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Rai, S
Nietfeld, W
Reiter, S
Rodrigues, F
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Authors
Souza, E
Schenatto, K
Rodrigues, F
Rocha, D
Bazzi, C.L
Iwersen, M
Reiter, S
Schweinzer, V
Kickinger, F
Öhlschuster, M
Lidauer, L
Auer, W
Drillich, M
Berger, A
Tsukor, V
Scholz, C
Nietfeld, W
Heinrich, T
Mosler , T
Lorenz, F
Najdenko, E
Möller, A
Mentrup, D
Ruckelshausen, A
Hinck, S
Dua, A
Sharda, A
Schapaugh, W
Hessel, R
Rai, S
Rai, S
Sharda, A
Berretta, B.G
Topics
Precision Conservation Management
Precision Dairy and Livestock Management
Site-Specific Nutrient, Lime and Seed Management
Proximal and Remote Sensing of Soils and Crops (including Phenotyping)
Artificial Intelligence (AI) in Agriculture
Type
Poster
Oral
Year
2014
2018
2024
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Filter results5 paper(s) found.

1. Comparison Of Management Zones Generated By The K-Means And Fuzzy C-Means Methods

The generation of Management Zones (MZ) is an economic alternative to make viable the precision agriculture (RODRIGUES & ZIMBACK, 2002) because they work as operation units for the inputs localized application and as soil and culture sample indicators. For the field division in... E. Souza, K. Schenatto, F. Rodrigues, D. Rocha, C. Bazzi

2. Evaluation of an Ear Tag Based Accelerometer for Monitoring Rumination Time, Chewing Cycles and Rumination Bouts in Dairy Cows

The objective of this study was to evaluate the ear tag based accelerometer SMARTBOW (Smartbow, Weibern, Austria) for detecting rumination time, chewing cycles and rumination bouts in dairy cows. For this, the parameters were determined by analyses of video recordings as reference and compared with the results of the accelerometer system. Additionally, the intra- and inter-observer reliability as well as the agreement of direct cow observations and video recordings was tested. Ten Simmental cows... M. Iwersen, S. Reiter, V. Schweinzer, F. Kickinger, M. Öhlschuster, L. Lidauer, W. Auer, M. Drillich, A. Berger

3. 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

4. Rapid Assessment of Yield Using Machine Learning Models and UAV Multispectral Imagery for Soybean Breeding Plots

Advances in precision agriculture in data collection, crop monitoring, screening, and management over the 10-15 years are revolutionizing on-farm agricultural research trials. In crop breeding plots, this approach is called "High Throughput Phenotyping", which uses innovative technology to extract phenotypic data for large populations. Remote sensing has become one of the commonly used platforms for rapid acquisition of imagery data at spatial and temporal scale. Particularly, the unmanned... A. Dua, A. Sharda, W. Schapaugh, R. Hessel, S. Rai

5. Enhancing Seeding Efficiency: Evaluating Row Cleaners with Computer Vision in Precision Agriculture

In precision agriculture, the effective sowing of seeds is crucial but often hindered by challenges like hair pinning, low soil temperatures, and heavy residue on the soil surface. To address these issues, row cleaners are employed to clear the path for seeder opener discs, ensuring a clean, uniform trench for seed placement. This study examines the performance of various row cleaner models and introduces a novel method for their automatic, quantitative evaluation using computer vision technology.  We... F. Sidharth, A. Sharda, B.G. Berretta