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García, C.E
Gosselin, B
Ghimire, D
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Authors
Celades, J.A
Caicedo, J.H
García, C.E
Mora, H
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
Ghimire, D
Maharjan, B
Topics
Profitability and Success Stories in Precision Agriculture
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
In-Season Nitrogen Management
Type
Poster
Oral
Year
2018
2022
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1. Toward a Precision Agricultural Implementation for Sugar Cane Plantations in Southwestern Region of Colombia, South America

The Colombian Sugar Cane Research Center, CENICAÑA, has initiated an ambitious project for the implementation of Precision Agriculture (PA) technologies in the Cauca river valley region, where one of its main objectives is to have the ability to collect large volumes of geospatial data. The main sugarcane growers in the country perform their work in the selected work area, which covers an area of ​​approximately 242,000 ha, characterized by diverse topographic and edaphic conditions.... J.A. Celades, J.H. Caicedo, C.E. García, H. Mora

2. Sun Effect on the Estimation of Wheat Ear Density by Deep Learning

Ear density is one of the yield components of wheat and therefore a variable of high agronomic interest. Its traditional measurement necessitates laborious human observations in the field or destructive sampling. In the recent years, deep learning based on RGB images has been identified as a low-cost, robust and high-throughput alternative to measure this variable. However, most of the studies were limited to the computer challenge of counting the ears in the images, without aiming to convert... S. Dandrifosse, E. Ennadifi, A. Carlier, B. Gosselin, B. Dumont, B. Mercatoris

3. Assessment of Active Crop Canopy Sensor As a Tool for Optimal Nitrogen Management in Dryland Winter Wheat

Optimum nitrogen (N) fertilizer application is important for agronomic, economic, and environmental reasons. Among different N management tools, active crop canopy sensors are a recent and promising tool widely evaluated for use in corn but still under-evaluated for use in winter wheat. The objective of this study was to determine whether vegetation indices derived from in-season active crop canopy sensor data can be used to predict winter wheat grain yield and protein content and subsequently... D. Ghimire