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| Filter results7 paper(s) found. |
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1. Comparison Of Different Vegetation Indices And Their Suitability To Describe N-uptake In Winter Wheat For Precision FarmingTo avoid environment pollution and to minimize the costs of using mineral fertilizers an efficient fertilization system, tailored to the plant needs becomes more and more important. For that, the essential information can be determined by detecting certain crop parameters, like dry matter of the plant biomass above ground, N-content and N-uptake. By using fluorescence and reflectance measurements of the canopy and the mathematical analysis these parameters are appreciable. In three years,... M. Strenner, F. Maidl |
2. Use Of Vegetation Indices In Variable Rate Application Of Potato Haulm Killing HerbicidesVariable rate application (VRA) of pesticides based on measured spatial variation in crop biomass is possible with currently available crop reflection sensors (remote and proximity), GNSS technology and modern field sprayers. VRA has the potential to contribute to a more sustainable use of pesticide. Dose rates are optimized based on local requirements at a scale of about 5-50 m2, leading to less adverse side effects, less costs and higher yields. In the longer term, we... C. Kempenaar, T. Been, F.V. Evert |
3. Towards Data-intensive, More Sustainable Farming: Advances in Predicting Crop Growth and Use of Variable Rate Technology in Arable Crops in the NetherlandsPrecision farming (PF) will contribute to more sustainable agriculture and the global challenge of producing ‘More with less’. It is based on the farm management concept of observing, measuring and responding to inter- and intra-field variability in crops. Computers enabled the use of Farm Management Information Systems (FMIS) and farm and field specific Decision Support Systems (DSS) since mid-1980s. GIS and GNSS allowed since ca. 2000 geo-referencing of data and controlled traffic... C. Kempenaar, F. Van evert, T. Been, C. Kocks, K. Westerdijk, S. Nysten |
4. Large-scale UAS Data Collection, Processing and Management for Field Crop ManagementNorth Dakota State University research and Extension personnel are collaborating with Elbit Systems of America to compare the usefulness and economics of imagery collected from a large unmanned aircraft systems (UAS), small UAS and satellite imagery. Project personnel are using a large UAS powered with an internal combustion engine to collect high-resolution imagery over 100,000 acres twice each month during the crop growing season. Four-band multispectral Imagery is also being collected twice... J. Nowatzki, S. Bajwa, D. Roberts, M. Ossowski, A. Scheve, A. Johnson, Y. Chaplin |
5. Nitrogen Sensing by Using Spectral Reflectance Measurements in Cereal Rye CanopyCereal rye (cereale secale L.) is a winter crop well suited for cultivation especially besides high yield areas because of its relatively low demands on the soil and on the climate as well. In 2016 about 4.9% of arable land in Germany was cultivated with cereal rye (Statistisches Bundesamt, 2017). Unlike other crops such as wheat, there is little research on cereal rye for site specific farming. Furthermore, also in a cereal rye cultivation it is necessary to minimize nitrogen loss.... M. Strenner, F.X. Maidl, K.J. Hülsbergen |
6. Akkerweb: A Platform for Precision Farming Data, Science, and PracticeThe concept of precision farming (PF) was formulated about 40 years ago and the scientific knowledge for some applications of PF in The Netherlands has been available for almost 20 years. Also, in many cases equipment is available to implement PF in practice. In spite of all this PF uptake is still limited. An important reason for the limited uptake of PF is in the challenges that must be overcome to let data flow from sensors to data storage, to combine data sources and process them into recommendations,... F.K. Van evert, T. Been, J.A. Booij, C. Kempenaar, G.J. Kessel, L.P. Molendijk |
7. Next in Precision Agriculture: Detecting and Correcting Pixels with Machinery Track Line Within FarmsWith more satellites orbiting the earth, monitoring of fields using satellite data has become easier and ubiquitous. Frequent observations of a field can provide vital cues about field health and management practices. However, farm analytical statistics derived from such datasets often need modification to create practical applications. This paper focuses on the detection and removal of field machinery track line pixels to reduce their effect on satellite-based agronomic recommendation and product... G. Rathee, M. Sielenkemper |