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Bodnár, K.B
Brant, V
Bonomi, A
Barnes, E
Butts, C
Walsh, K
Berti, M
Besga, G
Davadant, P
Hauser, J.S
Hongo, C
Honma, K
Neupane, D
Yongtao, L
Drexler, D
Holpp, M
Wieland, S
Husni, M.H
Gornushkin, I
Dworak, V
Bier, J
Roberts, R.K
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Authors
Hongo, C
Furukawa, T
Sigit, G
Maki, M
Honma, K
Yoshida, K
Oki, K
Shirakawa, H
Thompson, N.M
Larson, J.A
English, B.C
Lambert, D.M
Roberts, R.K
Velandia, M
Wang, C
Hongo, C
Niwa, K
Unamunzaga, O
Castell, A
Besga, G
Perez-Parmo, R
Aizpurua, A
Larson, J.A
Mooney, D.F
Roberts, R.K
English, B.C
Velandia, M
Mooney, D.F
Roberts, R.K
English, B.C
Larson, J.A
Lambert, D.M
Larkin, S.L
Marra, M.C
Rejesus, R
Martin, S.W
Paxton, K.W
Mishra, A
Wang, C
Segarra, E
Reeves, J.M
Harper, D.C
Lambert, D.M
English, B.C
Larson, J.A
Roberts, R.K
Velandia, M
Mooney, D.F
Larkin, S.L
Parajulee, M
Neupane, D
Wang, C
Carroll, S
Shrestha, R
Linker, R
Payne, A
Walsh, K
Cohen, O
Tamura, E
Aijima, K
Niwa, K
Nagata, O
Wakabayashi, K
Hongo, C
Hongo, C
Ogasawara, C
Tamura, E
Sigit, G
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Maharlooei, M
Bajwa, S
Mireei, S.A
Shirzadi, A
Sivarajan, S
Berti, M
Nowatzki, J
Balasundram, S.K
Husni, M.H
Holpp, M
Anken, T
Seatovic, D
Grueninger, R
Hueppi, R
Sanches, G.M
Cardoso, T.F
Chagas, M.F
Luciano, A.C
Duft, D.G
Magalhães, P.S
Franco, H.C
Bonomi, A
Bodnár, K.B
Nagy, J
Gombos, B
Kroulik, M
Brant, V
Zabransky, P
Chyba, J
Krcek, V
Skerikova, M
Cullop, J
Griffin, T.W
Ibendahl, G
Barnes, E
Shockley, J
Devine, J
Issaka, F
Yongtao, L
Jiuhao, L
Buri, M.M
Asenso, E
Sheka Kanu, A
Zhao, Z
Cammarano, D
Drexler, D
Hinsinger, P
Martre, P
Draye, X
Sessitsch, A
Pecchioni, N
Cooper, J
Helga, W
Voicu, A
Hauser, J.S
Wagner, P
Hongo, C
Isono, S
Sigit, G
Utoyo, B
Tamura, E
Sridharan, S
Sornapudi, S
Hu, Q
Kumpatla, S
Bier, J
Kang, C
Karkee, M
Zhang, Q
Shcherbatyuk, N
Davadant, P
Keller, M
Gallios, I
Vellidis, G
Butts, C
Wieland, S
Kelley, A
Topics
Remote Sensing Applications in Precision Agriculture
Profitability, Sustainability and Adoption
Remote Sensing Applications in Precision Agriculture
Precision Nutrient Management
Profitability, Sustainability, and Adoption
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Food Security and Precision Agriculture
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Traceability
Spatial and Temporal Variability in Crop, Soil and Natural Resources
Precision Agriculture and Global Food Security
Smart Weather for Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Robotics, Guidance and Automation
Land Improvement and Conservation Practices
Big Data, Data Mining and Deep Learning
Applications of Unmanned Aerial Systems
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
Industry Sponsors
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2018
2022
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Filter results27 paper(s) found.

1. Estimation Of Sugar Beet Yield Brfore Harvesting Using Meteorological Data And Spot Satellite Data

    In Japan, sugar beet is only cultivated in Hokkaido, the northernmost island. The area of sugar beet cultivation in Tokachi District is 30,000ha, which is equal to about 45% of the total national production area. Because sugar beet is suited to cool weather conditions, it is an important rotation crop in Hokkaido. The production of beet sugar in Hokkaido is about 640,000 tons, which is 75... C. Hongo, K. Niwa

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

  Knowledge of spatial variability of soil nutrient contents is very important to design a fertilization strategy based on the needs of the vine. Matching fertilization and nutritional plant needs is very important due to the influence of nutritional status of vineyards on productive and qualitative factors. The aim of this work was to study the spatial and vertical variability of P, K and Mg in a vineyard soil by two methods: (i) the grid sampling at three depth ranges (0-30,... O. Unamunzaga, A. Castell, G. Besga, R. Perez-parmo, A. Aizpurua

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

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

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

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

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

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

6. 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

7. Estimation of Rice Yield from MODIS Data in West Java, Indonesia

Chiharu Hongo1*, Takaaki Furukawa1, Gunardi Sigit2, Masayasu Maki3, Koki Honma3,... C. Hongo, T. Furukawa, G. Sigit, M. Maki, K. Honma, K. Yoshida, K. Oki, H. Shirakawa

8. The Adoption of Information Technologies and Subsequent Changes in Input Use in Cotton Production

The use of precision farming has become increasingly important in cotton production. It allows farmers to take advantage of knowledge about infield variability by applying expensive inputs at levels appropriate to crop needs. Essential to the success of the precision... N.M. Thompson, J.A. Larson, B.C. English, D.M. Lambert, R.K. Roberts, M. Velandia, C. Wang

9. Detection Of Fruit In Canopy Night-Time Images: Two Case Studies With Apple And Mango

Reliable estimation of the expected yield remains a major challenge in orchards. In a recent work we reported the development of an algorithm for estimating the number of fruits in images of apple trees acquired in natural daylight conditions. In the present work we tested this approach with night-time images of similar apple trees and further adapted this approach to night-time images of mango trees. Working with the apple images required only... R. Linker, A. Payne, K. Walsh, O. Cohen

10. Creation Of Prescription For Optimal Nitrogen Fertilization Through Evaluation Of Soil Carbon Amount Using Remotely Sensed Data

    In these years, drastic increase of agricultural production costs has been induced, which was triggered by the sharp rise of costs relating to agricultural production materials such as fertilizers and oil. In Japan, the substantial negative influence is anticipated to spread over to management of the farmers particularly  in Hokkaido, the northern part of Japan. As one of the measures against this influence, a plan of effective fertilizer application and also... E. Tamura, K. Aijima, K. Niwa, O. Nagata, K. Wakabayashi, C. Hongo

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

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

12. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

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

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

14. Application of Radio Frequency Identification Technology in Agriculture: a Case with Dragon Fruit

Global and local concerns about food safety are turning food traceability into a trade requirement. Typically, a Food Traceability Scheme (FTS) discloses information about food production and its distribution process. A reliable FTS will increase consumer trust in the quality and safety of farm produce. In Malaysia, dragon fruit is a profitable commodity that is growing in export value. Hence, dragon fruit is an excellent candidate for FTS solution development.  ... S.K. Balasundram, M.H. Husni

15. 3d Object Recognition, Localization and Treatment of Rumex Obtusifolius in Its Natural Environment

Rumex obtusifolius is one of the most highly competitive and persistent sorts of weed in agriculture. An automatic recognition and plant-treatment system is currently under development as an alternative treatment technique. An infrared-laser triangulation sensor and a high-resolution smart camera are used to generate 3D images of the weeds and their natural environment. In a segmentation process, contiguous surface patches are separated from one other. These 3D surface patches... M. Holpp, T. Anken, D. Seatovic, R. Grueninger, R. Hueppi

16. 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

17. 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

18. Machine Monitoring As a Smartfarming Concept Tool

Current development trends are associated with the digitization of production processes and the interconnection of individual information layers from multiple sources into common databases, contexts and functionalities. In order to automatic data collection  of machine operating data, the farm tractors were equipped with monitoring units ITineris for continuous collection and transmission of information from tractors CAN Bus. All data sets are completed with GPS location data. Acreage... M. Kroulik, V. Brant, P. Zabransky, J. Chyba, V. Krcek, M. Skerikova

19. Economics of Swarm Bot Profitability for Cotton Harvest

Improved equipment management is one way which producers can increase profits. For cotton, this is especially true due to specialized equipment used for the sole purpose of harvest. Questions are raised regarding a way to either reduce or replace traditional cotton pickers. The main alternative being discussed is an investment in autonomous “swarm bots” to replace traditional equipment. Swarm bots are fully automated robots tasked with the responsibility of picking cotton one row at... J. Cullop, T.W. Griffin, G. Ibendahl, E. Barnes, J. Shockley, J. Devine

20. Characterization of Soil Properties, Nutrient Distribution and Rice (Oryza Sativa.) Productivity As Influenced by Tillage Methods in a Typical Gleysols

Global emphasis and interest in conservation Tillage in agricultural soils has tremendously increased in the last few years, especially no tillage with its potential to improve soil physicochemical properties, reduce nutrient leaching as well as improve crop productivity in a more sustainable manner.  Several questions still exist with regard to the true role of no tillage in improving soil fertility. A two year field study was conducted to characterize the effects of different tillage methods... F. Issaka, L. Yongtao, L. Jiuhao, M.M. Buri, E. Asenso, A. Sheka kanu, Z. Zhao

21. Shared Protocols and Data Template in Agronomic Trials

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

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

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

23. Application of Drone Data to Assess Damage Intensity of Bacterial Leaf Blight Disease on Rice Crop in Indonesia

The Government of Indonesia has launched agricultural insurance program since 2016. A key in agricultural insurance is damage assessment which is required to be as precise, quick, quantitative and inexpensive as possible. Current method is to inspect the damage by human eyes of specialist having experiences. This method, however, costs much and is difficult to estimate disease infected fields precisely in wide area. So, there is increasing need to develop effective, simplified and low cost method... C. Hongo, S. Isono, G. Sigit, B. Utoyo, E. Tamura

24. A Generative Adversarial Network-based Method for High Fidelity Synthetic Data Augmentation

Digital Agriculture has led to new phenotyping methods that use artificial intelligence and machine learning solutions on image and video data collected from lab, greenhouse, and field environments. The availability of accurately annotated image and video data remains a bottleneck for developing most machine learning and deep learning models. Typically, deep learning models require thousands of unique samples to accurately learn a given task. However, manual annotation of a large dataset will... S. Sridharan, S. Sornapudi, Q. Hu, S. Kumpatla, J. Bier

25. Diagnosis of Grapevine Nutrient Content Using Proximal Hyperspectral Imaging

Nutrient deficiencies on grapevines could affect the fruit yield and quality, which is a major concern in vineyards. Nutrient deficiencies may be recognizable by foliar symptoms that vary by mineral nutrient and stress severity, but it is too late to manage when visible deficiency symptoms become apparent. The nutrient analysis in the laboratory is the way to get an accurate result, but it is time and cost-intensive. The differences in leaf nutrient levels also alter spectral characteristics outside... C. Kang, M. Karkee, Q. Zhang, N. Shcherbatyuk, P. Davadant, M. Keller

26. Making Irrigator Pro an Adaptive Irrigation Decision Support System

Irrigator Pro is a public domain irrigation scheduling model developed by the USDA-ARS National Peanut Research Laboratory. The latest version of the model uses either matric potential sensors to estimate the plant’s available soil water or manual data input. In this project, a new algorithm is developed, which will provide growers and consultants with much more flexibility in how they can feed data to the model. The new version will also run with Volumetric Water Content sensors, giving... I. Gallios, G. Vellidis, C. Butts

27. EarthScout, GBC

EarthScout is a precision remote sensor technology that provides farmers and researchers with reliable data in real time, straight from your field to your desktop and mobile devices. In season data allows users to access current conditions for smarter decision making in irrigation and nitrogen management. EarthScout is a crop agnostic tool that is used in any soil type and climate. Our plug and play field sensors need no calibration and set up only takes about 5 minutes. There are no data subscription... S. Wieland, A. Kelley