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Mat Su, A
Mailwald, M
Emmons, A
Farooque, A
Carter, P
Mansouri, M.M
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Authors
Mansouri, M.M
Adamchuk, V.I
Mat Su, A
Bean, G
Kitchen, N.R
Franzen, D.W
Miles, R.J
Ransom, C
Scharf, P
Camberato, J
Carter, P
Ferguson, R.B
Fernandez, F.G
Laboski, C
Nafziger, E
Sawyer, J
Shanahan, J
Gebbers, R
Dworak, V
Mahns, B
Weltzien, C
Büchele, D
Gornushkin, I
Mailwald, M
Ostermann, M
Rühlmann, M
Schmid, T
Maiwald, M
Sumpf, B
Rühlmann, J
Bourouah, M
Scheithauer, H
Heil, K
Heggemann, T
Leenen, M
Pätzold, S
Welp, G
Chudy, T
Mizgirev, A
Wagner, P
Beitz, T
Kumke, M
Riebe, D
Kersebaum, C
Wallor, E
Esau, K
Zaman, Q
Farooque, A
Schumann, A
Mohamed, M.M
Zaman, Q
Esau, T
Farooque, A
Ali, U
Esau, T.J
Farooque, A
Zaman, Q
Khan, H
Esau, T
Farooque, A
Abbas, F
Leininger, A
Verhoff, K
Lovejoy, K
Thomas, A
Davis, G
Emmons, A
Fulton, J.P
Zaman, Q.U
Farooque, A
Jamei, M
Esau, T.J
Topics
Food Security and Precision Agriculture
Proximal Sensing in Precision Agriculture
Precision Nutrient Management
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Decision Support Systems
Precision Agriculture and Global Food Security
Drone Spraying
Big Data, Data Mining and Deep Learning
Type
Oral
Poster
Year
2014
2016
2018
2022
2024
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Authors

Filter results10 paper(s) found.

1. Predicting Winter Wheat Biomass And Grain Protein Content

Dynamic crop models such as EPIC [1], SALUS [2], and STICS [3] are non-linear models that describe the growth and development of a crop interacting with environmental factors (soil and climate) and agricultural practices (crop species, tillage type, fertilizer amount…). They are developed to predict crop yield and quality or to optimize the farming practices in order to satisfy agricultural objectives, as the reduction of nitrogen lixiviation. More recently, crop... M.M. Mansouri

2. Evaluation Of The Temporal And Operational Stability Of Apparent Soil Electrical Conductivity Measurements

Measuring apparent soil electrical conductivity (ECa), using galvanic contact resistivity (GCR) and electromagnetic induction (EMI) techniques is frequently used to implement site-specific crop management. Various research projects have demonstrated the possibilities for significant changes in the measured quantities over time with relatively stable spatial structure representations. The objective of this study was to quantify the effects of temporal drift and operational noise for three... V.I. Adamchuk, A. Mat su

3. Modifying the University of Missouri Corn Canopy Sensor Algorithm Using Soil and Weather Information

Corn production across the U.S. Corn belt can be often limited by the loss of nitrogen (N) due to leaching, volatilization and denitrification. The use of canopy sensors for making in-season N fertilizer applications has been proven effective in matching plant N requirements with periods of rapid N uptake (V7-V11), reducing the amount of N lost to these processes. However, N recommendation algorithms used in conjunction with canopy sensor measurements have not proven accurate in making N recommendations... G. Bean, N.R. Kitchen, D.W. Franzen, R.J. Miles, C. Ransom, P. Scharf, J. Camberato, P. Carter, R.B. Ferguson, F. Fernandez, C. Laboski, E. Nafziger, J. Sawyer, J. Shanahan

4. Integrated Approach to Site-specific Soil Fertility Management

In precision agriculture the lack of affordable methods for mapping relevant soil attributes is a funda­mental problem. It restricts the development and application of advanced models and algorithms for decision making. The project “I4S - Integrated System for Site-Specific Soil Fertility Management” combines new sensing technologies with dynamic soil-crop models and decision support systems. Using sensors with different measurement principles improves the estimation of soil fertility... R. Gebbers, V. Dworak, B. Mahns, C. Weltzien, D. Büchele, I. Gornushkin, M. Mailwald, M. Ostermann, M. Rühlmann, T. Schmid, M. Maiwald, B. Sumpf, J. Rühlmann, M. Bourouah, H. Scheithauer, K. Heil, T. Heggemann, M. Leenen, S. Pätzold, G. Welp, T. Chudy, A. Mizgirev, P. Wagner, T. Beitz, M. Kumke, D. Riebe, C. Kersebaum, E. Wallor

5. 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

6. 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

7. 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

8. Suitability of ML Algorithms to Predict Wild Blueberry Harvesting Losses

The production of wild blueberries (Vaccinium angustifolium.) is contributing 112.2 million dollars to the Canada’s revenue which can be further increased through controlling harvest losses. A precise prediction of blueberry harvesting losses is necessary to mitigate such losses. In this study, the performance of three machine learning (ML) models was evaluated to predict the wild blueberry harvest losses on the ground. The data from four commercial fields in Atlantic Canada were... H. Khan, T. Esau, A. Farooque, F. Abbas

9. Deposition Characteristics of Different Style Spray Tips at Varying Speeds and Altitudes from an Unmanned Aerial System

The application of pesticides with a UAS has become a popular practice over the past few years within crop production. The ability to carry larger volumes of liquid i onboard, reduced costs, and simple operation has attributed to the increased popularity. Additionally, the increased number of fungicide applications in corn due to the tar spot disease has shown that the demand for aerial applications of all types has increased with UAS pesticide application technology providing the opportunity... A. Leininger, K. Verhoff, K. Lovejoy, A. Thomas, G. Davis, A. Emmons, J.P. Fulton

10. Application of Advanced Soft Computing to Estimate Potato Tuber Yield: a Case Study from Atlantic Canada

The potato crop plays a crucial role in the economy of Atlantic Canada, particularly in Prince Edward Island and New Brunswick, where it contributes significantly to potato production. To help farmers make informed decisions for sustainable and profitable farming, this study was conducted to examine the variations in potato tuber yield based on thirty soil properties collected over four growing seasons through experimental trials. The study employed an advanced and explainable ensemble model called... Q.U. Zaman, A. Farooque, M. Jamei, T.J. Esau