program users... J.A. Larson, D.F. Mooney, R.K. Roberts, B.C. English

62. Cotton Precision Farming Adoption In The Southern United States: Findings From A 2009 Survey

The objectives of this study were 1) to determine the status of precision farming technology adoption by cotton producers in 12 states and 2) to evaluate changes in cotton precision farming technology adoption between 2000 and 2008. A mail survey of cotton producers located in Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, Tennessee, Texas and Virginia was conducted in February and March of 2009 to establish the use of precision farming tec... M. Velandia, D.F. Mooney, R.K. Roberts, B.C. English, J.A. Larson, D.M. Lambert, S.L. Larkin, M.C. Marra, R. Rejesus, S.W. Martin, K.W. Paxton, A. Mishra, C. Wang, E. Segarra, J.M. Reeves

63. Adoption And Perceived Usefulness Of Precision Soil Sampling Information In Cotton Production

  Soil testing assists farmers in identifying nutrient variability to optimize input placement and timing. Anecdotal evidence suggests that soil test information has a useful life of 3–4 years. However, perceived usefulness may depend on a variety of factors, including field variability, farmer experience and education, farm size, Extension, and factors indirectly related to farming. In 2009, a survey of cotton farmers in 12 Southeastern states collected information... D.C. Harper, D.M. Lambert, B.C. English, J.A. Larson, R.K. Roberts, M. Velandia, D.F. Mooney, S.L. Larkin

64. Crop Rotation Impacts ‘Temporal Sampling’ Needed For Landscape-defined Management Zones

Yield and landscape position are used to delineate management zones, but this approach is confounded by yield’s weather dependence, causing yield to evidence temporal variability/lack of yield stability. Management options (e.g. crop rotation) also influence yield stability. Our objective was to build a model that would describe the influence of crop rotation on the temporal yield stability of landscape defined management zones. Corn (Zea mays L.) yield data for two rotat... E.M. Pena-yewtukhiw, J. Grove

65. Evaluation Of A Controlled Release N-P Fertilizer Using A Modified Drill For Variable Rate Fertilization

Base NP or NPK fertilization is a common practice in cereal production in Chile. Usually, a physical NPK blend is band applied with the seed at planting with the drill. Normal fertilizer rates vary from 400 to 500 kg ha-1; however, there is a tendency in the market to move from physical blend towards chemical blends (monogranule) and, more recently, to controlled release fertilizers (CRF). The CRF are usually recommended at very low rates, varying from 70 to 120 kg ha-1, however this rates ar... R.A. Ortega, J.F. Reyes, W. Esquivel, J. Orellana

66. Yield Limiting Factors In The Conditions Of Southern Alberta

The main goal of our experiment was to determine the main factors determining yield of green biomass of spring barley in the conditions of Southern Alberta. To analyze soil properties in the field, grid sampling was conducted at 1-ha grid. Soil samples were collected from the depths of 0…15 and 15…60 cm and analyzed for over 20 different characteristics including soil organic matter content, pH, cation exchange capacity (CEC), and the concentrations of macro- and micronutrients.... A. Melnitchouck

67. Cognitive Radio In Precision Agriculture

 This is an attempt to design a precision agriculture (PA) model, to control the required parameters in greenhouse with wireless sensor network (WSN). This proto type model of wireless sensor and actuators network is designed as per required parameters of available crops in a greenhouse. The design of the sensor node consists of sensors, a micro-controller and a low-powered radio module. Real-time data, enable the operators to characterise the operating parameters of the greenhouse and a... S.P. Nayse, D.D. Choudhari, V.M. Wadhai

68. Study Of Nitrogen Fixation And Nodulation In Annual Medic(medicago Rigidula) In Inoculation With Foreign And Inside Root Symbiotic Bacteria

  Annual species of Medicago are important pasture legumes in western parts of iran. Their productions are affected by suitable soil Rhizobium meliloti strains and environmental conditions. The principle objective of this study was to find a suitable Rhizobium meliloti strain(s) for Medicago rigidula. Two experiments: one in the greenhouse and the other one on the field were conducted in 2006 to determine nodulation, and ni... E. Nabizadeh

69. Site Specific Management Of An Oxisol Cultivated With Corn For Application Of Lime And Gypsum

Due to the necessity to improve soil fertility diagnostic, the researchers have been searched for more efficient technologies on agronomic, economic and environmental aspects. One of these technologies is the use of the concept of site-specific for soil fertility management. This research was conducted in a farm field (100 ha) located in Corinto, Minas Gerais state. The soil is classified as clayey Oxisol, cropped with corn (Zea mays L.) and irrigated with a center-pivot sprinkler irrigation ... A. Coelho, T.F. Cunha, T.F. Cunha

70. Laboratory Evaluation Of Ion-selective Electrodes For Simultaneous Analysis Of Macronutrients In Hydroponic Solution

... H. Kim, , , , K.A. Sudduth

71. Optimizing Vineyard Irrigation Through The Automatic Resistivity Profiling (arp) Technology. The Proposal Of A Methodological Approach

 In Tuscany, central Italy, grape cultivation and wine production (i.e., Chianti DOCG, Brunello di Montalcino) are farming activities appreciated worldwide. Differently from the past, irrigation is allowed to meet the intense physiological stress that may occur during seasons affected by the increasing climate variability, in order to guarantee quality product and hence high market profitability in many vines areas. Most ... P. Pagni, G.P. Ghinassi, M.P. Vieri

72. Pa Adoption By A Korean Rice Farming Group: Case Study Of Pyeongtaek City

Research on precision agriculture (PA) has been conducted in Korea for about 10 years since 1999. Most of the research was focused on rice paddy fields that were flooded, flat, and small sized (e.g., 30 m x 100 m). Accomplishment during the period includes investigation on spatial variability in soil, crop growth, and yield properties, application of imported sensors and variable rate applicators, and development of Korean version of these ... S. Chung, H. Yoo, S. Hong

73. Effect Of Nitrogen Application Rate On Soil Residual N And Cotton Yield

A long-term study was conducted on nitrogen application rate and its impact on soil residual nitrogen and cotton (FM960B2RF) lint yield under a drip irrigation production system near Plainview, Texas. The experiment was a randomized complete block design with five nitrogen application rates (0, 56, 112, 168 and 224 kg per ha) and five replications. The soil nitrogen treatment was applied as side dressing. Cotton yield, leaf N, seed N, soil residual nitrate, amount of irrigation, and rainfall ... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

74. Canopy Reflectance-based Nitrogen Management Strategies For Subsurface Drip Irrigated Cotton

Nitrogen (N) fertilizer management in subsurface drip irrigation (SDI) systems for cotton (Gossypium hirsutum L.) can be very efficient when N is fertigated on a near daily time step.  Determining the amounts and timing of the N fertigation, however are questions that weekly canopy reflectance measurements may answer.   The main objective of this 3-yr. study was to test two canopy reflectance strategies for adjusting urea ammonium nitrate (UAN) fertilizer in-season injections... K. Bronson

75. Generating Herbicide Effective Application Rate Maps Based On GPS Position, Nozzle Pressure, And Boom Section Actuation Data Collected From Sprayer Control Systems

The application of pre- and post- emergence burn-down herbicides (i.e., glyphosate) continues to increase as producers attempt to reduce both negative environmental impacts from tillage and input costs from labor, machinery and materials.  The use of precision agriculture technologies such as automatic boom section control allows producers to reduce off-target application when applying herbicides.  While automatic boom section control has provided benefits, pressure differences acro... J.D. Luck, A. Sharda, S.K. Pitla, J.P. Fulton, S.A. Shearer

76. Precision Agriculture Development In Canada

This poster provides an overview of precision agriculture development in Canada.  It focuses on the specific practices of auto steer tracking and variable rate nutrient application in the prairie region.  The development of these practices has been largely driven by technology innovation and private sector crop consultants and equipment providers.  Nevertheless, academia and government have supported this development through research since the 1990’s and funding incentive... D. Haak

77. Soil Quality Improvement Through Proper Combination Of Tillage, Nitrogen Fertilization And Cover Cropping Systems

No-tillage, N fertilization and cover cropping affect physical, chemical and biological qualities of soil. We investigated the effect of 15-yr of tillage systems, N fertilization and cover crops on soil organic matter, aggregation, bulk density and on microbial community in the sandy loam soil of central Italy. The soil in no-tillage (NT) system had 50% more organic matter and 3 folds higher aggregate stability than the soil in conventional tillage (CT) system. The NT system significantly inc... T.B. Sapkota

78. Effect Of Precision Guided Cultivation On Weed Control In Wide Row Cropping Systems

Wide row cropping has been traditionally followed in summer crops but it is also becoming popular in winter crops such as chickpeas and lupins.  High precision guidance systems with 2 cm accuracy offer unique opportunities to cultivate closer to the row and increase weed control efficiency in wide row cropping systems. Two field experiments were conducted in chickpeas with a Real Time Kinematic Differential Global Positioning System (RTK-DGPS) controlled mechanical cultivation. Cultivati... M. Gupta, ,

79. Edxrfs-based Sensing Of Phosphorus And Other Mineral Macronutrient Distribution In Field Soils

Phosphorus (P) requirements for major agronomic crops have been currently based on a pre-plant mass balance method.  Fertilizer needs are estimated from crop needs, available soil P and other external nutrient inputs that include animal manure, crop residues, etc...  Thus, this approach uses f... T.H. Dao

80. Application of Information Technologies in Precision Apiculture

Apiculture, widely known as beekeeping, is one of the agriculture’s sub directions, where Precision Agriculture (PA) methods can be successfully applied. Adaptation of PA methods and technics into Apiculture, as well as integrating information technologies into beekeeping process can change and improve the beekeepers understanding of bee... E. Stalidzans, A. Zacepins, J. Meitalovs

81. Evaluation of Photovoltaic Modules at Different Installation Angles and Times of the Day

Several electricity-consuming components for cooling and heating, illumination, ventilation, and irrigation are used to maintain proper environments of protected crop cultivation facilities. Photovoltaic system is considered as one of the most promising alternative power source for protected cultivation. Effects of environm... S. Chung, J. Kong, Y. Huh, K. Bae, S. Hur, D. Lee, Y. Chae

82. Climatological Diagnostic Analysis: A Case Study for Parbhani District in Marathwada Region of India

... S.N. Pawar, A.K. Gore, G.U. Shinde, M.S. Pendke

83. Radio Frequency Identification For Implementing Traceability In The Cotton Production In The Brazilian Midwest

According to the International Cotton Advisory Committee - ICAC projection for the fiber in cotton production for the crop year 2012/2013 is expected to reach an amount of 15.19 million tons , according to a forecast released in August 2012 . In the Brazilian context , according to the Ministry of Agriculture, Livestock and Supply of Brazil cotton cultivation in Brazil has grown especially in the Midwest . In particular , exports of cotton fiber increased twice in one season in 2003/2004... C. Santos, E.O. Weschter, M.A. Dota, C.E. Cugnasca

84. Precision Sensors For Improved Nitrogen Recommendations In Wheat

Crop sensor-based systems with developed algorithms for making mid-season fertilizer nitrogen (N) recommendations are commercially available to producers in some parts of the world. Although there is growing interest in these technologies by grain producers in Montana, use is limited by the lack of local research under Montana’s semiarid conditions. A field study was carried out at two locations in 2011, three locations in 2012, and two locations in 2013 in North West Mont... O.S. Walsh, A. Pandey, R. Christiaens

85. Toward More Precise Sugar Beet Management Based On Geostatistical Analysis Of Spatial Variabilty Within Fields

Abstract: Sugar beet (Beta vulgaris L.) yields in England are predicted to increase in the future, due to the advances in plant breeding and agronomic progress, but the intra-field variations in yield due to the variability in soil properties is considerable. This paper explores the within-field spatial variation in environmental variables and crop development during the growing season and their link to spatial variation in sugar beet y... A.J. Murdoch, S.A. Mahmood

86. Analyzing Organic Farming Training In The Curriculum Of The University Of Kwazulu-Natal, Pietermaritzburg

  ANALYZING ORGANIC FARMING TRAINING IN THE CURRICULUM OF THE UNIVERSITY OF KWAZULU-NATAL, PIETERMARITZBURG      SJ, Polepole * and SH, Worth        Agricultural Extension and Rural Resource Management Program;      University of KwaZulu-Natal; Scho... S.H. Worth, S.J. Polepole

87. Applications Of Small UAV Systems For Tree And Nursery Inventory Management

Unmanned aerial vehicles (UAV) systems could provide low-cost and high spatial resolution aerial images. These features and ease of operation make it a practical tool for applications in precision agriculture and horticulture. This paper highlights the application of UAV systems in tree counting, which is vital for tree inventory management and yield estimation. In this paper, two types of trees were discussed. One type is with non-uniform canopy area (e.g. container plants and ... Y. She, R. Ehsani, J. Robbins, J. Owen, J.N. Leiva

88. Estimating Spatial Variation In Annual Pasture Yield

Yield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers.   Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett

89. The Spatial And Temporal Variability Analysis Of Wheat Yield in suburban of Beijing

  Abstract: The yield map is the basis of the fertilization maps and plant maps. In order to diagnose the cause of variation accurately, not only the spatial variation of annual yield data, but also the successive annual yield data of temporal variability should be understood.The introduction of yield monitor system, global positioning system (GPS), and geographic information system have provided new methods to obtain wheat yield in precision agriculture.... Z. Meng, Z. Wang, G. Wu, W. Fu, X. An

90. First Results Of Development Of A Smart Farm In The Netherlands

GNSS technology has been introduced on about 20 % of the Dutch arable farms in The Netherlands today. Use of sensor technology is also slowly but gradually being adopted by farmers, providing them large amounts of digital data on soil, crop and climate conditions. Typical data are spatial variation in soil organic matter, crop biomass, crop yield, and presence of pests and diseases. We still have to make major steps to use all this data in a way that agriculture becomes more sus... T. Feher, C. Kocks, C. Kempenaar, K. Westerdijk

91. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategi... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

92. A Comprehensive Model for Farmland Quality Evaluation with Multi-source Spatial Information

Farmland quality represents various properties, including two parts of natural influencing factors and social influencing factors. The natural factors and social factors are interrelated and interaction, which determine the developing direction of farmland system. In order to overcome the limitation of subjective factors and fuzzy incompatible information, a more scientific evaluation method of farmland quality should be developed to reflect the essential characteristic of farml... Y. Dong, Y. Wang, X. Song, X. Gu

93. Nitrogen Fertilisation Recommendations : Could They Be Improved Using Stochastically Generated Climates In Conjunction With Crop Models ?

In the context of precision nitrogen (N) management, to ensure that the yield potential could be reached each year, farmers have too often applied quantities of fertilizers much larger than what was strictly required. However, since 2002, the Belgian Government transposed the European Nitrate Directive 91/676/EEC in the Belgian law, with the aim to maintain the productivity and the revenue of Belgian's farmers while reducing the environmental impact of excessive N management... B. Basso, J. Destain, B. Bodson, M. Destain, B. Dumont

94. Physiological Repsonses Of Corn To Variable Seeding Rates In Landscape-Scale Strip Trials

Many producers now have the capability to vary seeding rates on-the-go. Methods are needed to develop variable rate seeding approaches in corn but require an understanding of the physiological response of corn to soil-landscape and weather conditions. Interplant competition fundamentally differs at varied seeding rate and may affect corn leaf area, transpiration, plant morphology, and assimilate partitioning. Optimizing these physiological effects with optimal seeding rates in a site-spe... D.B. Myers, N.R. Kitchen, K.A. Sudduth, B.J. Leonard

95. Building Proactive Predictive Models With Big Data Technology For Precision Agriculture

In a world with ever increasing shortages of food production due to increasing populations and depletion of resources, the need for new technologies and techniques for sustainable and efficient agriculture with long term financial, environmental and cultural benefits are critical.  An area of scientific study concerning crop-production management called Precision Agriculture (PA) is a concept based on integrating modern information technologies such as Big Data Analytics, G... C. Lai, C. Belsky

96. Spatial Variation And Correlation Between Electric Conductivity (EM38), Penetration Resistance And CO2 Emissions From A Cultivated Peat Soil

Peatlands in their natural state accumulate organic matter and bind large quantities of carbon (5 - 50 g C/m2/year). The drainage and cultivation of peat soils increase the aeration of the soil, which increase the brake down of the organic matter. The degradation of the organic material release greenhouse gases such as CO2, N2O and CH4. CO2 emissions dominate when the soil has high oxygen levels, while CH4 mainly ... &.E. Berglund

97. Penetration Resistance And Yield Variation At Field Scale

In order to better explain spatial variations within fields, soil physical properties need to be studied in more depth. Relationships between soil physical parameters and yield, especially in the subsoil, are seldom studied since the characterization of soil variability at field or subfield scale using conventional methods is a labor intensive, very expensive, and time-consuming procedure, particularly when high-resolution data is required. However, soil physical prope... E. Bölenius, J. Arvidsson

98. Autonomous Service Robots For Orchards And Vineyards: 3D Simulation Environment Of Multi Sensor-Based Navigation And Applications

In order to fulfill economical as well as ecological boundary conditions information technologies and sensor are increasingly gaining importance in horticulture.  In combination with the reduced availability of human workers automation technologies thus play a key role in the international competition in vinicultures and orchards and have the potential to reduce the costs as well as environmental impacts.   The authors are working in t... J. Hertzberg, A. Ruckelshausen, E. Wunder, A. Linz

99. Optimization Of Maize Yield: Relationship Between Management Zones, Hybrids And Plant Population

Corn is highly sensitive to variations in plant population and it is one of the most important practices influencing in grain yield. Knowledge about plant physiology and morphology allow understanding how the crop interacts with plant population variation. Considering that for each production system there is a population that optimizes the use of available resources it is necessary to manage plant population to reach maximum grain yield on each particular environment. This study... A.A. Anselmi, J.P. Molin, R. Khosla

100. Water And Nitrogen Use Efficiency Of Corn And Switchgrass On Claypan Soil Landscapes

Claypan soils cover a significant portion of Missouri and Illinois crop land, approximately 4 million ha. Claypan soils, characterized with a pronounced argilic horizon at or below the soil surface, can restrict nutrient availability and uptake, plant water storage, and water infiltration. These soil characteristics affect plant growth, with increasing depth of the topsoil above the claypan horizon having a strong positive correlation to grain crop production. In the case of low... A. Thompson, D.L. Boardman, N. Kitchen, E. Allphin

101. A Study On Diagnostic System Based On ISOAgLIB For Agricultural Vehicles

  Nowadays the growth of the embedded electronics and communications has demanded the development of applications in agricultural machinery in Korean agroindustry. The root reason is that most of agricultural machineries produced in Korea does not apply international standard. Therefore, the incompatibility problem between hardware, software and data formats has become a major obstacle for exporting agricultural products made by Korea to the world. I... J. Moon, S. Kim, J. Lee, W. Yang, D. Kim

102. Heavy Metal PB2+ Pollution Detection In Soil Using Terahertz Time-domain Spectroscopy For Precision Agriculture

Soil is an important natural resource for human beings. With the rapid development of modern industry, heavy metals pollution in soil has made prominent influences on farmland environment. It was reported that, one fifth of China's cultivated lands and more than 217,000 farms in the US have been polluted at different levels by heavy metals. The crop grows in the polluted soil and the heavy metal ions transfer from soil to the plant and agro-products. As a result, the crop yi... C. Zhao, B. Li

103. Climate Change And Sustainable Precision Crop Production With Regard To Maize (Zea Mays L.)

Precision crop production research activities were started during the mid-‘90s at the Institute of Biosystems Engineering, Faculty of Agricultural and Food Sciences, University of West Hungary. On the basis of the experiences with DSSAT (Decision Support System for Agrotechnology Transfer) the impact of climate change on maize yield (three soil types) was investigated until 2100. DSSAT crop growth model is used worldwide. The coupled model intercomparison ... A.J. Kovács, A. Nyéki, G. Milics, M. Neményi

104. Precision Nutrient Management In Cotton At Different Yield Targets In Northern Transitional Zone Of Karnataka

  Nutrient management in cotton is complex due to the simultaneous production of vegetative and reproductive structures during the active growth phase. Lot of spatial variation in soil available nutrients is observed under similar management situation. In view of this an experiment ... C.C. Pgowda

105. Design Of ECU Monitoring System For Agricultural Vehicle Based On ISO 11783

International standard for implementation of electronic control unit (ECU) in agricultural tractors has been requirement for inter-operation compatibility of various agricultural vehicles. The ISO 11783 standard is basically based on  communication technology designated using the controller area network (CAN), it is typical standard technology for implementation of ECU in agricultural vehicle. CAN bus Communication system was developed to the distribution control of ECUs to... W. Yang , S. Kim, J. Moon, D. Kim

106. Soil And Crop Spatial Variability In Cotton Grown On Deep Black Cotton Soils

Soil spatial variation is observed under similar management situation in cotton growing soils of Northern Karnataka. In view of this an experiment was conducted to study the spatial variability in soil with respect soil reaction (pH), Electrical conductivity (Ec), Organic carbon (OC%), all major (N,P,K), secondary (Ca, Mg and S) and micronutrients (Fe, Zn, Cu and Mn) by assessing soil nutrients in deep black cotton soils of the experimental station ... C.C. Parashuramegowda

107. 3D Map in the Depth Direction of Field for Precision Agriculture

 By a change in eating habits with economic development and the global population growth, we have been faced with the need for increased food production again. In order to solve the food problem in the future, the introduction of agriculture organization is progressing in emerging countries as well as developed countries. However, the occurrence of natural disasters and abnormal weather, which is becoming a worldwide problem at present, is further weakening the crops of far... H. Umeda, S. Shibusawa, Q. Li, K. Usui, M. Kodaira

108. Study On The Automatic Monitoring Technology For Fuji Fruit Color Based On Machine Vision

  Fruit color is one of the important indicators of quality and commodities. Three kinds of the traditional methods are used to evaluate fruit color, including artificial visual identification, fruit standard color cards and color measurement instrument. These methods are needed to be conducted in the field by persons, which are time-consuming and labored, and also difficult to obtain the dynamic color information of the target fruits in the growth process. This study ... M. Chen, M. Li, J. Qian, W. Li, Y. Wang, Y. Zhang, X. Yang

109. Developing A High-Resolution Land Data Assimilation And Forecast System For Agricultural Decision Support

Technological advances in weather and climate forecasting and land surface and hydrology modeling have led to an increased ability to predict soil temperature, and soil moisture, near-surface weather elements. These variables are critical building blocks to the development of high-level agriculture-specific models such as pest models and crop yield models. The National Center for Atmospheric Research (NCAR) has developed a high-resolution agriculture-oriented land-data assimilat... W. Mahoney, M. Barlage, D. Gochis, F. Chen

110. Management Zones Delineation In Brazilian Citrus Orchards

Precision Agriculture (PA) is in its first steps in Brazil citrus production. Variable rate fertilization based on soil grid sampling and yield maps has been tested in São Paulo orchards. In a long term study results showed potential on increasing fertilizer use efficiency and improving soil fertility management. Despite the good results, in some cases it is noticed that systematic methods of investigation (grid sampling and yield data) and prescription (standardized prescription ... M. Ruiz, D. Yida, J.P. Molin, A.F. Colaço

111. Assessing Definition Of Management Zones Trough Yield Maps

Yield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two ... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan

112. Variable-Rate Application Of Nitrogen And Potassium Fertilizers In Louisiana Sugarcane Production Systems.

If sugar and cane yields are to be optimized and profitability improved, it is critical that a sugarcane crop receive the proper levels of plant nutrients.  Under-fertilization can result in reduced cane yields, while over-fertilization can reduce sugar recovery.  In addition, improper fertilization may increase crop susceptibility to environmental stresses and disease and insect pests. Nitrogen (N) continues to be one of the most important and co... B.J. Viator, R.M. Johnson

113. Estimation Of Nitrogen And Chlorophyll Content In Wheat Crop Using Hand Held Sensors

A Field experiment was conducted to estimate crop nitrogen (N) status and chlorophyll content in wheat crop by using chlorophyll content meter(Apogee’s CCM-200) and N-Tester®  (Make YARA International). The experiment was conducted by sowing university recommended wheat variety viz. PBW 550 with 5 nitrogen levels i.e. 0, 30, 60, 90, 120 & 150 kg N/ha. It was found that at tillering stage when nitrogen rates were increased from 0 to 150 kg ha-1 , the... M.S. Makkar, A. Kaul, R. Kumar, A. Sharma, B.S. Sekhon, C.S. Pannu

114. Multilayer And Multiyear Data Analysis In Precision Yield Planning

This work covers two separate field experiments. In the first one, the results of 1-ha grid soil analysis for soil organic matter (OM), pH, cation exchange capacity (CEC), nitrate N, P, K, S, Ca, Mg and soluble salts were compared with the results of yield mapping, biomass index from optical on-the-go sensors, as well as multispectral imagery analysis for the last 30 years.  As a result, it was found that none of the analyzed soil characteristics was predominant for determining yiel... A. Melnitchouck

115. Effect Of A Variable Rate Irrigation Strategy On The Variability Of Crop Production In Wine Grapes In California

Pruning and irrigation are the cultural practices with the highest potential impact on yield and quality in wine grapes. In particular, irrigation start date, rates and frequency can be synchronized with crop development stages to control canopy growth and, in turn, positively influence light microclimate, berry size and fruit quality. In addition, canopy management practices can be implemented in vineyards with large canopies to ensure fruit zone microclima... L.A. Sanchez, L.J. Klein, A. Claassen, D. Lew, M. Mendez-costabel, B. Sams, A. Morgan, N. Hinds, H.F. Hamann, N. Dokoozlian

116. Spatial Dependence Of Soil Compaction In Annual Cycle Of Different Culture Of Cane Sugar For Sandy Soil

The Currently practiced mechanization for the production of sugar cane involves a heavy traffic of machinery and equipment. Studying the culture in its development environment generates a huge amount of information to fit the top managements and varieties for specific environments. The sugar cane cultivation has a heavy traffic of machinery and equipment, having more than 20 operations per cycle, and being more intense during harvest, providing incre... I. Marasca, F.C. Masiero, D.A. Fiorese, S.S. Guerra, K.P. Lancas

117. A Method To Estimate Irrigation Efficiency With Evapotranspiration Data

Irrigation efficiency is defined as the ratio of irrigation water consumed by the crops to the water diverted (Wg) from a river or reservoir or wells. This terminology serves for better irrigation systems designation and irrigation management practices improvement. But it is hard or high cost with labor intensity to estimate irrigation efficiency from field measurement. This paper proposes an estimating method of irrigation efficiency at the scale of irrigat... H. Zeng, B. Wu, N. Yan

118. Trials Of Precision Restoring Agriculture In Japan

The objective of the paper is to describe a tentative scheme of precision restoring agriculture in Japan. “3.11” in 2011 is the day the northeast Japan was attacked by the tri-disaster; a M 9.0 super earthquake, 10-m–high huge Tsunami, and explosions of Fukushima nuclear power station. Huge damage has been confirmed across the cities and rural communities, including agriculture and industry sectors along the coastline of more than 500 km. In th... S. Shibusawa

119. Response Of Rhodes Grass (Chloris Gayana Kunth) To Variable Rate Application Of Irrigation Water And Fertilizer Nitrogen

Rhodes grass is cultivated extensively in Saudi Arabia under center pivot sprinkler irrigation system. The research work was carried out to optimize irrigation water and fertilizer nitrogen levels for the crop. The objectives of the study were: 1. To delineate the field in to management zones, 2. To study the effects of variable rate application (VRA) of irrigation water and fertilizer nitrogen on the yield of Rhodes grass. A field experiment was carried out fro... V. Patil, R. Madugundu, E. Tola, S. Marey, D.J. Mulla, S.K. Upadhyaya, K.A. Al-gaadi

120. Precision Agriculture In Sugarcane Production. A Key Tool To Understand Its Variability.

Precision agriculture (PA) for sugarcane represents an important tool to manage local application of fertilizers, mainly because sugarcane is third in fertilizer consumption among Brazilian crops, after soybean and corn. Among the limiting factors detected for PA adoption in the sugarcane industry, one could mention the cropping system complexity, data handling costs, and lack of appropriate decision support systems. The objective of our research group ha... P.S. Graziano magalhães, G.M. Sanches, O.T. Kolln, H.C. Franco, O.A. Braunbeck, C. Driemeier

121. Optical Sensors To Predict Nitrogen Demand By Sugarcane

The low effectiveness of nitrogen (N) from fertilizer is a substantial concern in worldwide which has been threatening the sustainability of sugarcane production. The increment of nitrogen use efficiency (NUE) by sugarcane genotypes associated to the best practices of fertilizer management and nutritional diagnosis methods have higher potential to reduce environment impacts of nitrogen fertilization. Due to the difficult to determine N status in soil test as well as there is not... O.T. Kolln, G.M. Sanches, J. Rossi neto, S.G. Castro, E. Mariano, R. Otto, R. Inamasu, P.S. Magalhães, O.A. Braunbeck, H.C. Franco

122. Basic Tests Of pH And EC Probes For Automatic Real Time Nutrient Control In Protected Crop Production

Research on greenhouse and plant factory has been actively conducting to provide a stable growth environment. In plant factory, EC concentration (EC) and acidity (pH) of nutrient have a significant impact on physiological and morphological of plant. Therefore, EC and pH are important element for automatic control of nutrient solution. In this study, performance pH and EC sensors was evaluated for the responsiveness, accuracy and displacement. This study includes development of e... Y. Choo, S. Chung, Y. Huh, Y. Kim, S. Jang, K. Jung

123. Effect Of Land Use Over Spatial Variability Of Nitrogen Mineralization And Some Of Chemical Soil Properties In Mirabad Area Of Iran

Abstract Any changes in ecosystem conditions and land management impact on ecology of soil inorganic nitrogen. Understanding of the biology soil is increasingly important for sustainable ecosystem. The aim of this study was to investigate the spatial variability and zoning of nitrogen mineralization, organic carbon and calcium carbonate influenced by the user of apple orchards, crop production and pasture, and compare the two interpola... E. Nabizadeh, S. Kaboodi

124. Research On Measurement Device For NO3- Ion Concentration Of Nutrient Solution

The management of water and ion concentration in nutrient solution is crucial in precision agriculture. Poor management may leads to the increasing of energy consumption and cost as well as low efficiency. The measurement of ion concentration in nutrient solution is prerequisite for optimal control and management of nutrient solution. Real-time detection of NO3-, as an important component of nitrogenous fertilizer, is always a big problem over the world. Th... X. Zhang, Y. Li, K. Xu, X. Sun

125. Site Specific Drip Fertigation

Two test plots, one from high fertility zone and one from low fertility zone were identified and delineated with the help of GPS for raising the test crop. Soil samples were collected from the experimental sites one month before planting. The samples were analyzed for available N, P and K. Site specific nutrient recommendations were made using the Decision Support System for Integrated Fertilizer Recommendation (DSSIFER) software (Murugappan et al. 2004) for optimum yie... A.H. V.m.

126. The Central China Agricultural High-Tech Industry Development Zone

This is a presentation on precision ag opportunities in China. ... E. You fu

127. A Novel Portable System For Improving Accuracy Of Reimbursement For Fruit Picking

Various methods for reimbursing pickers have been employed worldwide, with most fruit growers now paying a piece-rate to small picking teams for bins (e.g. for pome fruit) or for buckets (e.g. for sweet cherries, blueberries).  Regardless, paying piece-rate is beset with inaccuracies that cause significant financial losses. Our tests in commercial sweet cherry and apple orchards revealed variability of 25 – 30% of final weight among bins and buckets. For example, in s... Y.G. Ampatzidis, M.D. Whiting

128. Precision Nutrient Management For Enhancing The Yield Of Groundnut In Peninsular India

               Groundnut is an important oil seed crop grown in an area of around 8 lakh hectares in Karnataka state of India under rainfed conditions. In these situations farmers applied inadequate fertilizer without knowing the initial nutrient status of the soil which resulted in low nutrient use efficiency that intern lead to low productivity of groundnut in these areas. Soil fertility deterioration due to... M. Giriyappa, T. Sheshadri, D. Hanumanthappa, M. Shankar, S.B. Salimath, T. Rudramuni, N. Raju, N. Devakumar, G. Mallikaarjuna, M.T. Malagi, S. Jangandi

129. Exploiting The Variability In Pasture Production On New Zealand Hill Country.

New Zealand has about four million hectares in medium to steep hill country pasture to which granular solid fertiliser is applied by airplane.  On most New Zealand hill country properties where cultivation is not possible the only means of influencing pasture production yield is through the addition of fertilizers and paddock subdivision to control grazing and pasture growth rates. Pasture response to fertilizer varies in production zones within the farm which can be modell... M.Q. Grafton, P.J. Mcveagh, R.R. Pullanagari, I.J. Yule

130. Application of Semantic Sensor Web in Agriculture

      In July 2013, heavy rainstorms across the Midwestern region of the US caused many rivers to breach their banks. Residents of Valley Park, a small town along the Meramec River, Missouri, had to decide whether to rely on a newly constructed levee or abandon their homes for higher ground. Although the levee held, many chose the latter option and fled their homes; it was a chaotic situation that might have been avoided through access to better situational knowle... Y. Zhang, T. Chen

131. Study Of Spatio-Temporal Variation Of Soil Nutrients In Paddy Rice Planting Farm

It is significant to analysis the spatial and temporal variation of soil nutrients for precision agriculture especially in large-scale farms. For the data size of soil nutrients grows once after sampling which mostly by the frequency of one year or months, to discover the changing trends of exact nutrient would be instructive for the fertilization in the future. In this study, theories of GIS and geostatistics were used to characterize the spatial and temporal variability of soi... C. Wang, T. Chen, J. Dong, C. Li

132. The Most Sensitive Growth Stage To Quantify Nitrogen Stress In Sugarcane Using Active Crop Canopy Sensor

The use of sensors that allow the application of nitrogen fertilizer at variable rate has been widely used by researchers in many agricultural crops, but without success in sugarcane, probably due to the difficulty of diagnosing the nutritional status of the crop for nitrogen (N). Active crop canopy sensors are based on the principle that the spectral reflectance curve of the leaves are modified by N level. Researchers in USA indicated that in-season N stress in corn can be dete... S.G. Castro, O.T. Kolln, H.S. Nakao, H.C. Franco, O. Braunbeck, P.S. Graziano magalhães, G.M. Sanches

133. Nutrient Expert Software For Nutrient Management In Cereal Crops

Many countries in Asia have started replacing blanket fertilizer recommendations for vast areas of rice, maize, or wheat with more site-specific guidelines adapted to local needs. This process has been accompanied with a shift from traditional on-station research to on-farm development and evaluation of novel practices. A key challenge faced by the local extension agencies remains the complex nature of factors influencing nutrient requirements.  To aid in this process, the ... M. Pampolino, K. Majumdar, S. Phillips

134. Assessing Impact Of Precision On Agricultural Energy Requirements: Weed Control Case Study

The anticipated world population increase demands growth in sustainable food production. The current trend is to use more efficient agricultural processes in order to increase food production. Precision agriculture (PA) technology provides the means to increase equipment productivity and field and input efficiency. The concept of small modular and scalable intelligent machines tries to address the challenge of more productivity with the goal of reduced cost and power. In additio... S. Brian, O.M. Toledo, L. Tang

135. Precision Nutrient Management Through Use Of LCC And Nutrient Expert In Hybrid Maize Under Laterite Soil Of India

Nutrient management has played a crucial role in achieving self sufficiency in food grain production. Energy crisis resulted in high price index of chemical fertilizers. Coupled with their limited production, fertilizer cost, soil health, sustainability and pollution have gave rise to interest in precision nutrient management tools. Field experiment was conducted to study the effect of variety and nutrient management on the growth and productivity of maize under lateritic belt of West Be... M. Banerjee, S. Dutta, G. Bhuiya, G. Malik, D. Maiti

136. Site-Specific Variability Of Grape Composition And Wine Quality

Precision Viticulture (PV) is the application of site-specific tools to delineate management zones in vineyards for either targeting inputs or harvesting blocks according to grape maturity status. For the creation of management zones, soil properties, topography, canopy characteristics and grape yield are commonly measured during the growing season. The majority of PV studies in winegrapes have focused on the relation of soil and vine-related spatial data with grape co... S. Fountas, Y. Kotseridis, A. Balafoutis, E. Anastasiou, S. Koundouras, S. Kallithraka, M. Kyraleou

137. Comparison Of The Variable Potassium Fertilization On The Light And Heavy Soils

Introduction. Determination of the spatial variability of the nutrient levels in soil facilitated adaptation of the fertilizer doses to the soluble forms availability. Nowadays, an increasing use of this method of the fertilizer application is observed, with this being associated with both economical and environmental advantages, as well as, with growing assortment of the purpose-built agricultural instrumentation. An accurate determination of the spatial distri... P. Grocholski, P. Stepien, G. Kulczycki, A. Michalski

138. Beyond The 4-Rs Of Nutrient Management In Conjunction With A Major Reduction In Tillage

Agribusiness and government agencies have embraced the 4-R concept (right form, rate, time, and place) to improve nutrient management and environmental quality. No-ti... J.S. Schepers, B. Mclure, G. Swanson

139. Probability Distributions And Alternative Transformations Of Soil Test NO3-N And PO4-P, Implications For Precision Agriculture

Recommendations for fertilizer N in crop production and precision agriculture depend on statistical analyses of data which represent soil NO3-N and PO4-P fertility typical of management zones and fields.  Non-normal distributions of soil test N are commonly log transformed prior to statistical analysis for interpolation with methods such as kriging, regression, or principle component analysis.  These data are transformed to ensure that analysis meet the assumptions of normality... A. Moulin

140. Does Nitrogen Balance Surplus Done At Field Level Help To Assess Environmental Effects Of Variable Nitrogen Application In Winter Wheat?

Increased nitrogen use efficiency (NUE) is important as a specific consideration to decrease negative impacts of nitrogen (N) on the environment and provide better crop quality. Therefore, in many European countries N is used with restrictions due to UE regulations, set to increase NUE. This is particularly important in wheat production because this crop in EU accounts for 48% of cereal production and uses about 25% of total N-fertilizer applied. One of the methods applied to increase NU... S.M. Samborski

141. In-Season Decision Support Tools For Estimating Nitrogen Side-Dress Rates For Maize (Zea Mays L.)

Nitrogen fertilizer has been synthetically produced to nourish plants, increase yield and improve harvest quality. One of the way to increase NUE is called split application which is apply portion of N fertilizer from the beginning and apply another portion during vegetative stage (V4-V6). Improving accuracy of corn side dress N rate recommendations can improve profitability and reduce potential negative environmental impacts of over fertilization. The objective of this experime... B. Chim

142. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance Spectra

Successful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and ... A. Gholizadeh, M. Saberioon, L. Borůvka

143. Detection of Nitrogen Stress on Winter Wheat by Multispectral Machine Vision

Hand-held sensors (SPAD meter, N-Tester, …) used for detecting the leaves nitrogen  concentration (Nc) present several drawbacks. The nitrogen concentration is gained by an indirect way through the chlorophyll concentration and the leaves have to be fixed in a defined position for the measurements. These drawbacks could be overcome by an imaging device that measures the canopy reflectance. Hence, the objective of the paper is to analyse the potential of multispectral imaging for d... M. Destain, V. Leemans, G. Marlier, J. Goffart, B. Bodson, B. Mercatoris, F. Gritten

144. Use of Satellite Data to Improve Damage Assessment Process for Agricultural Insurance Scheme in Indonesia

Goal is to develop new method utilizing satellite data for assessment of damage in paddy field which can contribute toward substantial reduction of the damage assessment time and costs in framework of agricultural insurance in Indonesia. For the damage assessment, estimation of yield in each paddy plot is a key, so the research on the estimation of rice yield was carried out using satellite data which was acquired in harvesting season. Multiple linear regression analysis was conducted for the... C. Hongo, C. Ogasawara, E. Tamura, G. Sigit

145. Site Specific Costs Concerning Machine Path Orientation

Computer algorithms have been created to simulate in advance the orientation/pattern of a machine operation on a field. Undesired impacts were obtained and quantified for these simulations, like: maneuvering and overlap of inputs in headlands; servicing of secondary units; and soil loss by water erosion. While the efforts could minimize the overall costs, they disregard the fact that these costs aren’t uniformly distributed over irregular fields. The cost of a non-productive machine pro... M. Spekken, J.P. Molin, T.L. Romanelli, M.N. Ferraz

146. NIR Spectroscopy to Map Quality Parameters of Sugarcane

Precision Agriculture aims to explore the potential of each crop considering the differences within the field. One information that is considered the most important is the yield or the obtained income in the field. However, in the case of sugarcane, quality will also directly influence farmer’s income. Several studies suggest harvester automation aiming to monitor yield, but few consider the quality analysis in the process. Among the existing methods for measuring sugar content the one ... M.N. Ferraz, J.P. Molin

147. A Multi Sensor Data Fusion Approach for Creating Variable Depth Tillage Zones.

Efficiency of tillage depends largely on the nature of the field, soil type, spatial distribution of soil properties and the correct setting of the tillage implement.  However, current tillage practice is often implemented without full understanding of machine design and capability leading to lowered efficiency and further potential damage to the soil structure. By modifying the physical properties of soil only where the tillage is needed for optimum crop growth, variable depth tillage (... D. Whattoff, D. Mouazen, D. Waine

148. Considering Farmers' Situated Expertise in AgriDSS Development to Fostering Sustainable Farming Practices in Precision Agriculture

Agriculture is facing immense challenges and sustainable intensification has been presented as a way forward where precision agriculture (PA) plays an important role. More sustainable agriculture needs farmers who embrace situated expertise and can handle changing farming systems. Many agricultural decision support systems (AgriDSS) have been developed to support farm management, but the traditional approach to AgriDSS development is mostly based on knowledge transfer. This has resulted in te... C. Lundström, J. Lindblom

149. Proximal Sensing of Leaf Temperature and Microclimatic Variables to Implement Precision Irrigation in Almond and Grape Crops

Irrigation decisions based on traditional soil moisture sensing often leads to uncertainty regarding the true amount of water available to the plant. Plant based sensing of water stress decreases this uncertainty. In specialty crops grown in California’s Central Valley, precision deficit irrigation based on plant water stress could be used to decrease water use and increase water use efficiency by supplying the necessary quantity of water only when it is needed by the plant. However, th... E. Kizer, S.K. Upadhyaya, F. Rojo, S. Ozmen, C. Ko-madden, Q. Zhang

150. Mapping Spatial Production Stability in Integrated Crop and Pasture Systems: Towards Zonal Management That Accounts for Both Yield and Livestock-landscape Interactions.

Precision farming technologies are now widely applied within Australian cropping systems. However, the use of spatial monitoring technologies to investigate livestock and pasture interactions in mixed farming systems remains largely unexplored. Spatio-temporal patterns of grain yield and pasture biomass production were monitored over a four-year period on two Australian mixed farms, one in the south-west of Western Australia and the other in south-east Australia. A production stability index ... P. Mcentee, S. Bennett, M. Trotter, R. Belford, J. Harper

151. Comparing Adapt-N to Static N Recommendation Approaches for US Maize Production

Large temporal and spatial variability in soil N availability leads many farmers across the US to over apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses.  Static N recommendation tools are typically promoted in the US, but new dynamic model-based tools allow for more precise and adaptive N recommendations that account for specific production environments and conditions. This study compares two static N recommendation tools... H. Van es, S. Sela, R. Marjerison, B. Moebiu-clune, R. Schindelbeck, D. Moebius-clune

152. 'Spatial Discontinuity Analysis' a Novel Geostatistical Algorithm for On-farm Experimentation

Traditional agronomic experimentation is restricted to small plots. Under appropriate experimental designs the effects of uncontrolled environmental variables are minimized and the measured responses (e.g. in yields) are compared to controllable inputs (seed, tillage, fertilizer, pesticides) using well-trusted design-based statistical methods. However, the implementation of such experiments can be complex and the application, management, and harvesting of treated areas might have to... S. Rudolph, B.P. Marchant, V. Gillingham, D. Kindred, R. Sylvester-bradley

153. Surplus Science and a Non-linear Model for the Development of Precision Agriculture Technology

The advent of ‘big data technologies’ such as hyperspectral imaging means that Precision Agriculture (PA) developers now have access to superabundant and highly  heterogeneous data.  The authors explore the limitations of the classic science model in this situation and propose a new non-linear process that is not based on the premise of controlled data scarcity. The study followed a science team tasked with developing highly advanced hyperspectral techniques for a &lsquo... M.Z. Cushnahan, I.J. Yule, B.A. Wood, R. Wilson

154. Proximal Hyperspectral Sensing in Plant Breeding

The use of remote sensing in plant breeding is challenging due to the large number of small parcels which at least actually cannot be measured with conventional techniques like air- or spaceborne sensors. On the one hand crop monitoring needs to be performed frequently, which demands reliable data availability. On the other hand hyperspectral remote sensing offers new methods for the detection of vegetation parameters in crop production, especially since methods for safe and efficient detecti... H. Lilienthal, P. Wilde, E. Schnug

155. Data Normalization Methods for Definition of Management Zones

The use of management zones is considered a viable economic alternative for the management of crops due to low cost of adoption as well as economic and environmental benefits. The decision whether or not to normalize the attributes before the grouping process (independent of use) is a problem of methodology, because the attributes have different metric size units, and may influence the result of the clustering process. Thus, the aim of this study was to use a Fuzzy C-Means algorithm to evalua... K. Schenatto, E.G. De souza, C.L. Bazzi, A. Gavioli, N.M. Betzek, H.M. Beneduzzi

156. EZZone - An Online Tool for Delineating Management Zones

Management zones are a pillar of Precision Agriculture research.  Spatial variability is apparent in all fields, and assessing this variability through measurement devices can lead to better management decisions.  The use of Geographic Information Systems for agricultural management is common, especially with management zones.  Although many algorithms have been produced in research settings, no online software for management zone delineation exists.  This research used a ... G. Vellidis, C. Lowrance, S. Fountas, V. Liakos

157. Non-destructive Plant Phenotyping Using a Mobile Hyperspectral System to Assist Breeding Research: First Results

Hybrid plants feature a stronger vigor, an increased yield and a better environmental adaptability than their parents, also known as heterosis effect. Heterosis of winter oilseed rape is not yet fully understood and conclusions on hybrid performance can only be drawn from laborious test crossings. Large scale field phenotyping may alleviate this process in plant breeding. The aim of this study was to test a low-cost mobile ground-based hyperspectral system for breeding research to e... H. Gerighausen, H. Lilienthal, E. Schnug

158. Estimation of Soil Profile Properties Using a VIS-NIR-EC-force Probe

Combining data collected in-field from multiple soil sensors has the potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate many important soil properties, such as soil carbon, water content, and texture. Other common soil sensors include penetrometers that measure soil strength and apparent electrical conductivity (ECa) sensors. Previous field research has related those sensor measuremen... Y. Cho, K.A. Sudduth

159. Smart Agriculture: A Futuristic Vision of Application of the Internet of Things (IoT) in Brazilian Agriculture

With the economy based on agribusiness, Brazil is an important representative on the world stage in agricultural production, either in terms of quantity or cultivated diversity due to a scenario with vast arable land and favorable climate. There are many crops that are adapteble to soils of the country. Despite the global representation, it is known that the Brazilian agricultural production does not yet have a modern agriculture by restricting the use of new technologies to farmers with bett... C.L. Bazzi, R. Araujo, E.G. Souza, K. Schenatto, A. Gavioli, N.M. Betzek

160. Laboratory Evaluation of Two VNIR Optical Sensor Designs for Vertical Soil Sensing

Visible and near infrared reflectance spectroscopy (VNIR) is becoming an extensively researched technology to predict soil properties such as soil organic carbon, inorganic carbon, total nitrogen, moisture  for precision agriculture. Due to its rapid, non-destructive nature and ability to infer multiple soil properties simultaneously, engineers have been trying to develop proximal sensors based on the VNIR technology to enable horizontal soil sensing and mapping. Since the vertical varia... N. Wijewardane, Y. Ge

161. Analysis of High Yield Condition Using a Rice Yield Predictive Model

Rice production in Japan is facing problems of yield and quality instability owing to recent climate changes and a decline in rice prices, and possible competition with foreign inexpensive rice. Thus, it is becoming more important to stably achieve high yield and quality, while reducing production costs. Various data, including crop growth, farmer’s management styles, yield and quality, has recently become accessible in actual fields using advanced information and communication technolo... Y. Hirai, T. Yamakawa, E. Inoue, T. Okayasu, M. Mitsuoka

162. Development of Micro-tractor-based Measurement Device of Soil Organic Matter Using On-the-go Visual-near Infrared Spectroscopy in Paddy Fields of South China

Soil organic matter (SOM) is an essential soil property for assessing the fertility of paddy soils in South China. In this study, a set of micro-tractor-based on-the-go device was developed and integrated to measure in-situ soil visible and near infrared (VIS–NIR) spectroscopy and estimate SOM content. This micro-tractor-based on-the-go device is composed of a micro-tractor with toothed-caterpillar band, a USB2000+ VIS–NIR spectroscopy detector, a self-customized steel plow and a ... Z. Lianqing, S. Zhou, C. Songchao, Y. Yafei

163. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the Netherlands

Precision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traff... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten

164. Development of a Sensing Device for Detecting Defoliation in Soybean

Estimating defoliation by insects in an agricultural field, specifically soybean, is performed by manually removing multiple leaf samples, visually inspecting the leaves for feeding, and assigning a value representing a “best guess” at the level of leaf material missing. These estimates can require considerable time and are subjective. The goal of this study was to design a low-cost system containing light sensors and a microcontroller that could remotely record and report long-te... P. Astillo, J. Maja, J. Greene

165. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education

The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby

166. Evaluating low-cost Lidar and Active Optical Sensors for pasture and forage biomass assessment

Accurate and reliable assessment of pasture or forage biomass remains one of the key challenges for grazing industries. Livestock managers require accurate estimates of the grassland biomass available over their farm to enable optimal stocking rate decisions. This paper reports on our investigations into the potential application of affordable Lidar (Light Detection and Ranging) systems and Active Optical (reflectance) Sensors (AOS) to estimate pasture biomass. We evaluated the calibration ac... M. Trotter, K. Andersson, M. Welch, M. Chau, L. Frizzel, D. Schneider

167. Open Data for Food Quality and Food Security Control: a Case Study of the Czech Republic

Food quality and food security is of a high public interest in the European Union. In the Czech Republic, food quality and food security is under control of three different public authorities: the Czech Trade Inspection Authority (CTIA) that is affiliated with the Ministry of Industry and Trade of the Czech Republic, the Czech Agriculture and Food Inspection Authority (CAFIA) that is affiliated with the Ministry of Agriculture of the Czech Republic and the regional network of hygienic station... M. Ulman, M. Stoces, J. Jarolimek, P. Simek

168. Agronomic Characteristics of Green Corn and Correlations with Productivity for the Establishment of Management Zones in Vale Do Ribeira, SP, Brazil

In Brazil, the progressive development in the cultivation of the corn for consumption in the green stadium stands by the relevant socio-economic role that this related to multiple applications, the attractive market price and continuous demand for the product in nature. Therefore, this study was to analyze the correlations and spatial variability of the productivity of the culture of the green corn in winter, in alluvial soil of the type Cambisols eutrophic in the amount areas and Hydromorphi... W.J. Souza, V.S. Akune, S.H. Benez, L.C. Citon, P.H. Nakazawa, A.J. Santana neto

169. North American Soil Test Summary

With the assistance and cooperation of numerous private and public soil testing laboratories, the International Plant Nutrition Institute (IPNI) periodically summarizes soil test levels in North America (NA). Soil tests indicate the relative capacity of soil to provide nutrients to plants. Therefore, this summary can be viewed as an indicator of the nutrient supplying capacity or fertility of soils in NA. This is the eleventh summary completed by IPNI or its predecessor, the Potash ... Q. Rund, S. Murrell, A. Erbe, R. Williams, E. Williams

170. Sensor Based Soil Health Assessment

Quantification and assessment of soil health involves determining how well a soil is performing its biological, chemical, and physical functions relative to its inherent potential. Due to high cost, labor requirements, and soil disturbance, traditional laboratory analyses cannot provide high resolution soil health data. Therefore, sensor-based approaches are important to facilitate cost-effective, site-specific management for soil health. In the Central Claypan Region, visible, near-infrared ... K. Veum, K. Sudduth, N. Kitchen

171. On Farm Studies to Determine Seeding Rate in Corn

Seeding rate (SDR) is one of the most critical production practices impacting productivity and economic return for corn (Zea mays L.) By changing SDRs in different zones within a field, herein termed as site-specific management, better economic results can be produced as the outcome of reducing SDRs in low productivity areas and increasing SDRs under high-yielding environments, relative to the uniform SDR management performed by the producer. The aim of this study was to analyze yield respons... G. Balboa, S. Varela, I. Ciampitti, S. Duncan, T. Maxwell, D. Shoups, A. Sharda

172. Translating Data into Knowledge - Precision Agriculture Database in a Sugarcane Production.

The advent of Information Technology in agriculture, surveying and data collection became a simple task, starting the era of "Big Data" in agricultural production. Currently, a large volume of data and information associated with the plant, soil and climate are collected quick and easily. These factors influence productivity, operating costs, investments and environment impacts. However, a major challenge for this area is the transformation of data and in... G.M. Sanches, O.T. Kolln, H.C. Franco, P.S. Magalhaes, D.G. Duft

173. Soil Attributes Estimation Based on Diffuse Reflectance Spectroscopy and Topographic Variability

The local management of crop areas, which is the basic concept of precision agriculture, is essential for increasing crop yield. In this context, diffuse reflectance spectroscopy (DRS) and digital elevation modelling (DEM) appears as an important technique for determining soil properties, on an adequate scale to agricultural management, enabling faster and less costly evaluations in soil studies. The objective of this work was to evaluate the use of DRS together with topographic parameters fo... J.V. fontenelli, L.R. Amaral, J.M. Demattê, P.G. Magalhães, G. Sanches

174. Integrated Analysis of Multilayer Proximal Soil Sensing Data

Data revealing spatial soil heterogeneity can be obtained in an economically feasible manner using on-the-go proximal soil sensing (PSS) platforms. Gathered georeferenced measurements demonstrate changes related to physical and chemical soil attributes across an agricultural field. However, since many PSS measurements are affected by multiple soil properties to different degrees, it is important to assess soil heterogeneity using a multilayer approach. Thus, analysis of multiple layers of geo... V.I. Adamchuk, N. Dhawale, A. Biswas, S. Lauzon‎, P. Dutilleul

175. Closing Yield Gaps with GxExM and Precision Agriculture

There are many challenges to be faced by agriculture if the global population of nine billion people projected for 2050 is to be fed and clothed, especially given the effects of changing climate.  A focus on the interactions of genetics x environment x management (GxExM) offers potential for meeting the yield, and environment and economic sustainability goals that are integral to these challenges.  The yield gap –defined as the difference between current farmer yields and pote... C. Walthall, J. Hatfield, S. Schneider, M. Vigil

176. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane Fields

One important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-m... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco

177. On-the-go Measurements of pH in Tropical Soil

The objective of this study was to assess the performance of a mobile sensor platform with ion-selective antimony electrodes (ISE) to determine pH on-the-go in a Brazilian tropical soil. The field experiments were carried out in a Cambisol in Piracicaba-SP, Brazil. To create pH variability, increasing doses (0, 1, 3, 5, 7 and 9 Mg ha-1) of lime were added on the experimental plots (25 x 10 m) one year before the data acquisitions. To estimate soil pH levels we used a Mobile Sensor ... M.T. Eitelwein, R.G. Trevisan, A.F. Colaço, M.R. Vargas, J.P. Molin

178. Comparing Predictive Performance of Near Infrared Spectroscopy at a Field, Regional, National and Continental Scales by Using Spiking and Data Mining Techniques

The development of accurate visible and near infrared (vis-NIR) spectroscopy calibration models for selected soil properties is a crucial step for variable rate application in precision agriculture. The objective of the present study was to compare the prediction performance of vis-NIR spectroscopy at local, regional, national and continental scales using data mining techniques including spiking. Fresh soil samples collected from farms in the UK, Czech Republic, Germany, Denmark and the Nethe... S.M. Nawar, A.M. Mouazen, D. George, A. Manfield

179. Time Series Study of Soybean Response Based on Adjusted Green Red Index

Four time-lapse cameras, Bushnell Nature View HD Camera (Bushnell, Overland Park, KS) were installed in a soybean field to track the response of soybean plants to solar radiation, air temperature, relative humidity, soil surface temperature, and soil temperature at 5-cm depth. The purpose was to confirm if visible spectroscopy can provide useful data for tracking the condition of crops and, if so, whether game and trail time-lapse cameras can serve as reliable crop sensing and monitoring devi... P.A. Larbi, S. Green

180. A Data Fusion Method for Yield and Soil Sensor Maps

Utilizing yield maps to their full potential has been one of the challenges in precision agriculture.  A key objective for understanding patterns of yield variation is to derive management zones, with the expectation that several years of quality yield data will delineate consistent productivity zones.  The anticipated outcome is a map that shows where soil productive potentials differ.  In spite of the widespread usage of yield monitors, commercial agriculture has found it dif... E. Lund, C. Maxton, T. Lund

181. Precision Farming Basics Manual - a Comprehensive Updated Textbook for Teaching and Extension Efforts

Today precision agricultural technologies are limited by the lack of a workforce that is technology literate, creative, innovative, fully trained in their discipline, able to utilize and interpret information gained from information-age technologies to make smart management decisions, and have the capacity to convert locally collected information into practical solutions. As part of a grant entitled Precision Farming Workforce Development:  Standards, Working Groups, and Experimental Lea... K. Shannon

182. A Content Review of Precision Agriculture Courses Across the US

Knowledge of what precision agriculture (PA) content is currently taught across the United States will help build a better understanding for what PA instructors should incorporate into their classes in the future. The University of Missouri partnered with several universities throughout the nation on a USDA challenge grant. Precision Agriculture faculty from 24 colleges/universities from across the U.S. shared their PA content by sharing their syllabi from 43 different courses. The syllabi we... D. Skouby, L. Schumacher, M. Yost, N.R. Kitchen

183. Knowledge, Skills and Abilities Needed in the Precision Ag Workforce: an Industry Survey

Precision agriculture encompasses a set of related technologies aimed at better utilization of crop inputs, increasing yield and quality, reducing risks, and enabling information flow throughout the crop supply and end-use chains.  The most widely adopted precision practices have been automated systems related to equipment steering and precise input application, such as autoguidance and section controllers.  Once installed, these systems are relatively easy for farmers and their sup... B. Erickson, D.E. Clay, S.A. Clay, S. Fausti

184. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility Study

The fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffus... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki

185. Development of an Airborne Remote Sensing System for Aerial Applicators

An airborne remote sensing system was developed and tested for recording aerial images of field crops, which were analyzed for variations of crop health or pest infestation. The multicomponent system consists of a multi-spectral camera system, a camera control system, and a radiometer for normalizing images. To overcome the difficulties currently associated with correlating imagery data with what is actually occurring on the ground (a process known as ground truthing); a hyperspectral reflect... Y. Lan, Y. Huang, D.E. Martin, W.C. Hoffmann, B.K. Fritz, J.D. López

186. Precision Farming by Means of Remote Sensing.

In order to improve the wine quality a study has been carried out on a vineyard. From two different types of satellite images, 5 products have been obtained and represented in maps. DMC-UK images, with a resolution of 32 meters and QUICK-BIRD images, with a resolution of 0.6 meters have been used. Through the bands of these images, the following products were obtained: the NDVI, with which users find out which zones in their estates have the worst condition; Mean Vegetation State, which is a ... J.L. Casanova, S. Fraile, A. Romo, J. Sanz, C. Moclán

187. Remote Sensing-based Biomass Maps for an Efficient Use of Fertilizers

For decades the main objective of farmers was to get the highest yields from their farmland. Nowadays, quality of agricultural products is becoming more and more important for the largest returns. In addition, the effects on our environment are also becoming important. These put increasing limitations on modern agriculture. So-called site-specific management can optimize the input of, for instance, nutrients and pesticides to the need of the plants. In this study, the objective was to study w... J.G. P.w clevers, K.H. Wijnholds, J.N. Jukema

188. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)

Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching pa... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba

189. Crop Water Stress Mapping for Site Specific Irrigation by Thermal Imagery and Artificial Reference Surfaces

Variable rate irrigation machines or solid set systems have become technically feasible; however, crop water status mapping is necessary as a blueprint to match irrigation quantities to site-specific crop water demands. Remote thermal sensing can provide these maps in sufficient detail and at a timely delivery. In a set of aerial and ground scans at the Hula Valley, Israel, digital crop water stress maps were generated using geo-referenced high- resolution thermal imagery and artificial refer... M. Meron, J. Tsipris, V. Orlov, V. Alchnatis, Y. Cohen

190. Refractive Index Based Brix Measurement System for Sugar and Allied Industries

An attempt has been made to design optimization of Refractormetric based method for the measurement of Brix.  Optimization of various constructional parameters including selection and location of source, prism and detector, position of source, angular position and height of source from prism plane, divergent angle of source, refractive index of prism, size of prism, the location of detector to pick up the optimum reflected light, refractive index of sample, critical angle, choice of suit... M.L. Dongare, B.T. Jadhav, A.D. Shaligram

191. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for s... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli

192. Digital Transformation of Canadian Agri-Food

Agriculture in Canada is on the cusp of a dramatic revolution as a result of the digital transformation of the industry driven by the emergence of tools such as Precision Agri-Food Technologies and the Internet of Things (IoT, a network of interconnected physical devices capable of connecting to the internet). With the expected exponential growth of data from the application of innovative technologies such as IoT by the Canadian Agri-Food industry, Canada has the potential to gain valuable in... K.J. Hand

193. From Data to Decisions - Ag Technologies Provide New Opportunities and Challenges with On-Farm Research

U.S. farmers are challenged to increase crop production while achieving greater resource use efficiency.  The Nebraska On-Farm Research Network (NOFRN), enables farmers to answer critical production, profitability, and sustainability questions with their own fields and equipment. The NOFRN is sponsored by the University of Nebraska – Lincoln Extension and derives from two separate on-farm research efforts, the earliest originating in 1990.  Over the course of the last 29 years... L. Thompson, K. Glewen, N. Mueller, J. Luck

194. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry Harvesting

Wild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the p... K. Esau, Q. Zaman, A. Farooque, A. Schumann

195. Three Years of On-Farm Evaluation of Dynamic Variable Rate Irrigation: What Have We Learned?

This paper will present a dynamic Variable Rate Irrigation System developed by the University of Georgia. The system consists of the EZZone management zone delineation tool, the UGA Smart Sensor Array (UGA SSA) and an irrigation scheduling decision support tool. An experiment was conducted in 2015, 2016 and 2017 in two different peanut fields to evaluate the performance of using the UGA SSA to dynamically schedule Variable Rate Irrigation (VRI). For comparison reasons strips were designed wit... V. Liakos, W. Porter, X. Liang, M. Tucker, A. Mclendon, C. Perry, G. Vellidis

196. Optimal Sensor Placement for Field-Wide Estimation of Soil Moisture

Soil moisture is one of the most important parameters in precision agriculture. While techniques such as remote sensing seems appropriate for moisture monitoring over large areas, they generally do not offer sufficiently fine resolution for precision work, and there are time restrictions on when the data is available. Moreover, while it is possible to get high resolution-on demand data, but the costs are often prohibitive for most developing countries. Direct ground level measuremen... H. Pourshamsaei, A. Nobakhti

197. A Case Study Comparing Machine Learning and Vegetation Indices for Assessing Corn Nitrogen Status in an Agricultural Field in Minnesota

Compact hyperspectral sensors compatible with UAV platforms are becoming more readily available. These sensors provide reflectance in narrow spectral bands while covering a wide range of the electromagnetic spectrum. However, because of the narrow spectral bands and wide spectral range, hyperspectral data analysis can benefit greatly from data mining and machine learning techniques to leverage its power. In this study, rainfed corn was grown during the 2017 growing season using four nitrogen ... A. Laacouri, T. Nigon, D. Mulla, C. Yang

198. Weed Detection Among Crops by Convolutional Neural Networks with Sliding Windows

One of the primary objectives in the field of precision agriculture is weed detection. Detecting and expunging weeds in the initial stages of crop growth with deep learning technique can minimize the usage of herbicides and maximize the crop yield for the farmers. This paper proposes a sliding window approach for the detection of weed regions using convolutional neural networks. The proposed approach involves two processes: (1) Image extraction and labelling, (2) building and training our neu... K. Kantipudi, C. Lai, C. Min, R.C. Chiang

199. Changing the Cost of Farming: New Tools for Precision Farming

Accurate prescription maps are essential for effective variable rate fertilizer application.  Grid soil sampling has most frequently been used to develop these prescription maps.  Past research has indicated several technical and economic limitations associated with this approach.  There is a need to keep the number of samples to a minimum while still allowing a reasonable level of map quality.  As can be seen, precision agriculture managemen... P. Nagel, K. Fleming

200. On-Farm Digital Solutions and Their Associated Value to North American Farmers

Digital tools and data collection have become standard in a wide variety of present day agricultural operations. An array of digital tools, such as high resolution operational mapping, remote sensing, and farm management software offer solutions to many of the problems in modern agriculture. These technologies and services can, if implemented correctly, provide both immediate and long term agronomic value. A growing number of producers in Ohio and around North America question the proper meth... R. Colley iii, J. Fulton, N. Douridas, K. Port

201. An Efficient Data Warehouse for Crop Yield Prediction

Nowadays, precision agriculture combined with modern information and communications technologies, is becoming more common in agricultural activities such as automated irrigation systems, precision planting, variable rate applications of nutrients and pesticides, and agricultural decision support systems. In the latter, crop management data analysis, based on machine learning and data mining, focuses mainly on how to efficiently forecast and improve crop yield. In recent years, raw and semi-pr... V.M. Ngo, N. Le-khac, M. Kechadi

202. Learn, Share, Connect and Be Inspired: How One Farming Group in Australia is Driving PA Adoption

The use of Precision Agriculture (PA) technologies and techniques continues to expand in Australia. The Society of Precision Agriculture Australia (SPAA) has been instrumental in driving the adoption and development of these techniques to support industry and Australian farming communities. SPAA supports innovation, and innovation includes people. Founded in 2002, SPAA, a not for profit extension body, is Australia’s only dedicated farming group communicating and advocating fo... N.F. Dimos, J.K. Koch

203. Utilizing GPS Technology and Science to Improve Digital Literacy Among Students in Australia and the United States of America

A key issue facing regional, rural and remote communities, in both Australia and the United States of America (USA), is the low level of digital literacy among some cohorts of students. This is particularly the case for students involved in agricultural studies where it is commonly perceived that digital literacy is not relevant to their future occupation. However, this perception is far from the truth, as the reality of farming today means students who intend on entering the agricultural wor... C.W. Knight, A. Cosby, M. Trotter

204. Reverse Modelling of Yield-Influencing Soil Variables in Case of Few Soil Data

Our hypothesis was that simple models can be applied to predict yield by using only those yield data which spatially coincide with the soil data and the remaining yield data and the models can be used to test different sampling and interpolation approaches commonly applied in precision agriculture and to better predict soil variables at not observed locations. Three strategies for composite sample collection were compared in our study. Point samples were taken 1.) along lines within homogenou... I. Sisák, A. Benő, K. Szabó, M. Kocsis, J. Abonyi

205. AgDataBox – API (Application Programming Interface)

E-agricultural is an emerging field focusing in the enhancement of agriculture and rural development through improve in information and data processing. The data-intensive characteristic of these domains is evidenced by the great variety of data to be processed and analyzed. Countrywide estimates rely on maps, spectral images from satellites, and tables with rows for states, regions, municipalities, or farmers. Precision agriculture (PA) relies on maps of within field variability of soil and ... C.L. Bazzi, E.P. Jasse, E.G. Souza, P.S. Magalhães, G.K. Michelon, K. Schenatto, A. Gavioli

206. Accelerating Precision Agriculture to Decision Agriculture: Enabling Digital Agriculture in Australia

For more than two decades, the success of Australia’s agricultural and rural sectors has been supported by the work of the Rural Research and Development Corporations (RDCs). The RDCs are funded by industry and government. For the first time, all fifteen of Australia’s RDC’s have joined forces with the Australian government to design a solution for the use of big data in Australian agriculture. This is the first known example of a nationwide approach for the digital transfor... J. Trindall, R. Rainbow

207. Optimized Soil Sampling Location in Management Zones Based on Apparent Electrical Conductivity and Landscape Attributes

One of the limiting factors to characterize the soil spatial variability is the need for a dense soil sampling, which prevents the mapping due to the high demand of time and costs. A technique that minimizes the number of samples needed is the use of maps that have prior information on the spatial variability of the soil, allowing the identification of representative sampling points in the field. Management Zones (MZs), a sub-area delineated in the field, where there is relative homogeneity i... G.K. Michelon, G.M. Sanches, I.Q. Valente, C.L. Bazzi, P.L. De menezes, L.R. Amaral, P.G. Magalhaes

208. Optimal Placement of Proximal Sensors for Precision Irrigation in Tree Crops

In agriculture, use of sensors and controllers to apply only the quantity of water required, where and when it is needed (i.e., precision irrigation), is growing in importance. The goal of this study was to generate relatively homogeneous management zones and determine optimal placement of just a few sensors within each management zone so that reliable estimation of plant water status could be obtained to implement precision irrigation in a 2.0 ha almond orchard located in California, USA. Fi... C.L. Bazzi, K. Schenatto, S. Upadhyaya, F. Rojo

209. Prediction of Corn Economic Optimum Nitrogen Rate in Argentina

Static (i.e. texture and soil depth) and dynamic (i.e. soil water, temperature) factors play a role in determining field or subfield economically optimal N rates (EONR). We used 50 nitrogen (N) trials from Argentina at contrasting landscape positions and soil types, various soil-crop measurements from 2012 to 2017, and statistical techniques to address the following objectives: a) characterize corn yield and EONR variability across a multi-landscape-year study in central west Buenos Aire... L. Puntel, A. Pagani, S. Archontoulis

210. Field Test of a Satellite-Based Model for Irrigation Scheduling in Cotton

Cotton irrigation in Israel began in the mid-1950s. It is based on an irrigation protocol developed over dozens of years of cotton farming in Israel, and proved to provide among the world's best cotton yield results. In this experiment, we examined the use of an irrigation recommendation system that is based on satellite imagery and hyper-local meteorological data, "Manna treatment", compared to the common irrigation protocols in Israel, which use a crop coefficient (Kc) table a... O. Beeri, S. May-tal, J. Raz, R. Rud

211. Variable Selection and Data Clustering Methods for Agricultural Management Zones Delineation

Delineation of agricultural management zones (MZs) is the delimitation, within a field, of a number of sub-areas with high internal similarity in the topographic, soil and/or crop characteristics. This approach can contribute significantly to enable precision agriculture (PA) benefits for a larger number of producers, mainly due to the possibility of reducing costs related to the field management. Two fundamental tasks for the delineation of MZs are the variable selection and the cluster anal... A. Gavioli, E.G. Souza, C.L. Bazzi, N.M. Betzek, K. Schenatto

212. Creating Thematic Maps and Management Zones for Agriculture Fields

Thematic maps (TMs) are maps that represent not only the land but also a topic associated with it, and they aim to inform through graphic symbols where a specific geographical phenomenon occurs. Development of TMs is linked to data collection, analysis, interpretation, and representation of the information on a map, facilitating the identification of similarities, and enabling the visualization of spatial correlations. Important issues associated with the creation of TMs are: selection of the... E. Souza, K. Schenatto, C. Bazzi

213. Pest Detection on UAV Imagery Using a Deep Convolutional Neural Network

Presently, precision agriculture uses remote sensing for the mapping of crop biophysical parameters with vegetation indices in order to detect problematic areas, and then send a human specialist for a targeted field investigation. The same principle is applied for the use of UAVs in precision agriculture, but with finer spatial resolutions. Vegetation mapping with UAVs requires the mosaicking of several images, which results in significant geometric and radiometric problems. Furthermore, even... Y. Bouroubi, P. Bugnet, T. Nguyen-xuan, C. Bélec, L. Longchamps, P. Vigneault, C. Gosselin

214. Data Power: Understanding the Impacts of Precision Agriculture on Social Relations

Precision agriculture has been greatly promoted for the potential of these technologies to sustainably intensify food production through increasing yields and profits, decreasing the environmental impacts of production, and improving food safety and transparency in the food system through the data collected by precision agriculture technologies.  However, little attention has been given to the potential of these technologies to impact social relations within the agricultural industry.&nb... E. Duncan, E. Fraser

215. 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

216. Field Grown Apple Nursery Tree Plant Counting Based on Small UAS Imagery Derived Elevation Maps

In recent years, growers in the state are transitioning to new high yielding, pest and disease resistant cultivars. Such transition has created high demand for new tree fruit cultivars. Nursery growers have committed their incoming production of the next few years to meet such high demands. Though an opportunity, tree fruit nursery growers must grow and keep the pre-sold quantity of plants to supply the amount promised to the customers. Moreover, to keep the production economical amidst risin... M. Martello, J.J. Quirós, L. Khot

217. Optimising Nitrogen Use in Cereal Crops Using Site-Specific Management Classes and Crop Reflectance Sensors

The relative cost of Nitrogen (N) fertilisers in a cropping input budget, the 33% Nitrogen use efficiency (NUE) seen in global cereal grain production and the potential environmental costs of over-application are leading to changes in the application rates and timing of N fertiliser. Precision agriculture (PA) provides tools for producers to achieve greater synchrony between N supply and crop N demand. To help achieve these goals this research has explored the use of management classes derive... B. Whelan, M. Fajardo

218. AgronomoBot: A Smart Answering Chatbot Applied to Agricultural Sensor Networks

Mobile devices advanced adoption has fostered the creation of various messaging applications providing convenience and practicality in general communication. In this sense, new technologies arise bringing automatic, continuous and intelligent features for communication through messaging applications by using web robots, also called Chatbots. Those are computer programs that simulate a real conversation between humans to answer questions or do tasks, giving the impression that the person is ta... G.M. Mostaço, L.B. Campos, C.E. Cugnasca, I.R. Souza

219. Improving the Precision of Maize Nitrogen Management Using Crop Growth Model in Northeast China

The objective of this project was to evaluate the ability of the CERES-Maize crop growth model to simulate grain yield response to plant density and N rate for two soil types in Northeast China, with the long-term goal of using the model to identify the optimum plant density and N fertilizer rate forspecific site-years. Nitrogen experiments with six N rates, three plant densities and two soil types were conducted from 2015 to 2017 in Lishu county, Jilin Province in Northeast China. The CERES-... X. Wang, Y. Miao, W.D. Batchelor, R. Dong, D.J. Mulla

220. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water f... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

221. Precision Irrigation Management Through Conjunctive Use of Treated Wastewater and Groundwater in Oman

Agriculture under arid environment is always become a challenge due to water scarcity and salinity problems.  With average rainfall of 100 mm, agriculture in Oman is limited due to the arid climate and limited arable lands. More than 50 percent of the arable lands are located in the 300 km northern coastal belt of Al-Batinah region. In addition, country is facing severe problem of sea water intrusion into the groundwater aquifers due to undisciplined excessive groundwater (GW) abstractio... H. Jayasuriya, A. Al-busaidi, M. Ahmed

222. Shared Protocols and Data Template in Agronomic Trials

Due to the overlap of many disciplines and the availability of novel technologies, modern agriculture has become a wide, interdisciplinary endeavor, especially in Precision Agriculture. The adoption of a standard format for reporting field experiments can help researchers to focus on the data rather than on re-formatting and understanding the structure of the data. This paper describes how a European consortium plans to: i) create a “handbook” of protocols for reporting definition... D. Cammarano, D. Drexler, P. Hinsinger, P. Martre, X. Draye, A. Sessitsch, N. Pecchioni, J. Cooper, W. Helga, A. Voicu

223. Improving the Use of Artificial Neural Networks for 
Site-Specific Nitrogen Fertilization

For the planning of site-specific nitrogen fertilization, adequate decision rules are needed. Prerequisite for site specific nitrogen fertilization is the site specific forecast of yield. For this the use of artificial neural networks (ANN) has proven particularly interesting. Therefore, ANN based small-scale yield forecasts are realized in order to deviate the economic optimum of fertilization. The basis of yield forecasts with ANN are different site-specific input variables that have presum... J.S. Hauser, P. Wagner

224. Data Clustering Tools for Understanding Spatial Heterogeneity in Crop Production by Integrating Proximal Soil Sensing and Remote Sensing Data

Remote sensing (RS) and proximal soil sensing (PSS) technologies offer an advanced array of methods for obtaining soil property information and determining soil variability for precision agriculture. A large amount of data collected using these sensors may provide essential information for precision or site-specific management in a production field. In this paper, we introduced a new clustering technique was introduced and compared with existing clustering tools for determining relatively hom... M. Saifuzzaman, V.I. Adamchuk, H. Huang, W. Ji, N. Rabe, A. Biswas

225. Harness the Power of the Internet to Improve Yield

It’s rare to find a fertile farm or ranch that has complete cellular coverage across the entirety of its property. Because networking options like Wi-Fi are limited by restricted infrastructure in these areas, maintaining a reliable flow of connectivity is difficult. Yet, even if consistent cellular coverage is available, it’s frequently cost prohibitive for farm monitoring. Similarly, alternate wireless devices that require batteries aren’t practical because of high mainten... M. Finegan, D. Wallace

226. Overview and Value of Digital Technologies for North American Soybean Producers

In the current state of digital agriculture, many digital technologies and services are offered to assist North American soybean producers.  Opportunities for capturing and analyzing information related to soybean production methods are made available through the adoption of these technologies.  However, often it is difficult for producers to know which digital tools and services are available to them or understand the value they can provide.  The objective of th... J. Lee, J. Fulton, K. Port, R. Colley iii

227. Tracking Two Decades of Precision Agriculture Through the Croplife Purdue Survey

The CropLife/Purdue University precision dealer survey is the longest-running continuous survey of precision farming adoption.  The 2017 survey is the 18th, conducted every year from 1997 to 2009, and then every other year following.  For individuals working in agriculture there is great value in knowing who is doing what and why, to get a better understanding of the utilities and applications, and to guide investments.  A major revision in survey questions was m... B. Erickson, J. Lowenberg-deboer, J. Bradford

228. Data-Driven Agricultural Machinery Activity Anomaly Detection and Classification

In modern agriculture, machinery has become the one of the necessities in providing safe, effective and economical farming operations and logistics. In a typical farming operation, different machines perform different tasks, and sometimes are used together for collaborative work. In such cases, different machines are associated with representative activity patterns, for example, in a harvest scenario, combines move through a field following regular swaths while grain carts follow irregular pa... Y. Wang, A. Balmos, J. Krogmeier, D. Buckmaster

229. ADAPT: A Rosetta Stone for Agricultural Data

Modern farming requires increasing amounts of data exchange among hardware and software systems. Precision agriculture technologies were meant to enable growers to have information at their fingertips to keep accurate farm records (and calculate production costs), improve decision-making and promote effi­cien­cies in crop management, enable greater traceability, and so forth. The attainment of these goals has been limited by the plethora of proprietary, incompatible data formats among... D.D. Danford, K.J. Nelson, S.T. Rhea, M.W. Stelford, R. Ferreyra, J.A. Wilson, B.E. Craker

230. Exploring Wireless Sensor Network Technology in Sustainable Okra Garden: A Comparative Analysis of Okra Grown in Different Fertilizer Treatments

The goal of this project was to explore commercial agricultural and irrigation sensor kits and to discern if the commercial wireless sensor network (WSN) is a viable tool for providing accurate real-time farm data at the nexus of food energy and water. The smart garden consists of two different varieties of Abelmoschus esculentus (okra) planted in raised beds, each grown under two different fertilizer treatments. Soil watermark sensors were programed to evaluate soil moisture and dictate irri... L. Burton, K. Jayachandran, S. Bhansali, Y. Mekonnen, A. Sarwat

231. Development of an Online Decision-Support Infrastructure for Optimized Fertilizer Management

Determination of an optimum fertilizer application rate involves various influential factors, such as past management, soil characteristics, weather, commodity prices, cost of input materials and risk preference. Spatial and temporal variations in these factors constitute sources of uncertainties in selecting the most profitableapplication rate. Therefore, a decision support system (DSS) that could help to minimize production risks in the context of uncertain crop performance is needed. ... S. Shinde, V. Adamchuk, R. Lacroix, N. Tremblay, Y. Bouroubi

232. Precision Agriculture: A Paradigm Shift for Espousal of Advanced Farming Practices Among Progressive Farmers in Punjab –Pakistan

Precision agriculture provides innovative farm information tools for improved decision making regarding crop growth and yield. Creating awareness for future applications of precision agriculture among progressive farmers in Pakistan was an instrumental force to conduct this study. The purpose was to appraise the awareness level of the respondents for applications of precision agriculture in the field. The objectives such as assessing the awareness level, available information sources, future ... E. Ashraf, H.K. Shurjeel, R. Rasheed

233. Analyzing Trends for Agricultural Decision Support System Using Twitter Data

The trends and reactions of the general public towards global events can be analyzed using data from social platforms, including Twitter. The number of tweets has been reported to help detect variations in communication traffic within subsets like countries, age groups and industries. Similarly, publicly accessible data and (in particular) data from social media about agricultural issues provide a great opportunity for obtaining instantaneous snapshots of farmers’ opinions and a method ... S. Jha, D. Saraswat, M.D. Ward

234. Survey of Pesticide Application Practices and Technologies in Georgia Agricultural Crops

Georgia is a leading producer of numerous crops including cotton, peanut, blueberries, pecans, bell peppers, cabbage, watermelons, and peaches in the United States. Pesticide applications are critical for the successful production of these crops. Pesticide regulations and application technologies are changing rapidly due to growing concerns around off-target movement and increased focus on improving the efficiency and efficacy of pesticide applications. In order to provide suitable ... S.S. Virk, E.P. Prostko

235. Evaluation of Indwelling Rumen Temperature Monitoring System for Dairy Calf Illness Detection and Management

Precision Dairy Farming technology has mostly focused on tools to improve cow care, but new tools are available to improve the care of pre-wean calves and heifers. These technologies apply real-time monitoring to measure individual animal data and detect a deviation from normal. On-farm validation of new technologies remains important for successful deployment of new technologies within commercial farms to understand how the technology can improve dairy calf welfare, performance, and health. ... J.M. Hartschuh, J.P. Fulton, S.A. Shearer, B.D. Enger, G.M. Schuenemann

236. Precision Agriculture Education in Africa: Perceptions, Opportunities and Challenges, and the Way Forward

Precision Agriculture is critical for accelerated transformation of the agrifood systems in Africa for shared prosperity and enhanced livelihoods. The paper presents an overview of the perceptions of faculty, undergraduate and postgraduate students from Ghanaian universities about PA education, and its opportunities and challenges. The study involves a case study of two public universities, the University of Cape Coast and the Technical University of Cape Coast, respectively a and a desk revi... K.A. Frimpong

237. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in Argentina

The lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomis... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito

238. Teaching Mathematics Towards Precision Agriculture Through Data Analysis and Models

Precision agriculture is used in a wide variety of field operations and agricultural practices that affect our daily lives. Many fields of agriculture are increasingly adopting equipment automation, robotics, and machine learning techniques. These all lead to recognize that data collection and exploitation is a valuable tool assisting in real-time farming and livestock decisions. Thus, the immediate need to empower students in Agriculture Sciences with mathematical tools using data analysis i... R. Sviercoski

239. Automatic Body Condition Score Classification System for Individual Beef Cattle Using Computer Vision

Body condition scoring (BCS) is a widely used parameter for assessing the utilization of energy reserves in the fat and muscle of cattle. It fulfills the needs of animal welfare and precision livestock farming by enabling effective monitoring of individual animals. It serves as a crucial parameter for optimizing nutrition, reproductive performance, overall health, and economic outcomes in beef cattle. The precise and consistent assessment of BCS relies on personal experience using visuals tha... M. Islam, J. Yoder, H. Gan

240. Improving Site-specific Nutrient Management in the Southeastern US: Variable-rate Fertilization Based on Yield Goal by Management Zone

Site-specific nutrient management is a critical aspect of row crop production, especially when aiming to achieve improved yields in the highly variable fields in the Southeastern United States. Variable-rate (VR) fertilizer application is a common practice to implement site-specific nutrient management and relies heavily on the use of precision soil sampling methods (grid or zone) to obtain accurate information on spatial nutrient variability within the fields. Most fields in the southeastern... S. Virk, T. Colley, C. Kamerer, G. Harris, D. Beasley

241. Assessing Crop Yield and Profitability with Site-specific Seed Rate Management in Corn and Soybean Cropping Systems

Integrating the information about soil and topographic properties for variable rate seeding is a prerequisite for improved crop production and thus profit. However, limited studies have explored the geospatial and machine learning approaches to understand factors influencing crop yield and profit under site-specific seed rate management. The objectives of this study were to: a) observe the effect of variable seeding rate based on soil and topographic properties on soybean and corn grain ... J. Neupane, N. Joshi, J.P. Fulton, S. Khanal, A. B k, B. Bhattarai

242. Hierarchical Zoning: Targeted Sampling for Soil Attribute Mapping

The mapping of soil attributes for fertilizer recommendation remains challenging in precision agriculture. Traditionally, this mapping is done through soil sampling in a regular grid, which generally yields good results when done in denser grids. However, due to the high costs associated with sampling and analysis, sparser grids have been adopted, which has not produced good prediction results. Some studies with directed sampling points to obtain more accurate soil maps have been adopted to a... D.D. Melo, I.A. Da cunha, T.L. Brasco, H. Oldoni, L.R. Amaral

243. Prescription Map Creation for Optimal Variable-rate Seeding in Arkansas Fields

Soybean seeding rate selection in Arkansas depends on cultivar, planting date, and soil characteristics. Guidelines were developed to maximize profitability from whole field management and little information is available to optimize smaller-scale management. Nevertheless, Arkansas cropland is expected to be a good candidate for variable-rate seeding (VRS) because of heterogeneous soil parent materials, large field sizes, and added spatial variability introduced by the normalization of land-le... W. France, A. Poncet, U. Sigdel, J. Ross

244. Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur Management

The ongoing decline in sulfur (S) atmospheric depositions and high yield crop production have resulted in S deficiency and the need for S fertilizer applications in corn cropping systems. Many farmers are applying S fertilizers uniformly across their fields. Little has been reported on the within-field spatial variability in optimal S rates and the potential benefits of variable rate S applications. The objectives of this study were to 1) assess within-field variability of optimal S rates (OS... R.P. Negrini, Y. Miao, K. Mizuta, K. Stueve, D. Kaiser, J.A. Coulter

245. Using Soil Samples and Soil Sensors to Improve Soil Nutrient Estimations

Estimating soil nutrient levels, especially immobile nutrients like P and K, has been a primary activity for providers of precision agriculture services.  Soil nutrients often vary widely within fields and growers have been eager to manage them site-specifically.  There are many causes of the variability, including pedogenic factors such as soil texture, organic matter, landscape position and other factors that have resulted in an accumulation of unused nutrients in some areas of th... C.R. Maxton, T. Lund, E. Lund

246. On-farm Evaluation of the Potential Benefits of Variable Rate Seeding for Corn in Minnesota

Many farmers in Minnesota are interested in adopting variable rate seeding technology for corn, however, little has been reported about their potential benefits. The objectives of this study were to 1) determine within-field variability of optimal seeding rates, and 2) evaluate the potential benefits of variable rate seeding in commercial corn fields in Minnesota. Four on-farm variable rate seeding trials were conducted in Minnesota in 2022 and 2023, with seeding rates ranging from 31,000 to ... Y. Miao, A. Kechchour, S. Folle, K. Mizuta

247. Site Specific Evaluation of Dynamic Nitrogen Recommendation Tools

Management tools are a potential solution for increased profit and N use efficiency (NUE) in corn production. Most previous studies evaluating these tools used small plot research which does not accurately represent large scale performance and inhibits adoption. Two dynamic model-based N management tools, which were commercially available in 2021 and 2022 (Adapt-N and Granular), were tested at fifteen on-farm research locations in Nebraska. The objective of this study were to evaluate the sit... S. Norquest, L. Puntel, G. Balboa, L. Thompson

248. Sampling-based on Plant Vigor Zones As a Strategy for Creating Soil Attribute Maps

Mapping agronomically relevant soil properties for fertilizer recommendation remains challenging in precision agriculture. Traditionally, this mapping is conducted through soil sampling on a regular grid basis, where points are equally spaced primarily to ensure spatial coverage. However, directing soil sampling points based on plant vigor may be more efficient in capturing soil variability that directly affects plant development. Several commercial platforms offer solutions for defining mana... D.D. Melo, T.L. Brasco, I.A. Da cunha, S.G. Castro, L.R. Amaral

249. Enhancing Phosphorus Nutrient Management in Corn Through Tissue Analysis and Diagnostic Tools

Phosphorus (P) plays a pivotal role in crop growth, and optimizing its application is crucial for sustainable agriculture. This research focuses on advancing nutrient management by precisely evaluating tissue phosphorus concentrations in corn. The study delves into identifying critical P levels during various growth stages, assessing alternative diagnostic tools, and exploring correlations to refine phosphorus nutrition strategies. Across 26 locations in Kansas, field experiments employed a r... G. Roa acosta, D. Ruiz diaz

250. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of Sows

The lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D comp... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre

251. Lameness Detection in Dairy Cattle Using GPS and Accelerometers Wearable Sensors

Lameness significantly impacts cow health and welfare on dairy farms, yet identifying lamecows remains challenging. Wearable sensors like GPS and accelerometers show promise for automated lameness detection, but their effectiveness outdoors is still unclear. Therefore, there are gaps in understanding their applicability and the necessary features for outdoor settings. Additionally, it is uncertain whether environmental factors, such as temperature and time of day, influence their the model pe... N. Mhlongo, H. De knegt, W.F. De boer, F. Van langevelde

252. Optimizing Soil Nutrient Management: Agricultural Policy/environmental Extender (APEX) Model Simulation for Field Scale Phosphorous Loss Reduction in Virginia

Managing soil nutrients is crucial for enhancing crop productivity and meeting consumptions demands while minimizing environmental impacts. Sustainable agriculture relies on well-planned soil nutrient management strategies. Phosphorous (P) stands out among the 16 essential soil nutrients, particularly in Virginia, where natural P levels are typically low. Adequate amount of P is necessary for the early root formation and plant growth. However, excess amount of P in the soil leads to increase ... S. Kumari, J. Rathore, S. Mitra, M. Gardezi, O. Walsh

253. Response of Canola and Wheat to Application of Enhanced Efficiency Nitrogen Fertilizers on Contrasting Management Zones

Investment on nitrogen (N) fertilizers is a major cost of growers, and variable rate (VR) application of N fertilizers could help optimize its usage. In the growing season of 2023, field experiments were conducted at four sites (i.e., Watrous – Saskatchewan SK and two fields in the vicinity of Strathmore, Alberta AB, Canada). The main objectives were to (i) determine performance of Enhanced Efficiency N Fertilizers - EENF (i.e., Coated urea, urea with double inhibitors - DI, urea mixed ... H. Asgedom, G. Hehar, C. Willness, W. Anderson, H. Duddu, P. Mooleki, J. Schoenau, M. Khakbazan, R. Lemke, E. derdall, J. Shang, K. Liu, J. Sulik, E. Karppinen, I. Mbakwe