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Precision Agriculture and Climate Change
Education and Outreach in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
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Authors
Acevedo, E
Adamchuk, V.I
Albrecht, H
Allphin, E
Amin, S
Antuniassi, U
Baghernejad, M
Baio, F
Balboa, G
Balzarini, M
Bartzanas, T
Biscaro, A
Bochtis, D
Bongiovanni, M
Bongiovanni, R
Borchert, A
Brodbeck, C.J
Bryan, W
Carrow, R
Carson, T
Cendrero Mateo, M.P
Cerliani, C
Cerri, D.G
Chantuma, D
Charvat Jr., K
Charvat, K
Chen, L
Cline, V
Darr, M.J
Debuisson, S
Degioanni, A
Del Solar, D.E
Deng, W
Emadi, M.M
Esau, T.J
Esposito, G
Farooque, A.A
Fergugson, R.B
Flitcroft, I
Fountas, S
Frimpong, K.A
Fulton, J.P
Gonzalez, J
Green, O
Griffin, S
Henderson, W
Horakova, S
Hossain, B
J, R
Jonjak, A.K
KANDA, R
Kalmar, J
Keller, B
Kepka, M
Khalilian, A
Khosla, R
Khosla, R
Khosla, R
Kirkpatrick, T
Kitchen, N.R
Kodaira, M
Kodaira, M
Kodaira, M
Kovacs, A.J
Krum, J
Kruse, R
Longchamps, L
Lukas, V
MacDonald, L
Macy, T
Maglh, P.S
Mata-Padrino, D
Melchiori, R
Milics, G
Monfort, S
Mueller, J
Mueller-Linow, M
Muller, O
Mzuku, M
NAGAMI, Y
Neményi, M
Ninomiya, K
Norwood, S.H
Nyeki, A
Olfs, H
Orloff, S
Ortega, R.A
Overstreet, C
Pena-Yewtukhiw, E.M
Percival, D.C
Pieruschka, R
Pinto, F
Pravia, V
Prostko, E.P
Rascher, U
Reich, R
Reich, R
Reznik, T
Rice, K
Rodekohr, D
Rodrigues Jr, F
Roel
Ru, G
SVIERCOSKI, R
Scaramuzza, F
Scharf, P
Schelde, K
Schickling, A
Schneider, M
Schumann, A.W
Schurr, U
Shaner, D
Shaner, D
Shapiro, C.A
Shaw, J.N
Shibusawa, S
Shibusawa, S
Shibusawa, S
Smith, F
Sorensen, C
Splichal, M
Stauffer, T
Stromberger, M
Suddeth, K.A
Sulastri, N
Terra, J.A
Thompson, A
Thomsen, A
Trautz, D
Videla, H
Virk, S.S
Winstead, A.T
Wortmann, C.S
Wu, G
Xue, X
Zach, D
Zaller, M
Zaman, Q
http://icons.paqinteractive.com/16x16/ac, G
marine, L
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Agriculture and Climate Change
Education and Outreach in Precision Agriculture
Type
Oral
Poster
Year
2010
2016
2022
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Topics

Filter results38 paper(s) found.

1. Spectral Discrimination Of Early Dchinochloa Crasgalli And Echinochloa Crusgalli In Corn And Soybean By Using Support Vector Machines

    The key to realize precise chemical application is weed identification. This paper introduces a kind of multi-classification mode based on Support Vector Machines (SVM) and one-against-one-algorithm for weed seedlings (Dchinochloa crasgalli, and Echinochloa crusgalli) in corn and soybean fields. A handheld FieldSpec® 3 Spectroradiometer manufactured by ASD Inc., in USA was used to measure the spectroscopic data of the canopies of the seedlings of corn, soy... W. Deng, G. Wu

2. A Comparison Of Conventional And Sensor-based Lime Requirement Maps

Successful variable-rate applications of agricultural inputs, such as lime, rely on quality of input data. Systematic soil sampling is... A.K. Jonjak, V.I. Adamchuk, C.S. Wortmann, C.A. Shapiro, R.B. Fergugson

3. Development Of A System For Site-specific Nematicide Placement In Cotton

Nematode distribution varies significantly in cotton fields. Population density throughout a field is highly correlated to soil texture. Field-wide application of a uniform nematicide rate results in the chemical being applied to areas without nematodes or where nematode densities are below an economic threshold, or the application of sub-effective levels in areas with high nematode densities. The investigators have developed a “Site- Specific Nematicide Placement”... A. Khalilian, W. Henderson, J. Mueller, T. Kirkpatrick, S. Monfort, C. Overstreet

4. A Clustering Approach For Management Zone Delineation In Precision Agriculture

In recent years, an increasing amount of research has been devoted to the delineation of management zones. There have been quite a number of approaches towards using small-scale data for subdividing the field into a small number of zones, usually three or four. However, these zones are usually static, often require multi-year data sets and are based on low-resolution sampling methods for data acquisition. Furthermore, existing research into th... G. Ru, M. Schneider, R. Kruse

5. On The Go Soil Sensor For Soil Ec Mapping

This paper describes spatial variation maps of soil electrical conductivity (EC) obtained by both spectroscopic and capacitance methods using on the go soil sensor ( a real-time soil sensor -RTSS) SAS 1000, commercialized by Shibuya Kogyo Co. The experiments were conducted over a 2 year period on an experimental Hokkaido farm with an alluvial soil type. The comparison in soil EC records between the spectroscopy and the capacitance were also discussed. The spectroscopic approach used the soi... N. Sulastri, S. Shibusawa, M. Kodaira

6. Using Multiplex® And GreenseekerTM To Manage Spatial Variation Of Vine Vigor In Champagne

Sébastien Debuisson1, Marine Le Moigne2, Mathieu Grelier1, Sébastien Evain2, Laurent Panigai1, Zoran G. Cerovic3 1CIVC, 5 rue Henri-Martin, boîte postale 135, Epernay, France 2Force-A, Université Paris Sud, Bât 503, Orsa... S. Debuisson, L. Marine

7. Spatial Mapping Of Penetrometer Resistance On Turfgrass Soils For Site-specific Cultivation

Site-specific management requires site-specific information.  Soil compaction at field capacity is a major stress on recreational turfgrass sites that requires frequent cultivation. Spatial mapping of penet... K. Rice, T. Carson, J. Krum, I. Flitcroft, V. Cline, R. Carrow

8. Nitrogen Loss In Corn Production Varies As A Function Of Topsoil Depth

  Understanding availability and loss potential of nitrogen for varying topsoil depths of poorly-drained claypan soil landscapes could help producers make improve decisions when managing crops for feed grain or bio-fuels.  While it has been well documented that topsoil depth on these soils plays an important role in storing water for crop growth, it is not well known how this same soil... E. Allphin, N.R. Kitchen, K.A. Suddeth, A. Thompson

9. The Soil P2O5 Mapping Using The Real Time Soil Sensor

    Many researches related to P­2O5 measurement using Vis-NIR spectroscopy have been performed in laboratory. There are not so many researches to perform on-the-go measurement of P­2O5. One of the researches which performe... M. Kodaira, Y. Nagami, S. Shibusawa, R. Kanda

10. Spatial Variability Analyse And Correlation Between Physical Chemical Soil Attributes And Sugarcane Quality Parameters

With the high increment in the ethanol demand, the trend is that the planted area with sugar cane in Brazil will increase from the actual 7 million ha up to 12 million ha in 15 years. The sugar cane expansion demands, beyond the enlargement of the boundaries with the installation of new industrial units, better use of the production areas and improvement of the yield and quality, together with production costs reduction. In such a way, the adoption of Precision Ag... F. Rodrigues jr, P.S. Maglh, D.G. Cerri

11. Dozen Parameters Soil Mapping Using The Real-time Soil Sensor

 A Real-time soil sensor (RTSS) can be predicted soil parameters using near-infrared underground soil reflectance sensor in commercial farms. ... M. Kodaira, S. Shibusawa, K. Ninomiya

12. Spatial Variability Of Measured Soil Properties Across Site- Specific Management Zones

The spatial variation of productivity across farm fields can be classified by delineating site-specific management zones. Since productivity is influenced by soil characteristics, the spatial pattern of productivity could be caused by a corresponding variation in certain soil properties. Determining the source of variation in productivity can help achieve more effective site-specific management, the objectives of this study were (i) to characterize the spatial variability of soil physical pro... M. Mzuku, R. Khosla, R. Reich, G. Http://icons.paqinteractive.com/16x16/ac, F. Smith, L. Macdonald

13. Spatial-temporal Management Zones For Biomass Moisture

 Biomass handling operations (harvesting, raking, collection, and transportation) are critical operations within the agricultural production system since they constitute the first link in the biomass supply chain, a fact of substantial importance considering the increasingly involvement of biomass in bio-refinery and bio-energy procedures. Nevertheless, the inherent uncertainty, imposed by the interaction between environmental, biological, and machinery factors, makes the available sched... S. Fountas, D. Bochtis, C. Sorensen, O. Green, R. J, T. Bartzanas

14. Interaction Between Air Spray Drift And Climatic Conditions Creating Drift Map Related To The Aerial Application Of Pesticides Using Low Volumes In Brazil

Between 30 to 50% of the pesticides total applied over agricultural areas can be lost by the air, depending of the applying conditions, by the spray drift action. This spray drift problem is increased when the field is too close to the urban locations, bringing environmental contamination, and when the application is made with oil on the tank mixture. The society demands ... F. Baio, U. Antuniassi

15. A Case Study For Variable-rate Seeding Of Corn And Cotton In The Tennessee Valley Of Alabama

      Farmers have recently become more interested in implementing variable-rate seeding of corn and cotton in Alabama due to increasing seed costs and the potential to maximize yields site-specifically due to inherent field variability.  Therefore, an on-farm case study was conducted to evaluate the feasibility of variable-rate seeding for a corn and cotton rotation.... S.H. Norwood, J.P. Fulton, A.T. Winstead, J.N. Shaw, D. Rodekohr, C.J. Brodbeck, T. Macy

16. Estimating Soil Moisture And Organic Matter Content Variabality Using Electromagnatic Induction Metod

  Abstract: Electromagnetic induction (EMI) methods are gaining popularity due to their non-destructive nature, rapid response and ease of integration into mobile platforms for assessment of the soil moisture content, water table depth, and salinity etc. The objective of this study was to estimate and map soil moisture content and organic matter content using Dua... A. Farooque, Q. Zaman, A.W. Schumann, D.C. Percival, T.J. Esau, T. Stauffer

17. Assessment Of The Success Of Variable Rate Seeding Based On EMI Maps

  Good plant establishment is the critical first step in growing a crop. To achieve this, the correct seed rate must be calculate. This is done by assessing the optimum target plant population per m² and then making an estimate of any  losses over winter. Losses will depend on the quality of seedbed created which is related to texture, stoniness and compaction of the soil. If there is any variation in these field characteristics then the correct see... S. Griffin, M. Darr

18. Spatio-temporal Analysis Of Atrazine Degradation And Associated Attributes In Eastern Colorado Soils

Atrazine catabolism is an example of a rapidly evolved soil microbial adaptation. In the last 20 years, atrazine-degrading bacteria have become globally distributed, and many soils have developed enhanced capacities to degrade atrazine, reducing its half-life from 60 to a few days or less. While the presence of atrazine-degrading bacteria determine a soil's potential to catabolize at... M. Stromberger, R. Khosla, D. Shaner, D. Zach

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

20. Carbohydrate Reserves On Tapping Systems And Production Of Hevea Brasiliensis

CARBOHYDRATE RESERVES ON TAPPING SYSTEMS AND PRODUCTION OF Hevea brasiliensis Chantuma P1., Lacointe A2., Kasempsap P3., Thanysawanyangkura S4., Gohet E5., Clément A6., Guilliot A7., Améglio T2., Thaler P8. and Chantuma A1. 1 Agriculture Scientist Senior, Chachoengsao Rubber Research Center, RRIT-DOA, Ministry of Agriculture and Cooperative, Sanam Chai Ket, Thailand. 2 INRA, UMR 547 PIAF, F-60100 Clermont-Ferrand, France. 3 Departmen... D. Chantuma, M. Zaller

21. Spatial Variability Of Important Soil Characteristics In Semiarid Ecosystems, A Case Study In Arsanjan Plain, Southern Iran

Timely information on the content and distribution of key soil nutrients in highly calcareous ecosystems is vital to support precision agriculture. Efficient tools to measure within-field spatial variation in soil are important when establishing agricultural field trials and in precision farming. Therefore, soil samples were collected at 0-30 cm depth in highly calcareous soils (Arsanjan plain) and chemically analyzed for nitrate (NO3-), e... M.P. Baghernejad, M.M. Emadi

22. Does Pasture Longevity Under Direct Grazing Affect Field-scale Sorghum Yield Spatial Variability In Crop-pasture Rotation Systems?

Crop yield spatial variability is usually related to terrain attributes and soil properties. In pasture systems, soil properties are affected by animal grazing. However, soil and terrain attributes relation with crop yield variability has not been assessed in crop-pasture rotat... V. Pravia, J.A. Terra, Roel

23. Application Of A Canopy Multisensor

The MobilLas mobile canopy sensor was initially developed for variable rate fertilisation and plant protection. Because of the several canopy variables sensed the sensor has wider application in crop and soil variability studies, detailed crop water balance studies, spatial modelling of p... A. Thomsen, K. Schelde

24. Site-specific Phosphorus And Potassium Fertilization Of Alfalfa: Fertilizer Usage And Sampling Density Comparison

Alfalfa accounts for the largest cropping area in both the High Desert and Intermountain regions in California, and the use of site-specific management (SSM) can potentially improve farmers’ fertilization practices and crop nutritional status. These areas have limited to no studies regarding nutrient SSM, and variable rate (VR) fertilizer application has not been commonly used by farmers in either area. Considerable range of soil nutrient levels have... A. Biscaro, S. Orloff

25. 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 r... E.M. Pena-yewtukhiw, D. Mata-padrino, W. Bryan

26. Spatial Variability Of Spikelet Sterility In Temperate Rice In Chile

Spikelet sterility (blanking) causes large economic losses to rice farmers in Chile. The most common varieties are susceptible to low air and water temperatures during pollen formation and flowering, which is the main responsible for the large year to year variation observed in terms of blanking and, therefore, of grain yield. The present work had for objective to study the spatial variability of spikelet sterility within two rice fields, during two consecutive seasons, and relate it to water... R.A. Ortega, D.E. Del solar, E. Acevedo

27. Spatial And Temporal Changes In Atrazine Degradation Rates In Soil

Atrazine is a widely used soil-applied herbicide to control many broadleaf and grassy weeds in corn, sugarcane, and non-cropland areas.  Atrazine is also found as a contaminant in surface and ground water.  One of the strengths and weaknesses of atrazine has been the long residual activity in the soil that provides good weed control but also increases the leaching of the herbicide.  In the las... D. Shaner

28. Measuring Multi-depth Soil Moisture Content In A Vertisol Soils With EM38

Over the years, electromagnetic induction sensors, such as EM38, have been used to monitor soil salinity or local electrical conductivity (ECa) and their output has been instrumented in establishing models for depth profiling of ECa. In the previous work both the forward propagation and inverse matrix approaches offered potential to produce depth profiles of soil ECa. However, it remains a question whether EM38 is able to measure v in different depths. This present study concerns itse... B. Hossain

29. Spatial Variation Patterns Of Soil Properties And Winter Wheat Growth Parameters In China National Experiment Station For Precison Agriculture

Understanding of spatial patterns of soil properties and crop growth and their relationship is neccesary for variable-rate management of farmland in precision agriculture. This paper presents spatial variation patterns of soil properties such as depth of soil diagnostic horizons, cation exchange capacity, organic matter content, soil solution nutrients concentration, and winter wheat growth and yield parameters in China National Experiment Station for Precison A... X. Xue, L. Chen

30. 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 influenc... K. Charvat, T. Reznik, V. Lukas, K. Charvat jr., S. Horakova, M. Splichal, M. Kepka

31. Climate Smart Precision Nitrogen Management

Climate Smart Agriculture (CSA) aims at improving farm productivity and profitability in a sustainable way while building resilience to climate change and mitigating the impacts of agriculture on greenhouse gas emissions. The idea behind this concept is that informed management decision can help achieve these goals. In that matter, Precision Agriculture goes hand-in-hand with CSA. The Colorado State University Laboratory of Precision Agriculture (CSU-PA) is conducting research on CSA practice... L. Longchamps, R. Khosla, R. Reich

32. Field Phenotyping Infrastructure in a Future World - Quantifying Information on Plant Structure and Function for Precision Agriculture and Climate Change

Phenotyping in the field is an essential step in the phenotyping chain. Phenotyping begins in the well-defined, controlled conditions in laboratories and greenhouses and extends to heterogeneous, fluctuating environments in the field. Field measurements represent a significant reference point for the relevance of the laboratory and greenhouse approaches and an important source of information on potential mechanisms and constraints for plant performance tested at controlled conditions. In this... O. Muller, M.P. Cendrero mateo, H. Albrecht, F. Pinto, M. Mueller-linow, R. Pieruschka, U. Schurr, U. Rascher, A. Schickling, B. Keller

33. Sensor-based Variable-rate N on Corn Reduced Nitrous Oxide Emissions

More nitrogen fertilizer is applied to corn than to all other U.S. crops combined, contributing to atmospheric heat trapping when nitrous oxide is produced.  Higher nitrogen rate is well known to increase nitrous oxide emissions, and earlier N application time may increase the window during which nitrous oxide can form.  An experiment was initiated in 2012 comparing nitrogen management and drainage effects on corn yield and nitrous oxide emissions.  Two nitrogen treatments... P. Scharf

34. Climate Sensitivity Analysis on Maize Yield on the Basis of Precision Crop Production

In this paper by prediction we have defined maize yield in precision plant production technologies according to five different climate change scenarios (Ensembles Project) until 2100 and in one scenario until 2075 using DSSAT v. 4.5.0. CERES-Maize decision support model. Sensitivity analyses were carried out. The novelty of the method presented here is that precision, variable rate technologies from relatively small areas (in our case 2500 m2) enable a large amount of data to be co... A. Nyeki, G. Milics, A.J. Kovacs, M. Neményi, J. Kalmar

35. 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

36. 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

37. 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

38. 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