Proceedings
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| Filter results4 paper(s) found. |
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1. Key Data Ownership, Privacy and Protection Issues and Strategies for the International Precision Agriculture IndustryPrecision agriculture companies seek to leverage technology to process greater volumes of data, greater varieties of data, and at a velocity unfathomable to most. The promises of boundless benefits are coupled with risks associated with data ownership, stewardship and privacy. This paper presents some risks related to the management of farm data, in general, as well as those unique to operating in the international arena. Examples of U.S. and international laws related to data protection... J.K. Archer, C.A. Delgadillo, F. Shen |
2. Apparent Electrical Conductivity Sensors and Their Relationship with Soil Properties in Sugarcane FieldsOne important tool within the technological precision agriculture (PA) package are the apparent electrical conductivity (ECa) sensors. This kind of sensor shows the ability in mapping soil physicochemical variability quickly, with high resolution and at low cost. However, the adoption of this technology in Brazil is not usual, particularly on sugarcane fields. A major issue for farmers is the applicability of ECa, how to convert ECa data in knowledge that may assist the producer in decision-making... G.M. Sanches, L.R. Amaral, T. Pitrat, T. Brasco, P.S. Magalhaes, D.G. Duft, H.C. Franco |
3. Correlations Between Meteorological Parameters and the Water Loss of Maize from Silking to HarvestingThe University of Debrecen provides outstanding conditions for the development of “Smart Weather for Precision Agriculture” programs. The reliability of research is provided by the Polyfactoral Long-term Field Experiments of Debrecen (hybrid x fertilisation x plant density x tillage x irrigation) established in 1983. Within this research program, it is possible to examine various crop cultures, cultivars and hybrids under changing natural, environmental and weather circumstances,... K.B. Bodnár, J. Nagy, B. Gombos |
4. 3D Computer Vision with a Spatial-temporal Neural Network for Lameness Detection of SowsThe lameness of sows is one of the biggest concerns for swine producers, which can lead to considerable economic losses due to reduced productivity and welfare. There is a real need for early detection of lameness in sows to enable timely intervention and minimize loss. Currently, lame detection relies on visual observation and locomotion scoring of sows, which is subjective, labor-intensive, and difficult to conduct for large groups of animals within a short time. This study presents 3D computer... Y. Wang, Y. Lu, D. Morris, M. Benjamin, M. Lavagnino, J. Mcintyre |