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Santos, I.M
Conway, L.S
Sudduth, K.A
Steffan, S
Sacco, D
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Authors
Cugnasca, C.E
Santos, I.M
Nguyen, A.T
Thompson, A.L
Sudduth, K.A
Vories, E.D
Nguyen, A.T
Cordero, E
Sacco, D
Moretti, B
Miniotti, E.F
Tenni, D
Beltarre, G
Romani, M
Grignani, C
Luck, B
Drewry, J
Chassen, E
Steffan, S
Conway, L.S
Vong, C
Kitchen, N.R
Sudduth, K.A
Anderson, S.H
Sudduth, K.A
Kitchen, N.R
Conway, L.S
Topics
Proximal Sensing in Precision Agriculture
Engineering Technologies and Advances
In-Season Nitrogen Management
Applications of Unmanned Aerial Systems
Site-Specific Nutrient, Lime and Seed Management
Type
Poster
Oral
Year
2012
2016
2018
2022
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Filter results6 paper(s) found.

1. Pesticide Drift Control with Wireless Sensor Networks

Precision Agriculture is an agricultural practice that uses technology based on the principle of variability. The geographically referenced data implement the process of agricultural automation so as to dose fertilizers and pesticides. The efficient application of low cost pesticides without contamination the environment is an agricultural production challenge. The main effect to be avoided during application is pesticide drift. To minimize it is important to know the environmental conditions,... C.E. Cugnasca, I.M. Santos

2. Automated Support Tool for Variable Rate Irrigation Prescriptions

Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS data layers of grid-based field soil texture properties and fertility needs in making management decisions. The program can automatically develop a variable rate application prescription along the lateral... A.T. Nguyen, A.L. Thompson, K.A. Sudduth, E.D. Vories, A.T. Nguyen

3. Deriving Fertiliser VRA Calibration Based on Ground Sensing Data from Specific Field Experiments

Nitrogen (N) fertilisation affects both rice yield and quality. In order to improve grain yield while limiting N losses, providing N fertilisers during the critical growth stages is essential. NDRE is considered a reliable crop N status indicator, suitable to drive topdressing N fertilisation in rice. A multi-year experiment on different rice varieties (Gladio, Centauro, and Carnaroli) was conducted between 2011 and 2017 in Castello d’Agogna (PV), northwest Italy, with the aim of i) establishing... E. Cordero, D. Sacco, B. Moretti, E.F. Miniotti, D. Tenni, G. Beltarre, M. Romani, C. Grignani

4. Unmanned Aerial Systems and Remote Sensing for Cranberry Production

Wisconsin is the largest producer of Cranberries in the United States with 5.6 million barrels produced in 2017. To date, Precision Agriculture technologies adapted to cranberry production have been limited. The objective of this research was to assess the feasibility of the use of commercial remote sensing devices and Unmanned Aerial Systems in cranberry production. Two commercially available sensors were assessed for use in cranberry production: 1) MicaSense Red Edge and 2) Zenmuse XT. Initial... B. Luck, J. Drewry, E. Chassen, S. Steffan

5. Predicting Corn Emergence Uniformity with On-the-go Furrow Sensing Technology

Integration of proximal soil sensors into commercial row-crop planter components have allowed for a dense quantification of within-field soil spatial variability. These technologies have potential to guide real-time management decisions, such as on-the-go variable seeding rate or depth. However, little is known about the performance of these systems. Therefore, research was conducted in central Missouri, USA to determine the relationship between planter sensor metrics, and corn (Zea mays L.) ... L.S. Conway, C. Vong, N.R. Kitchen, K.A. Sudduth, S.H. Anderson

6. Soil, Landscape, and Weather Affect Spatial Distributions of Corn Population and Yield

As more planters are equipped with the technology to vary seeding rate, evaluation of the within-field relationships between plant stand density (or population) and yield is needed. One aspect of this evaluation is determining how stand loss and yield are related to soil and landscape factors, and how these relationships vary with different weather conditions. Therefore, this research examined nine site-years of mapped corn yield, harvest population, and soil and landscape data obtained for a... K.A. Sudduth, N.R. Kitchen, L.S. Conway