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Pal, P
Pajuelo Madrigal, V
Peerlinck, A
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Authors
Sheppard, J
Peerlinck, A
Maxwell, B
Morales, G
Sheppard, J.W
Peerlinck, A
Hegedus, P
Maxwell, B
Cabrera Dengra, M
Ferraz Pueyo, C
Pajuelo Madrigal, V
Moreno Heras, L
Inunciaga Leston, G
Fortes, R
Peerlinck, A
Sheppard, J
Morales Luna, G.L
Hegedus, P
Maxwell, B
Bhandari, M
Landivar, J
Ghansah, B
Zhao, L
Landivar, J
Pal, P
Topics
On Farm Experimentation with Site-Specific Technologies
Big Data, Data Mining and Deep Learning
Profitability and Success Stories in Precision Agriculture
Decision Support Systems
Artificial Intelligence (AI) in Agriculture
Type
Oral
Year
2018
2022
2024
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1. Using Deep Learning in Yield and Protein Prediction of Winter Wheat Based on Fertilization Prescriptions in Precision Agriculture

Precision Agriculture has been gaining interest due to the significant growth in the fields of engineering and computer science, hence leading to more sophisticated methods and tools to improve agricultural techniques. One approach to Precision Agriculture involves the application of mathematical models and machine learning to fertilization optimization and yield prediction, which is what this research focuses on. Specifically, in this work we report the results of predicting yield and protein... J. Sheppard, A. Peerlinck, B. Maxwell

2. Generation of Site-specific Nitrogen Response Curves for Winter Wheat Using Deep Learning

Nitrogen response (N-response) curves are tools used to support farm management decisions. Conventionally, the N-response curve is modeled as an exponential function that aims to identify an important threshold for a given field: the economic optimum point. This is useful to determine the nitrogen rate beyond which there is no actual profit for the farmers. In this work, we show that N-response curves are not only field-specific but also site-specific and, as such, economic optimum points should... G. Morales, J.W. Sheppard, A. Peerlinck, P. Hegedus, B. Maxwell

3. Use of MLP Neural Networks for Sucrose Yield Prediction in Sugarbeet

INTRODUCTION Sugar beet is one of the more technified agro industries in Spain. In the last years, it has leaded as well the digital transformation with the objective of maintaining sugar beet competitivity both national and internationally. Among other lines, very high potential has been identified in determining the sucrose content using a combination of Artificial Intelligence and Remote Sensing. This work presents the conclusions of an extensive data acquisition task, creation of... M. Cabrera dengra, C. Ferraz pueyo, V. Pajuelo madrigal, L. Moreno heras, G. Inunciaga leston, R. Fortes

4. Optimizing Nitrogen Application to Maximize Yield and Reduce Environmental Impact in Winter Wheat Production

Field-specific fertilizer rate optimization is known to be beneficial for improving farming profit, and profits can be further improved by dividing the field into smaller plots and applying site-specific rates across the field. Finding optimal rates for these plots is often based on data gathered from said plots, which is used to determine a yield response curve, telling us how much fertilizer needs to be applied to maximize yield. In related work, we use a Convolutional Neural Network, known... A. Peerlinck, J. Sheppard, G.L. Morales luna, P. Hegedus, B. Maxwell

5. Cotton Yield Estimation Using High-resolution Satellite Imagery Obtained from Planet SkySat

Satellite images have been used to monitor and estimate crop yield. Over the years, significant improvements on spatial resolution have been made where ortho images can be generated at 30-centimeter resolution. In this study, we wanted to explore the potential use of Planet SKYSAT satellite system for cotton yield predictions. This system provided imagery data at 50 centimeters resolution, and we collected data 14 times during the season. The data were collected from two different cotton... M. Bhandari