Proceedings

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Moulin, A
Marshall, J
Miller, C
Morley, T.G
McKay, K
Morata, G
Metcalf, S
Mazzeo, B
Madani, A
Mizuta, K
Menendez III, H
Musetescu, L
Mufradi, I
Meena, R
Maharjan, B
McAvoy, T
Mata-Padrino, D
Mußhoff, O
Maack, D
Mohammad, A.S
M. Rabello, L
Moreira, B
Makarov, J
Maja, J.M
Mi, G
Midtiby, H.S
Mandel, R
Mimić, G
Magalhães, P.S
Manfrini, L
Mangus, D
Musil, M
Morgan, A
Mackenzie, M
MacEachern, C
Jego, G
Goyer, C
Dandrifosse, S
Charvat, K
Regen, C
Dhoubhadel, S
Rainbow, R
Mendes, I
Desai, V
Yi, Z
Sapkota, T.B
Shirley, A
Hedley, M
Welp, G
Serfa Juan, R.O
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Authors
Giselsson, T.M
Jørgensen, R.N
Midtiby, H.S
Ehsani, R
Sankaran, S
Maja, J.M
Neto, J.C
Khan, F.S
Zaman, Q.U
Schumann, A.W
Madani, A
Percival, D.C
Farooque, A.A
Saleem, S.R
Khan, F.S
M. Rabello, L
R. D. Pereira, R
C. Lopes, W
Y. Inamasu, R
V. de Sousa, R
Pattey, E
Jego, G
Tremblay, N
Drury, C
Ma, B
Sansoulet, J
Beaudoin, N
Pullanagari, R
Yule, I
Tuohy, M
Hedley, M
King, W
Dynes, R
Slaeem, S
Zaman, Q.U
Madani, A
Schumann, A
Percival, D
Ahmad, H.N
Farooque, A.A
Khan, F
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Charvat, K
Gnip, P
Charvat, K
Cepicky, J
Gnip, P
Charvat, K
Jezek, J
Musil, M
Krivanek, Z
Gnip, P
Pena-Yewtukhiw, E.M
Mata-Padrino, D
Bryan, W
Mandel, R
Sapkota, T.B
Nayse, S.P
Mohammad, A.S
Dhillon, R
Upadhyaya, S
Roach, J
Crawford, K
Lampinen, B
Metcalf, S
Rojo, F
Büscher, P
Twickler, P
Marquering, D
Müller, M
Maack, D
Sanchez, L.A
Klein, L.J
Claassen, A
Lew, D
Mendez-Costabel, M
Sams, B
Morgan, A
Hinds, N
Hamann, H.F
Dokoozlian, N
Casiano, P.M
Morley, T.G
Sadeque, Z
Wang, X
Hu, Y
Yi, Z
Ciampitti, I.A
Shroyer, K
Prasad, V
Sharda, A
Stamm, M.J
Wang, H
Price, K
Mangus, D
Moulin, A
Moulin, A
Khakbazan, M
Zude-Sasse, M
Regen, C
Käthner, J
Walsh, O.S
Belmont, K
McClintick-Chess, J
Marshall, J
Jackson, C
Thompson, C
Swoboda, K
Lum, C
Dunbabin, M
Shaw-Feather, C
Mackenzie, M
Luker, E
Charvat, K
Reznik, T
Charvat jr., K
Lukas, V
Horakova, S
Kepka, M
Charvat, K
Reznik, T
Lukas, V
Charvat Jr., K
Horakova, S
Splichal, M
Kepka, M
Bonfil, D.J
Mufradi, I
Asido, S
Long, D.S
Bonfil, D.J
Mufradi, I
Asido, S
Long, D.S
Cerri, D.G
Gray, G.R
Magalhães, P.S
Musetescu, L
Gidea, M
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Zebarth, B
Goyer, C
Neupane, S
Li, S
Mills, A
Whitney, S
Cambouris, A
Perron, I
Moulin, A
Khakbazan, M
Khakbazan, M
Moulin, A
Huang, J
Michiels, P
Xie, R
Maharjan, B
Reddy, S
Biradar, D.P
Patil, V.C
Desai, B.L
Nargund, V.B
Patil, P
Desai, V
Tulasigeri, V
Channangi, S.M
John, W
Trindall, J
Rainbow, R
Wang, X
Miao, Y
Xia, T
Dong, R
Mi, G
Mulla, D.J
Dhoubhadel, S
Griffin, T.W
Leenen, M
Pätzold, S
Heggemann, T
Welp, G
Pätzold, S
Heggemann, T
Leenen, M
Koszinski, S
Schmidt, K
Welp, G
Boatswain Jacques, A.A
Adamchuk, V.I
Cloutier, G
Clark, J.J
Miller, C
G, S
Biradar, D.P
Desai, B.L
Patil, V.C
Patil, P
Nargund, V.B
Desai, V
John, W
Channangi, S.M
Tulasigeri, V
Charvat, K
Berzins, R
Bergheim, R
Zadrazil, F
Macura, J
Langovskis, D
Snevajs, H
Kubickova, H
Horakova, S
Charvat Jr., K
Charvat, K
Kepka, M
Berzins, R
Zadrazil, F
Langovskis, D
Musil, M
MacEachern, C
Esau, T
Zaman, Q
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
Sela, S
Graff, N
Mizuta, K
Miao, Y
Hachisuca, A
Souza, E.G
Mercante, E
Sobjak, R
Ganascini, D
Abdala, M
Mendes, I
Bazzi, C
Rodrigues, M
Ortiz, B.V
Lena, B.P
Morlin , F
Morata, G
Duarte de Val, M
Prasad, R
Gamble, A
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Lacerda, L.N
Miao, Y
Mizuta, K
Stueve, K
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Mizuta, K
Zhang, J
Li, D
Ghimire, D
Maharjan, B
Michels, M
Wever, H
Mußhoff, O
Michels, M
Bonke, V
Wever, H
Mußhoff, O
Byers, C
Meena, R
Kichler, J
Kemerait, R.C
Hand, L
Virk, S
Barbosa, M
Duron, D
Rontani, F
Bortolon, G
Moreira, B
Oliveira, L
Setiyono, T
Shiratsuchi, L
Silva, R.P
Holland, K.H
Barbosa, M
Oliveira, L
Tyson, C
Shirley, A
Santos, R
Sales, L
Vargas, R
van Evert, F
Van Oort, P
Maestrini, B
Pronk, A
Boersma, S
Kopanja, M
Mimić, G
Scholz, O
Uhrmann, F
Weule, M
Meyer, T
Gilson, A
Makarov, J
Hansen, J
Henties, T
Alahe, M
Chang, Y
Kemeshi, J.O
Gummi, S
Menendez III, H
Bedwell, E
Lacerda, L
McAvoy, T
Ortiz, B.V
Snider, J
Vellidis, G
Yu, Z
Negrini, R.P
Miao, Y
Mizuta, K
Stueve, K
Kaiser, D
Coulter, J.A
Morales, A.C
Quinn, D.
Mizuta, K
Miao, Y
Miao, Y
Kechchour, A
Sharma, V
Flores, A
Lacerda, L
Mizuta, K
Lu, J
Huang, Y
Miao, Y
Kechchour, A
Folle, S
Mizuta, K
Mizuta, K
Miao, Y
Lu, J
Negrini, R.P
Craven, S
Sandholtz, C
Mazzeo, B
Armstrong, P.R
Pordesimo, L.O
Siliveru, K
Gerken, A.R
Serfa Juan, R.O
Topics
Precision Crop Protection
Precision Horticulture
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Precision A-Z for Practitioners
Profitability, Sustainability, and Adoption
Optimizing Farm-level use of Spatial Technologies
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Education and Training in Precision Agriculture
Precision Nutrient Management
Sensor Application in Managing In-season CropVariability
Precision Dairy and Livestock Management
Precision Horticulture
Engineering Technologies and Advances
Profitability, Sustainability and Adoption
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Spatial Variability in Crop, Soil and Natural Resources
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Precision Nutrient Management
Unmanned Aerial Systems
Standards & Data Stewardship
Precision Agriculture and Climate Change
Precision Management / Precision Conservation
Engineering Technologies
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Profitability and Success Stories in Precision Agriculture
Precision Agriculture and Global Food Security
Applications of Unmanned Aerial Systems
In-Season Nitrogen Management
Robotics, Guidance and Automation
Geospatial Data
Drainage Optimization and Variable Rate Irrigation
Precision Crop Protection
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Nutrient, Lime and Seed Management
Decision Support Systems
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Drivers and Barriers to Adoption of Precision Ag Technologies or Digital Agriculture
Drone Spraying
Artificial Intelligence (AI) in Agriculture
Precision Horticulture
In-Season Nitrogen Management
Robotics and Automation with Row and Horticultural Crops
Site-Specific Pasture Management
Decision Support Systems
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
On Farm Experimentation with Site-Specific Technologies
Wireless Sensor Networks and Farm Connectivity
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results72 paper(s) found.

1. Revising Nitrogen Recommendations For Wheat In Response To The Need For Support Of Variable-rate Nitrogen Application

Sampling studies in North Dakota conducted from 1994 to 2003 showed that variable-rate N application could be practically directed with zone soil sampling. Results from variable-rate N studies using zone soil sampling were often less than rewarding due in part to the use of a whole-field predicted yield-based formula for developing the N recommendation in each zone. Nitrogen rate studies on spring wheat and durum were established in 2005 through 2009 to reexamine N recommendations. The results... D. Franzen, G. Endres, R. Ashley, J. Staricka, J. Lukach, K. Mckay

2. Vision Of Farm Of Tomorrow

... K. Charvat, P. Gnip

3. New Geospatial Technologies For Precision Farming

... K. Charvat, J. Cepicky, P. Gnip

4. Vlite Node – New Sensor Technology For Precision Farming

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

5. Impact Of Winter Grazing On Forage Biomass Topography Soil Strength Spatial Relationships

Spatial relationships between soil properties, forage productivity, and landscape can be used to manage site-specific grazing. Soil penetration resistance and forage biomass were collected for three years in winter grazing experiment. The three ha experimental area was divided into six paddocks, hay was cut twice per year in the months of May and June, and forage stockpiled after the second cutting. Animals were admitted to paddocks at the end of November, at a stocking rate... E.M. Pena-yewtukhiw, D. Mata-padrino, W. Bryan

6. Farmer Perspectives Of Precision Agriculture In Western Australia

Many farmers in the Western Australian wheatbelt have successfully adopted guidance and yield mapping technologies. However they have so far avoided adopting variable rate technology (VRT).  While agronomists and farmers can determine the limiting factors to production, whether it is soil fertility, pH, plant available water capacity (PAWC) or others, they have less confidence in managing spatial variability. Although WA farmers understand the need to adopt these techniques they have... R. Mandel

7. 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 increased... T.B. Sapkota

8. Estimating the Plant Stem Emerging Points (PSEPS) of Sugar Beets at Early Growth Stages

Successful intra-row mechanical weed control of sugar beet (beta vulgaris) in early growth stages requires precise knowledge about location of crop plants. A computer vision system for locating Plant Stem Emerging Point (PSEP) of sugar beet in early growth stages was developed and tested. The system is based on detection of individual leaves; each leaf location is described by center of mass and petiole location. After leaf detection the true PSEP locations were annotated manually and... T.M. Giselsson, R.N. Jørgensen, H.S. Midtiby

9. Affordable Multi-Rotor Remote Sensing Platform for Applications In Precision Horticulture.

Satellite and aerial imaging technologies have been explored for a long time as an extremely useful source of collecting cost-effective data for agricultural applications. In spite of the availability of such technologies, very few growers are using the technology... R. Ehsani, S. Sankaran, J.M. Maja, J.C. Neto

10. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields

  One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan

11. Implementation of a Controller Unit Based on the ISO 11783 Standard for Automatic Measurement of the Electrical Conductivity of the Soil

... L. M. rabello, R. R. d. pereira, W. C. lopes, R. Y. inamasu, R. V. de sousa

12. Performance Evaluation of STICS Crop Model to Simulate Corn Growth Attributes in Response to N Rate and Climate Variations

Improving nitrogen use efficiency in crop plants contributes to increase the sustainability of agriculture. Crop models could be used as a tool to test the impact of climatic conditions on crop growth under several N management practices and to refine N application recommendation and strategy. STICS, a crop growth simulator developed by INRA (France), has the capability to assimilate leaf area index (LAI) from remote sensing to re-initialize input parameters, such as seeding date and seeding... E. Pattey, G. Jego, N. Tremblay, C. Drury, B. Ma, J. Sansoulet, N. Beaudoin

13. Proximal Sensing Tools to Estimate Pasture Quality Parameters.

To date systems for estimating pasture quality have relied on destructive sampling with measurement completed in a laboratory which was very time consuming and expensive. Results were often not received until after the pasture was grazed which defeated the point of the measurement, as farmers required the information to make decisions about grazing strategies to effectively... R. Pullanagari, I. Yule, M. Tuohy, M. Hedley, W. King, . Dynes

14. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields

Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan

15. Application based Wireless Sensor Node for Underground Moisture Sensing for Precision Agriculture

In this paper, we are attempting to examine the WUWSN (wireless underground water sensor node*) for precision agriculture. The development and function of this sensor along with its software application is described in this paper. The equipment is under testing and the laboratory results and interpretations are discussed in this paper. This equipment is based on the new concept of sensing underground soil moisture. The sensor is cost effective sensor and has a long... S.P. Nayse, A.S. Mohammad

16. Modeling Canopy Light Interception For Estimating Yield In Almond And Walnut Trees

A knowledge of spatio-temporal variability in potential yield is essential for site-specific nutrient management in crop production. The objectives of this project were to develop a model for photosynthetically active radiation (PAR) intercepted by almond and walnut trees based on data obtained from respective tree(s) and estimate potential crop yield in individual trees or in blocks of five trees. This project uses proximally sensed PAR interception data measured using a lightbar... R. Dhillon, S. Upadhyaya, J. Roach, K. Crawford, B. lampinen, S. Metcalf, F. Rojo

17. NIRS Sensor Controlled Total-Mixed-Ration For Nutrient Optimized Feeding Of Dairy Cattle

The exact regulation of dry matter, energy and ingredients in fodder rations provides a large advantage in order to optimize an economical animal nutrition. Feed mixer wagons are used to feed Gras and Maize silage together with other components. It can be used in combination with a transponder system for feed concentrate as well as for feeding of a total mixed ration. The online measurement system based on NIR-spectrometric sensors to measure DM-content and other nutrients should... P. Büscher, P. Twickler, D. Marquering, M. Müller, D. Maack

18. 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 microclimate... L.A. Sanchez, L.J. Klein, A. Claassen, D. Lew, M. Mendez-costabel, B. Sams, A. Morgan, N. Hinds, H.F. Hamann, N. Dokoozlian

19. GNSS Positioning Techniques For Agriculture

Broadacre, row crop and high value crops each have different positioning needs.  Within these agricultural groups, individual practices such as mapping, guidance and machine control for tillage, application and harvest each have their own Global Navigation Satellite Systems (GNSS) needs for an optimal price/performance and value equation.  New research and algorithm development by NovAtel has resulted in a significant simplification of positioning methodology with increased... P.M. Casiano, T.G. Morley, Z. Sadeque

20. World Patent Map Analysis Of Mechanization Technologies Relatitng To Rice Production

Patents comprise a unique source for technological knowledge. They are considered to be a good proxy for invention skills, R&D activities and for the scope of technological innovation of countries, regions, sectors and firms. Rice is one of the main field crops. The research focuses on patent mechanization technologies of soil working, planting and harvesting of rice production. Based on DWPI patent database and TI patent analysis software. The temporal examination by publication year... X. Wang, Y. Hu, Z. Yi

21. sUAVS Technology For Better Monitoring Crop Status For Winter Canola

The small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus

22. 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

23. Statistical Variability of Crop Yield, Soil Test N and P Within and Between Producer’s Fields

Soil test N and P significantly affect crop production in the Canadian Prairies, but vary considerably within and between producer's fields.  This study describes the variability of crop yield, soil test N and P within and between producer's fields in the context of variable fertilizer rates.  Yield, terrain attribute, soil test N and P data were collected for 10 fields in Alberta, Saskatchewan and Manitoba Canada in 2014 and 2015.  The influence of fertilizer... A. Moulin, M. Khakbazan

24. Robustness of Pigment Analysis in Tree Fruit

The non-destructive application of spectrophotometry for analyzing fruit pigments has become a promising tool in precise fruit production. Particularly, the pigment contents are interesting to the growers as they provide information on the harvest maturity and fruit quality for marketing. The absorption of chlorophyll at its Q band provides quantitative information on the chlorophyll pool of fruit. As a challenge appears the in-situ measurement at varying developmental stage of the fruit due to... M. Zude-sasse, C. Regen, J. Käthner

25. UAV-based Crop Scouting for Precision Nutrient Management

Precision agriculture – is one of the most substantial markets for the Unmanned Aerial Vehicles (UAVs). Mounted on the UAVs, sensors and cameras enable rapid screening of large numbers of experimental plots to identify crop growth habits that contribute to final yield and quality in a variety of environments. Wheat is one of the Idaho’s most important cereal crops grown in 42 of 44 Idaho counties. We are working on establishing a UAV-based methodology for in-season prediction of wheat... O.S. Walsh, K. Belmont, J. Mcclintick-chess, J. Marshall, C. Jackson, C. Thompson, K. Swoboda

26. Multispectral Imaging and Elevation Mapping from an Unmanned Aerial System for Precision Agriculture Applications

As the world population continues to grow, the need for efficient agricultural production becomes more pressing.  The majority of farmers still use manual techniques (e.g. visual inspection) to assess the status of their crops, which is tedious and subjective.  This paper examines an operational and analytical workflow to incorporate unmanned aerial systems (UAS) into the process of surveying and assessing crop health.  The proposed system has the potential to significantly reduce... C. Lum, M. Dunbabin, C. Shaw-feather, M. Mackenzie, E. Luker

27. FOODIE Data Model for Precision Agriculture

The agriculture sector is a unique sector due to its strategic importance for both citizens (consumers) and economy (regional and global), which ideally should make the whole sector a network of interacting organizations. The FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production. The FOODIE service platform deals with including their thematic, spatial, and temporal... K. Charvat, T. Reznik, K. Charvat jr., V. Lukas, S. Horakova, M. Kepka

28. Quo Vadis Precision Farming

The agriculture sector is a unique sector due to its strategic importance for both citizens and economy which, ideally, should make the whole sector a network of interacting organizations. There is an increasing tension, the like of which is not experienced in any other sector, between the requirements to assure full safety and keep costs under control, but also assure the long-term strategic interests of Europe and worldwide. In that sense, agricultural production influences, and is influenced... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

29. Precision Nitrogen Management Based on Nitrogen Removal in Rainfed Wheat

Growers of hard red spring wheat may capture price premiums for maximizing the protein concentration of their grain. Nitrogen (N) nutrition adequacy is crucial to achieving high grain protein concentration. The objective of this study was to determine the usefulness of N removal maps by comparing grain protein, yields, and dollar returns obtained from this precision N management approach with that from conventional uniform N management. Strip plot experiments were designed to compare spatially... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long

30. On-combine Near Infrared Spectroscopy Applied to Prediction of Grain Test Weight

Whole grain near infrared (NIR) spectroscopy is a widely accepted method for analysis of the protein and moisture contents of grain, but is seldom applied to predict test weight. Test weight is a widely used specification for grading of wheat and predictor of flour yield. The objective of this study was to determine whether NIR spectroscopy could be used for measuring the test weight of grain. Reference grain samples of hard red spring wheat were obtained from dryland fields in the semiarid Negev... D.J. Bonfil, I. Mufradi, S. Asido, D.S. Long

31. Technological Improvement on Sugar Cane Yield Monitor

This paper presents the technological improvement on sugar cane yield monitor. The system designed employs load cells as an instrument for weighing billets, set up on the side conveyor of the harvester before the sugar cane billets are dropped into a field transport wagon. This data, along with the information gathered by GPS installed on the harvester, enabled the elaboration of a digital yield map using GIS. In order to improve the yield monitor a re-design of the first prototype was accomplished.... D.G. Cerri, G.R. Gray, P.S. Magalhães

32. Evaluation of Utilization Potential for Methods of Georeference in the Management of Weed Contamination of Potato Cultures

Combating crop contamination with harmful invasive species is one of the main themes of agricultural research. For the potato cultures, the weed contamination decreases not only the quality but also the quantity of the harvest. The most invasive contamination for this culture is represented by the Agropyron repens and Sorgum halepense, two invasive and very nocive species characterized by underground stems able to penetrate the potato¢s tubercle and decrease their storage... L. Musetescu, M. Gidea

33. 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 specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli

34. Soil Microbial Communities Have Distinct Spatial Patterns in Agricultural Fields

Soil microbial communities mediate many important soil processes in agricultural fields, however their spatial distribution at distances relevant to precision agriculture is poorly understood. This study examined the soil physico-chemical properties and topographic features controlling the spatial distribution of soil microbial communities in a commercial potato field in eastern Canada using next generation sequencing. Soil was collected from a transect (1100 m) with 83 sampling points in a landscape... B. Zebarth, C. Goyer, S. Neupane, S. Li, A. Mills, S. Whitney, A. Cambouris, I. Perron

35. Spatial Variability of Canola Yield Related to Terrain Attributes Within Producer's Fields

Canola production in the Canadian Prairies varies considerably within and between producer's fields.  This study describes the variability of crop yield in producer's fields in the context of terrain attributes, and in relation to fertilizer rates in management zones determined from historical yield.  Canola yield data were collected for 27 fields in Alberta, Saskatchewan and Manitoba Canada in 2014, 2015, 2016 and 2017.  Several terrain attributes accounted for a considerable... A. Moulin, M. Khakbazan

36. Evaluation of the Potential for Precision Agriculture and Soil Conservation at Farm and Watershed Scale: A Case Study

Precision agriculture and soil conservation have the potential to increase crop yield and economic return while reducing environmental impacts. Landform, spatial variability of soil processes, and temporal trends may affect crop N response and should be considered for precision agriculture. The objective of this research was to evaluate the viability of precision agriculture in improving N use efficiency and profitability at the farm and watershed level in western Canada. Two studies are described... M. Khakbazan, A. Moulin, J. Huang, P. Michiels, R. Xie

37. Introducing Precision Ag Tools to Over-100 Year Old Historical Experiment

The historic Knorr-Holden experimental site near Scottsbluff, Nebraska, US, established in 1912 is the oldest irrigated maize plot in North America. Over years, the treatment has been revised a few times to reflect and address contemporary practices. The N fertilization is found to be capable of restoring most of production capacity of the soil. After a full century of the experiment, in 2014, N treatments were revised again. Now, the experiment is a split-plot randomized complete block design... B. Maharjan

38. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. Reddy, D.P. Biradar, V.C. Patil, B.L. Desai, V.B. Nargund, P. Patil, V. Desai, V. Tulasigeri, S.M. Channangi, W. John

39. 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 transformation... J. Trindall, R. Rainbow

40. Improving Active Canopy Sensor-Based In-Season N Recommendation Using Plant Height Information for Rain-Fed Maize in Northeast China

The inefficient utilization of nitrogen (N) fertilizer due to leaching, volatilization and denitrification has resulted in environmental pollution in rain-fed maize production in Northeast China. Active canopy sensor-based in-season N application has been proven effective to meet maize N requirement in space and time. The objective of this research was to evaluate the feasibility of using active canopy sensor for guiding in in-season N fertilizer recommendation for rain-fed maize in Northeast... X. Wang, Y. Miao, T. Xia, R. Dong, G. Mi, D.J. Mulla

41. The Impact of Precision Agriculture Technologies on Farm Profitability in Kansas

Even with more than a decade long adoption of the precision agriculture (PA) technologies in the United States, its impact on farm profitability is still not clear. This paper uses farm level data from Kansas Farm Management Association (KFMA) to conduct the ex-post evaluation of PA technologies on farm profitability in Kansas. The analysis of the data using propensity score matching method indicates that there is on an average $60,000 difference in net returns of the farm with at least one PA... S. Dhoubhadel, T.W. Griffin

42. Rapid Acquisition of Site Specific Lime Requirement with Mid-Infrared Spectroscopy

In Germany, the lime requirement of arable topsoils is derived from the organic matter content, clay content, and pH(CaCl2). For this purpose, it is common practice to determine the lime requirement of a field size up to three hectares from only one composite soil sample, whereby site heterogeneity is regularly not taken into account. To consider site heterogeneity, a measurement technique is required which allows a rapid and high resolution data acquisition. Mid-infrared... M. Leenen, S. Pätzold, T. Heggemann, G. Welp

43. Towards Universal Applicability of On-the-Go Gamma-Spectrometry for Soil Texture Estimation in Precision Farming by Using Machine Learning Applications

High resolution soil data are an essential prerequisite for the application of precision farming techniques. Sensor-based evaluation of soil properties may replace or at least reduce laborious, time-consuming and expensive soil sampling with subsequent measurements in the lab. Gamma spectrometry usually provides information that can be translated into topsoil texture data after calibration. This is because the natural content of the radioactive isotopes 40-K, 232-Th, and 238-U as well... S. Pätzold, T. heggemann, M. Leenen, S. Koszinski, K. Schmidt, G. Welp

44. Development of a Machine Vision Yield Monitor for Shallot Onion Harvesters

Crop yield estimation and mapping are important tools that can help growers efficiently use their available resources and have access to detailed representations of their farm. Technical advancements in computer vision have improved the detection, quality assessment and yield estimation processes for crops, including apples, citrus, mangoes, maize, figs and many other fruits. However, similar methods capable of exporting a detailed yield map for vegetable crops have not yet been fully developed.... A.A. Boatswain jacques, V.I. Adamchuk, G. Cloutier, J.J. Clark, C. Miller

45. Prototype Unmanned Aerial Sprayer for Plant Protection in Agricultural and Horticultural Crops

Aerial application of pesticides has the potential to reduce the amount of pesticides required as chemicals are applied where needed. A prototype Unmanned Aerial Sprayer with a payload of 20 kg; a spraying rate of 6 liters per minute; a spraying swathe of 3 meters, coverage rate of 2 to 4 meters per second and 10 minutes of flight time was built using state of the art technologies. The project is a joint development by University of Agricultural Sciences, Dharwad, KLE Technological University,... S. G, D.P. Biradar, B.L. Desai, V.C. Patil, P. Patil, V.B. Nargund, V. Desai, W. John, S.M. Channangi, V. Tulasigeri

46. Map Whiteboard As Collaboration Tool for Smart Farming Advisory Services

Precision agriculture, a branch of smart farming, holds great promise for modernization of European agriculture both in terms of environmental sustainability and economic outlook.  The vast data archives made available through Copernicus and related infrastructures, combined with a low entry threshold into the domain of AI-technologies has made it possible, if not outright easy, to make meaningful predictions that divides  individual agricultural fields into zones where variable rates... K. Charvat, R. Berzins, R. Bergheim, F. Zadrazil, J. Macura, D. Langovskis, H. Snevajs, H. Kubickova, S. Horakova, K. Charvat jr.

47. SmartAgriHubs FIE20 - Groundwater and Meteo Sensors and Earth Observation for Precision Agriculture

The solution developed under the SmartAgriHubs project in the scope of the Flagship Innovation Experiment FIE20 Groundwater and meteo sensors is an expert system to support farmers in decision-making process and planning process of field interventions. This FIE20 solution integrates various data sources and different analytical processes in a complete system and provides users an easy-to-use web map application as a common user interface. The FIE20 system integrates components developed during... K. Charvat, M. Kepka, R. Berzins, F. Zadrazil, D. Langovskis, M. Musil

48. Development of a Granular Herbicide Spot Applicator for Management of Hair Fescue (Festuca Filiformis) in Wild Blueberry (Vaccinium Angustifolium)

Hair fescue has quickly become the pest of greatest concern for the wild blueberry industry. This is largely due to its ability to outcompete wild blueberry for critical resources including water, nutrients and most importantly space. In Nova Scotia, between 2001 and 2019, hair fescue had increased in field frequency from 7% to 68% and in field uniformity from 1.4% to 25%. This rapidly spreading and economically destructive weed is likewise a significant challenge to manage, with only a single... C. Maceachern, T. Esau, Q. Zaman

49. Sun Effect on the Estimation of Wheat Ear Density by Deep Learning

Ear density is one of the yield components of wheat and therefore a variable of high agronomic interest. Its traditional measurement necessitates laborious human observations in the field or destructive sampling. In the recent years, deep learning based on RGB images has been identified as a low-cost, robust and high-throughput alternative to measure this variable. However, most of the studies were limited to the computer challenge of counting the ears in the images, without aiming to convert... S. Dandrifosse, E. Ennadifi, A. Carlier, B. Gosselin, B. Dumont, B. Mercatoris

50. Spatially Explicit Prediction of Soil Nutrients and Characteristics in Corn Fields Using Soil Electrical Conductivity Data and Terrain Attributes

Site specific nutrient management (SSNM) in corn production environments can increase nutrient use efficiency and reduce gaseous and leaching losses. To implement SSNM plans, farmers need methods to monitor and map the spatial and temporal trends of soil nutrients. High resolution electrical conductivity (EC) mapping is becoming more available and affordable. The hypothesis for this study is that EC of the soil, in conjunction with detailed terrain attributes, can be used to map soil nutrients... S. Sela, N. Graff, K. Mizuta, Y. Miao

51. AgDataBox-IoT Application Development for Agrometeorogical Stations in Smart Farm

Currently, Brazil is one of the world’s largest grain producers and exporters. Brazil produced 125 million tons of soybean in the 2019/2020 growing season, becoming the world’s largest soybean producer in 2020. Brazil’s economic dependence on agribusiness makes investments and research necessary to increase yield and profitability. Agriculture has already entered its 4.0 version, also known as digital agriculture, when the industry has entered the 4.0 era. This new paradigm uses... A. Hachisuca, E.G. Souza, E. Mercante, R. Sobjak, D. Ganascini, M. Abdala, I. Mendes, C. Bazzi, M. Rodrigues

52. Can Topographic Indices Be Used for Irrigation Management Zone Delineation

Soil water movement is affected by soil physical properties and field terrain changes. The identification of within-field areas prone to excess or deficit of soil moisture could support the implementation of variable rate irrigation and adoption of irrigation scheduling strategies. This study evaluated the use of the topographic wetness index (TWI) and topographic position index (TPI) to understand and explain within-field soil moisture variability. Volumetric water content (VWC) collected in... B.V. Ortiz, B.P. Lena, F. morlin , G. Morata, M. Duarte de val, R. Prasad, A. Gamble

53. Evaluating a Satellite Remote Sensing and Calibration Strip-based Precision Nitrogen Management Strategy for Corn in Minnesota and Indiana

Precision nitrogen (N) management (PNM) aims to match N supply with crop N demand in both space and time and has the potential to improve N use efficiency (NUE), increase farmer profitability, and reduce N losses and negative environmental impacts. However, current PNM adoption rate is still quite low. A remote sensing and calibration strip-based PNM strategy (RS-CS-PNM) has been developed by the Precision Agriculture Center at the University of Minnesota.... K. Mizuta, Y. Miao, A.C. Morales, L.N. Lacerda, D. Cammarano, R.L. Nielsen, R. Gunzenhauser, K. Kuehner, S. Wakahara, J.A. Coulter, D.J. Mulla, D. . Quinn, B. Mcartor

54. Identifying Key Factors Influencing Yield Spatial Pattern and Temporal Stability for Management Zone Delineation

Management zone delineation is a practical strategy for site-specific management. Numerous approaches have been used to identify these homogenous areas in the field, including approaches using multiple years of historical yield maps. However, there are still knowledge gaps in identifying variables influencing spatial and temporal variability of crop yield that should be used for management zone delineation. The objective of this study is to identify key soil and landscape properties affecting... L.N. Lacerda, Y. Miao, K. Mizuta, K. Stueve

55. Evaluating the Potential of Improving In-season Nitrogen Status Diagnosis of Potato Using Leaf Fluorescence Sensors and Machine Learning

Precision nitrogen (N) management is particularly important for potato crops due to their high N fertilizer demand and high N leaching potential caused by their shallow root systems and preference for coarse-textured soils. Potato farmers have been using a standard lab analysis called petiole nitrate-N (PNN) test as a tool to diagnose potato N status and guide in-season N management. However, the PNN test suffers from many disadvantages including time constraints, labor, and cost of analysis.... S. Wakahara, Y. Miao, S. Gupta, C. Rosen, K. Mizuta, J. Zhang, D. Li

56. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter Wheat

Optimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequently... D. Ghimire

57. Treetop Tech: Uplifting German Foresters' Drone Perspectives Through the Technology Acceptance Model

Forests play a key role in nature as they purify water, stabilize soil, cycle nutrients, store carbon and also provide habitats for wildlife. Economically, forest product industries provide jobs and economic wealth. Sustainable forest management and planning requires foresters’ understanding of the forests dynamics for which the collection of field data is necessary, which can be time consuming and expensive. Unmanned aerial vehicles or drones can improve the efficiency of tradition acquisition... M. Michels, H. Wever, O. Mußhoff

58. Farming for a Greener Future: the Behavioural Drive Behind German Farmers’ Alternative Fuel Machinery Purchase Intentions

Climate change due to greenhouse gas emissions, e.g. anthropogenic carbon dioxide (CO2), in the atmosphere will lead to damages caused by global warming, increases in heavy rainfall, flooding as well as permafrost melt. One of the main issues for reducing greenhouse gas emissions is the dependence on oil for fueling transportation and other sectors. Accordingly, policy makers aim to reduce dependency on fossil fuels with the accelerated roll-out of renewable energy. Among others, the... M. Michels, V. Bonke, H. Wever, O. Mußhoff

59. Spray Deposition and Efficacy of Pesticide Applications with Spray Drones in Row Crops in the Southeastern US

The use of spray drones for pesticide applications is expanding rapidly in agriculture, with one of the top uses currently being in the row crop production. Several research studies were undertaken in 2022 and 2023 to measure and assess spray deposition and efficacy of pesticides applied with spray drones in the major row crops (corn, cotton and peanuts) grown in the southeastern US. These studies also evaluated and compared the deposition and pesticide efficacy of spray drones with traditional... C. Byers, R. Meena, J. Kichler, R.C. Kemerait, L. Hand, S. Virk

60. Multi-sensor Remote Sensing: an AI-driven Framework for Predicting Sugarcane Feedstock

Predicting saccharine and bioenergy feedstocks in sugarcane enables stakeholders to determine the precise time and location for harvesting a better product in the field. Consequently, it can streamline workflows while enhancing the cost-effectiveness of full-scale production. On one hand, Brix, Purity, and total reducing sugars (TRS) can provide meaningful and reliable indicators of high-quality raw materials for industrial food and fuel processing. On the other hand, Cellulose, Hemicellulose,... M. Barbosa, D. Duron, F. Rontani, G. Bortolon, B. Moreira, L. Oliveira, T. Setiyono, L. Shiratsuchi, R.P. Silva, K.H. Holland

61. UAV Multispectral Data As a Suitable Tool for Predicting Sweetness, Size, and Yield of Vidalia Onions

Vidalia onions is a specialty crop cultivated solely within the southeastern region of Georgia. The key distinguishing characteristic of Vidalia onions is its high sugar content, making them highly prized and widely consumed. Ten thousand acres are grown with Vidalia Onions each year approximately, and the market value (~$150Mi/year) makes the crop very important for the State of Georgia. Traditionally, the planting, weeding, spraying, harvesting, and post-harvesting operations are usually done... M. Barbosa, L. Oliveira, C. Tyson, A. Shirley, R. Santos, L. Sales, R. Vargas

62. A Digital Twin for Arable Crops and for Grass

There is an opportunity to use process-based cropping systems models (CSMs) to support tactical farm management decisions, by monitoring the status of the farm, by predicting what will happen in the next few weeks, and by exploring scenarios. In practice, the responses of a CSM will deviate more and more from reality as time progresses because the model is an abstraction of the real system and only approximates the responses of the real system. This limitation may be overcome by using the CSM... F. Van evert, P. Van oort, B. Maestrini, A. Pronk, S. Boersma, M. Kopanja, G. Mimić

63. Creating a Comprehensive Software Framework for Sensor-driven Precision Agriculture

Robots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if their... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties

64. Design of an Automatic Travelling Electric Fence System for Sustainable Grazing Management

Fences are used in Precision Livestock Farming (PLF) to prevent herbivores from overgrazing and under grazing forages. While effective in controlling animal entry and exit, traditional fences are not flexible enough to meet the needs of both foraging animals and plants in terms of both nutrient availability and physiological demands. An electric fencing system is a form of traditional fencing that employs an electric charge to create a barrier and dissuade animals or people from crossing it. Even... M. Alahe, Y. Chang, J.O. Kemeshi, S. Gummi, H. Menendez iii

65. Using Remote Sensing to Benchmark Crop Coefficient Curves of Sweet Corn Grown in the Southeastern United States

Irrigation is responsible for over 75% of global freshwater use, making it the largest consumer of the world’s freshwater resources. With freshwater scarcity increasing worldwide, increased efficient irrigation water use is necessary. Smart irrigation is described as ‘the linking of technology and fundamental knowledge of crop physiology to significantly increase irrigation water use efficiency'. Irrigation scheduling tools such as smartphone applications have become... E. Bedwell, L. Lacerda, T. Mcavoy, B.V. Ortiz, J. Snider, G. Vellidis, Z. Yu

66. 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 (OSR),... R.P. Negrini, Y. Miao, K. Mizuta, K. Stueve, D. Kaiser, J.A. Coulter

67. Effects of Crop Rotation on In-season Estimation of Optimal Nitrogen Rates for Corn Based on Proximal and Remote Sensing Data

A remote sensing and calibration strip-based precision nitrogen (N) management (RS-CS-PNM) strategy has been developed by the Precision Agriculture Center at the University of Minnesota to provide in-season N recommendation rates based on satellite imagery. This strategy involves the application of multiple N rates before planting and the identification of the agronomic optimum N rate (AONR) at V7-V8 growth stages using normalized difference vegetation index (NDVI) calculated using satellite imagery.... A.C. Morales, D. . Quinn, K. Mizuta, Y. Miao

68. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote Sensing

For irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang

69. 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 41,000... Y. Miao, A. Kechchour, S. Folle, K. Mizuta

70. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial Data

On-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, the... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini

71. Long-range Bluetooth Smart Stakes and High-gain Receivers for High-density Sensing in Precision Agriculture

To achieve the goals of precision agriculture, accurate spatial-temporal soil information is needed, especially because soil properties can change within and between growing seasons. While remote sensing can provide high coverage, some soil properties must be measured in situ. Current existing industry solutions are too expensive per unit to deploy in sufficiently high density for dynamic management zones, creating a need for low-cost sensor networks.... S. Craven, C. Sandholtz, B. Mazzeo

72. Advanced Classification of Beetle Doppelgängers Using Siamese Neural Networks and Imaging Techniques

The precise identification of beetle species, especially those that have similar macrostructure and physical characteristics, is a challenging task in the field of entomology. The term "Beetle Doppelgängers" refers to species that exhibit almost indistinguishable macrostructural characteristics, which can complicate tasks in ecological studies, conservation efforts, and pest management. The core issue resides in their striking similarity, frequently confusing both experts and automated... P.R. Armstrong, L.O. Pordesimo, K. Siliveru, A.R. Gerken, R.O. Serfa juan