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Hoffmann, W.C
Hopkins, B
Zillmann, E
Nagy, J
Kaiser, D
Grisham, M.P
Sekhon, B.S
Stępień, M
Saiz-Rubio, V
Avanzi, J.C
Franco, H.C
Kodaira, M
SEYHAN, G.T
Evans, F.H
Webber III, C.L
Gimenez, V
Ferraz Pueyo, C
Knight, C.W
Acuna, T
Nakazawa, P.H
Kim, H
Kantipudi, K
Zhang, Y
Figueiredo, G.K
Anderson, L
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Authors
Sekhon, B.S
Mukherjee, J
Sharma, A
Thind, S.K
Kaur, R
Makkar, M.S
Rodrigues Jr., F.A
Magalhães, P.S
Franco, H.C
Cerri, D.G
Chung, S
Kim, K
Kim, H
Choi, J
Zhang, Y
Kang, S
Han, K
Hur, S
Kanda, R
Kodaira, M
Shibusawa, S
Shibusawa, S
Ninomiya, K
Kodaira, M
Zainal Abidin, M.B
Shibusawa, S
Ohaba, M
Li, Q
Kodaira, M
Khalid, M.B
Shibusawa, S
Ohaba, M
Zainal Abidin, M.B
Kodaira, M
Li, Q
Bortolon, L
Borghi, E
Luchiari Junior, A
Bortolon, E.S
Freitas, A.A
Inamasu, R.Y
Avanzi, J.C
Ohaba, M
Zainal Abidin, M.B
Li, Q
Shibusawa, S
Kodaira, M
Osato, K
Fusamura, R
Shibusawa, S
Kodaira, M
Huang, Y
Hoffmann, W.C
Lan, Y
Thomson, S.J
Fritz, B.K
Sulastri, N
Shibusawa, S
Kodaira, M
Kodaira, M
NAGAMI, Y
Shibusawa, S
KANDA, R
Kaho, T
Kodaira, M
Shibusawa, S
Kodaira, M
Shibusawa, S
Ninomiya, K
Lan, Y
Zhang, H
Yang, C
Martin, D
Lacey, R
Huang, Y
Hoffmann, W.C
Moulton, P
Lan, Y
Hoffmann, W.C
Westbrook, J
Zaller, M
Borghi, E
Luchiari Junior, A
Bortolon, L
Bortolon, E.S
Inamasu, R.Y
Bernardi, A.C
Avanzi, J.C
Kodaira, M
Shibusawa, S
Shibusawa, S
Kodaira, M
Kana, I
Baharom, S.N
Umeda, H
Shibusawa, S
Li, Q
Usui, K
Kodaira, M
Shibusawa, S
Umeda, H
Usui, K
Kodaira, M
Li, Q
Makkar, M.S
Kaul, A
Kumar, R
Sharma, A
Sekhon, B.S
Pannu, C.S
Sanches, G.M
Graziano Magalhães, P.S
Franco, H.C
Remacre, A.Z
Graziano Magalhães, P.S
Sanches, G.M
Kolln, O.T
Franco, H.C
Braunbeck, O.A
Driemeier, C
Kolln, O.T
Sanches, G.M
Rossi Neto, J
Castro, S.G
Mariano, E
Otto, R
Inamasu, R
Magalhães, P.S
Braunbeck, O.A
Franco, H.C
Castro, S.G
Kolln, O.T
Nakao, H.S
Franco, H.C
Braunbeck, O
Graziano Magalhães, P.S
Sanches, G.M
Walsh, O.S
Samborski, S.M
Stępień, M
Gozdowski, D
Lamb, D.W
Gacek, E.S
Drzazga, T
Walsh, O.S
Samborski, S.M
Gozdowski, D
Stępień, M
Leszczyńska, E
Frotscher, K.J
Schacht, R
Smith, L
Zillmann, E
Mulla, D
Zermas, D
Kaiser, D
Bazakos, M
Papanikolopoulos, N
Stanitsas, P
Morellas, V
Mulla, D
Laacouri, A
Kaiser, D
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Jeon, C
Kim, H
Han, X
Moon, H
Yegul, U
TALEBPOUR, B
TÜRKER, U
EMİNOĞLU, B.M
SEYHAN, G.T
ÇOLAK, A
Souza, W.J
Akune, V.S
Benez, S.H
Citon, L.C
Nakazawa, P.H
Santana Neto, A.J
Castro, S.G
Sanches, G.M
Cardoso, G.M
Silva, A.E
Franco, H.C
Magalhães, P.S
Souza, W.J
Benez, S.H
Nakazawa, P.H
Santana Neto, A.J
Citon, L.C
Akune, V.S
Sanches, G.M
Kolln, O.T
Franco, H.C
Magalhaes, P.S
Duft, D.G
Johnson, R.M
Grisham, M.P
Sanches, G.M
Amaral, L.R
Pitrat, T
Brasco, T
Magalhaes, P.S
Duft, D.G
Franco, H.C
Webber III, C.L
Taylor, M.J
Shrefler, J.W
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Sanches, G.M
Magalhães, P.S
Franco, H.C
Remacre, A.Z
Saiz-Rubio, V
Diago, M
Tardaguila, J
Gutierrez, S
Rovira-Más, F
Alves, F
Bodnár, K.B
Nagy, J
Gombos, B
Kantipudi, K
Lai, C
Min, C
Chiang, R.C
Kodaira, M
Shibusawa, S
Knight, C.W
Cosby, A
Trotter, M
Evans, F.H
Andrew, J
Scanlan, C
Cook, S
Rátonyi, T
Ragán, P
Sulyok, D
Nagy, J
Harsányi, E
Vántus, A
Csatári, N
Li, Q
Sugihara, T
Kodaira, M
Shibusawa, S
Ragán, P
Harsányi, E
Nagy, J
Ágnes, T
Rátonyi, T
Vántus, A
Csatári, N
Nándor, C
Rátonyi, T
Harsányi, E
Ragán, P
Hagymássy, Z
Nagy, J
Vántus, A
Caron, J
Anderson, L
Sauvageau, G
Gendron, L
Cabrera Dengra, M
Ferraz Pueyo, C
Pajuelo Madrigal, V
Moreno Heras, L
Inunciaga Leston, G
Fortes, R
Pereira, F.R
Dos Reis, A.A
Freitas, R.G
Oliveira, S.R
Amaral, L.R
Figueiredo, G.K
Antunes, J.F
Lamparelli, R.A
Moro, E
Pereira, N.D
Magalhães, P.S
Pereira, F.R
Lima, J.P
Freitas, R.G
Dos Reis, A.A
Amaral, L.R
Figueiredo, G.K
Lamparelli, R.A
Pereira, J.C
Magalhães, P.S
Kerry, R
Shumate, S
Ingram, B
Hammond, K
Gunther, D
Jensen, R
Schill, S
Hansen, N
Hopkins, B
Lingua, L.N
Carcedo, A
Gimenez, V
Maddonni, G
Ciampitti, I
Cano, P.B
CARCEDO, A
Gomez, F
Hernandez, C
Gimenez, V
Ciampitti, I
Topics
Remote Sensing Applications in Precision Agriculture
Modeling and Geo-statistics
Precision Horticulture
Engineering Technologies and Advances
Proximal Sensing in Precision Agriculture
Profitability, Sustainability and Adoption
Engineering Technologies and Advances
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Modeling and Geo-statistics
Profitability, Sustainability and Adoption
Proximal Sensing in Precision Agriculture
Sensor Application in Managing In-season CropVariability
Spatial Variability in Crop, Soil and Natural Resources
Precision Nutrient Management
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Agricultural Education
Engineering Technologies and Advances
Decision Support Systems in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Big Data Mining & Statistical Issues in Precision Agriculture
Proximal Sensing in Precision Agriculture
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Precision Agriculture and Global Food Security
Site-Specific Nutrient, Lime and Seed Management
Robotics, Guidance and Automation
Smart Weather for Precision Agriculture
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Education and Outreach in Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Drainage Optimization and Variable Rate Irrigation
Precision Dairy and Livestock Management
Precision Horticulture
Profitability and Success Stories in Precision Agriculture
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Drainage Optimization and Variable Rate Irrigation
Data Analytics for Production Ag
Country Representative Report
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
2024
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Filter results61 paper(s) found.

1. Development Of Unmanned Aerial Vehicles For Site-specific Crop Production Management

... Y. Huang, W.C. Hoffmann, Y. Lan, S.J. Thomson, B.K. Fritz

2. 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 soil... N. Sulastri, S. Shibusawa, M. Kodaira

3. 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 performed... M. Kodaira, Y. Nagami, S. Shibusawa, R. Kanda

4. Prediction Of Soil Moisture Content And Penetration Resistance Using Real-time Soil Meter

A real-time soil compaction meter that refers to the air injection subsoiler, is developed.  The final goal is to predict standarized soil compaction that is converted from soil moisture content, working resistance and working speed.  This experiment confirmed performance of predicting the soil moisture content and of measuring the working resistance was conducted.  The equipments of the meter are a working resistance measurement device received from the soil and a spectroscope... T. Kaho, M. Kodaira, S. Shibusawa

5. 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

6. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field Mapping

  A wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by synthesizing... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton

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

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

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. Using Soil Attributes To Model Sugar Cane Quality Parameters

The crop area of sugar cane production in Brazil has increased substantially in the last few years, especially to meet the global bioethanol demand. Such increasing production should take place not only in new sugar cane crop areas but mainly with the goal of improving the quality of raw material like sugar content (Pol). Hence, models that can describe the behaviour of the quality parameters of sugar cane may be important to understand the effects of the soil attributes on those parameters. The... F.A. Rodrigues jr., P.S. Magalhães, H.C. Franco, D.G. Cerri

10. Remote Control System for Greenhouse Environment Using Mobile Devices

Protected crop production facilities such as greenhouse and plant factory have drawn interest and the area is increasing in Korea as well as in other countries in the world. Remote... S. Chung, K. Kim, H. Kim, J. Choi, Y. Zhang, S. Kang, K. han, S. Hur

11. Measuring Error on Working Depth of Real-time Soil Sensor

This paper described about the measuring error on working depth of the Real-time soil sensor (RTSS). It is necessary for accurately evaluating to observe the variation on the working depth, because the RTSS run in various real field conditions, such as soft or hard and even or uneven, and the RTSS has various using objective. In this paper, the RTSS run on asphalt with steps while the three-point hitch was free and position-controlled. In position-controlled, the measuring depth that is the... R. Kanda, M. Kodaira, S. Shibusawa

12. Nineteen-Soil-Parameter Calibration Models and Mapping for Upland Fields Using the Real-Time Soil Sensor

In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for soil management, crop quality control using fertilizer, manure and compost, and variable-rate input for soil... S. Shibusawa, K. Ninomiya, M. Kodaira

13. Transient Water Flow Model in a Soil-Plant System for Subsurface Precision Irrigation

The spatial variability of plant-water characteristic in the soil is still unclear. This limits the attempt to model the soil-plant-atmosphere system with this factor. Understanding the non-steady water flow along the soil-plant component is essential to understand their spatial variability.... M.B. Zainal abidin, S. Shibusawa, M. Ohaba, Q. Li, M. Kodaira, M.B. Khalid

14. Water Distribution Response in a Soil-Root System for Subsurface Precision Irrigation

A subsurface capillary irrigation system with a water source buried in a soil has been developed for precision irrigation. This system has advantages in the efficient irrigation to save much water and the real time measurement of evapotranspiration of plants. Creating this new subsurface capillary... S. Shibusawa, M. Ohaba, M.B. Zainal abidin, M. Kodaira, Q. Li

15. Adoption and Tendencies of Precision Agriculture Technologies in the Tocantins State, Brazil

Although precision agriculture is widely used throughout Brazilian crop production, it has not been used to increase the efficiency use of agricultural inputs. Besides, technologies available have not been... L. Bortolon, E. Borghi, A. Luchiari junior, E.S. Bortolon, A.A. Freitas, R.Y. Inamasu, J.C. Avanzi

16. Adaptive Control of Capillary Water Flow Under Modified Subsurface Irrigation Based on a SPAC Model

Soil moisture in a rhizosphere of a tomato is controlled adaptively based on a simple soil-plant-atmosphere continuum (SPAC) model. The water flow from a soil through a plant to the atmosphere is governed by the analogous rule of the SPAC model. In our experiment, we assume that plant transpiration is only affected by the water-potential of air when the soil moisture... M. Ohaba, M.B. zainal abidin, Q. Li, S. Shibusawa, M. Kodaira, K. Osato

17. An Approach to Making Non-Smell Composting System : Case Study in Fuchu

The project to form ... R. Fusamura, S. Shibusawa, M. Kodaira

18. Adoption Level Of Precision Agriculture For Brazilian Farmers - 2011/12 Crop Year

Although Precision Agriculture (PA) concepts and technologies are widespread in Brazil, its application still little used in some important crop production regions. The purpose of this study was to survey the current adoption level of PA by printed and online questionnaire. We started making a specific questionnaire to farmers and PA service companies using some technology related to PA. The questionnaires were developed based on the methodology of Whipker and Akridge (2009),... E. Borghi, A. Luchiari junior, L. Bortolon, E.S. Bortolon, R.Y. Inamasu, A.C. Bernardi, J.C. Avanzi

19. Soil Mapping And Modeling On Twenty-Five Ingredients Using A Real-Time Soil Sensor

Visible and near-infrared spectroscopy is an effective measurement method for estimating many soil ingredients at once. In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for soil management, crop quality control using fertilizer, manure and compost, and variable-rate input for soil variability in a field. We obtained Twenty-five calibration models based on Vis-NIR (305 - 1700 nm) underground soil reflectance... M. Kodaira, S. Shibusawa

20. Comparison Of Calibration Models Developed For A Visible-Near Infrared Real-Time Soil Sensor

The visible-near infrared (Vis-NIR) based real-time soil sensor (RTSS) is found to be a great tool for determining distribution of various soil properties for precision agriculture purposes. However, the developed calibration models applied on the collected spectra for prediction of soil properties were site-specific (local). This is found to be less practical since the RTSS needs to be calibrated separately for every field. General calibration approach is expected to minimize... S. Shibusawa, M. Kodaira, I. Kana, S.N. Baharom

21. 3D Map in the Depth Direction of Field for Precision Agriculture

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

22. Using A Potable Spectroradiometer For In-Situ Measurement Of Soil Properties In A Slope Citrus Field

     In precision agriculture, rapid, non-destructive, cost-effective and convenient soil analysis techniques are needed for crop and soil management. However, the spatial variability of soil properties is consider to be high cost and time consuming to characterize using traditional soil analysis method. To achieve cost and time reduction, the potential benefits of in-situ measurement of soil spectra have been recognized.     ... S. Shibusawa, H. Umeda, K. Usui, M. Kodaira, Q. Li

23. 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

24. Multivariate Geostatistics As A Tool To Estimate Physical And Chemical Soil Properties With Reduced Sampling In Area Planted With Sugarcane

Precision Agriculture (PA) can be described as a set of tools and techniques applied to agriculture in order to enable localized production management, considering the spatial and temporal variability of crop fields. Among the numerous existing tools, one of the most important ones is the use of geostatistics, whose main objective is the description of spatial patterns and estimation data in non-sampled places. Nowadays, one of the most limiting factors to the... G.M. Sanches, P.S. Graziano magalhaes, H.C. Franco, A.Z. Remacre

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

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

26. Optical Sensors To Predict Nitrogen Demand By Sugarcane

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

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

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

28. Winter Wheat Genotype Effect on Canopy Reflectance: Implications for Using NDVI for In-season Nitrogen Topdressing Recommendations

Active optical sensors (AOSs) measure crop reflectance at specific wavelengths and calculate vegetation indices (VIs) that are used to prescribe variable N fertilization. Visual observations of winter wheat (Triticum aestivum L.) plant greenness and density suggest that VI values may be genotype specific. Some sensor systems use correction coefficients to eliminate the effect of genotype on VI values. This study was conducted to assess the effects of winter wheat cultivars and growing conditions... O.S. Walsh, S.M. Samborski, M. Stępień, D. Gozdowski, D.W. Lamb, E.S. gacek, T. Drzazga

29. On-Farm Evaluation of an Active Optical Sensor Performance for Variable Nitrogen Application in Winter Wheat

Winter wheat (Triticum aestivum L.) represents almost 50% of total cereal production in the European Union, accounting for approximately 25% of total mineral nitrogen (N) fertilizer applied to all crops. Currently, several active optical sensor (AOS) based systems for optimizing variable N fertilization are commercially available for a variety of crops, including wheat. To ensure successful adoption of these systems, definitive measurable benefits must be demonstrated. Nitrogen management strategies... O.S. Walsh, S.M. Samborski, D. Gozdowski, M. Stępień, E. Leszczyńska

30. Planet Labs' Monitoring Solution in Support of Precision Agriculture Practices

Satellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann

31. Early Detection of Nitrogen Deficiency in Corn Using High Resolution Remote Sensing and Computer Vision

The continuously growing need for increasing the production of food and reducing the degradation of water supplies, has led to the development of several precision agriculture systems over the past decade so as to meet the needs of modern societies. The present study describes a methodology for the detection and characterization of Nitrogen (N) deficiencies in corn fields. Current methods of field surveillance are either completed manually or with the assistance of satellite imaging, which offer... D. Mulla, D. Zermas, D. Kaiser, M. Bazakos, N. Papanikolopoulos, P. Stanitsas, V. Morellas

32. Comparison Between High Resolution Spectral Indices and SPAD Meter Estimates of Nitrogen Deficiency in Corn

Low altitude remote sensing provides an ideal platform for monitoring time sensitive nitrogen status in crops. Research is needed however to understand the interaction between crop growth stage, spatial resolution and spectral indices derived from low altitude remote sensing. A TetraCam camera equipped with six bands including the red edge and near infrared (NIR) was used to investigate corn nitrogen dynamics. Remote sensing data were collected during the 2013 and 2014 growing seasons at four... D. Mulla, A. Laacouri, D. Kaiser

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

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

34. Development of a Crop Edge Line Detection Algorithm Using a Laser Scanner for an Autonomous Combine Harvester

The high cost of real-time kinematic (RTK) differential GPS units required for autonomous guidance of agricultural machinery has limited their use in practical auto-guided systems especially applicable to small-sized farming conditions. A laser range finder (LRF) scanner system with a pan-tilt unit (PTU) has the ability to create a 3D profile of objects with a high level of accuracy by scanning their surroundings in a fan shape based on the time-of-flight measurement principle. This paper describes... C. Jeon, H. Kim, X. Han, H. Moon

35. Development of Sensor Reflection Indices To Predict Yield And Protein Content Based On In-Season N Status

Environmental and economic demands make it necessary for farmers to adopt   management systems that improve Nitrogen Use Efficiency. The premium paid to producers has made farmers striving for maximum grain protein levels because protein is a very important quality component of grains and an important attribute in the market place. The protein content of wheat grains approximately ranges from 8 to 20%. The optimization of nitrogen (N) fertilization is the object of intense research efforts... U. Yegul, B. Talebpour, U. TÜrker, B.M. EmİnoĞlu, G.T. Seyhan, A. Çolak

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

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

37. Use of Crop Canopy Reflectance Sensor in Management of Nitrogen Fertilization in Sugarcane in Brazil

Given the difficulty to determine N status in soil testing and lack of crop parameters to recommend N for sugarcane in Brazil raise the necessity of identify new methods to find crop requirement to improve the N use efficiency. Crop canopy sensor, such as those used to measure indirectly chlorophyll content as N status indicator, can be used to monitor crop nutritional demand. The objective of this experiment was to assess the nutritional status of the sugarcane fertilized with different nitrogen... S.G. Castro, G.M. Sanches, G.M. Cardoso, A.E. Silva, H.C. Franco, P.S. Magalhães

38. Spatial Variability and Correlations Between Soil Attributes and Productivity of Green Corn Crop

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

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

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

40. Assessing the Variability of Red Stripe Disease in Louisiana Sugarcane Using Precision Agriculture Methods

Symptoms of red stripe disease caused by Acidovorax avenae subsp. avenae in Louisiana between 1985 and 2010 were limited to the leaf stripe form which caused no apparent yield loss.  During 2010, the more severe top rot form was observed, and a study was initiated to investigate the distribution of red stripe in the field and determine its effects on cane and sugar yields. Two fields of cultivar HoCP 00-950, one plant-cane (PC) crop and one first-ratoon (FR) crop, affected by top rot were... R.M. Johnson, M.P. Grisham

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

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

42. Precision Placement of Corn Gluten Meal for Weed Control in Organic Vegetable Production

Organic vegetable producers rank weeds as one of their most troublesome, time consuming, and costly production problems. As a result of the limited number of organically approved weed control herbicides, the precision placement of these materials increases their potential usefulness in organic production systems. As a non-selective preemergence or preplant-incorporated herbicide, corn gluten meal (CGM) inhibits root development; decreases shoot length, and reduces plant survival. The development... C.L. Webber iii, M.J. Taylor, J.W. Shrefler

43. Economic and Environmental Impacts in Sugarcane Production to Meet the Brazilian Ethanol Demands by 2030: The Role of Precision Agriculture

The agreement signed at COP-21 reaffirms the vital compromise of Brazil with sugarcane and ethanol production. To meet the established targets, the ethanol production should be 54 billion liters in 2030. From the agronomic standpoint, two alternatives are possible; increase the planted area and/or agricultural yield. The present study aimed to evaluate the economic and environmental impacts in sugarcane production meeting the established targets in São Paulo state. In this context, were... G.M. Sanches, T.F. Cardoso, M.F. Chagas, A.C. Luciano, D.G. Duft, P.S. Magalhães, H.C. Franco, A. Bonomi

44. Potential of Apparent Soil Electrical Conductivity to Describe Soil Spatial Variability in Brazilian Sugarcane Fields

The soil apparent electrical conductivity (ECa) has been highlighted in the literature as a tool with high potential to map the soil fertility of fields. However, sugarcane fields still lack results that show the applicability of this information to define the soil spatial variability and its fertility conditions. The objective of the present paper was to provide a comprehensive assessment of the relationship between ECa, evaluated by electromagnetic induction (EMI) sensor, and the spatial variability... G.M. Sanches, P.S. Magalhães, H.C. Franco, A.Z. Remacre

45. Canopy Temperature Mapping with a Vineyard Robot

The wine industry is a strategic sector in many countries worldwide. High revenues in the wine market typically result in higher investments in specialized equipment, so that producers can introduce disruptive technology for increasing grape production and quality. However, many European producers are approaching retirement age, and therefore the agricultural sector needs a way for attracting young farmers who can assure the smooth transition between generations; digital technology offers an opportunity... V. Saiz-rubio, M. Diago, J. Tardaguila, S. Gutierrez, F. Rovira-más, F. Alves

46. Correlations Between Meteorological Parameters and the Water Loss of Maize from Silking to Harvesting

The University of Debrecen provides outstanding conditions for the development of “Smart Weather for Precision Agriculture” programs. The reliability of research is provided by the Polyfactoral Long-term Field Experiments of Debrecen (hybrid x fertilisation x plant density x tillage x irrigation) established in 1983. Within this research program, it is possible to examine various crop cultures, cultivars and hybrids under changing natural, environmental and weather circumstances,... K.B. Bodnár, J. Nagy, B. Gombos

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

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

48. Two-Layer Multiple Soil-Property Mapping Measured with a Real-Time Soil Sensor

We obtained calibration models for 32 soil properties based on Vis-NIR (350 - 1700 nm) underground soil diffuse reflectance spectra collected using a real-time soil sensor (SAS3000) with a DGPS system, in order to generate soil property maps. We have previously demonstrated one-layer soil maps for soil management decision making by growers; however, for effective crop management, growers often wish to obtain complex layer information for their fields. Thus, in the present study, we measured two-layer... M. Kodaira, S. Shibusawa

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

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

50. Modifying Agro-Economic Models to Predict Effects of Spatially Varying Nitrogen on Wheat Yields for a Farm in Western Australia

Agricultural research in broadacre farming in Western Australia has a strong history, resulting in a significant public resource of knowledge about biophysical processes affecting crop performance. However, translation of this knowledge into improved on-farm decision making remains a challenge to the industry. Online and mobile decision support tools to assist tactical farm management decisions are not widely adopted, for reasons including: (1) they take too much time and training to learn; and... F.H. Evans, J. Andrew, C. Scanlan, S. Cook

51. Evaluation of Strip Tillage Systems in Maize Production in Hungary

Strip tillage is a form of conservation tillage system. It combines the benefits of conventional tillage systems with the soil-protecting advantages of no-tillage. The tillage zone is typically 0.25 to 0.3 m wide and 0.25 to 0.30 m deep. The soil surface between these strips is left undisturbed and the residue from the previous crop remain on the soil surface. The residue-covered area reaches 60-70%. Keeping residue on the surface helps prevent soil structure and reduce water loss from the soil.... T. Rátonyi, P. Ragán, D. Sulyok, J. Nagy, E. Harsányi, A. Vántus, N. Csatári

52. Water Use Efficiency of Precision Irrigation System Under Critical Water-Saving Condition

Non-transpiration water loss is often neglected when evaluating water use efficiency (WUE) of precision irrigation system, due to the difficulties in determining water loss from the root zone. The objective of this study is to investigate the feasibility of a new water saving approach by controlling soil water retention around root zone during the plant growth. We grew two tomato cultivars (Anemo, Japanese variety) in an environmental controlled growth chamber, with previously oven dried and sieved... Q. Li, T. Sugihara, M. Kodaira, S. Shibusawa

53. Examining the Relationship Between SPAD, LAI and NDVI Values in a Maize Long-Term Experiment

In Hungary, the preconditions for the use of precision crop production have undergone enormous development over the last five years. RTK coverage is complete in crop production areas. Consultants are increasingly using the vegetation index maps from Landsat and Sentinel satellite data, but measurements with on-site proximal plant sensors are also needed to exclude the influence of the atmosphere. The aim of our studies was to compare the values measured by proximal plant sensors in the... P. Ragán, E. Harsányi, J. Nagy, T. Ágnes, T. Rátonyi, A. Vántus, N. Csatári

54. The Spread of Precision Livestock Farming Technology at Dairy Farms in East Hungary

During the survey, 25 dairy farms were examined in East Hungary in Hajdú-Bihar (H-B) County between 2017 and 2018 by methodical observation and oral interviews with the farm managers, about the spread of Precision Livestock Farming (PLF) technologies. Among Holstein Friesian dairy farms in the County 60% were questioned, and the representativity was above 47 percent ins each size category. Nine precision farming equipment were examined on the farms: milking robot or robotic carousel milking... C. Nándor, T. Rátonyi, E. Harsányi, P. Ragán, Z. Hagymássy, J. Nagy, A. Vántus

55. Real Time Precision Irrigation with Variable Setpoint for Strawberry to Generate Water Savings

Water is a precious resource that is becoming increasingly scarce as the population grows and water resources are depleted in some locations or under increased control elsewhere, due to local availability or groundwater contamination issues. It obviously affects strawberry (Fragaria x ananassa Duch.) production in populated areas and water cuts are being imposed to many strawberry growers to save water, with limited information on the impact on crop yield. Precision irrigation technologies are... J. Caron, L. Anderson, G. Sauvageau, L. Gendron

56. Use of MLP Neural Networks for Sucrose Yield Prediction in Sugarbeet

INTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes

57. A Framework for Imputation of Missing Parts in UAV Orthomosaics Using Planetscope and Sentinel-2 Data

In recent years, the emergence of Unmanned Aerial Vehicles (UAV), also known as drones, with high spatial resolution, has broadened the application of remote sensing in agriculture. However, UAV images commonly have specific problems with missing areas due to drone flight restrictions. Data mining techniques for imputing missing data is an activity often demanded in several fields of science. In this context, this research used the same approach to predict missing parts on orthomosaics obtained... F.R. Pereira, A.A. Dos reis, R.G. Freitas, S.R. Oliveira, L.R. Amaral, G.K. Figueiredo, J.F. Antunes, R.A. Lamparelli, E. Moro, N.D. Pereira, P.S. Magalhães

58. Nitrogen Status Prediction on Pasture Fields Can Be Reached Using Visible Light UAV Data Combined with Sentinel-2 Imagery

Pasture fields under integrated crop-livestock system usually receive low or no nitrogen fertilization rates, since the expectation is that nitrogen demand will be provided by the soybean remaining straw cropped previously. However, keeping nitrogen at suitable levels in the entire field is the key to achieving sustainability in agricultural production systems. In this sense, remote sensing technologies play an essential role in nitrogen monitoring in pastures and crops. With the launch of the... F.R. Pereira, J.P. Lima, R.G. Freitas, A.A. Dos reis, L.R. Amaral, G.K. Figueiredo, R.A. Lamparelli, J.C. Pereira, P.S. Magalhães

59. Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management

The Western United States is currently experiencing a “Mega Drought”. This makes efficient water use more important than ever. Turfgrass is a major vegetation type in urban areas and performs many ecosystem services such as cooling through evapotranspiration, fixing carbon from the atmosphere and reducing wild-fire risk. There are now more acres of irrigated turfgrass (>40 million) in the USA than irrigated corn, wheat and fruit trees combined (Milesi et al., 2005). It has been... R. Kerry, S. Shumate, B. Ingram, K. Hammond, D. Gunther, R. Jensen, S. Schill, N. Hansen, B. Hopkins

60. Environmental Characterization for Rainfed Maize Production in the US Great Plains Region

Identifying regions with similar productivity and yield-limiting climatic factors enables the design of tailored strategies for rainfed maize (Zea mays L.) production in vulnerable environments. Within the United States (US) Great Plains region, rainfed maize production in Kansas is susceptible to weather fluctuations. This study aims to delimit environmental regions with similar crop growth conditions and to identify the main climatic factors limiting rainfed maize yield, using the state... L.N. Lingua, A. Carcedo, V. Gimenez, G. Maddonni, I. Ciampitti

61. Trends in Agricultural Technology Advancements: Insights from US Patent Analysis

Meeting the demand for food, fiber, and fuel production while addressing environmental concerns and enhancing societal benefits underscores the need to transition to conservation approaches and sustainable intensification pathways in current agricultural cropping systems. Technological advances in agriculture offer promising opportunities to facilitate this transition. Following this rationale, this study aims to analyze prevailing trends in agricultural technology advancements. Active patents... P.B. Cano, A. Carcedo, F. Gomez, C. Hernandez, V. Gimenez, I. Ciampitti