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Douaik, A

Mohamed, Z

Mercatoris, B

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Authors

EL-MEJJAOUY, Y

Dumont, B

Vermeulen, P

Oukarroum, A

Mercatoris, B

Abail, Z

Benaouda, H

Chikhaoui, M

Benyahia, H

Iben Halima, O

Baraka, M

Douaik, A

Iaaich, H

Zouahri, A

Omari, F

Boughattas, N

Marwa, K

Mohamed, Z

Sawsen, A

Soumaya, A

Hafedh, H

Imen, H

Youssef, T

Topics

Proximal and Remote Sensing

Precision Nutrient Management

Type

Oral

Year

2022

2024

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Authors

Filter results3 paper(s) found.
1. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat Leaves The assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium content... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris 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. Optimizing Durum Wheat Nitrogen Nutrition Index (NNI) Prediction Through Sentinel-2 Vegetation Index Integration Nitrogen is crucial for durum wheat growth and productivity, but excess or insufficient levels can harm both the environment and farmers' finances. Remote sensing offers rapid, cost-effective, and nondestructive ways to assess crop nutrition, with vegetation indices (VIs) indicating plant health. This study aims to enhance the accuracy of durum wheat nitrogen status prediction by investigating modified formulations of Nitrogen Nutrition Index (NNI) coupled with various vegetation indices (VIs),... N. Boughattas, K. Marwa, Z. Mohamed, A. Sawsen, A. Soumaya, H. Hafedh, H. Imen, T. Youssef Download paper

Filter results3 paper(s) found.

1. Leaf-proximal Hyperspectral Data and Multivariate Modelling Approaches to Estimate Phosphorus and Potassium Content of Wheat Leaves

The assessment of plant nutrient status to provide sufficient fertilization for rapid and continuous uptake by plants has been based on visual diagnosis in the field, which is quick but demands a lot of experience and has low operability. Visible near-infrared spectroscopy (VNIS) has shown to be a quick, non-destructive, accurate, and cost-effective analytical method in precision agriculture. In this study, we assessed the potential of this technology to predict phosphorus and potassium content... Y. El-mejjaouy, B. Dumont, P. Vermeulen, A. Oukarroum, B. Mercatoris

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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. Optimizing Durum Wheat Nitrogen Nutrition Index (NNI) Prediction Through Sentinel-2 Vegetation Index Integration

Nitrogen is crucial for durum wheat growth and productivity, but excess or insufficient levels can harm both the environment and farmers' finances. Remote sensing offers rapid, cost-effective, and nondestructive ways to assess crop nutrition, with vegetation indices (VIs) indicating plant health. This study aims to enhance the accuracy of durum wheat nitrogen status prediction by investigating modified formulations of Nitrogen Nutrition Index (NNI) coupled with various vegetation indices (VIs),... N. Boughattas, K. Marwa, Z. Mohamed, A. Sawsen, A. Soumaya, H. Hafedh, H. Imen, T. Youssef

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