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Marin-Barrero, C
Morgan, S
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Authors
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Maritan, E
Behrendt, K
Lowenberg-DeBoer, J
Morgan, S
Rutter, M.S
Topics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Site-Specific Pasture Management
Type
Oral
Year
2018
2024
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1. Feasibility of Estimating the Leaf Area Index of Maize Traits with Hemispherical Images Captured from Unmanned Aerial Vehicles

Feeding a global population of 9.1 billion in 2050 will require food production to be increased by approximately 60%. In this context, plant breeders are demanding more effective and efficient field-based phenotyping methods to accelerate the development of more productive cultivars under contrasting environmental constraints. The leaf area index (LAI) is a dimensionless biophysical parameter of great interest to maize breeders since it is directly related to crop productivity. The LAI is defined... M. Perez-ruiz, E. Apolo-apolo, G. Egea, J. Martinez-guanter, C. Marin-barrero

2. A Multi-objective Optimisation Analysis of Virtual Fencing in Precision Grazing

Virtual fencing is a precision livestock farming tool consisting of invisible boundaries created via Global Navigation Satellite Systems (GNSS) and managed remotely and in real time by app-based technology. Grazing livestock are equipped with battery-powered collars capable of delivering audio or vibration cues and possibly electric shocks when approaching or crossing an invisible boundary. Virtual fencing makes precision grazing possible without the need for physical fences. This technology originated... E. Maritan, K. Behrendt, J. Lowenberg-deboer, S. Morgan, M.S. Rutter