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Zillmann, E
Zaman, Q.U
Zhang, F
Zendonadi, N
Zhu, Y
Zimba, P.V
Zengin, M
Zaman, Q.U
Zia, S
Zotarelli, L
Zhang, J
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Authors
Zhao, G
Miao, Y
Zhang, F
Fan, M
Khan, F.S
Zaman, Q.U
Schumann, A.W
Madani, A
Percival, D.C
Farooque, A.A
Saleem, S.R
Khan, F.S
Slaeem, S
Zaman, Q.U
Madani, A
Schumann, A
Percival, D
Ahmad, H.N
Farooque, A.A
Khan, F
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Zia, S
Ma, W
Zhao, C
Zaman, Q.U
Zach, D
Guo, J
Chen, L
wang, X
Zhang, R
Zotarelli, L
Frotscher, K.J
Schacht, R
Smith, L
Zillmann, E
Thomson, S.J
DeFauw, S.L
English, P.J
Hanks, J.E
Fisher, D.K
Foster, P.N
Zimba, P.V
Pecker, K
Botsali, F.M
Topal, A
Zengin, M
Liu, X
Cao, Q
Tian, Y
Zhu, Y
Zhang, Z
Cao, W
Li, S
Cao, Q
Liu, X
Tian, Y
Zhu, Y
Muller, O
Keller, B
Zimmermanm, L
Jedmowski, C
Pingle, V
Acebron, K
Zendonadi, N
Steier, A
Pieruschka, R
Schurr, U
Rascher, U
Kraska, T
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Miao, Y
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Chen, X
Li, Y
Zhang, J
Wang, W
Fu, Z
Cao, Q
Tian, Y
Zhu, Y
Cao, W
liu, X
Liu, Z
liu, X
Tian, Y
Zhu, Y
Cao, W
Cao, Q
Topics
Food Security and Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Remote Sensing Applications in Precision Agriculture
Precision Horticulture
Precision Nutrient Management
Remote Sensing Applications in Precision Agriculture
Remote Sensing Application / Sensor Technology
Adoption of Precision Agriculture
Applications of Unmanned Aerial Systems
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Big Data, Data Mining and Deep Learning
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2016
2008
2018
2022
2024
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Filter results17 paper(s) found.

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

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

2. Relationship of Soil Properties to Apparent Ground Conductivity in Wild Blueberry Fields

  One of the fundamental deficiencies in high value crops is the lack of detailed, up-to-date and pertinent geo-referenced soil information for site-specific crop management to improve productivity. This experiment was designed to estimate and map soil properties rapidly and reliably using an electromagnetic induction (EMI) method. Two wild blueberry... F.S. Khan, Q.U. Zaman, A.W. Schumann, A. Madani, D.C. Percival, A.A. Farooque, S.R. Saleem, F.S. Khan

3. Impact of Variable Rate Fertilization on Nutrients Losses in Surface Runoff for Wild Blueberry Fields

Wild blueberry producers apply agrochemicals uniformly without considering substantial variation in soil properties, topographic features that may affect fruit yield within field. A wild blueberry field was selected to evaluate the impact of variable rate (VR) fertilization on nutrient losses in surface runoff from steep slope to low lying areas to improve crop... S. Slaeem, Q.U. Zaman, A. Madani, A. Schumann, D. Percival, H.N. Ahmad, A.A. Farooque, F. Khan

4. Sensor Fusion on a Wild Blueberry Harvester for Fruit Yield, Plant Height and Topographic Features Mapping to Improve Crop Productivity

  Site-specific crop management can improve profitability and environmental risks of wild blueberry crop having large spatial variation in soil/plant characteristics, topographic features which may affect fruit yield. An integrated automated sensor fusion system including an ultrasonic sensor, a digital color camera, a slope sensor,... A.A. Farooque, Q.U. Zaman, D. Groulx, A.W. Schumann, T.J. Esau, Y.K. Chang

5. A Step Towards Precision Irrigation: Plant Water Status Detection With Infrared Thermography

The increasing demand for water all over the world calls for precision agriculture which accounts globally about 70 percent of all water withdrawal. Therefore, there is a need to optimizing water use efficiency and making the best use of available water for irrigation. Plant water status detection for advanced irrigation scheduling is frequently done by predawn leaf water potential (ΨPD) or leaf stomata conductance (gL) measurements. However, these measurements are time and labour consuming.... S. Zia

6. Design And Experiment On Target Spraying Robot For Greenhouse

In greenhouse, the robot sprayers give rise to concern as they  reduce the labor intensity and improve the accuracy of  the spraying. This paper details the progress to date in the development of a precision robot sprayer. The precision robot sprayer is able to adjust both liquid and air volume to match, the branches contour and location of the greenhouse crops with two ultrasonic sensors  which ensures the position of the plants in the greenhouse. The spraying robot with the... W. Ma, C. Zhao, Q.U. Zaman, D. Zach

7. The Effect Of Variable-Rate Fertilizer Nitrogen Decision-Making On Winter Wheat

Precision ... J. Guo, L. Chen, X. Wang, R. Zhang, L. Zotarelli

8. Planet Labs' Monitoring Solution in Support of Precision Agriculture Practices

Satellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann

9. Thermal Characterization and Spatial Analysis of Water Stress in Cotton (Gossypium Hirsutum L.) and Phytochemical Composition Related to Water Stress in Soybean (Glycine Max)

Studies were designed to explore spatial relationships of water and/or heat stress in cotton and soybeans and to assess factors that may influence yield potential. Investigations focused on detecting the onset of water/heat stress in row crops using thermal and multispectral imagery with ancillary physicochemical data such as soil moisture status and photosynthetic pigment concentrations. One cotton field with gradations in soil texture showed distinct patterns in thermal imagery, matching patterns... S.J. Thomson, S.L. Defauw, P.J. English, J.E. Hanks, D.K. Fisher, P.N. Foster, P.V. Zimba

10. The Review of Studying and Using Advanced Technologies for Site Specific Management in Konya, Turkey

Using advanced (information) technologies in agriculture is increasing rapidly especially in the developed countries such as USA, Japan, and some members of EU. Advanced technologies in agriculture are mostly based on sensors. Site specific management is a form of agricultural management, which is governed by optimum use of variables. Input such as chemical, water, and seed in agricultural production can be managed by using the technologies. Geographic information systems (GIS), Global Position... K. Pecker, F.M. Botsali, A. Topal, M. Zengin

11. Using Unmanned Aerial Vehicle and Active-Optical Sensor to Monitor Growth Indices and Nitrogen Nutrition of Winter Wheat

Using unmanned aerial vehicle (UAV) remote sensing monitoring system can rapidly and cost-effectively provide crop canopy information for growth diagnosis and precision fertilizer regulation. RapidScan CS-45 (Holland, Lincoln, NE, USA) is a portable active-optical sensor designed for timely, non-destructive obtaining plant canopy information without being affected by weather condition. UAV equipped with RapidScan, is of great significant for rapidly monitoring crop growth and nitrogen (N) status.... X. Liu, Q. Cao, Y. Tian, Y. Zhu, Z. Zhang, W. Cao

12. Using a UAV-Based Active Canopy Sensor to Estimate Rice Nitrogen Status

Active canopy sensors have been widely used in the studies of crop nitrogen (N) estimation as its suitability for different environmental conditions. Unmanned aerial vehicle (UAV) is a low-cost remote sensing platform for its great flexibility compared to traditional ways of remote sensing. UAV-based active canopy sensor is expected to take the advantages of both sides. The objective of this study is to determine whether UAV-based active canopy sensor has potential for monitoring rice N status,... S. Li, Q. Cao, X. Liu, Y. Tian, Y. Zhu

13. Field Phenotyping and an Example of Proximal Sensing of Photosynthesis

Field phenotyping conceptually can be divided in five pillars 1) traits of interest 2) sensors to measure these traits 3) positioning systems to allow high throughput measurements by the sensors 4) experimental sites and 5) environmental monitoring. In this paper we will focus on photosynthesis as trait of interest, measured by remote active fluorescence. The sensor presented is the Light Induced Fluorescence Transient (LIFT) instrument. The LIFT instrument is integrated in three positioning systems.... O. Muller, B. Keller, L. Zimmermanm, C. Jedmowski, V. Pingle, K. Acebron, N. Zendonadi, A. Steier, R. Pieruschka, U. Schurr, U. Rascher, T. Kraska

14. Meta Deep Learning Using Minimal Training Images for Weed Classification in Wild Blueberry

Deep learning convolutional neural networks (CNNs) have gained popularity in recent years for their ability to classify images with high levels of accuracy. In agriculture, they have been applied for disease identification, crop growth monitoring, animal behaviour tracking, and weed classification. Datasets traditionally consisting of thousands of images of each desired target are required to train CNNs. A recent survey of Nova Scotia wild blueberry (Vaccinium angustifolium Ait.) fields,... P.J. Hennessy, T.J. Esau, A.W. Schumann, A.A. Farooque, Q.U. Zaman, S.N. White

15. Developing a Wheat Precision Nitrogen Management Strategy by Combining Satellite Remote Sensing Data and WheatGrow Model

Precision nitrogen (N) management (PNM) is becoming increasingly popular due to its ability to synchronize crop N demand with soil N supply spatiotemporally. The previous evidence has demonstrated that variable rate fertilization contributes to achieving high yields and high efficiencies. However, PNM at the regional level remains unclear and challenging. This study aims to develop a novel management zone (MZ)-based PNM strategy (MZ-PNM) to optimize the basal and topdressing N rates at the regional... Y. Miao, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao, X. Chen, Y. Li

16. Potential Benefits of Variable Rate Nitrogen Topdressing Strategy Coupled with Zoning Technique: a Case Study in a Town-scale Rice Production System

Integrating remote sensing (RS)-based variable rate nitrogen (N) recommendation (VRNR) algorithms and management zones (MZs) may improve the accuracy and efficiency of site-specific N management. However, its potential benefits for application in commercial rice production systems can hardly be assessed, since it requires to intervene in common agricultural practices and causes certain economic and environmental consequences. Through a machine learning approach, this study aims to comprehensively... J. Zhang, W. Wang, Z. Fu, Q. Cao, Y. Tian, Y. Zhu, W. Cao, X. Liu

17. Optimizing Nitrogen Application in Global Wheat Production by an Integrated Bayesian and Machine Learning Approach

Wheat production plays a pivotal role in global food security, with nitrogen fertilizer application serving as a critical factor. The precise application of nitrogen fertilizer is imperative to maximize wheat yield while avoiding environmental degradation and economic losses resulting from excess or inadequate usage. The integration of Bayesian and machine learning methodologies has gained prominence in the realm of agricultural research. Bayesian and machine learning based methods have great... Z. Liu, X. Liu, Y. Tian, Y. Zhu, W. Cao, Q. Cao