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Amin, M.E

Graff, N

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Authors

Amin, M.E

Abdelfattah, M.A

Mohamed, E.S

Belal, A.A

Nabil, M

Mahmoud, A.G

Ludemann, C

Dobermann, A

Graff, N

Sela, S

van Loon, M

Hijbeek, R

van Ittersum, M

Topics

Precision Planting/Harvesting

Precision Nutrient Management

Type

Poster

Oral

Year

2022

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Authors

Filter results2 paper(s) found.
1. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear Regression Traditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud
2. The Global Crop Nutrient Removal Database (Gcnrd): Development, Initial Analysis and Identification of Current Data Gaps Improved understanding of the factors affecting nutrient uptake can enable production optimization, increased nutrient use efficiencies, reduced environmental footprints, and overall higher economic returns for farmers. Crop uptake is affected by genetics, soil, weather, agronomic practices, and their interactions. As such, understanding the way crop nutrient uptake varies across different regions and production environments requires the coverage of various parameters, and necessitates collaboration... C. Ludemann, A. Dobermann, N. Graff, S. Sela, M. Van Loon, R. Hijbeek, M. Van Ittersum

Filter results2 paper(s) found.

1. Potato Yield Prediction Using Multi-temporal Sentinel-2 Data and Multiple Linear Regression

Traditional potato growth models have a number of flaws, i.e., the cost of data collection, quality of input data, and the absence of spatial information in some cases. To address these challenges, we created a multiple linear regression model (MLRM) that uses the multi-temporal Sentinel-2 derived indices to predict potato yield. Along the growing season (from October 2019 to February 2020) eight Sentinel-2 imageries were collected, afterwards, the normalized difference vegetation index (NDVI)... M.E. Amin, M.A. Abdelfattah, E.S. Mohamed, A.A. Belal, M. Nabil, A.G. Mahmoud

2. The Global Crop Nutrient Removal Database (Gcnrd): Development, Initial Analysis and Identification of Current Data Gaps

Improved understanding of the factors affecting nutrient uptake can enable production optimization, increased nutrient use efficiencies, reduced environmental footprints, and overall higher economic returns for farmers. Crop uptake is affected by genetics, soil, weather, agronomic practices, and their interactions. As such, understanding the way crop nutrient uptake varies across different regions and production environments requires the coverage of various parameters, and necessitates collaboration... C. Ludemann, A. Dobermann, N. Graff, S. Sela, M. Van Loon, R. Hijbeek, M. Van Ittersum