Proceedings
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| Filter results4 paper(s) found. |
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1. Soil Spatial Variability in the Everglades Agricultural Area in South FloridaThe Everglades agricultural area is composed by histosols laying on hard limestone bedrock in south Florida. Despite the common assumption of homogeneity of these soils, agricultural practices could result in the increase of soil variability. Therefore, soil spatial variability was studied on three fields (5.5 ha each) at the Everglades Research and Education Center to compare the changes... J.L. Pantoja, S.H. Daroub, O.A. Diaz |
2. The Application Of Fertilizer Using Management Zone (MZ) In Pampas Soils With Texture Variability Affects Residual Nitrate After HarvestThe maize yields are usually associated with soil texture heterogeneity in western Argentinean Pampas. In this area, the uniform fertilizer management (UM) increased the risk of nitrate leaching due to over-fertilizing but it could be minimized by using different management zones criteria (MZ). In a field experiment, the nitrates distribution in soil depth (0-1.80 m) at sowing and harvest times (residual Nitrate) and the maize... M. Rodriguez, G. Civeira, S. Urricariet, P. Muschietti, R. Lavado |
3. Overcoming Educational Barriers for Precision Agriculture Adoption: a University Diploma in Precision Agriculture in ArgentinaThe lack of educational programs in Precision Agriculture (PA) has been reported as one of the barriers for adoption. Our goal was to improve professional competence in PA through education in crop variability, management, and effective practices of PA in real cases. In the last 20 years different efforts has been made in Argentina to increase adoption of PA. The Universidad Nacional de Rio Cuarto (UNRC) launched in 2021 the first University Diploma in PA, a 9-month program to train agronomist... G. Balboa, A. Degioanni, R. Bongiovanni, R. Melchiori, C. Cerliani, F. Scaramuzza, M. Bongiovanni, J. Gonzalez, M. Balzarini, H. Videla, S. Amin, G. Esposito |
4. 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 |