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Lattanzi, P
Corá, J
Sharma, A
Lambert, D.M
Mueller, T.G
Musetescu, L
Trautz, D
Peterson, G
Castro, T
Miranda, C
Lukach, J
Corassa, G.M
Tubaña, B.S
Lena, B.P
Laboski, C.A
Cutulle, M
Parajulee, M
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Authors
Sekhon, B.S
Mukherjee, J
Sharma, A
Thind, S.K
Kaur, R
Makkar, M.S
Sharma, A
Makkar, M.S
Gupta, S
Borchert, A
Trautz, D
Olfs, H
Borchert, A
Recke, G
Dabbelt, D
Trautz, D
Olfs, H
Mueller, T
Corá, J
Castrignanò, A
Rodrigues, M
Rienzi, E
Franzen, D.W
Endres, G
Ashley, R
Staricka, J
Lukach, J
McKay, K
Dosskey, M.G
Mueller, T.G
Singh, M
Sharma, A
Singh, G
Fixen, P
Olfs, H
Trautz, D
Borchert, A
Ruckelshausen, A
Alheit, K.V
Busemeyer, L
Klose, R
Linz, A
Moeller, K
Rahe, F
Thiel, M
Trautz, D
Weiss, U
Peterson, G
Westfall, D
Sherrod, L.A
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Makkar, M.S
Kaul, A
Kumar, R
Sharma, A
Sekhon, B.S
Pannu, C.S
Amado, T.J
Santi, A.L
Corassa, G.M
Bisognin, M.B
Gaviraghi, R
Pires, J.L
Larson, J.A
Stefanini, M
Lambert, D.M
Yin, X
Boyer, C.N
Varco, J.J
Scharf , P.C
Tubaña, B.S
Dunn, D
Savoy, H.J
Buschermohle, M.J
Tyler, D.D
Corassa, G.M
Amado, T.J
Schwalbert, R.A
Reimche, G.B
Dalla Nora, D
Horbe, T.
Tabaldi, F.M
Schwalbert, R
Carneiro Amado, T.J
Horbe, T
Corassa, G.M
Gebert, F.H
Griffin, T.W
Lambert, D.M
Lowenberg-DeBoer, J
Musetescu, L
Gidea, M
Dallago, G.M
Figueiredo, D
Santos, R
Santos, D
Guimarães, L
Santos, C
Castro, T
Santos, A
Otoni, L
Andrade, J
Ransom, C.J
Kitchen, N.R
Camberato, J.J
Carter, P.R
Ferguson, R.B
Fernandez, F.G
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J
Sawyer, J.E
Ortiz, B.V
Lena, B.P
Morlin , F
Morata, G
Duarte de Val, M
Prasad, R
Gamble, A
Mathew, J.J
Flores, P.J
Stenger, J
Miranda, C
Zhang, Z
Das, A.K
Maja, J.J
Abenina, M
Cutulle, M
Melgar, J
Liu, H
Canavari, M
Lattanzi, P
Vitali, G
Emmi, L
Topics
Remote Sensing Applications in Precision Agriculture
Sensor Application in Managing In-season Crop Variability
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Precision A-Z for Practitioners
Precision Conservation
Sensor Application in Managing In-season Crop Variability
Spatial Variability in Crop, Soil and Natural Resources
Precision Carbon Management
Precision Nutrient Management
Precision Nutrient Management
Spatial Variability in Crop, Soil and Natural Resources
Profitability, Sustainability and Adoption
Precision Nutrient Management
Profitability, Adoption and Performance Evaluation
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Precision Dairy and Livestock Management
In-Season Nitrogen Management
Drainage Optimization and Variable Rate Irrigation
Precision Agriculture and Global Food Security
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Factors Driving Adoption
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Authors

Filter results25 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. Designing Variable-width Filter Strips Using GIS And Terrain Analysis

Filter strips are a widely-used practice for reducing the load of pollutants that leave agricultural fields in overland runoff. They are typically designed to intercept uniformly-distributed runoff with a constant width strip along a field margin. Non-uniform runoff flow, however, can reduce the effectiveness of a constant-width filter strip. Non-uniform flow is created by topographic undulations and swales in fields that concentrate runoff into certain locations... M.G. Dosskey, T.G. Mueller

3. 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 can... M. Singh, A. Sharma, G. Singh, P. Fixen

4. Validation Of On-the-go Soil Ph-measurements – Primary Results From Germany

Until recently in-field variability for soil pH could not be considered for agronomic decisions (e.g. liming rates) because reliable spatial information was hardly available. The required density of soil pH-measurements could not be achieved by manual soil sampling due to time constraints and analysis costs for the vast number of samples. A comprehensive... H. Olfs, D. Trautz, A. Borchert

5. 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 selectivities... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss

6. Landscape Position And Climatic Gradient Impacts On Carbon Turnover in Dryland Cropping Systems in Colorado

  Soil organic carbon has decreased in cultivated wheat-fallow systems due to increased carbon oxidation, low carbon input and soil erosion.  Implementation of more intensive cropping with no-till management has reversed the trend in soil carbon loss.  Our objective in this presentation is to review the effects of landscape position on soil carbon status as related to intensification of cropping system.  Our analysis will... G. Peterson, D. Westfall, L.A. Sherrod

7. 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 data... M. Parajulee, D. Neupane, C. Wang, S. Carroll, R. Shrestha

8. Spectral Models for Estimation of Chlorophyll Content, Nitrogen, Moisture Stress and Growth of Wheat Crop

  Field  experiments  were  conducted  during  2009-10  and  2010-11 at  research  farm  of the department of Farm Machinery and Power Engineering, Punjab Agricultural university, Ludhiana.  Three wheat ... B.S. Sekhon, J. Mukherjee, A. Sharma, S.K. Thind, R. Kaur, M.S. Makkar

9. Development of Ground Based Multi-source Crop Information Collection System.

Precision agriculture requires reliable technology to acquire accurate information on crop conditions. A ground-based integrated sensor and instrumentation system was developed to measure real-time crop conditions. The integration system included multispectral camera and N-sensor for real time Nitrogen application. The system was interfaced with a DGPS receiver to provide spatial coordinates for sensor readings. Before mounting of the sensors on modified paddy transplanter, different mountings... A. Sharma, M.S. Makkar, S. Gupta

10. Soil pH maps Derived from On-the-Go pH-Measurements as Basis for Variable Lime Application under German Conditions: Concept Development and Evaluation in Field Trials

... A. Borchert, D. Trautz, H. Olfs

11. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions

... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs

12. Spatial and Temporal Variability of Corn Grain Yield as a Function of Soil Parameters, and Climate Factors

Effective site-specific management requires an understanding the influence of soil and weather on yield variability. Our objective was to examine the influence of soil, precipitation, and temperature on spatial and temporal corn grain yield variability.  The study site (10 by 250 -m in size) was located in Jaboticabal, São Paulo State, on a Rhodic Hapludox. Corn yield (planted with 0.9-m spacing) was measured... T. Mueller, J. Corá, A. Castrignanò, M. Rodrigues, E. Rienzi

13. 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

14. Response of Soybean Cultivars According to Management Zones in Southern Brazil

The positioning of soybean cultivars on fields according your environmental response is new strategy to obtain high soybean yields. The aim of this study was to investigate the agronomic response of six soybean cultivars according management zones in Southern Brazil. The study was conducted in 2013/2014 and in two fields located in Boa Vista das Missões, Rio Grande do Sul, Brazil. The experimental design was a randomized complete block in a factorial arrangement (3x6), with three management... T.J. Amado, A.L. Santi, G.M. Corassa, M.B. Bisognin, R. Gaviraghi, J.L. Pires

15. Net Returns and Production Use Efficiency for Optical Sensing and Variable Rate Nitrogen Technologies in Cotton Production

This research evaluated the profitability and N use efficiency of real time on-the-go optical sensing measurements (OPM) and variable-rate technologies (VRT) to manage spatial variability in cotton production in the Mississippi River Basin states of Louisiana, Mississippi, Missouri, and Tennessee. Two forms of OPM and VRT and the existing farmer practice (FP) were used to determine N fertilizer rates applied to cotton on farm fields in the four states. Changes in yields and N rates due to OPM... J.A. Larson, M. Stefanini, D.M. Lambert, X. Yin, C.N. Boyer, J.J. Varco, P.C. Scharf , B.S. Tubaña, D. Dunn, H.J. Savoy, M.J. Buschermohle, D.D. Tyler

16. High-resolution Mapping with On-the-go Soil Sensor and Its Relation with Corn Yield and Soil Acidity in a Dystrophic Red Oxisol

Spatial representations of soil attributes with low resolution can lead to gross errors of recommendation and compromise the efficiency of soil corrections and consequently the grain yield. However, obtaining the spatial variability of soil attributes with high resolution by soil sampling is not recommended because of its large time spent and high cost of laboratory analysis what makes difficult their large-scale application. This way, the on-the-go soil sensing has been used in precision agriculture... G.M. Corassa, T.J. Amado, R.A. Schwalbert, G.B. reimche, D. Dalla nora, T. . horbe, F.M. tabaldi

17. Adjustment of Corn Population and Nitrogen Fertilization Based on Management Zones

The main objective of this study was to adjust the corn population and nitrogen fertilization according to management zones, based on past grain yield maps (seven of soybean and three of corn) and soil electrical conductivity. The study was carried out in Não-Me-Toque, Rio Grande do Sul, Brazil, and it was conducted in a factorial strip blocks with 3 repetitions in each management zone, being the treatments: corn populations (56000, 64000, 72000, 80000 and 88000 plants ha-1),... R. Schwalbert, T.J. Carneiro amado, T. Horbe, G.M. Corassa, F.H. Gebert

18. Economics of Gps-enabled Navigation Technologies

To address the economic feasibility of global positioning system (GPS) enabled navigation technologies including automated guidance and lightbar, a linear programming model was formulated using data from Midwestern U.S. Corn Belt farms. Five scenarios were compared: (i) a baseline scenario with foam, disk or other visual marker reference, (ii) lightbar navigation with basic GPS availability (+/-3 dm accuracy), (iii) lightbar with satellite subscription correction GPS (+/-1 dm), (iv) automated... T.W. Griffin, D.M. Lambert, J. Lowenberg-deboer

19. 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

20. Time Series Analysis of Somatic Cell Count from Dairy Herds in Minas Gerais - Brazil

The objective of this study was to analyze the temporal variation of somatic cell count (SCC) in milk of dairy cows from the state of Minas Gerais, Brazil. The Holstein Livestock Breeders Association of Minas Gerais provided data collected from 128 dairy farms located in the state of Minas Gerais between the years of 2000 and 2016. The database contains the SCC average of a total of 91,851 305-day lactations of Holstein animals. The annual SCC average was calculated as well as the percentage of... G.M. Dallago, D. Figueiredo, R. Santos, D. Santos, L. Guimarães, C. Santos, T. Castro, A. Santos, L. Otoni, J. Andrade

21. Improving Corn Nitrogen Rate Recommendations Through Tool Fusion

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

22. 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

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

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

24. Snap-shot Hyperspectral Camera for Potassium Prediction of Peach Trees Using Multivariate Analysis

Hyperspectral imaging (HSI) is an emerging technology being utilized in agriculture. This system could be used to monitor the overall health of plants or pest disease detection. As sensing technology advances, measuring nutrient levels and disease detection also progresses. This study aimed to predict the levels of potassium (K) content in peach leaves with the new snapshot hyperspectral camera. The study was conducted at the Clemson University Musser Fruit Research Farm (Seneca, SC, USA, 34.61... J.J. Maja, M. Abenina, M. Cutulle, J. Melgar, H. Liu

25. Robot Safety Issues in Field Crops - EU Regulatory Issues and Technical Aspects

The use of robots in Precision Agriculture is becoming of great interest, but they introduce a new kind of risk in the field due to their self-acting and self-driving capability. Safety issues appear with respect to people working in the same field in human-robot collaboration (HRC) framework or to the accidental presence of humans or animals. A robot out of control may also invade other areas causing unpredictable harm and damage. Currently, the safety of highly automated agricultural... M. Canavari, P. Lattanzi, G. Vitali, L. Emmi