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Mohammed, I.B

Cummings, C

Yusufu , F

Chikhaoui, M

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Authors

Dias Paiao, G

Nigon, T.J

Fernández, F.G

Cummings, C

Naeve, S.L

Tukur, A

Ajeigbe, H.A

Akinseye, F.M

Mohammed, I.B

Badamasi, M.M

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

Satellite Imagery

Precision Nutrient Management

Type

Oral

Year

2020

2022

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Authors

Filter results3 paper(s) found.
1. Estimating greensnap yield damage with canopy reflectance: a case study Grain yield reduction caused by storm-induced plant breakage (green snap) occurs often in corn fields. With climate change and an increasing frequency in the occurrence of extreme weather events, it is essential to develop methods that can accurately estimate green snap damage, so growers can be properly compensated by insurance companies for yield loss. Because plant breakage also affects crop canopy reflectance, this case study aimed to characterize the changes in crop canopy reflectance... G. Dias paiao, T.J. Nigon, F.G. Fernández, C. Cummings, S.L. Naeve
2. Predicting in-Season Sorghum yield potential using Remote Sensing Approach: a case study of Kano in Sudan Savannah agro- ecological zone, Nigeria The preliminary estimation of expected yields and the accuracy of this evaluation provide information for decision-making related to the harvest. Estimating crop yield using remote sensing techniques has proven to be successful, having the ability to provide yield estimates prior to harvest. This study was conducted to examine the applicability of Sentinel-2B for estimating sorghum yield during the 2018 rainy season in Bebeji, Dawakin-Kudu and Rano Local Government Areas Kano State, in the Sudan... A. Tukur, H.A. Ajeigbe, F.M. Akinseye, I.B. Mohammed, M.M. Badamasi 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 greensnap yield damage with canopy reflectance: a case study

Grain yield reduction caused by storm-induced plant breakage (green snap) occurs often in corn fields. With climate change and an increasing frequency in the occurrence of extreme weather events, it is essential to develop methods that can accurately estimate green snap damage, so growers can be properly compensated by insurance companies for yield loss. Because plant breakage also affects crop canopy reflectance, this case study aimed to characterize the changes in crop canopy reflectance... G. Dias paiao, T.J. Nigon, F.G. Fernández, C. Cummings, S.L. Naeve

2. Predicting in-Season Sorghum yield potential using Remote Sensing Approach: a case study of Kano in Sudan Savannah agro- ecological zone, Nigeria

The preliminary estimation of expected yields and the accuracy of this evaluation provide information for decision-making related to the harvest. Estimating crop yield using remote sensing techniques has proven to be successful, having the ability to provide yield estimates prior to harvest. This study was conducted to examine the applicability of Sentinel-2B for estimating sorghum yield during the 2018 rainy season in Bebeji, Dawakin-Kudu and Rano Local Government Areas Kano State, in the Sudan... A. Tukur, H.A. Ajeigbe, F.M. Akinseye, I.B. Mohammed, M.M. Badamasi

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