faculty member, University of Guilan, Iran
Dr. Fatemeh Rahimi Ajdadi is an Assistant Professor at the Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran. She specializes in agricultural machinery and intelligent systems, with a focus on soil mechanics, machine vision, and bioengineering. Dr. Rahimi Ajdadi has contributed to numerous research projects and has extensive experience in agricultural machinery performance testing and agricultural irrigation systems. She has published widely in international journals and actively participates in academic and professional collaborations. Dr. Rahimi Ajdadi has been recognized for her innovative research and impactful contributions in agricultural engineering.
Profiloe
Education
Dr. Fatemeh Rahimi Ajdadi holds a PhD in Mechanical Engineering of Agricultural Machinery from the University of Mohaghegh Ardabili (2016). Her thesis was focused on determining soil tilth and feasibility studies for estimating soil moisture content using intelligent systems. She also completed an MSc in Mechanical Engineering of Agricultural Machinery at the same university in 2010, where her thesis involved the comparison of two prototype sensors for measuring soil mechanical resistance. Dr. Rahimi Ajdadi’s BSc degree in Mechanical Engineering of Agricultural Machinery was obtained from the University of Tehran in 2004.
Experience
Dr. Fatemeh Rahimi Ajdadi has significant expertise in both academic and applied agricultural engineering. She has worked as an expert on several notable projects, including the construction of agricultural irrigation channels in Rezvanshahr, Iran, and research projects with the Rice Research Institute of Iran. She has also contributed to projects related to urban GIS with the Governorship of Guilan. In addition to her academic role, Dr. Rahimi Ajdadi has performed extensive research on agricultural machinery, soil mechanical resistance measurement, and intelligent systems. She has worked with companies like Fayamin Gil Co. and Noafarinan Sabz Some-Sara, focusing on testing agricultural equipment and providing solutions for soil and crop-related challenges.
Awards and Honors
Dr. Fatemeh Rahimi Ajdadi has received several prestigious awards throughout her academic career. She was awarded the 2nd prize at the Eleventh Festival of Outstanding, Inventive, and Innovative Students in Ardebil, Iran, in 2012. She ranked 3rd among 30 participants in her BSc graduation and 4th in the Iranian National PhD Entrance Exam in 2011. Dr. Rahimi Ajdadi was also recognized as the top graduate in her PhD program. These honors underscore her academic excellence, dedication to research, and innovative contributions to agricultural engineering.
Research Focus
Dr. Rahimi Ajdadi’s research focuses on the integration of intelligent systems and technology into agricultural practices. Her main areas of interest include soil mechanics, machine vision applications, soil moisture estimation, and agricultural machinery performance testing. She is particularly focused on the development of novel sensors for soil resistance measurement and the application of artificial neural networks and machine learning in agricultural engineering. Dr. Rahimi Ajdadi has explored the impact of moisture content on agricultural products like rice and peanuts and has also investigated the effects of salinity and irrigation regimes on rice stem properties. Her work is aimed at improving the efficiency and sustainability of agricultural systems through technology-driven solutions.
Publications
- Artificial neural network and stepwise multiple range regression methods for prediction of tractor fuel consumption 🚜📊
- Application of machine vision for classification of soil aggregate size 🌱📸
- Cutting energy of rice stem as influenced by internode position and dimensional characteristics of different varieties 🌾✂️
- Development of a novel machine vision procedure for rapid and non-contact measurement of soil moisture content 🌾💧
- Effect of moisture content on some engineering properties of peanut varieties 🥜🌡️
- Improved digital image-based assessment of soil aggregate size by applying convolutional neural networks 🌿🤖
- Effect of salinity and irrigation regimes on the internode physical variations of rice stem 🌾💧
- Remote sensing-based detection of tea land losses: The case of Lahijan, Iran 🍃📡
- Techno-economic performance of a self-propelled rice transplanter and comparison with hand transplanting for hybrid rice variety 🌾🚜
- Mechanical behavior of peanut kernel under compression loading as a function of moisture contents 🥜🛠️
- Effect of final paddy moisture content on breaking force and milling properties of rice varieties 🍚🔨
- Application of artificial neural network for predicting fuel consumption of tractor 🚜💡
- Effect of varying parboiling conditions on head rice yield for common paddy varieties in Iran 🍚🔥
- Design, construction and field evaluation of a multiple blade soil mechanical resistance sensor 🌱🛠️
- Flow properties of awned and de-awned paddy grains through a horizontal hopper orifice 🌾🔄
- A field comparison of two prototype sensors for horizontally on-the-go soil mechanical resistance measurement 🌾🛠️
- Image deblurring to improve the grain monitoring in a rice combine harvester 🌾📸
- A review on the soil compaction measurement systems 🌍📚
- Effective Pre-Treatments for Enhancement of Biodegradation of Agricultural Lignocellulosic Wastes in Anaerobic Digestion–A Review ♻️🌿
- Study of the Effective Parameters of an On-the-go Single Blade Soil Mechanical Resistance Measurement System 🌾🛠️