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Shao, Y
Schultz, E.D
Sánchez Tomás, J
Son, J
Sun, X
Sutrisna Wijaya, I
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Authors
Zhao, Y
Xu, X
Shao, Y
He, Y
Li, Q
Cho, W
Kim, D
Kang, C
Kim, H
Son, J
Chung, S
Jiang, J
Yun, H
Ferreyra, R
Applegate, D.B
Berger, A.W
Berne, D.T
Craker, B.E
Daggett, D.G
Gowler, A
Bullock, R.J
Haringx, S.C
Hillyer, C
Howatt, T
Nef, B.K
Rhea, S.T
Russo, J.M
Nieman, S.T
Sanders, P
Wilson, J.A
Wilson, J.W
Tevis, J.W
Stelford, M.W
Shearouse, T.W
Schultz, E.D
Reddy, L
Rai, N
Zhang, Y
Quanbeck, J
Christensen, A
Sun, X
Sánchez Virosta, Ã
Gómez-Candón, D
Montoya Sevilla, F
Pérez García, Y
Jiménez Castaño, V
González Piqueras, J
López-Urrea, R
Sánchez Tomás, J
Sutrisna Wijaya, I
Topics
Food Security and Precision Agriculture
Precision Nutrient Management
Standards & Data Stewardship
Big Data, Data Mining and Deep Learning
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Oral
Year
2014
2016
2022
2024
2025
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Filter results6 paper(s) found.

1. A Novel Hyperspectral Feature Extraction Algorithm Based On Waveform Resolving For Raisin Classification

Near infrared hyperspectral imaging technology was adopted in the paper to determine the variety of raisins produced in Xinjiang Uygur Autonomous Region, China. There are 2 varieties of raisins taking part in the research and the wavelengths of the hyperspectral images are from 900nm to 1700nm. A novel waveform resolving method was proposed in the paper to reduce the hyperspectral data and extract features. The waveform resolving method compresses the original hyperspectral data for one pixel... Y. Zhao, X. Xu, Y. Shao, Y. He, Q. Li

2. Precision Nutrient Management System Based on Ion and Crop Growth Sensing

Automated sensing and variable-rate supply of nutrients in hydroponic solutions according to the status of crop growth would allow more efficient nutrient management for crop growth in closed systems. The Structure from Motion (SfM) method has risen as a new image sensing method to obtain 3D images of plants that can be used to estimate their growth, such as leaf cover area (LCA), plant height, and fresh weight. In this sense, sensor fusion technology combining ion-selective electrodes (ISEs)... W. Cho, D. Kim, C. Kang, H. Kim, J. Son, S. Chung, J. Jiang, H. Yun

3. Toward Geopolitical-Context-Enabled Interoperability in Precision Agriculture: AgGateway's SPADE, PAIL, WAVE, CART and ADAPT

AgGateway is a nonprofit consortium of 240+ businesses working to promote, enable and expand eAgriculture. It provides a non-competitive collaborative environment, transparent funding and governance models, and anti-trust and intellectual property policies that guide and protect members’ contributions and implementations. AgGateway primarily focuses on implementing existing standards and collaborating with other organizations to extend them when necessary. In 2010 AgGateway identified... R. Ferreyra, D.B. Applegate, A.W. Berger, D.T. Berne, B.E. Craker, D.G. Daggett, A. Gowler, R.J. Bullock, S.C. Haringx, C. Hillyer, T. Howatt, B.K. Nef, S.T. Rhea, J.M. Russo, S.T. Nieman, P. Sanders, J.A. Wilson, J.W. Wilson, J.W. Tevis, M.W. Stelford, T.W. Shearouse, E.D. Schultz, L. Reddy

4. Spotweeds: a Multiclass UASs Acquired Weed Image Dataset to Facilitate Site-specific Aerial Spraying Application Using Deep Learning

Unmanned aerial systems (UASs)-based spot spraying application is considered a boon in Precision Agriculture (PA). Because of spot spraying, the amount of herbicide usage has reduced significantly resulting in less water contamination or crop plant injury. In the last demi-decade, Deep Learning (DL) has displayed tremendous potential to accomplish the task of identifying weeds for spot spraying application. Also, most of the ground-based weed management technologies have relied on DL techniques... N. Rai, Y. Zhang, J. Quanbeck, A. Christensen, X. Sun

5. Remote and Proximal Sensing for Sustainable Water Use in Almond Orchards in Southeast Spain in a Digital Farming Context

The increasing expansion of irrigated almond orchards in regions of southeast Spain, facing water scarcity, underscores the need for a more effective and precise monitoring of the crop water status to optimize irrigation scheduling and improve crop water use efficiency. Remote and proximal sensing, combining visible, multispectral and thermal capabilities at different scales allows to estimate water needs, detect and quantify crop water stress, or identify different productivity zones within an...

6. Enhancing Rice Disease Management: Estimating Pathogen Damage Through Multispectral Imaging Analysis

This study investigates the application of multispectral imaging (MSI) in conjunction with machine learning algorithms for the early detection and estimation of pathogen damage in rice crops, with a specific focus on Bacterial Leaf Blight (BLB) and Blast diseases. Rice plays a crucial role in global food security, yet these diseases significantly compromise its production. Traditional diagnostic methods are often labor-intensive and time-consuming, necessitating the adoption of innovative technologies.... I. Sutrisna wijaya