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Huang, Y
Lins, E.C
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Authors
Huang, Y
Thomson, S.J
Huang, Y
Hoffmann, W.C
Lan, Y
Thomson, S.J
Fritz, B.K
Ortiz, B
Thomson, S.J
Huang, Y
Reddy, K
Lan, Y
Zhang, H
Yang, C
Martin, D
Lacey, R
Huang, Y
Hoffmann, W.C
Moulton, P
Deng, W
Wang, X
Zhao, C
Huang, Y
Lu, J
Miao, Y
Huang, Y
Shi, W
Huang, Y
Brand, H
Pennington, D
Reddy, K
Thomson, S.J
Lins, E.C
Belasque Junior, J
Marcassa, L.G
Zhen, X
Miao, Y
Feng, G
Huang, Y
Yang, Z
Liu, P
Bindish, R
Miao, Y
Kechchour, A
Sharma, V
Flores, A
Lacerda, L
Mizuta, K
Lu, J
Huang, Y
Topics
Precision Aerial Application
Engineering Technologies and Advances
Remote Sensing Applications in Precision Agriculture
Precision Crop Protection
Unmanned Aerial Systems
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Weather and Models for Precision Agriculture
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Type
Poster
Oral
Year
2012
2010
2014
2016
2008
2024
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Authors

Filter results10 paper(s) found.

1. Response and Positioning Accuracy of a Variable-Rate Aerial Application System and Use of Enhanced Imagery for Creation of Prescription Maps

Experiments were conducted to evaluate a variable rate aerial application system in the field, and experiences with iterative system improvement are outlined. Spray cards placed in the field determined application accuracy, and system... Y. Huang, S.J. Thomson

2. Development Of Unmanned Aerial Vehicles For Site-specific Crop Production Management

... Y. Huang, W.C. Hoffmann, Y. Lan, S.J. Thomson, B.K. Fritz

3. Determination Of Crop Injury From Aerial Application Of Glyphosate Using Vegetation Indices And Geostatistics

Injury to crops caused by off-target drift of glyphosate can seriously reduce growth and yield, and is of great concern to farmers and aerial applicators. Determining an indirect method for assessing the levels and extent of crop injury could support management decisions. The objectives of this study were to evaluate multiple vegetation indices (VIs) as surrogate variables for glyphosate injury identification and to evaluate the combined use of Geostatistical methods and the VIs to assess... B. Ortiz, S.J. Thomson, Y. Huang, K. Reddy

4. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field Mapping

  A wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by synthesizing... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton

5. Weed Identification From Seedling Cabbages Using Visible And Near-Infrared Spectrum Analysis

Target identification is one of the main research content and also a key point in precision crop protection. The main purpose of the study is to choose the characteristic wavelengths (CW for short) to classify the cabbages and the weeds at their seedling stage using different data analysis methods. Using a handheld full-spectrum FieldSpec-FR, the canopies of the seedling plants, cabbage ‘8398, cabbage ‘zhonggan’, Barnyard grass, green foxtail, goosegrass,... W. Deng, X. Wang, C. Zhao, Y. Huang

6. In-season Diagnosis of Rice Nitrogen Status Using Crop Circle Active Canopy Sensor and UAV Remote Sensing

Active crop canopy sensors have been used to non-destructively estimate nitrogen (N) nutrition index (NNI) for in-season site-specific N management. However, it is time-consuming and challenging to carry the hand-held active crop sensors and walk across large paddy fields. Unmanned aerial vehicle (UAV)-based remote sensing is a promising approach to overcoming the limitations of proximal sensing. The objective of this study was to combine unmanned aerial vehicle (UAV)-based remote sensing system... J. Lu, Y. Miao, Y. Huang, W. Shi

7. Assessing Soybean Injury from Dicamba Using RGB and CIR Images Acquired on Small UAVs

Dicamba is an herbicide used for postemegence control of several broadleaf weeds in corn, grain sorghum, small grains, and non-cropland. Currently, dicamba-tolerant (DT) soybean and cotton are under development, which provide new options to combat weeds resistant to glyphosate, the most widely used herbicide.  With the use of DT-trait cotton and soybean, off-target dicamba drift onto susceptible crops will become a concern. To relate soybean injury to different rates of dicamba applications,... Y. Huang, H. Brand, D. Pennington, K. Reddy, S.J. Thomson

8. Detection of Citrus Canker in Orange Plantation Using Fluorescence Spectroscopy

Citrus canker is a serious disease, caused by Xanthomonas axonopodis pv. Citri bacteria, which infects orange trees (Citrus aurantium L.), leading to a large economic loss in the orange juice production. Brazil produces 50% of the industrialized orange juice in the world. Therefore, the early detection and control of such disease is important for Brazilian economy. However this task is very hard and so far it has been done by naked eye inspection of each tree. Our goal is to... E.C. Lins, J. Belasque junior, L.G. Marcassa

9. Evaluating the Potential of In-season Spatial Prediction of Corn Yield and Responses to Nitrogen by Combining Crop Growth Modeling, Satellite Remote Sensing and Machine Learning

Nitrogen (N) is a critical yield-limiting factor for corn (Zea mays L.). However, over-application of N fertilizers is a common problem in the US Midwest, leading to many environmental problems. It is crucial to develop efficient precision N management (PNM) strategies to improve corn N management. Different PNM strategies have been developed using proximal and remote sensing, crop growth modeling and machine learning. These strategies have both advantages and disadvantages. There is... X. Zhen, Y. Miao, K. Mizuta, S. Folle, J. Lu, R.P. Negrini, G. Feng, Y. Huang

10. In-season Diagnosis of Corn Nitrogen and Water Status Using UAV Multispectral and Thermal Remote Sensing

For irrigated corn fields, how to optimize nitrogen (N) and irrigation simultaneously is a great challenge. A promising strategy is to use remote sensing to diagnose corn N and water status during the growing season, which can then be used to guide in-season variable rate N application and irrigation management. The objective of this study was to evaluate the effectiveness of UAV multispectral and thermal remote sensing in simultaneous diagnosis of corn N and water status. Two field experiments... Y. Miao, A. Kechchour, V. Sharma, A. Flores, L. Lacerda, K. Mizuta, J. Lu, Y. Huang