Dr. Abdelraouf Ali
With over 15 years of experience, I, Abdelraouf M. Ali, have established a strong foundation in remote sensing, UAV technology, and geospatial data analysis, specializing in agricultural applications and food security. My academic and professional journey includes roles at leading institutions such as the National Authority for Remote Sensing and Space Sciences (NARSS) in Egypt, the Digital Photogrammetry Research Group (DPRG) at Purdue University, and the Agrarian Technological Institute at RUDN University in Russia. I have led and contributed to numerous large-scale projects, collaborating with geoinformatics systems for crop mapping, integrated crop monitoring for water resource management, and precision agriculture solutions using IoT and AI technologies. These projects, often in collaboration with international partners like CIHEAM in Greece and the World Bank, have focused on sustainable agricultural development and climate change mitigation. My expertise spans satellite imagery processing, machine learning, UAV applications, and spectroradiometric analysis to optimize irrigation, predict crop yields, and assess soil conditions. As an award-winning researcher and journal reviewer, I have supervised postgraduate students and conducted training programs to build capacity in the field of agricultural remote sensing. My dedication to innovation and sustainable practices drives my continued efforts to enhance food security and resource efficiency globally.to improve agricultural productivity, including developing
Dr. Abdelraouf Ali
Automated wheat Phenotyping and Trait Development Platform for salt tolerance to mitigate climate change impacts an food security using remote sensing data
Salt stress, as one of the most significant abiotic stresses, causes considerable yield reduction worldwide, posing a direct threat to global food security. In Egypt, where high population growth rates and frequent soil degradation exacerbate agricultural challenges, the impact of salt stress is especially critical. Therefore, salt-tolerant plants offer a sustainable solution for many developing countries by enabling crop production on land and water resources unsuitable for conventional crops. These crops can provide essential food, fodder, and fuel, reducing pressure on arable lands while supporting food security initiatives. To maximize the potential of salt-tolerant plants, it is crucial to identify and understand the genetic and physiological mechanisms underlying salt stress tolerance.
Despite their importance, the molecular bases of salt stress tolerance remain largely unexplored, especially the differences in global gene expression between salt-tolerant and susceptible genotypes. One of the key challenges is the limited ability to collect high-resolution, accurate phenotypic data, which hinders the integration of this information with genomic data to identify and modify essential genes for breeding improved crop varieties. Overcoming this bottleneck by using advanced sensing technologies on both ground-based mobile and remote platforms for automated phenotyping could significantly enhance plant breeding programs. This would help improve the resilience of crops like wheat to salinity stress, thereby contributing to greater food security.
Our interdisciplinary team at NARSS, supported by the FAO (Food and Agriculture Organization of the United Nations) and the Agriculture Research Center (ARC), will develop an automated, high-throughput system called the Automated Wheat Phenotyping and Trait Development Platform. This platform is designed to enable end users to assess and improve wheat productivity and resilience by quantifying field performance variations and identifying critical genomic traits for salinity tolerance. By integrating airborne and ground-based sensor technologies, validated with ground-referenced data, this system will match agronomic performance data with genotypic data through complex analytics. The resulting optimization of wheat yield and biomass production under high salinity conditions will mitigate climate change impacts and strengthen food security.
Our objectives include: (a) optimizing high-throughput remote sensing technologies to acquire relevant data on wheat plant phenotypes, (b) implementing data analytics algorithms for segmentation and feature extraction, (c) developing predictive models for plant growth and performance under stress conditions, (d) designing and implementing sophisticated genetic analysis pipelines to identify genes controlling wheat performance, (e) creating a user-friendly platform to provide breeders and other end users with easy access to data and analytics, and (f) identifying differentially expressed genes in the leaves of Egyptian wheat genotypes with varying salt tolerance to assist in breeding salt-tolerant strains.
This study will select wheat genotypes with varying degrees of salt tolerance, characterized through physiological measurements such as relative water content, chlorophyll fluorescence, sugar and proline content, and ion concentrations (Na+, K+, Cl-, and Ca2+). Gene expression responses to salt stress in both tolerant and sensitive genotypes will be monitored using advanced molecular techniques, including microarray technology and quantitative RT-PCR. These innovations will enable breeders to develop improved wheat varieties, increasing agricultural productivity, enhancing resource efficiency, and ultimately bolstering national and global food security.