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Xiu, W
Oyumaa, M
Lapen, D
Erdle, K
Verma, A.P
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Authors
Mistele, B
Schmidhalter, U
Erdle, K
Schmidhalter, U
Erdle, K
Jian, S
Xiu, W
Yan, Z.D
Qingchun, F
Xiu, W
Xiaonan, W
Guohua, W
Tumenjargal, E
Batbayar, E
Munkhbayar, S
Tsogt-Ochir, S
Oyumaa, M
Chung, K
Ham, W
Gandorfer, M
Schleicher, S
Erdle, K
Kross, A
Kaur, G
Callegari, D
Lapen, D
Sunohara, M
McNairn, H
Rudy, H
van Vliet, L
Kross, A
Kaur, G
Znoj, E
Callegari, D
Sunohara, M
McNairn, H
Lapen, D
Rudy, H
van Vliet, L
Saxena, A
Dash, M
Verma, A.P
Topics
Sensor Application in Managing In-season Crop Variability
Remote Sensing Applications in Precision Agriculture
Precision Crop Protection
Engineering Technologies and Advances
Robotics, Guidance and Automation
Profitability and Success Stories in Precision Agriculture
Decision Support Systems
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Geospatial Data
Type
Poster
Oral
Year
2012
2014
2016
2018
2022
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Filter results9 paper(s) found.

1. Comparison of Active and Passive Spectral Sensors in Discriminating Biomass Parameters and Nitrogen Status in Wheat Cultivars

Several sensor systems are available for ground-based remote sensing in crops. Vegetation indices of multiple active and passive sensors have seldom been compared in determining plant health. This study was aimed to compare active and passive sensing systems in terms of their ability to recognize agronomic parameters. One bi-directional passive radiometer (BDR) and three active sensors (Crop Circle, GreenSeeker, and an active flash sensor (AFS)) were tested for their ability to assess six destructively... B. Mistele, U. Schmidhalter, K. Erdle

2. Spectral High-Throughput Assessments Of Phenotypic Differences In Spike Development, Biomass And Nitrogen Partitioning During Grain Filling Of Wheat Under High Yielding Western European Conditions

Single plant traits such as green biomass, spike dry weight, biomass and nitrogen (N) transfer to grains are important traits for final grain yield. However, methods to assess these traits are laborious and expensive. Spectral reflectance measurements allow researchers to assess cultivar differences of yield-related plant traits and translocation parameters that are affected by different genetic material and varying amounts of available N. In a field experiment, six high-yielding wheat cultivars... U. Schmidhalter, K. Erdle

3. A Portable Instrument For Recognition Of Farm Weeds And Management Of Chemical Spray

With the information technology being popularization and application and farmers’ knowledge level being increase in China, smartphone has been accepted by peasants used as terminal of information collection and query. Recently, because of the serious diseases and insect pests, it is impossible to prevent and control these disasters when we only rely on grassroots staffs’ investigation or professors’ instruction. If each of these farmers distributed in all of the country... S. Jian, W. Xiu, Z.D. Yan

4. A Harvesting Robot System for Fresh Cherry Tomato in Greenhouse

In order to improve the , a new harvesting robot system for cherry tomato was designed and tested, which mainly consisted of a railed-type vehicle, a visual servo unit, a manipulator, a picking end-effector, and other accessories. According to the greenhouse environment and the standard planting mode, the robot configuration was determined, whose operating space could be adjusted horizontally and vertically in order to enlarge the harvesting range. Besides, a harvested fruits automatic transport... F. Qingchun, W. Xiu, W. Xiaonan, W. Guohua

5. Design and Analysis of ISO 11783 Task Controller's Functionality in Server - Client ECU for Agricultural Vehicles

A modern agricultural vehicle's electronic control units (ECU) communicated based on the ISO 11783 standards. The connection of different machines, implements, different manufacturers into a single bus for the exchange of control commands and sensor data are a challenge for the precision agriculture. One of main functionality is the Task controller in the intelligent monitoring system. The task controller is to log data and assign set-point values for automated work (task) sequences... E. Tumenjargal, E. Batbayar, S. Munkhbayar, S. Tsogt-ochir, M. Oyumaa, K. Chung, W. Ham

6. Barriers to Adoption of Smart Farming Technologies in Germany

The number of smart farming technologies available on the market is growing rapidly. Recent surveys show that despite extensive research efforts and media coverage, adoption of smart farming technologies is still lower than expected in Germany. Media analysis, a multi stakeholder workshop, and the Adoption and Diffusion Outcome Prediction Tool (ADOPT) (Kuehne et al. 2017) were applied to analyze the underlying adoption barriers that explain the low to moderate adoption levels of smart farming... M. Gandorfer, S. Schleicher, K. Erdle

7. Spatial Decision Support System: Controlled Tile Drainage – Calculate Your Benefits

Climate projection studies suggest that extreme heat waves and floods will become more frequent, affecting future crop yields by 20%-30%, globally. Managing vulnerability and risk begins at the farm level where best management practices can reduce the impacts associated with extreme weather events. A practice that can assist in mitigating the impact of some extreme events is controlled tile drainage (CTD). With CTD, producers use water flow control structures to manage the drainage of water from... A. Kross, G. Kaur, D. Callegari, D. Lapen, M. Sunohara, H. Mcnairn, H. Rudy, L. Van vliet

8. Evaluation of an Artificial Neural Network Approach for Prediction of Corn and Soybean Yield

The ability to predict crop yield during the growing season is important for crop income, insurance projections and for evaluating food security. Yet, modeling crop yield is challenging because of the complexity of the relationships between crop growth and the interrelated predictor variables. Artificial neural networks (ANNs) are useful for such complex systems as they can capture non-linear relationships of data without explicitly knowing the underlying processes. In this study, an ANN-based... A. Kross, G. Kaur, E. Znoj, D. Callegari, M. Sunohara, H. Mcnairn, D. Lapen, H. Rudy, L. Van vliet

9. 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