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LOTSI, K

Zouahri, A

Gatto, S

Abrahams, M

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Authors

Kayad, A

Sozzi, M

Pirotti, F

Marinello, F

Sartori, L

Gatto, S

Abail, Z

Benaouda, H

Chikhaoui, M

Benyahia, H

Iben Halima, O

Baraka, M

Douaik, A

Iaaich, H

Zouahri, A

Omari, F

LARE, M

SOGBEDJI, J

LOTSI, K

AMOUZOU, K

ALE GONH-GOH, A

AGNEROH , A

Abrahams, M

Topics

Satellite Imagery

Precision Nutrient Management

Economics of Precision Agriculture

Small Holders and Precision Agriculture

Type

Oral

Year

2020

2022

2024

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Authors

Filter results4 paper(s) found.
1. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture Applications Currently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto Download paper
2. Assessment of Nitrogen and Phosphorus Content (NP) in Citrus Trees Using UAV-imagery Derived Vegetation Indices and Machine Learning Algorithms Monitoring nutrient status of citrus trees is fundamental to ensure optimum fruit yield and quality. However, this task is traditionally time-consuming and laborious. Unmanned Aerial Vehicles (UAVs), with their high temporal and spatial resolution imagery, are demonstrating a great potential to substitute traditional methods in assessing nutrient status of several crops, including citrus. In this study, we evaluated the performance of vegetation indices (VIs) derived from UAV multispectral images... Z. Abail, H. Benaouda, M. Chikhaoui, H. Benyahia, O. Iben halima, M. Baraka, A. Douaik, H. Iaaich, A. Zouahri, F. Omari
3. Recommandation De Formules De Fertilisation Site-spécifique Pour La Production Du Maïs Dans La Région Des Savanes Du Togo Dans le contexte actuel de la dégradation des terres agricoles et des difficultés de disponibilité et d'accès aux intrants agricoles en particulier les engrais, la maximisation de l'efficience d'utilisation des nutriments en nutrition des plantes devient plus que jamais une nécessité. Nous avons conduit en 2020 sous culture de maïs (Zea mays L.), des essais soustractifs à base de l'azote (N), du phosphore (P) et du potassium... M. Lare, J. Sogbedji, K. Lotsi, K. Amouzou, A. Ale gonh-goh, A. Agneroh Download paper
4. Assessing the Potential of UAV-Acquired Multispectral Imagery Combined with Machine Learning Techniques in Mapping the Spatial Distribution of Taro And Sweet Potato in Smaller Holder Farms ... M. Abrahams

Filter results4 paper(s) found.

1. Monitoring Corn (Zea mays) Yield using Sentinel-2 and Machine Learning for Precision Agriculture Applications

Currently, there is a growing demand to apply precision agriculture (PA) management practices at agricultural fields expecting more efficient and more profitable management. One of PA principal components for site-specific management is crop yield monitoring which varies temporally between seasons and spatially within-field. In this study, we investigated the possibility of monitoring within-field variability of corn grain yield in a 22ha field located in Ferarra, North Italy. Archived yield data... A. Kayad, M. Sozzi, F. Pirotti, F. Marinello, L. Sartori, S. Gatto

Download paper

2. Assessment of Nitrogen and Phosphorus Content (NP) in Citrus Trees Using UAV-imagery Derived Vegetation Indices and Machine Learning Algorithms

Monitoring nutrient status of citrus trees is fundamental to ensure optimum fruit yield and quality. However, this task is traditionally time-consuming and laborious. Unmanned Aerial Vehicles (UAVs), with their high temporal and spatial resolution imagery, are demonstrating a great potential to substitute traditional methods in assessing nutrient status of several crops, including citrus. In this study, we evaluated the performance of vegetation indices (VIs) derived from UAV multispectral images... Z. Abail, H. Benaouda, M. Chikhaoui, H. Benyahia, O. Iben halima, M. Baraka, A. Douaik, H. Iaaich, A. Zouahri, F. Omari

3. Recommandation De Formules De Fertilisation Site-spécifique Pour La Production Du Maïs Dans La Région Des Savanes Du Togo

Dans le contexte actuel de la dégradation des terres agricoles et des difficultés de disponibilité et d'accès aux intrants agricoles en particulier les engrais, la maximisation de l'efficience d'utilisation des nutriments en nutrition des plantes devient plus que jamais une nécessité. Nous avons conduit en 2020 sous culture de maïs (Zea mays L.), des essais soustractifs à base de l'azote (N), du phosphore (P) et du potassium... M. Lare, J. Sogbedji, K. Lotsi, K. Amouzou, A. Ale gonh-goh, A. Agneroh

Download paper

4. Assessing the Potential of UAV-Acquired Multispectral Imagery Combined with Machine Learning Techniques in Mapping the Spatial Distribution of Taro And Sweet Potato in Smaller Holder Farms

... M. Abrahams