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Khot, L.R
Walsh, M
Zhang, X
Zamora, I
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Authors
Khot, L.R
Ehsani, R
Albrigo, G
Campoy, J
Wellington, C
Swen, W
Camergo Neto, J
Walsh, M
Zamora, I
Wulfsohn, D
Marcaida, M
Zhang, X
Srinivasagan, S
Shajahan, S
Ketterings, Q
Topics
Precision Horticulture
Precision A to Z for Practitioners
Applications of UAVs (unmanned aircraft vehicle systems) in precision agriculture
Data Analytics for Production Ag
Type
Poster
Oral
Year
2012
2014
2024
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Filter results4 paper(s) found.

1. Validation of Variable Rate Spray Decision Rules in Intricate Micro-Metrological Conditions

This study evaluated validity of modified spray decision rules formed to operate axial fan airblast sprayer retrofitted for use in citrus production. The sprayer was field tested in a spraying... L.R. Khot, R. Ehsani, G. Albrigo, J. campoy, C. Wellington, W. Swen, J. Camergo neto

2. Precision Agriculture and Springer

Maryse Walsh will be presenting Precision Agriculture, the Springer journal, but also the discipline and its place in the Springer publications overall. The community attending the ICPA has a major role in ensuring the positive development of these publications and the affiliation of the journal to the ISPA will only help. ... M. Walsh

3. The Use Of A Multirotor And High-Resolution Imaging For Precision Horticulture In Chile: An Industry Perspective

As part of the prototype development of a yield forecasting and precision agriculture service for Chilean horticulture, we evaluated the use of an eight-rotor Mikrokopter for high-resolution aerial imaging to support ground-based surveys. Specific considerations for UAV and communications performance under Chilean conditions are windy conditions, limited space for take-off and landing in orchards, tree height and plantation density, and the presence of high metal contents in soils. We discuss... I. Zamora, D. Wulfsohn

4. Can Soil Fertility Data and Topography Predict Yield Stability Zones for Corn Fields in New York?

Yield monitor systems play a vital role in precision agriculture given their ability to capture and map within-field yield variability. When three or more years of yield data are available, yield stability zone maps can be generated to show both the spatial and temporal variability of yield within a field. Based on the farm’s overall temporal mean and standard deviation for a specific crop, we can classify areas in the field as consistently high- (Q1) or low-yielding (Q4), and variably high-... M. Marcaida, X. Zhang, S. Srinivasagan, S. Shajahan, Q. Ketterings