Proceedings

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Stenberg, M
Francisco, E
Noland, R
Leite, N.J
Kubickova, H
Strachan, I.B
Moreno Heras, L
Min, C
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Authors
Santiago, W.E
Barreto, A.R
Figueredo, D.G
Tinini, R.C
Mederos, B.T
Leite, N.J
Söderström, M
Stadig, H
Martinsson, J
Stenberg, M
Piikki, K
Kantipudi, K
Lai, C
Min, C
Chiang, R.C
Biswas, A
Vidana Gamage, D.N
Strachan, I.B
Lai, C
Min, C
Chiang, R
Hafferman, A
Morgan, S
Porter, W
Daughtry, D
Harris, G
Noland, R
Snider, J
Virk, S
Charvat, K
Berzins, R
Bergheim, R
Zadrazil, F
Macura, J
Langovskis, D
Snevajs, H
Kubickova, H
Horakova, S
Charvat Jr., K
Cabrera Dengra, M
Ferraz Pueyo, C
Pajuelo Madrigal, V
Moreno Heras, L
Inunciaga Leston, G
Fortes, R
Duarte, P.R
Ortiz, B.V
Abban-Baidoo, E
Francisco, E
de Oliveira, M.F
Nunes, L
Francisco, E
Prasad, R
Ortiz, B.V
Abban-Baidoo , E
Worosz, M
Robinette , M
O'Connor, C
Gamble, A
Topics
Precision Crop Protection
Remote Sensing Applications in Precision Agriculture
Big Data, Data Mining and Deep Learning
Drainage Optimization and Variable Rate Irrigation
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Applications of Unmanned Aerial Systems
Geospatial Data
Profitability and Success Stories in Precision Agriculture
In-Season Nitrogen Management
Extension or Outreach Education of Precision Agriculture
Type
Oral
Poster
Year
2014
2016
2018
2022
2024
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Filter results10 paper(s) found.

1. Recognition And Classification Of Weeds In Sugarcane Using The Technique Of The Bag Of Words

The production of sugar and ethanol in Brazil is very prominent economically and the reducing costs and improving the production system being necessary. The management crops operations of sugarcane and the control of weed is one of the processes that cause the greatest increase in production costs; because the competition that exists between cane plants and weed, for water, nutrients and sunlight is big, contribute to the loss of up to 20% of the useful cane. The use of image processing techniques... W.E. Santiago, A.R. Barreto, D.G. Figueredo, R.C. Tinini, B.T. Mederos, N.J. Leite

2. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in Scandinavia

CropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable images... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki

3. 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

4. High Resolution Soil Moisture Monitoring Using Active Heat Pulse Method with Fiber Optic Temperature Sensing at Field Scale

Knowledge of spatial and temporal variability of soil moisture is critical for site specific irrigation management at field scale. However, installation feasibility, cost and between-sensor variability restrict the use of many point–based sensors at field scale. Active heat pulse method with fiber optic temperature sensing (AHFO) has shown a potential to provide soil moisture data at sub-meter intervals along a fiber optic cable to a distance >10000 meters. Despite the limited number... A. Biswas, D.N. Vidana Gamage, I.B. Strachan

5. Precision Agriculture Research Infrastructure for Sustainable Farming

Precision agriculture is an emerging area at the intersection of engineering and agriculture, with the goal of intelligently managing crops at a microscale to maximize yield while minimizing necessary resource. Achieving these goals requires sensors and systems with predictive models to constantly monitor crop and environment status. Large datasets from various sensors are critical in developing predictive models which can optimally manage necessary resources. Initial experiments at University... C. Lai, C. Min, R. Chiang, A. Hafferman, S. Morgan

6. Correlating Plant Nitrogen Status in Cotton with UAV Based Multispectral Imagery

Cotton is an indeterminate crop; therefore, fertility management has a major impact on the growth pattern and subsequent yield. Remote sensing has become a promising method of assessing in-season cotton N status in recent years with the adoption of reliable low-cost unmanned aerial vehicles (UAVs), high-resolution sensors and availability of advanced image processing software into the precision agriculture field. This study was conducted on a UGA Tifton campus farm located in Tifton, GA. The main... W. Porter, D. Daughtry, G. Harris, R. Noland, J. Snider, S. Virk

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

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

8. 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

9. Exploring the Use of a Model-based Nitrogen Recommendation Tool and Vegetation Indices for In-season Corn Nitrogen Management in Alabama

Efficient nitrogen (N) management is critical for sustainable agriculture. Crop N needs and uptake changes within a field and it is annually influenced by weather conditions. Hence, site-specific in-season N application strategies are important to achieve optimum corn yield while minimizing negative impacts on the environment. This study evaluates the Adapt-N tool for in-season variable rate N application at two farmers’ fields in Alabama. The Adapt-N tool integrates soil and crop-based... P.R. Duarte, B.V. Ortiz, E. Abban-baidoo, E. Francisco, M.F. De Oliveira

10. Participatory Irrigation Extension Programs to Increasing Adoption of Best Irrigation Strategies

Farmers in Alabama, Tennessee, and other US southeastern states lack experience in irrigation water management and adoption of the state-of-the-art technologies and practices to increase irrigation water use efficiency. Several federal and state-funded projects are being implemented to demonstrate and train farmers and consultants on irrigation scheduling strategies and variable rate irritation. Half a dozen on-farm demonstration sites are selected every year to evaluate, demonstrate, and train... L. Nunes, E. Francisco, R. Prasad, B.V. Ortiz, E. Abban-baidoo , M. Worosz, M. Robinette , C. O'connor, A. Gamble