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Miao, Y
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Authors
Zhao, G
Miao, Y
Zhang, F
Fan, M
Miao, Y
Li, F
Yao, Y
Miao, Y
Huang, S
Gnyp, M.L
Khosla, R
Jiang, R
Bareth, G
Cao, Q
Miao, Y
Feng, G
Gao, X
Liu, B
Khosla, R
Liu, B
Miao, Y
Feng, G
Yue, S
Li, F
Gao, X
Miao, Y
Cao, Q
Cui, Z
Li, F
Dao, T.H
Khosla, R
Chen, X
Yao, Y
Miao, Y
Huang, S
Gnyp, M.L
Jiang, R
Chen, X
Bareth, G
Cao, Q
Miao, Y
Feng, G
Li, F
Liu, B
Gao, X
Liu, Y
Cao, Q
Miao, Y
Shen, J
Cheng, S
Khosla, R
Liu, F
Yu, W
Miao, Y
Hu, S
Shen, J
Wang, H
Huang, S
Miao, Y
Yuan, F
Gnyp, M.L
Yao, Y
Cao, Q
Lenz-Wiedemann, V
Bareth, G
Lu, J
Miao, Y
Huang, Y
Shi, W
Lu, J
Wang, H
Miao, Y
Wang, X
Miao, Y
Batchelor, W.D
Dong, R
Mulla, D.J
Wang, X
Miao, Y
Xia, T
Dong, R
Mi, G
Mulla, D.J
Sela, S
Graff, N
Mizuta, K
Miao, Y
Li, D
Miao, Y
Fernández, .G
Kitchen, N.R
Ransom, C.
Bean, G.M
Sawyer, .E
Camberato, J.J
Carter, .R
Ferguson, R.B
Franzen, D.W
Franzen, D.W
Franzen, D.W
Franzen, D.W
Laboski, C.A
Nafziger, E.D
Shanahan, J.F
Mizuta, K
Miao, Y
Morales, A.C
Lacerda, L.N
Cammarano, D
Nielsen, R.L
Gunzenhauser, R
Kuehner, K
Wakahara, S
Coulter, J.A
Mulla, D.J
Quinn, D.
McArtor, B
Lacerda, L.N
Miao, Y
Mizuta, K
Stueve, K
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Mizuta, K
Zhang, J
Li, D
Dong, R
Miao, Y
Wang, X
Elvir Flores, A
Miao, Y
Sharma, V
Lacerda, L
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Chen, X
Miao, Y
Yu, K
chang, Q
li, F
Miao, Y
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Chen, X
Li, Y
Wakahara, S
Miao, Y
Gupta, S
Rosen, C
Negrini, R.P
Miao, Y
Mizuta, K
Stueve, K
Kaiser, D
Coulter, J.A
Morales, A.C
Quinn, D.
Mizuta, K
Miao, Y
Lacerda, L
Miao, Y
Sharma, V
E. Flores, A
Kechchour, A
Lu, J
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
Miao, Y
Kechchour, A
Folle, S
Mizuta, K
Mizuta, K
Miao, Y
Lu, J
Negrini, R.P
Lu, J
Miao, Y
Ransom, C.J
Fernández, F
Topics
Food Security and Precision Agriculture
Precision Nutrient Management
Sensor Application in Managing In-season Crop Variability
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Sensor Application in Managing In-season Crop Variability
Precision Nutrient Management
Sensor Application in Managing In-season CropVariability
Proximal Sensing in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Unmanned Aerial Systems
Precision Agriculture and Global Food Security
Decision Support Systems
In-Season Nitrogen Management
Site-Specific Nutrient, Lime and Seed Management
ISPA Community: Nitrogen
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Drainage Optimization and Variable Rate Irrigation
In-Season Nitrogen Management
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Weather and Models for Precision Agriculture
On Farm Experimentation with Site-Specific Technologies
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
2024
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Authors

Filter results34 paper(s) found.

1. Quantifying Spatial Variability Of Indigenous Nitrogen Supply For Precision Nitrogen Management In North China Plain

... Y. Miao, Q. Cao, Z. Cui, F. Li, T.H. Dao, R. Khosla, X. Chen

2. Developing An Active Crop Sensor-based In-season Nitrogen Management Strategy For Rice In Northeast China

  Crop sensor-based in-season N management strategies have been successfully developed and evaluated for winter wheat around the world, but little has been reported for rice. The objective of this study was to develop an active crop sensor-based in-season N management strategy for upland rice in Northeast... Y. Yao, Y. Miao, S. Huang, M.L. Gnyp, R. Jiang, X. Chen, G. Bareth

3. Developing an Integrated Rice Management System for Improved Yield and Nitrogen Use Efficiency in Northeast China

... G. Zhao, Y. Miao, F. Zhang, M. Fan

4. Deriving Nitrogen Indicators of Maize Using the Canopy Chlorophyll Content Index

Many spectral indices have been proposed to derive aerial nitrogen (N) status parameters of crops in recent decades. However, most of red light based spectral indices easily loss sensitivity at moderate-high aboveground biomass. The objective of present study is to assess the performance of red edge based... Y. Miao, F. Li

5. In-season Diagnosis of Rice Nitrogen Status Using an Active Canopy Sensor

... Y. Yao, Y. Miao, S. Huang, M. Gnyp, R. Khosla, R. Jiang, G. Bareth

6. 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

7. 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

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. Crop Circle Sensor-Based Precision Nitrogen Management Strategy For Rice In Northeast China

GreenSeeker (GS) sensor-based precision N management strategy for rice has been developed, significantly improved N fertilizer use efficiency. Crop Circle ACS-470 (CC) active sensor is a new user configurable sensor, with a choice of 6 possible bands. The objectives of this study were to identify important vegetation indices obtained from CC sensor for estimating rice yield potential and rice responsiveness to topdressing N application and evaluate their potential improvements over GS normalized... Q. Cao, Y. Miao, J. Shen, S. Cheng, R. Khosla, F. Liu

10. Evaluating Leaf Fluorescence Sensor Dualex 4 For Estimating Rice Nitrogen Status In Northeast China

Real-time non-destructive diagnosis of crop nitrogen (N) status is crucially important for the success of in-season site-specific N management. Chlorophyll meter (CM) has been commonly used to non-destructively estimate crop leaf chlorophyll concentration, and indirectly estimate crop N status. Dualex 4 is a newly developed leaf fluorescence sensor that can estimate both leaf chlorophyll concentration and polyphenolics, especially flavonoids. When N is deficient, N stress can induce... W. Yu, Y. Miao, S. Hu, J. Shen, H. Wang

Showing 1 to 10 of 34 entries