Manuelle Pereira | Forest Management and Ecology | Young Scientist Award

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Mrs. Manuelle Pereira | Forest Management and Ecology | Young Scientist Award

Universidade Federal dos Vales Jequitinhonha e Mucuri, Brazil

Mrs. Manuelle Pereira is a Forest Engineering graduate and current Master’s student in Forest Science at the Federal University of the Jequitinhonha and Mucuri Valleys, with a strong background in research, extension, and technological development in the Amazon. Her academic work focuses on forest ecology, biodiversity conservation, and soil–vegetation interactions, particularly involving large tree dynamics and biomass distribution. She has actively contributed to innovative projects such as the Solar Chestnut Kit, designed to improve working conditions for Amazonian extractivist communities, resulting in a utility model patent. Manuelle has participated in numerous scientific congresses and symposiums, presenting research on forest structure, ecological interactions, and environmental education. Her experience includes involvement in interdisciplinary research groups and international academic exchange in botany. She has also engaged in voluntary environmental conservation activities, demonstrating commitment to sustainable development. Her publications in peer-reviewed journals highlight her contributions to climate resilience, food security, and ecological studies in Amazonian regions. Recognized for her scientific excellence, she received the Young Scientist Award and other academic honors. Her skill set includes scientific methodology, plant analysis, and environmental monitoring. She maintains a strong interest in sustainable technologies and social innovation aimed at supporting traditional forest communities.

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Featured Publications

 

Nadia Saadati | Sustainable Agriculture (precision agriculture) | Women Researcher Award

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Mrs. Nadia Saadati | Sustainable Agriculture (precision agriculture) | Women Researcher Award

Mrs. Nadia Saadati | University of Mohaghegh Ardabili | Iran

Mrs. Nadia Saadati is a Ph.D. candidate in Agricultural Mechanization Engineering (Systems Analysis and Management) at the University of Mohaghegh Ardabili, Iran, with an outstanding focusing her doctoral research on the detection of infected corn leaves using image processing and deep learning. She holds both M.Sc. and B.Sc. degrees in Agricultural Mechanization Engineering from the same university, specializing in remote sensing, precision agriculture, and mechanization systems. Her research expertise spans agricultural innovation, technology transfer strategies, mechanization development, and smart agriculture applications. She has filed and registered seven patents in Iran covering agricultural machinery innovations such as snow blowers, garlic and lentil harvesters, potato harvesters, and crop evaluation systems, reflecting her strong inventive and engineering capability. Actively engaged in applied research, she leads projects on saffron quality assessment using electronic noses and bean characterization through spectrometry. As a technology manager and R&D member at Adaptive AgroTech and the University of Mohaghegh Ardabili’s Technology Growth Center, she contributes to developing practical agricultural technologies. She is also a patent evaluator at Ardabil Science and Technology Park and the founder and vice chairman of Arda Sanat Sabz Company, advancing sustainable mechanization solutions. Her professional memberships include WIIPA Middle East, ISIC, and the Iranian Society of Agricultural Machinery Engineering and Mechanization, along with editorial roles in the Nobel and Farmtech journals. Internationally certified, she has completed courses from WIPO, FAO, UN Women, HP LIFE, and the University of Leeds in AI, data science, programming, and agricultural innovation. She has received multiple awards, including the Best Young Inventor Award from WIPO and WIIPA and recognition as the top student at her university. Mrs. Saadati has published 10 research papers, with over 120 citations and an h-index of 6, demonstrating her growing impact in agricultural mechanization, AI in farming systems, and technology-driven sustainability. Her academic, inventive, and professional journey reflects a commitment to transforming agriculture through intelligent mechanization and interdisciplinary innovation.

Profiles:  Scopus | Orcid | Google Scholar 

Featured Publications

Saadati, N., & Najar, A. (2025). A hybrid artificial neural network–bee colony algorithm for developing a machine vision system to differentiate between two types of weeds. Biosystems Engineering and Renewable Energies.

Saadati, N., & Ahmadi Teshnizi, M. (2025). Development of a computer vision system for classifying leaves of five distinct tree species. Biosystems Engineering and Renewable Energies.

Saadati, N., Pourdarbani, R., Sabzi, S., & Hernandez-Hernandez, J. L. (2024). Identification of armyworm-infected leaves in corn by image processing and deep learning. Acta Technologica Agriculturae, 27(2), 103–110.