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Stueve, K
Hoffmann, W.C
Hartmann, B
Lu, J
Tekin, Y
Stamm, M.J
Saxena, A
Sinfort, C
Andrade, P
E. Flores, A
Zaman, Q
Schepters, J.S
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Authors
Zaman, Q
Chang, Y
Farooque, A.A
Schumann, A
Percival, D
Cheema, M
Esau, T.J
Zaman, Q
Esau, T.J
Farooque, A.A
Schumann, A.W
Percival, D.C
Chang, Y.K
Zaman, Q
Ulusoy, Y
Tümsavas, Z
Mouazen, A.M
Tekin, Y
Ciampitti, I.A
Shroyer, K
Prasad, V
Sharda, A
Stamm, M.J
Wang, H
Price, K
Mangus, D
Lu, J
Miao, Y
Huang, Y
Shi, W
Lan, Y
Huang, Y
Martin, D.E
Hoffmann, W.C
Fritz, B.K
López, J.D
Alheidary, M.H
Douzals, J
Sinfort, C
Esau, K
Zaman, Q
Farooque, A
Schumann, A
Dallago, G.M
Figueiredo, D
Santos, R
Andrade, P
Santos, D
Dallago, G.M
Figueiredo, D
Santos, R
Andrade, P
Santschi, D.E
Lacroix, R
Lefebvre, D.M
Lu, J
Wang, H
Miao, Y
Mohamed, M.M
Zaman, Q
Esau, T
Farooque, A
Rydahl, P
Boejer, O
Jensen, N
Hartmann, B
Jorgensen, R
Soerensen, M
Andersen, P
Paz, L
Nielsen, M.B
MacEachern, C
Esau, T
Zaman, Q
Ali, U
Esau, T.J
Farooque, A
Zaman, Q
Kitchen, N.R
Ransom, C.J
Schepters, J.S
Hatfield, J.L
Massey, R
Lacerda, L.N
Miao, Y
Mizuta, K
Stueve, K
Saxena, A
Dash, M
Verma, A.P
Lu, J
Chen, Z
Miao, Y
Li, Y
Zhang, Y
Zhao, X
Jia, M
Negrini, R.P
Miao, Y
Mizuta, K
Stueve, K
Kaiser, D
Coulter, J.A
Lacerda, L
Miao, Y
Sharma, V
E. Flores, A
Kechchour, A
Lu, J
Miao, Y
Kechchour, A
Sharma, V
Flores, A
Lacerda, L
Mizuta, K
Lu, J
Huang, Y
Mizuta, K
Miao, Y
Lu, J
Negrini, R.P
Lu, J
Miao, Y
Ransom, C.J
Fernández, F
Topics
Engineering Technologies and Advances
Proximal Sensing in Precision Agriculture
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Unmanned Aerial Systems
Remote Sensing Application / Sensor Technology
Precision Crop Protection
Decision Support Systems
Precision Dairy and Livestock Management
Precision Agriculture and Global Food Security
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Precision Crop Protection
Decision Support Systems
In-Season Nitrogen Management
Big Data, Data Mining and Deep Learning
Geospatial Data
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
On Farm Experimentation with Site-Specific Technologies
In-Season Nitrogen Management
Type
Poster
Oral
Year
2012
2014
2016
2008
2018
2022
2024
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Authors

Filter results25 paper(s) found.

1. Development of Sensing System Using Digital Photography Technique for Spot-Application of Herbicide in Wild Blueberry Fields

An automated sensing system, hardware and software, was developed for spot-application of herbicide with 6.1 m boom automated prototype sprayer.... Q. Zaman, T.J. Esau, A.A. Farooque, A.W. Schumann, D.C. Percival, Y.K. Chang

2. Spot- Application of Pre-Emergence Herbicide Using a Variable Rate Sprayer in Wild Blueberry

Wild blueberry producers apply herbicides uniformly to control grasses and weeds without considering the significant weed density variability and bare spots within fields. The repeated and excessive use of herbicides... Q. Zaman, Y. Chang, A. Farooque, A. Schumann, D. Percival, M. Cheema, T. Esau

3. Development of Variable Rate Applicators Using Real-Time Machine Vision Sensing and Control System for Spot-Application of Agrochemicals

The variable rate applicators comprised of a real-time sensing and control system were developed and tested for spot-application of agrochemicals (fertilizer and pesticides). ... Q. Zaman

4. sUAVS Technology For Better Monitoring Crop Status For Winter Canola

The small-unmanned aircraft vehicles (sUAVS) are currently gaining more popularity in agriculture with uses including identification of weeds and crop production issues, diagnosing nutrient deficiencies, detection of chemical drift, scouting for pests, identification of biotic or abiotic stresses, and prediction of biomass and yield. Research information on the use of sUAVS have been published and conducted in crops such as rice, wheat, and corn, but the development of... I.A. Ciampitti, K. Shroyer, V. Prasad, A. Sharda, M.J. Stamm, H. Wang, K. Price, D. Mangus

5. Prediction Of Cation Exchange Capacity Using Visible And Near Infrared Spectroscopy

Cation exchange capacity (CEC) of the soil is a measure of the soil ability to hold positively charged ions and is an important indicator of soil physicochemical characteristic. It is an important property for site specific management of soil nutrients in precision agriculture. The conventional analytical methods used for the determination of CEC are expensive, difficult and time consuming, because different cations must be extracted and determined. Visible and near infrared (vis-NIR) spectroscopy... Y. Ulusoy, Z. Tümsavas, A.M. Mouazen, Y. Tekin

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. Development of an Airborne Remote Sensing System for Aerial Applicators

An airborne remote sensing system was developed and tested for recording aerial images of field crops, which were analyzed for variations of crop health or pest infestation. The multicomponent system consists of a multi-spectral camera system, a camera control system, and a radiometer for normalizing images. To overcome the difficulties currently associated with correlating imagery data with what is actually occurring on the ground (a process known as ground truthing); a hyperspectral reflectance... Y. Lan, Y. Huang, D.E. Martin, W.C. Hoffmann, B.K. Fritz, J.D. López

8. Effective Use of a Debris Cleaning Brush for Mechanical Wild Blueberry Harvesting

Wild blueberries are an important horticultural crop native to northeastern North America. Management of wild blueberry fields has improved over the past decade causing increased plant density and leaf foliage. The majority of wild blueberry fields are picked mechanically using tractor mounted harvesters with 16 rotating rakes that gently comb through the plants. The extra foliage has made it more difficult for the cleaning brush to remove unwanted debris (leaf, stems, weeds, etc.) from the picker... K. Esau, Q. Zaman, A. Farooque, A. Schumann

9. Exploring Relationships Between Dairy Herd Improvement Metrics in Minas Gerais – Brazil Dairy Herds

The objective of the present study was to apply principal component analysis (PCA) on Brazilian Dairy Herd Improvement (DHI) data to discover the subset of most meaningful variables to describe complete lactations. The Holstein Livestock Breeders Association of Minas Gerais provided data collected between 2005 and 2016 from 122 dairy farms located in the State of Minas Gerais – Brazil. Twelve numerical variables were selected from the original dataset and four additional variables were created.... G.M. Dallago, D. Figueiredo, R. Santos, P. Andrade, D. Santos

10. Relationships Between First Test Day Metrics of First Lactation Cows to Evaluate Transition Period

The objective of this study was to apply principal component analysis (PCA) and multiple correspondence analysis (MCA) on Dairy Herd Improvement (DHI) data of animals on their first lactation to discover the most meaningful set of variables that describe the outcome on the first test day. Data collected over 4 years were obtained from 13 dairy herds located in Québec – Canada. The data set was filtered to contain only information from first test day of animals on their first lactation,... G.M. Dallago, D. Figueiredo, R. Santos, P. Andrade, D.E. Santschi, R. Lacroix, D.M. Lefebvre

11. Active Canopy Sensor-Based Precision Rice Management Strategy for Improving Grain Yield, Nitrogen and Water Use

The objective of this research was to develop an active crop sensor-based precision rice (Oryza sativa L.) management (PRM) strategy to improve rice yield, N and water use efficiencies and evaluate it against farmer’s rice management in Northeast China. Two field experiments were conducted from 2011 to 2013 in Jiansanjiang, Heilongjiang Province, China, involving four treatments and two varieties (Kongyu 131 and Longjing 21). The results indicated that PRM system significantly increased... J. Lu, H. Wang, Y. Miao

12. Experimental Study Using Wind Tunnel for Measuring Variability of Spray Drift Sedimentation

Spray drift is defined as physical movement of pesticides by air action as a particle droplet and is not deposited on the intended target. Evaluation of the parameters affecting on spray drift is difficult. The accurate studies are expensive, as well as, the variability is high under field conditions due to instability in wind speed and turbulence. Wind tunnel experiments are adequate to simulate the results of field measurements for spray drift. A laboratory experiments were carried out to study... M.H. Alheidary, J. Douzals, C. Sinfort

13. Design of Ground Surface Sensing Using RADAR

Ground sensing is the key task in harvesting head control system. Real time sensing of field topography under vegetation canopy is very challenging task in wild blueberry cropping system. This paper presents the design of an ultra-wide band RADAR sensing, scanning device to recognize the soil surface level under the canopy structure. Requirements for software and hardware were considered to determine the usability of the ultra-wide band RADAR system.An automated head elevation... M.M. Mohamed, Q. Zaman, T. Esau, A. Farooque

14. Economic Potential of RoboWeedMaps - Use of Deep Learning for Production of Weed Maps and Herbicide Application Maps

In Denmark, a new IPM ‘product chain’ has been constructed, which starts with systematic photographing of fields and ends up with field- or site-specific herbicide application. A special high-speed camera, mounted on an ATV took sufficiently good pictures of small weed plants, while driving up to 50 km/h. Pictures were uploaded to the RoboWeedMaps online platform, where appointed internal- and external persons with agro-botanical experience executed ‘virtual field inspection’... P. Rydahl, O. Boejer, N. Jensen, B. Hartmann, R. Jorgensen, M. Soerensen, P. Andersen, L. Paz, M.B. Nielsen

15. Development of a Granular Herbicide Spot Applicator for Management of Hair Fescue (Festuca Filiformis) in Wild Blueberry (Vaccinium Angustifolium)

Hair fescue has quickly become the pest of greatest concern for the wild blueberry industry. This is largely due to its ability to outcompete wild blueberry for critical resources including water, nutrients and most importantly space. In Nova Scotia, between 2001 and 2019, hair fescue had increased in field frequency from 7% to 68% and in field uniformity from 1.4% to 25%. This rapidly spreading and economically destructive weed is likewise a significant challenge to manage, with only a single... C. Maceachern, T. Esau, Q. Zaman

16. Integration of High Resolution Multitemporal Satellite Imagery for Improving Agricultural Crop Classification: a Case Study

Timely and accurate agriculture information is vital for ensuring global food security. Satellite imagery has already been proved as a reliable tool for remote crop mapping. Planet satellite imagery provides high cadence, global satellite coverage with higher temporal and spatial resolution than the Landsat-8 and Sentinel-2. This study examined the potential of utilizing high-resolution multitemporal imagery along with and normalized difference vegetation index (NDVI) to map the agricultural crops... U. Ali, T. Esau, A. Farooque, Q. Zaman

17. Spatial and Temporal Factors Impacting Incremental Corn Nitrogen Fertilier Use Efficiency

Current tools for making crop N fertilizer recommendations are primarily based on plot and field studies that relate the recommendation to the economic optional N rate (EONR).  Some tools rely entirely on localized EONR (e.g., MRTN). In recent years, tools have been developed or adapted to  account for within-field variation in crop N need or variable within season factors. Separately, attention continues to elevate for how N fertilizer recommendations might account for environmental... N.R. Kitchen, C.J. Ransom, J.S. Schepters, J.L. Hatfield, R. Massey

18. Identifying Key Factors Influencing Yield Spatial Pattern and Temporal Stability for Management Zone Delineation

Management zone delineation is a practical strategy for site-specific management. Numerous approaches have been used to identify these homogenous areas in the field, including approaches using multiple years of historical yield maps. However, there are still knowledge gaps in identifying variables influencing spatial and temporal variability of crop yield that should be used for management zone delineation. The objective of this study is to identify key soil and landscape properties affecting... L.N. Lacerda, Y. Miao, K. Mizuta, K. Stueve

19. Cloud Correction of Sentinel-2 NDVI Using S2cloudless Package

Optical satellite-derived Normalized Difference Vegetation Index (NDVI) is by far the most commonly used vegetation index value for crop monitoring. However, it is quite sensitive to the cloud, and cloud shadows and significantly decreases its usability, especially in agricultural applications. Therefore, an accurate and reliable cloud correction method is mandatory for its effective application. To address this issue, we have developed an approach to correct the NDVI values of each and every... A. Saxena, M. Dash, A.P. Verma

20. In-season Diagnosis of Winter Wheat Nitrogen Status Based on Rapidscan Sensor Using Machine Learning Coupled with Weather Data

Nitrogen nutrient index (NNI) is widely used as a good indicator to evaluate the N status of crops in precision farming. However, interannual variation in weather may affect vegetation indices from sensors used to estimate NNI and reduce the accuracy of N diagnostic models. Machine learning has been applied to precision N management with unique advantages in various variables analysis and processing. The objective of this study is to improve the N status diagnostic model for winter wheat by combining... J. Lu, Z. Chen, Y. Miao, Y. Li, Y. Zhang, X. Zhao, M. Jia

21. Within-field Spatial Variability in Optimal Sulfur Rates for Corn in Minnesota: Implications for Precision Sulfur Management

The ongoing decline in sulfur (S) atmospheric depositions and high yield crop production have resulted in S deficiency and the need for S fertilizer applications in corn cropping systems. Many farmers are applying S fertilizers uniformly across their fields. Little has been reported on the within-field spatial variability in optimal S rates and the potential benefits of variable rate S applications. The objectives of this study were to 1) assess within-field variability of optimal S rates (OSR),... R.P. Negrini, Y. Miao, K. Mizuta, K. Stueve, D. Kaiser, J.A. Coulter

22. Estimating Water and Nitrogen Deficiency in Corn Using a Multi-parameter Proximal Sensor

The Crop Circle Phenom (CCP) is an innovative integrated proximal sensor that can be potentially used to perform in-season diagnosis of nitrogen and water status. In addition to measuring spectral reflectance in several bands including the red, red edge, and near-infrared wavelengths, the CCP can also measure canopy and air temperatures and provides several parameters that can be associated with chlorophyll content, crop vigor, and water status. These capabilities differentiate the CCP from other... L. Lacerda, Y. Miao, V. Sharma, A. E. flores, A. Kechchour, J. Lu

23. 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

24. Evaluating Different Strategies to Analyze On-farm Precision Nitrogen Trial Data

On-farm trials are being conducted by more and more researchers and farmers. On-farm trials are very different to traditional small plot experiments due to the existence of significant within-field variability in soil-landscape conditions. Traditional statistical techniques like analysis of variance (ANOVA) are commonly adopted for on-farm trial analysis to evaluate overall performance of different treatments, assuming uniform environmental and management factors within a field. As a result, the... K. Mizuta, Y. Miao, J. Lu, R.P. Negrini

25. On-farm Evaluation of a Satellite Remote Sensing-based Precision Nitrogen Management Strategy

Improper management of nitrogen (N) fertilizers in the cropping systems of the U.S. Midwest has resulted in significant N leaching into the Mississippi River Basin that flows to the Gulf of Mexico. The majority of the U.S. Midwest states need to develop a plan for a nutrient loss reduction strategy to decrease N and phosphorous loadings into waters and the Gulf of Mexico by 45% by 2050. In Minnesota, high nitrate concentration and loads have not been significantly reduced in surface and ground... J. Lu, Y. Miao, C.J. Ransom, F. Fernández