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Sclemmer, M.R
Sihi, D
Spekken, M
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Authors
Molin, J.P
Spekken, M
Eitelwein, M.T
Molin, J.P
Spekken, M
Trevisan, R.G
Sclemmer, M.R
Holland, K.H
Spekken, M
Molin, J.P
Romanelli, T.L
Ferraz, M.N
Spekken, M
Molin, J.P
Nazrul, F
Kim, J
Dey, S
Palla, S
Sihi, D
Whitaker, B
Jha, G
Topics
Guidance, Robotics, Automation, and GPS Systems
Spatial Variability in Crop, Soil and Natural Resources
Engineering Technologies and Advances
Decision Support Systems in Precision Agriculture
Robotics, Guidance and Automation
Weather and Models for Precision Agriculture
Type
Poster
Oral
Year
2012
2014
2016
2018
2024
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Filter results6 paper(s) found.

1. Optimizing Path Planning By Avoiding Short Corner Tracks

... J.P. Molin, M. Spekken

2. Assessing Definition Of Management Zones Trough Yield Maps

Yield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two methods... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan

3. Rapid Data Acquisition For In-Field Plant Phenomics

High throughput sensing is necessary for the rapid acquisition of plant canopy physical and physiological parameters on field scales. Simultaneous measures of these descriptive parameters will provide a clearer picture of plant response to biotic and abiotic stressors. Information obtained can assist in early identification of desired genetic traits and the degree to which they are expressed. Identifying these traits and their expression can provide higher efficiency in genetic selection... M.R. Sclemmer, K.H. Holland

4. Site Specific Costs Concerning Machine Path Orientation

Computer algorithms have been created to simulate in advance the orientation/pattern of a machine operation on a field. Undesired impacts were obtained and quantified for these simulations, like: maneuvering and overlap of inputs in headlands; servicing of secondary units; and soil loss by water erosion. While the efforts could minimize the overall costs, they disregard the fact that these costs aren’t uniformly distributed over irregular fields. The cost of a non-productive machine process... M. Spekken, J.P. Molin, T.L. Romanelli, M.N. Ferraz

5. UAV Images As a Source for Retrieval of Machine Tracks and Vegetation Gaps Along Crop Rows

The trend of acquiring equipment and obtaining high resolution remote sensed images by Unmanned Aerial Vehicles (UAV) have been followed by sugarcane producers in Brazil, given its low cost. The images taken from fields have been used for retrieval of information like Digital Terrain Models (DTMs) from stereoscopy of overlapping images and spatial variance of biomass. In sugarcane production, driving deviations occur during planting because of manual steering inaccuracy, sliding of machines sideways... M. Spekken, J.P. Molin

6. Machine Learning Algorithms in Detecting Long-term Effect of Climatic Factors for Alfalfa Production in Kansas

The water levels of the Ogallala Aquifer are depleting so much that agricultural land returns in Kansas are expected to drop by $34.1 million by 2050. It is imperative to understand how frequent droughts and the contrasting rates of groundwater withdrawal and recharge are affected by climate shifts in Kansas. Alfalfa, the ‘Queen of Forages’, is a water demanding crop which supplies high nutritional feed for beef industry that offered Kansas producers a $500 million production value... F. Nazrul, J. Kim, S. Dey, S. Palla, D. Sihi, B. Whitaker, G. Jha