Salah Elsayed
About
Salah Elsayed is a scholar working on Plant Science, Ecology and Water Science and Technology.
According to data from OpenAlex, Salah Elsayed has authored 99 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Plant Science, 32 papers in Ecology and 27 papers in Water Science and Technology. Recurrent topics in Salah Elsayed's work include Leaf Properties and Growth Measurement (32 papers), Remote Sensing in Agriculture (31 papers) and Spectroscopy and Chemometric Analyses (25 papers). Salah Elsayed is often cited by papers focused on Leaf Properties and Growth Measurement (32 papers), Remote Sensing in Agriculture (31 papers) and Spectroscopy and Chemometric Analyses (25 papers). Salah Elsayed collaborates with scholars based in Egypt, Saudi Arabia and Germany. Salah Elsayed's co-authors include Mohamed Gad, Urs Schmidhalter, Hend Hussein, Farahat S. Moghanm, Salah El-Hendawy, Pablo Rischbeck, Nasser Al-Suhaibani, Osama Elsherbiny, Mohamed Farouk and Yaser Hassan Dewir and has published in prestigious journals such as PLoS ONE, Scientific Reports and Renewable Energy.
In The Last Decade
Salah Elsayed
91 papers receiving 2.6k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Salah Elsayed Egypt | 28 | 947 | 925 | 912 | 752 | 638 | 99 | 2.7k | ||
| Guangxin Zhang China | 29 | 410 0.4× | 987 1.1× | 415 0.5× | 364 0.5× | 212 0.3× | 195 | 2.7k | ||
| D. W. Meek United States | 31 | 531 0.6× | 759 0.8× | 954 1.0× | 434 0.6× | 253 0.4× | 72 | 3.6k | ||
| Dennis L. Corwin United States | 41 | 3.9k 4.1× | 515 0.6× | 1.2k 1.4× | 1.0k 1.3× | 260 0.4× | 118 | 6.7k | ||
| W. Dean Hively United States | 30 | 1.1k 1.2× | 564 0.6× | 455 0.5× | 1.3k 1.7× | 57 0.1× | 69 | 2.6k | ||
| Luboš Borůvka Czechia | 35 | 1.7k 1.8× | 261 0.3× | 599 0.7× | 798 1.1× | 220 0.3× | 157 | 4.3k | ||
| Qingrui Chang China | 23 | 410 0.4× | 239 0.3× | 434 0.5× | 693 0.9× | 80 0.1× | 92 | 2.0k | ||
| George Zalidis Greece | 29 | 974 1.0× | 316 0.3× | 399 0.4× | 865 1.2× | 50 0.1× | 110 | 2.8k | ||
| Bhabani S. Das India | 30 | 1.0k 1.1× | 172 0.2× | 485 0.5× | 256 0.3× | 63 0.1× | 98 | 2.3k | ||
| Gabriele Buttafuocò Italy | 31 | 1.3k 1.3× | 295 0.3× | 230 0.3× | 540 0.7× | 76 0.1× | 87 | 2.5k |
Countries citing papers authored by Salah Elsayed
Since
Specialization
Citations
This map shows the geographic impact of Salah Elsayed's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Salah Elsayed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salah Elsayed more than expected).
Fields of papers citing papers by Salah Elsayed
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Salah Elsayed. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Salah Elsayed. The network helps show where Salah Elsayed may publish in the future.
Co-authorship network of co-authors of Salah Elsayed
This figure shows the co-authorship network connecting the top 25 collaborators of Salah Elsayed. A scholar is included among the top collaborators of Salah Elsayed based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Salah Elsayed. Salah Elsayed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Elsayed, Salah, et al.. (2025). Hyperspectral technology and machine learning models to estimate the fruit quality parameters of mango and strawberry crops. PLoS ONE. 20(2). e0313397–e0313397.
2.
Elwakeel, Abdallah Elshawadfy, Salah Elsayed, Wael M. Elmessery, et al.. (2024). Development and Techno-Economic Analysis of a Tracked Indirect Forced Solar Dryer Integrated Photovoltaic System for Drying Tomatoes. Sustainability. 16(16). 7008–7008.
3.
Elwakeel, Abdallah Elshawadfy, Loai Nasrat, Mohamed Metwally Mahmoud, et al.. (2024). Advanced design and Engi-economical evaluation of an automatic sugarcane seed cutting machine based RGB color sensor. PLoS ONE. 19(10). e0306584–e0306584.
4.
Sharaf‐Eldin, Mohamed, Zaher Mundher Yaseen, Adel H. Elmetwalli, et al.. (2023). Modifying Walk-In Tunnels through Solar Energy, Fogging, and Evaporative Cooling to Mitigate Heat Stress on Tomato. Horticulturae. 9(1). 77–77.
5.
Hai, Tao, Sinan Q. Salih, Mustafa K. A. Mohammed, et al.. (2023). Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models. Atmospheric Research. 291. 106815–106815.
6.
Ibrahim, Hekmat, Zaher Mundher Yaseen, Miklas Scholz, et al.. (2023). Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study. Water. 15(4). 694–694.
7.
Elwakeel, Abdallah Elshawadfy, et al.. (2023). Design and Validation of a Variable-Rate Control Metering Mechanism and Smart Monitoring System for a High-Precision Sugarcane Transplanter. Agriculture. 13(12). 2218–2218.
8.
Gaagai, Aissam, Hani Amir Aouissi, Gilbert Hinge, et al.. (2023). Application of Water Quality Indices, Machine Learning Approaches, and GIS to Identify Groundwater Quality for Irrigation Purposes: A Case Study of Sahara Aquifer, Doucen Plain, Algeria. Water. 15(2). 289–289.
9.
Eid, Mohamed Hamdy, Mohssen Elbagory, Mohamed Gad, et al.. (2023). Evaluation of Groundwater Quality for Irrigation in Deep Aquifers Using Multiple Graphical and Indexing Approaches Supported with Machine Learning Models and GIS Techniques, Souf Valley, Algeria. Water. 15(1). 182–182.
10.
Gaagai, Aissam, Amor Ben Moussa, Kamel Zouari, et al.. (2023). Applying Multivariate Analysis and Machine Learning Approaches to Evaluating Groundwater Quality on the Kairouan Plain, Tunisia. Water. 15(19). 3495–3495.
11.
Elsayed, Salah, Salah El-Hendawy, Osama Elsherbiny, et al.. (2023). Estimating Chlorophyll Content, Production, and Quality of Sugar Beet under Various Nitrogen Levels Using Machine Learning Models and Novel Spectral Indices. Agronomy. 13(11). 2743–2743.
12.
Sharaf‐Eldin, Mohamed, Salah Elsayed, Adel H. Elmetwalli, et al.. (2023). Using Optimized Three-Band Spectral Indices and a Machine Learning Model to Assess Squash Characteristics under Moisture and Potassium Deficiency Stress. Horticulturae. 9(1). 79–79.
13.
Elwakeel, Abdallah Elshawadfy, et al.. (2023). Designing, Optimizing, and Validating a Low-Cost, Multi-Purpose, Automatic System-Based RGB Color Sensor for Sorting Fruits. Agriculture. 13(9). 1824–1824.
14.
Eid, Mohamed Hamdy, Omar Saeed, András Székács, et al.. (2023). Integration of Geochemical Modeling, Multivariate Analysis, and Irrigation Indices for Assessing Groundwater Quality in the Al-Jawf Basin, Yemen. Water. 15(8). 1496–1496.
15.
Masoud, Milad, Maged El Osta, Abdulaziz Alqarawy, Salah Elsayed, & Mohamed Gad. (2022). Evaluation of groundwater quality for agricultural under different conditions using water quality indices, partial least squares regression models, and GIS approaches. Applied Water Science. 12(10).
16.
Alqarawy, Abdulaziz, Maged El Osta, Milad Masoud, Salah Elsayed, & Mohamed Gad. (2022). Use of Hyperspectral Reflectance and Water Quality Indices to Assess Groundwater Quality for Drinking in Arid Regions, Saudi Arabia. Water. 14(15). 2311–2311.
17.
Elsayed, Salah, Salah El-Hendawy, Mosaad Khadr, et al.. (2021). Combining Thermal and RGB Imaging Indices with Multivariate and Data-Driven Modeling to Estimate the Growth, Water Status, and Yield of Potato under Different Drip Irrigation Regimes. Remote Sensing. 13(9). 1679–1679.
18.
Elsayed, Salah, Salah El-Hendawy, Mosaad Khadr, et al.. (2021). Integration of Spectral Reflectance Indices and Adaptive Neuro-Fuzzy Inference System for Assessing the Growth Performance and Yield of Potato under Different Drip Irrigation Regimes. Chemosensors. 9(3). 55–55.
19.
Elsayed, Salah, Salah El-Hendawy, Yaser Hassan Dewir, et al.. (2021). Estimating the Leaf Water Status and Grain Yield of Wheat under Different Irrigation Regimes Using Optimized Two- and Three-Band Hyperspectral Indices and Multivariate Regression Models. Water. 13(19). 2666–2666.
20.
Khadr, Mosaad, Mohamed Gad, Salah El-Hendawy, et al.. (2020). The Integration of Multivariate Statistical Approaches, Hyperspectral Reflectance, and Data-Driven Modeling for Assessing the Quality and Suitability of Groundwater for Irrigation. Water. 13(1). 35–35.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
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