Proceedings

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Toledo, F.H
Trotter, T
Todman, L
Taylor, R
Tasissa, A
Thompson, L.J
Tuttle, G
Ogasawara, C
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Authors
Hongo, C
Ogasawara, C
Tamura, E
Sigit, G
Rodrigues Jr., F.A
Ortiz-Monasterio, I
Zarco-Tejada, P.J
Toledo, F.H
Schulthess, U
Gérard, B
Weckler, P
Wang, N
Zhai, C
Zhang, L
Luo, B
Long, J
Taylor, R
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Thompson, L.J
Maja, J.M
Blocker, A.K
Stuckey, E.G
Sell, S.G
Tuttle, G
Mueller, J
Andrae, J
Karampoiki, M
Todman, L
Mahmood, S
Murdoch, A
Paraforos, D
Hammond, J
Ranieri, E
Tasissa, A
Lichtenberg,, S
Tasissa, A
Li, L
Murphy, J.M
Topics
Food Security and Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Agricultural Education
In-Season Nitrogen Management
Farm Animals Health and Welfare Monitoring
Big Data, Data Mining and Deep Learning
Wireless Sensor Networks and Farm Connectivity
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2016
2018
2022
2024
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Filter results9 paper(s) found.

1. 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

2. High Resolution Hyperspectral Imagery to Assess Wheat Grain Protein in a Farmer's Field

The agricultural research sector is working to develop new technologies and management knowledge to sustainably increase food productivity, to ensure global food security and decrease poverty. Wheat is one of the most important crops into this scenario, being among the three most important cereal commodities produced worldwide. Precision Agriculture (PA) and specially Remote Sensing (RS) technologies have become in the recent years more affordable which has improved the availability and flexibility... F.A. Rodrigues jr., I. Ortiz-monasterio, P.J. Zarco-tejada, F.H. Toledo, U. Schulthess, B. Gérard

3. Evaluation of a Seed-fertilizer Application System Using a Laser Scanner

The system evaluated is a design that combines planter and sprayer technologies to allow clients to plant crops while simultaneously spraying initial fertilizer on or in close proximity to the seed.  The system is an idea Capstan Ag Systems has been pursuing for around 15 years, and has recently been revived in a partnership with Great Plains Manufacturing Company.  Great Plains Manufacturing released the final product under the name AccushotTM at the 2015... P. Weckler, N. Wang, C. Zhai, L. Zhang, B. Luo, J. Long, R. Taylor

4. 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

5. Using Drone Based Sensors to Direct Variable-Rate, In-Season, Aerial Nitrogen Application on Corn

Improving nutrient management on farms is a critical issue nationwide. Applying a portion of N fertilizer during the growing season, alongside the growing corn crop is one way to improve nitrogen management. Sidedress N applications allow the availability of N fertilizer to more closely match the time when the crop is rapidly uptaking N. Additionally, waiting to apply a portion of the N during the growing season allows for management which is responsive to current growing season conditions. Crop... L.J. Thompson

6. Development of a Small Tracking Device for Cattle Using IoT Technology

The US is the largest producer of beef in the world. Last year alone, it produces nearly 19% of the world’s beef.  This translate to about almost $90 billion in economic impact in the country. Aside from being a producer, the US also consumed more than 26 billion pounds of beef which have a retail value of the entire beef industry to more than $74B. For this level of production and consumption, each rancher in the US must produce a herd size of at least 100 or more to sustain the current... J.M. Maja, A.K. Blocker, E.G. Stuckey, S.G. Sell, G. Tuttle, J. Mueller, J. Andrae

7. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri

8. Nystrom-based Localization in Precision Agriculture Sensors

Wireless sensor networks play a pivotal role in a myriad of applications, ranging from agriculture and health monitoring and to tracking and structural health monitoring. One crucial aspect of these applications involves accurately determining the positions of the sensors. In this study, we study a novel Nystrom-based sampling protocol in which a selected group of anchor nodes, with known locations, establish communication with only a subset of the remaining sensor nodes. Leveraging partial distance... A. Tasissa, S. Lichtenberg,

9. Sparse Coding for Classification Via a Locality Regularizer: with Applications to Agriculture

High-dimensional data is commonly encountered in various applications, including genomics, as well as image and video processing. Analyzing, computing, and visualizing such data pose significant challenges. Feature extraction methods become crucial in addressing these challenges by obtaining compressed representations that are suitable for analysis and downstream tasks. One effective technique along these lines is sparse coding, which involves representing data as a sparse linear combination of... A. Tasissa, L. Li, J.M. Murphy