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1. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor DataCotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey |
2. Validation Of On-the-go Soil Ph-measurements – Primary Results From GermanyUntil recently in-field variability for soil pH could not be considered for agronomic decisions (e.g. liming rates) because reliable spatial information was hardly available. The required density of soil pH-measurements could not be achieved by manual soil sampling due to time constraints and analysis costs for the vast number of samples. A comprehensive... H. Olfs, D. Trautz, A. Borchert |
3. Sensor And System Technology For Individual Plant Crop ScoutingSensor and system technologies are key components for automatic treatment of individual plants as well as for plant phenotyping in field trials. Based on experiences in research and application of sensors in agriculture the authors have developed phenotyping platforms for field applications including sensors, system and software development and application-specific mountings. Sensor and data fusion have a high potential by compensating varying selectivities... A. Ruckelshausen, K.V. Alheit, L. Busemeyer, R. Klose, A. Linz, K. Moeller, F. Rahe, M. Thiel, D. Trautz, U. Weiss |
4. Categorization of Districts Based on Nonexchangeable Potassium: Generation GIS Maps and Implications in Efficient K Fertility Management in Indian AgricultureRecommendations of K fertilizer are made based on available (exchangeable + water soluble) K status only in India and other despite of substantial contribution of nonexchangeable fraction of soil K to crop K uptake. Present paper examines the information generated in the last 30 years on the status of nonexchangeable K in Indian soils, categorization of Indian soils based on exchangeable and nonexchangeable K fractions and making K recommendations. Data for both K fractions of different... C. Srinivasa rao, K. Rao, H. Magen, B. Venkateswarlu, A. Subba rao |
5. Stable Isotope N-15 as Precision Technique to Investigate Elemental Sulfur Effects on Fertilizer Nitrogen Use Efficiency of Corn Grown in Calcareous Sandy Soils... A.A. Soaud, .M. Rahman, F.H. Al darwish |
6. Soil pH maps Derived from On-the-Go pH-Measurements as Basis for Variable Lime Application under German Conditions: Concept Development and Evaluation in Field Trials... A. Borchert, D. Trautz, H. Olfs |
7. Economic Evaluation of a Variable Lime Application Strategy Based on Soil pH Maps Derived from On-The-Go pH-Measurements under German Conditions... A. Borchert, G. Recke, D. Dabbelt, D. Trautz, H. Olfs |
8. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS ImageryAerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimation... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster |
9. Influence of Ground Control Points and Processing Parameters on UAS Image Mosaicking for Plant Height EstimationDigital surface models (DSMs) and 3D point clouds, generated using overlapping images from unmanned aircraft systems (UASs), are often used for plant height estimation in phenotyping and precision agriculture. This study examined the effects of the quantity and placement of ground control points (GCPs) and image processing parameters on the creation of DSMs and 3D point clouds for plant height estimation. A 2-ha field containing multiple experimental plots with four crops (corn, cotton, sorghum,... C. Yang, H. Zhao, W. Guo, J. Zhang, C. Suh, B.K. Fritz |