Proceedings
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| Filter results5 paper(s) found. |
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1. The Ultimate Soil Survey in One Pass: Soil Texture, Organic Matter, pH, Elevation, Slope, and CurvatureThe goal of accurately mapping soil variability preceded GPS-aided agriculture, and has been a challenging aspect of precision agriculture since its inception. Many studies have found the range of spatial dependence is shorter than the distances used in most grid sampling. Other studies have examined variability within government soil surveys and concluded that they have limited utility in many precision applications. Proximal soil sensing has long been envisioned as a method... E. Lund, C. Maxton, G. Kweon |
2. Spatial Modelling Of Agricultural Crops For Parallel Loading OperationsThere is a trend in agricultural engineering towards high-performance harvesting machines with growing operating width and throughput. As much as performance and throughput are rising, the transportation units are characterized by increasing transportation volume. If harvesting and transport are combined in parallel operation (e.g. self-propelled forage harvester), the driver of the harvesting machine and the driver of the transport unit has to pay highest attention to the loading process.... G. Happich, T. Lang, H. Harms |
3. Implementation of a CAN Bus System to Monitor Hydroponic SystemsControlled Area Network (CAN) bus systems designed for greenhouse monitoring have been proposed to measure soil moisture content, yet they are still absent from hydroponic systems. In this study, irrigation control, monitoring of substrate moisture levels and temperature were achieved using a CAN bus system connected to hydroponic beds. In total, five nodes were mounted on five hydroponic beds and two irrigation methods were compared on lettuce and kale: first, where a pre-set timer activated... P. Tikasz, R.M. Buelvas, M. Lefsrud, V. Adamchuk |
4. Laser Triangulation for Crop Canopy MeasurementsFrom a Precision Agriculture perspective, it is important to detect field areas where variabilities in the soil are significant or where there are different levels of crop yield or biomass. Information describing the behavior of the crop at any specific point in the growing season typically leads to improvements in the manner the local variabilities are addressed. The proper use of dense, in-season sensor data allows farm managers to optimize harvest plans and shipment schedules under variable... R.M. Buelvas, V.I. Adamchuk |
5. Sampling Bumble Bees and Floral Resources Using Deep Learning and UAV ImageryPollinators, essential components of natural and agricultural systems, forage over relatively large spatial scales. This is especially true of large generalist species, like bumble bees. Thus, it can be difficult to estimate the amount and diversity of floral resources available to them. Floral cover and diversity are often estimated over large areas by extrapolation from small scale samples (e.g., a 1-m quadrat) but the accuracy of such estimates can vary depending on the spatial patchiness of... B. Spiesman, I. Grijalva, D. Holthaus, B. Mccornack |