Proceedings
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| Filter results4 paper(s) found. |
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1. Rationale for and Benefits of a Community for On-Farm Data SharingMost data sets for evaluating crop production practices have too few locations and years to create reliable probabilities from predictive analytical analyses for the success of the practices. Yield monitors on combines have the potential to enable networks of farmers in collaboration with scientists and farm advisors to collect sufficient data for calculation of more reliable guidelines for crop production showing the probabilities that new or existing practices will improve the efficiency of... T. Morris, N. Tremblay, P.M. Kyveryga, D.E. Clay, S. Murrell, I. Ciampitti, L. Thompson, D. Mueller, J. Seger |
2. Draft Privacy Guidelines and Proposal Outline to Create a Field-Scale Trial Data Repository for Data Collected by On-Farm NetworksImplementing better management practices in corn and soybeans that increase profitability and reduce pollution caused by the practices requires large numbers of field-scale, replicated trials. Numerous complex and often unmeasurable interactions among the environment, genetics and management at the field scale require large numbers of trials completed at the field scale in a systematic and uniform manner to enable calculation of probabilities that a practice will be an improvement compared with... T. Morris, N. Tremblay |
3. Rapid Acquisition of Site Specific Lime Requirement with Mid-Infrared SpectroscopyIn Germany, the lime requirement of arable topsoils is derived from the organic matter content, clay content, and pH(CaCl2). For this purpose, it is common practice to determine the lime requirement of a field size up to three hectares from only one composite soil sample, whereby site heterogeneity is regularly not taken into account. To consider site heterogeneity, a measurement technique is required which allows a rapid and high resolution data acquisition. Mid-infrared... M. Leenen, S. Pätzold, T. Heggemann, G. Welp |
4. Towards Universal Applicability of On-the-Go Gamma-Spectrometry for Soil Texture Estimation in Precision Farming by Using Machine Learning ApplicationsHigh resolution soil data are an essential prerequisite for the application of precision farming techniques. Sensor-based evaluation of soil properties may replace or at least reduce laborious, time-consuming and expensive soil sampling with subsequent measurements in the lab. Gamma spectrometry usually provides information that can be translated into topsoil texture data after calibration. This is because the natural content of the radioactive isotopes 40-K, 232-Th, and 238-U as well... S. Pätzold, T. heggemann, M. Leenen, S. Koszinski, K. Schmidt, G. Welp |