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Vasava, H

Chikhaoui, M

Vermeulen, P

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Authors

Biswas, A

Fu, Y

Taneja, P

Lin, S

Daggupati, P

Vasava, H

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

Topics

Proximal and Remote Sensing

Precision Nutrient Management

Type

Oral

Year

2020

2022

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Authors

Filter results3 paper(s) found.
1. Estimating soil organic carbon from cell phone images Soil organic matter (SOM) is considered as the backbone of soil health and soil quality. Thus, its’ estimation is critical to support the development of management decision including precision agriculture. To overcome challenges of laborious, rather expensive and time-consuming laboratory measurements, recent advances in image acquisition systems provided a new dimension of image-based SOM prediction. However, challenges remain in using soil images taken directly in the field due to variable... A. Biswas, Y. Fu, P. Taneja, S. Lin, P. Daggupati, H. Vasava Download paper
2. 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
3. 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

Filter results3 paper(s) found.

1. Estimating soil organic carbon from cell phone images

Soil organic matter (SOM) is considered as the backbone of soil health and soil quality. Thus, its’ estimation is critical to support the development of management decision including precision agriculture. To overcome challenges of laborious, rather expensive and time-consuming laboratory measurements, recent advances in image acquisition systems provided a new dimension of image-based SOM prediction. However, challenges remain in using soil images taken directly in the field due to variable... A. Biswas, Y. Fu, P. Taneja, S. Lin, P. Daggupati, H. Vasava

Download paper

2. 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

3. 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