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Gosselin, B
Galzki, J
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Authors
Wilson, G.L
Mulla, D.J
Galzki, J
Laacouri, A
Vetsch, J
Dandrifosse, S
Ennadifi, E
Carlier, A
Gosselin, B
Dumont, B
Mercatoris, B
Topics
In-Season Nitrogen Management
Proximal and Remote Sensing of Soil and Crop (including Phenotyping)
Type
Oral
Year
2018
2022
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1. Predicted Nitrate-N Loads for Fall, Spring, and VRN Fertilizer Application in Southern Minnesota

Nitrate-N from agricultural fields is a source of pollution to fresh and marine waters via subsurface tile drainage.  Sensor-based technologies that allow for in-season monitoring of crop nitrogen requirements may represent a way to reduce nitrate-N loadings to surface waters by allowing for fertilizer application on a more precise spatial and temporal resolution.  However, little research has been done to determine its effectiveness in reducing nitrate-N losses.  In this study,... G.L. Wilson, D.J. Mulla, J. Galzki, A. Laacouri, J. Vetsch

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