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Apolo-Apolo, E
Schmidt, R
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Authors
Perez-Ruiz, M
Apolo-Apolo, E
Egea, G
Martinez-Guanter, J
Marin-Barrero, C
Jha, G
Nazrul, F
Nocco, M
Pagé Fortin, M
Whitaker, B
Diaz, D
Gal, A
Schmidt, R
Dey, S
Topics
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Weather and Models for Precision Agriculture
Type
Oral
Poster
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. Prediction of Field-scale Evapotranspiration Using Process Based Modeling and Geostatistical Time-series Interpolation

Irrigation scheduling depends on the combination of evaporative demand from the atmosphere, spatial and temporal heterogeneity in soil properties and changes in crop canopy during a growing season. This on-farm trial is based on data collected in 72-acre processing tomato field in Central Valley of California. The Multiband Spectrometric Arable Mark 2 sensors at three different locations in the field. Multispectral and thermal imagery provided by Ceres Imaging were collected eight times during... G. Jha, F. Nazrul, M. Nocco, M. Pagé fortin, B. Whitaker, D. Diaz, A. Gal, R. Schmidt