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Filter results8 paper(s) found. |
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1. Monitoring Dairy Cow Activity With GPS-tracking And Supporting TechnologiesNutrient loss from dairy farms is an issue of serious concern to most dairy farmers around the world. On grazed systems such as those practiced in New Zealand animal excreta has been identified as a major source of nutrient loss, which for nitrogen (N) relates to cattle urine in particular. A study was commissioned to examine nutrient transfer around dairy farms associated with the cows with a view to developing improved precision nutrient application... I. Draganova, I.J. Yule, K. Betteridge, M.J. Hedley, K.J. Stafford |
2. Potential of Visible and Near Infrared Spectroscopy for Prediction of Paddy Soil Physical PropertiesA fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of Visible (Vis) and Near-infrared Reflectance Spectroscopy (NIRS) to predict paddy soil physical properties in a typical Malaysian paddy field. To assess the utility of spectroscopy for soil physical characteristics prediction, we used 118 soil samples for laboratory analysis and optical measurement in the Vis-NIR region... A. Gholizadeh, M. Saberioon, M. Mohd soom |
3. Development of a Quick Diagnosis Method to Target Fields with Better Potential for Site-Specific Weed ManagementSite-specific weed management appears as an innovative way of saving herbicides in crop while maintaining yield. This can potentially lead economic and ecological benefits. However, it was reported in the literature that savings range from 1 % to 94 % from one field to the other. This implies that certain fields... B. Panneton, M. Simard, G.D. Leroux, L. Longchamps |
4. Realising the Full Potential of Precision Agriculture: Encouraging Farmer 'Buy-in' by Building Trust in Data SharingUncertainty around the ownership, privacy and security of farm data are most commonly the reasons cited for farmer’s reluctance to “buy-in” to big data in agriculture. Evidence provided to the recent US Committee on Commerce, Science, and Transportation Subcommittee on Consumer Protections, Product Safety, Insurance, and Data Security, United States Senate Technology in Agriculture: Data Driven Farming (Nov 2017) highlighted that “data ownership, and related... L. Wiseman, J. Sanderson |
5. A Comparison of Three-Dimensional Data Acquisition Methods for Phenotyping ApplicationsCurrently Phenotyping is primarily performed using two-dimensional imaging techniques. While this yields interesting data about a plant, a lot of information is lost using regular cameras. Since a plant is three-dimensional, the use of dedicated 3D-imaging sensors provides a much more complete insight into the phenotype of the plant. Different methods for 3D-data acquisition are available, each with their inherent advantages and disadvantages. These have to be addressed depending on the particular... O. Scholz, F. Uhrmann, S. Gerth, K. Pieger, J. Claußen |
6. Variety Effects on Cotton Yield Monitor CalibrationWhile modern grain yield monitors are able to harvest variety and hybrid trials without imposing bias, cotton yield monitors are affected by varietal properties. With planters capable of site-specific planting of multiple varieties, it is essential to better understand cotton yield monitor calibration. Large-plot field experiments were conducted with two southeast Missouri cotton producers to compare yield monitor-estimated weights and observed weights in replicated variety trials. Two replications... E. Vories, A. Jones, G. Stevens, C. Meeks |
7. Creating a Comprehensive Software Framework for Sensor-driven Precision AgricultureRobots and GPS-guided tractors are the backbone of smart farming and precision agriculture. Many companies and vendors contribute to the market, each offering their own customized solutions for common tasks. These developments are often based on vendor-specific, proprietary components, protocols and software. Many small companies that produce sensors, actuators or software for niche applications could contribute their expertise to the global efforts of creating smart farming solutions, if their... O. Scholz, F. Uhrmann, M. Weule, T. Meyer, A. Gilson, J. Makarov, J. Hansen, T. Henties |
8. Cherry Yield Forecast: Harvest Prediction for Individual Sweet Cherry TreesDigitalization continues to transform the agricultural sector as a whole and also affects specific niches like horticulture. Particularly in fruit and wine production, the focus is on the application of sensor systems and data analysis aiming at automated detection of drought stress or pests in vineyards or orchards. As part of the “For5G” project, we are developing an end-to-end methodology for the creation of digital twins of fruit trees, with a strong focus... A. Gilson, L. Meyer, A. Killer, F. Keil, O. Scholz, D. Kittemann, P. Noack, P. Pietrzyk, C. Paglia |