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Gray, G.R
Gianello, E
Gore, A.K
Grappadelli, L.C
Guangwei, W
Gregory, S
Gao, X
Gholizadeh, A
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Authors
Gholizadeh , A
Mohd Soom , M
Saberioon, M
Gholizadeh, A
Saberioon, M
Mohd Soom, M
Guangwei, W
Zhijun, M
Liping, C
Weiqiang, F
Jianjun, D
Cao, Q
Miao, Y
Feng, G
Gao, X
Liu, B
Khosla, R
Liu, B
Miao, Y
Feng, G
Yue, S
Li, F
Gao, X
Mueller, T
Gianello, E
Mijatovic, B
Rienzi, E
Rodrigues, M
Pawar, S.N
Gore, A.K
Shinde, G.U
Pendke, M.S
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Borùvka, L
Saberioon, M
Vašát, R
Gholizadeh, A
Gholizadeh, A
Saberioon, M
Borůvka, L
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Cerri, D.G
Gray, G.R
Magalhães, P.S
Bresilla, K
Manfrini, L
Boini, A
Perulli, G
Morandi, B
Grappadelli, L.C
Topics
Sensor Application in Managing In-season Crop Variability
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Proximal Sensing in Precision Agriculture
Emerging Issues in Precision Agriculture (Energy, Biofuels, Climate Change)
Precision Nutrient Management
Proximal Sensing in Precision Agriculture
Proximal Sensing in Precision Agriculture
Agricultural Education
Engineering Technologies
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
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Filter results13 paper(s) found.

1. Estimation of Nitrogen of Rice in Different Growth Stages Using Tetracam Agriculture Digital Camera

Many methods are available to monitor nitrogen content of rice during various growth stages. However, this monitoring still requires a quick, simple, accurate and inexpensive technique that needs to be developed. In this study, Tetracam Agriculture Digital Camera (ADC) was used to acquire high spatial and temporal resolution in order to determine the status of nitrogen (N) and predict the grain yield of rice (Oriza sativa L.). In this study, 12 pots of rice with four different N treatments (0, 125,... A. Gholizadeh , M. Mohd Soom , M. Saberioon

2. Potential of Visible and Near Infrared Spectroscopy for Prediction of Paddy Soil Physical Properties

A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of Visible (Vis) and Near-infrared Reflectance Spectroscopy (NIRS) to predict paddy soil physical properties in a typical Malaysian paddy field. To assess the utility of spectroscopy for soil physical characteristics prediction, we used 118 soil samples for laboratory analysis and optical measurement in the Vis-NIR region... A. Gholizadeh, M. Saberioon, M. Mohd Soom

3. Evaluation of Application Effect of the Laser Land Leveling Technology in Typical Areas of China

The technology of laser land leveling can improve the accuracy of land leveling and it is the important measure of improving irrigation efficiency and facilitating more uniform distribution of irrigation water. The technology is more widely used in China in... W. Guangwei, M. Zhijun, C. Liping, F. Weiqiang, D. Jianjun

4. Performance of Two Active Canopy Sensors for Estimating Winter Wheat Nitrogen Status in North China Plain

... Q. Cao, Y. Miao, G. Feng, X. Gao, B. Liu, R. Khosla

5. Different Leaf Sensing Approaches for the Estimation of Winter Wheat Nitrogen Status

Nondestructive real time diagnosis of crop N status is crucial to the development of precision nitrogen (N) management strategies. Chlorophyll meter has been a popular sensor for such purposes and different approaches to use this sensor has been developed using a threshold value, nitrogen sufficiency index (NSI) or ratio of... B. Liu, Y. Miao, G. Feng, S. Yue, F. Li, X. Gao

6. On-The-Go pH Sensor: An Evaluation in a Kentucky Field

A commercially available on-the-go soil pH sensor measures and maps subsurface soil pH at high spatial intensities across managed landscapes.  The overall purpose of this project was to evaluate the potential for this sensor to be used in agricultural fields. The specific goals were to determine and evaluate 1) the accuracy with which this instrument can be calibrated, 2) the geospatial structure of soil pH measurements,... T. Mueller, E. Gianello, B. Mijatovic, E. Rienzi, M. Rodrigues

7. Climatological Diagnostic Analysis: A Case Study for Parbhani District in Marathwada Region of India

... S.N. Pawar, A.K. Gore, G.U. Shinde, M.S. Pendke

8. Evaluating Different Nitrogen Management Strategies For The Intensive Wheat-Maize System In North China Plain

The sustainable agricultural development involves both environmental challenges and production goals to meet growing food demand. However, excessive nitrogen (N) applications are threatening the sustainability of intensive agriculture in the North China Plain (NCP). Improved N management should result in greater N use efficiency (NUE) and producer profit while reducing the risk of environmental contamination. Therefore, developing and disseminating feasible N management strategies... Q. Cao, Y. Miao, G. Feng, F. Li, B. Liu, X. Gao, Y. Liu

9. Visible And Near-Infrared Spectroscopy For Monitoring Potentially Toxic Elements In Reclaimed Dumpsite Soils Of The Czech Republic

Due to rapid economic development, high levels of potentially harmful elements and heavy metals are continuously being released into the brown coal mining dumpsites of the Czech Republic. Elevated metal contents in soils not only dramatically impact the soil quality, but also due to their persistent nature and long biological half-lives, contaminant elements can accumulate in the food chain and can eventually endanger human health. Conventional methods for investigating potentially... L. Borùvka, M. Saberioon, R. Vašát, A. Gholizadeh

10. Memory Based Learning: A New Data Mining Approach to Model and Interpret Soil Texture Diffuse Reflectance Spectra

Successful estimation of spectrally active soil texture with Visible and Near-Infrared (VNIR, 400-1200 nm) and Short-Wave-Infrared (SWIR, 1200-2500 nm) spectroscopy depends mostly on the selection of an appropriate data mining algorithm. The aims of this paper were: to compare different data mining algorithms including Partial Least Squares Regression (PLSR), which is the most common technique in soil spectroscopy, Support Vector Machine Regression (SVMR), Boosted Regression Trees (BRT), and Memory... A. Gholizadeh, M. Saberioon, L. Borůvka

11. 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

12. Technological Improvement on Sugar Cane Yield Monitor

This paper presents the technological improvement on sugar cane yield monitor. The system designed employs load cells as an instrument for weighing billets, set up on the side conveyor of the harvester before the sugar cane billets are dropped into a field transport wagon. This data, along with the information gathered by GPS installed on the harvester, enabled the elaboration of a digital yield map using GIS. In order to improve the yield monitor a re-design of the first prototype was accomplished.... D.G. Cerri, G.R. Gray, P.S. Magalhães

13. Using Deep Learning - Convolutional Naural Networks (CNNS) for Real-Time Fruit Detection in the Tree

Image/video processing for fruit detection in the tree using hard-coded feature extraction algorithms have shown high accuracy on fruit detection during recent years. While accurate, these approaches even with high-end hardware are still computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks architecture based on single-stage detectors. Using deep-learning techniques eliminates the need for hard-code specific features for specific... K. Bresilla, L. Manfrini, A. Boini, G. Perulli, B. Morandi, L.C. Grappadelli