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Clark, N
Campoy, J
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Authors
Osann, A
Campos, I
Calera, M
Plaza, C
Bodas, V
Calera, A
Villodre, J
Campoy, J
Sanchez, S
Jimenez, N
Lopez, H
Grijalva Teran, I.A
Spiesman, B
Clark, N
McCornack, B
Topics
In-Season Nitrogen Management
Artificial Intelligence (AI) in Agriculture
Type
Oral
Poster
Year
2018
2024
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1. Practical Prescription of Variable Rate Fertilization Maps Using Remote Sensing Based Yield Potential

This paper describes a practical approach for the prescription of variable rate fertilization maps using remote sensing data (RS) based on satellite platforms, Landsat 8 and Sentinel-2 constellation. The methodology has been developed and evaluated in Albacete, Spain, in the framework of the project FATIMA (http://fatima-h2020.eu/). The global approach considers the prescription of N management prior to the growing season, based on a spatially distributed N balance. Although the diagnosis of N... A. Osann, I. Campos, M. Calera, C. Plaza, V. Bodas, A. Calera, J. Villodre, J. Campoy, S. Sanchez, N. Jimenez, H. Lopez

2. Detection of Sorghum Aphids with Advanced Machine Vision

Sorghum aphid, Melanaphis sorghi (Theobald), became a significant pest concern due to the significant yield losses caused in the sorghum production region. Different management practices, including monitoring and applying insecticides, have been used to manage this invasive pest in sorghum. The most common management strategy consists of visual assessments of aphids on sorghum leaves to determine an economic threshold level to spray. However, because of their rapid reproduction,... I.A. Grijalva teran, B. Spiesman, N. Clark, B. Mccornack