Proceedings
Authors
| Filter results4 paper(s) found. |
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1. Using Soil Attributes To Model Sugar Cane Quality ParametersThe crop area of sugar cane production in Brazil has increased substantially in the last few years, especially to meet the global bioethanol demand. Such increasing production should take place not only in new sugar cane crop areas but mainly with the goal of improving the quality of raw material like sugar content (Pol). Hence, models that can describe the behaviour of the quality parameters of sugar cane may be important to understand the effects of the soil attributes on those parameters. The... F.A. Rodrigues jr., P.S. Magalhães, H.C. Franco, D.G. Cerri |
2. Technological Improvement on Sugar Cane Yield MonitorThis paper presents the technological improvement on sugar cane yield monitor. The system designed employs load cells as an instrument for weighing billets, set up on the side conveyor of the harvester before the sugar cane billets are dropped into a field transport wagon. This data, along with the information gathered by GPS installed on the harvester, enabled the elaboration of a digital yield map using GIS. In order to improve the yield monitor a re-design of the first prototype was accomplished.... D.G. Cerri, G.R. Gray, P.S. Magalhães |
3. RMAPs: an Integrated Tool to Delimitate Homogeneous Management ZonesManagement zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa |
4. Sugarcane Yield Mapping Using an On-board Volumetric SensorFew alternatives are available to the sugarcane sector for monitoring crop productivity. However, in recent years, research has been dedicated to developing methods ranging from estimation based on engine parameters to using sensors and artificial intelligence. This study aims to present a new tool for monitoring productivity applied to sugarcane cultivation, which utilizes a volumetric optical sensor, in contrast to other methods already used for this measurement, and is recently being introduced... G. Balboa, J.C. Masnello, F. De oliveira moreira, R. Canal filho, E.R. Da silva, J.P. Molin |