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Scholz, C
Gombos, B
Zaman, Q.U
Maharlooei, M
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Authors
Khan, F.S
Zaman, Q.U
Schumann, A.W
Madani, A
Percival, D.C
Farooque, A.A
Saleem, S.R
Khan, F.S
Farooque, A.A
Zaman, Q.U
Groulx, D
Schumann, A.W
Esau, T.J
Chang, Y.K
Ma, W
Zhao, C
Zaman, Q.U
Zach, D
Göttinger, M
Hinck, S
Möller, K
Ruckelshausen, A
Scholz, C
Nowatzki, J
Bajwa, S
Sivarajan, S
Maharlooei, M
Kandel, H
Shirzadi, A
Maharlooei, M
hassanijalilian, O
Bajwa, S
Howatt, K
Sivarajan, S
Nowatzki, J
Maharlooei, M
Bajwa, S
Mireei, S.A
Shirzadi, A
Sivarajan, S
Berti, M
Nowatzki, J
Bodnár, K.B
Nagy, J
Gombos, B
Tsukor, V
Scholz, C
Nietfeld, W
Heinrich, T
Mosler , T
Lorenz, F
Najdenko, E
Möller, A
Mentrup, D
Ruckelshausen, A
Hinck, S
Hennessy, P.J
Esau, T.J
Schumann, A.W
Farooque, A.A
Zaman, Q.U
White, S.N
Topics
Spatial Variability in Crop, Soil and Natural Resources
Precision Horticulture
Engineering Technologies and Advances
Sensor Application in Managing In-season CropVariability
Remote Sensing Applications in Precision Agriculture
Proximal Sensing in Precision Agriculture
Smart Weather for Precision Agriculture
Site-Specific Nutrient, Lime and Seed Management
Big Data, Data Mining and Deep Learning
Type
Poster
Oral
Year
2012
2010
2014
2016
2018
2022
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Filter results10 paper(s) found.

1. 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

2. 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

3. 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

4. Automatic Soil Penetrometer Measurements And GIS-Based Documentation With The Autonomous Field Robot Platform BoniRob

For a sustainable agriculture, reliable measurements of soil properties and its interpretation are of highest relevance. Until today most of the measurements are carried out manually or by integrating off-line laboratories. Moreover, the number and density of measurement points is always an important aspect with respect to the statistical significance of the results. In this work a fully automatic measurement system has been developed and applied for the first time with free selectable... M. Göttinger, S. Hinck, K. Möller, A. Ruckelshausen, C. Scholz

5. Evaluation Of In-Field Sensors To Monitor Nitrogen Status In Soybean

In recent years, active optical crop sensors have been gaining importance to determine in-season nitrogen (N) fertilization requirements for on-the-go variable rate application.  Although most of these active in-field crop sensors have been evaluated in corn and wheat crops, they have not yet been evaluated in soybean production systems in North Dakota. Recent research from both South Dakota and North Dakota indicate that in-season N application in soybean can increase soybean yield... J. Nowatzki, S. Bajwa, S. Sivarajan, M. Maharlooei, H. Kandel

6. Greenhouse Study to Identify Glyphosate-resistant Weeds Based on Canopy Temperature

Development of herbicide-resistant crops has resulted in significant positive changes to agronomic practices, while repeated and intensive use of herbicides with the same mechanisms of action has caused the development of herbicide-resistant weeds. As of 2015, 35 weed species are reported to be resistant to glyphosate worldwide. A greenhouse study was conducted to identify characteristics which can be helpful in field mapping of glyphosate resistant weeds by using UAV imagery. The experiment included... A. Shirzadi, M. Maharlooei, O. Hassanijalilian, S. Bajwa, K. Howatt, S. Sivarajan, J. Nowatzki

7. Vis/NIR Spectroscopy to Estimate Crude Protein (CP) in Alfalfa Crop: Feasibility Study

The fast and reliable quality determination of alfalfa crop is of interest for producers to make management decisions, the dealers to determine the price, and the dairy producers for livestock management. In this study, the crude protein (CP), one of the main quality indices of alfalfa, was estimated using the visible and near-infrared (Vis/NIR) spectroscopy. A total of 68 samples from various variety trials of alfalfa crop were collected under the irrigated and rainfed conditions. The diffuse... M. Maharlooei, S. Bajwa, S.A. Mireei, A. Shirzadi, S. Sivarajan, M. Berti, J. Nowatzki

8. Correlations Between Meteorological Parameters and the Water Loss of Maize from Silking to Harvesting

The University of Debrecen provides outstanding conditions for the development of “Smart Weather for Precision Agriculture” programs. The reliability of research is provided by the Polyfactoral Long-term Field Experiments of Debrecen (hybrid x fertilisation x plant density x tillage x irrigation) established in 1983. Within this research program, it is possible to examine various crop cultures, cultivars and hybrids under changing natural, environmental and weather circumstances,... K.B. Bodnár, J. Nagy, B. Gombos

9. soil2data: Concept for a Mobile Field Laboratory for Nutrient Analysis

Knowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields... V. Tsukor, C. Scholz, W. Nietfeld, T. Heinrich, T. Mosler , F. Lorenz, E. Najdenko, A. Möller, D. Mentrup, A. Ruckelshausen, S. Hinck

10. 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