Assoc. Prof. Dr. Sinan Demir | Precision Farming | Best Researcher Award 

Assoc. Prof. Dr. Sinan Demir | Precision Farming | Best Researcher Award 

Assistant Professor | Isparta University of Applied Sciences | Turkey

Dr. Sinan Demir is an Assistant Professor at Isparta University of Applied Sciences, within the Faculty of Agriculture, specializing in Soil Science and Plant Nutrition. He earned his PhD from Isparta University of Applied Sciences in 2021, focusing on the use of unmanned aerial vehicles (UAVs) for monitoring oil rose (Rosa damascena mill.) gardens and developing yield prediction models. Prior to that, he completed a Master’s degree at Suleyman Demirel University, where he researched high-resolution satellite imagery applications for detecting poppy (Papaver somniferum) cultivation areas. His academic and research pursuits concentrate on digital agriculture, remote sensing, hyperspectral imaging, geographic information systems (GIS), and machine learning applications in agriculture. Dr. Demir has made significant contributions through publications in prestigious journals such as Environment, Development and Sustainability; Natural Hazards; Remote Sensing Applications: Society and Environment; and Trees, Forests and People. His work includes advanced studies on erosion assessment using Google Earth Engine, yield prediction through UAV multispectral imagery, and digital mapping of burn severity. He has authored several book chapters, notably on machine learning algorithms and remote sensing applications in agriculture. Dr. Demir actively participates in national and international research projects, including TUBITAK-supported initiatives focusing on hyperspectral data applications in agriculture and soil property classification using machine learning techniques. His editorial responsibilities include serving as an editor for the journal "Veri Bilimi". In addition to his research, Dr. Demir plays an important role in shaping future agricultural scientists by teaching courses such as Remote Sensing and GIS, Digital Agriculture, Hyperspectral Imaging Techniques, and Integration of UAV Data in Geographic Systems at undergraduate, master’s, and doctoral levels. His contributions have been recognized through competitive scholarships like the TÜBİTAK Doctoral Scholarship Program, and he has held multiple jury memberships for thesis evaluations. Dr. Demir’s commitment to advancing sustainable agricultural practices and innovative research methodologies positions him as a notable researcher in his field.

Profiles: Google Scholar | ORCID | Scopus

Featured Publications

1.Alaboz, P., Dengiz, O., Demir, S., & Şenol, H. (2021). Digital mapping of soil erodibility factors based on decision tree using geostatistical approaches in terrestrial ecosystem. Catena.
Cited: 60 times

2. Şenol, H., Alaboz, P., Demir, S., & Dengiz, O. (2020). Computational intelligence applied to soil quality index using GIS and geostatistical approaches in semiarid ecosystem. Arabian Journal of Geosciences.
Cited: 50 times

3. Demir, S., & Dursun, I. (2024). Assessment of pre-and post-fire erosion using the RUSLE equation in a watershed affected by the forest fire on Google Earth Engine: the study of Manavgat River Basin. Natural Hazards.
Cited: 28 times

4. Alaboz, P., Demir, S., & Dengiz, O. (2021). Assessment of various pedotransfer functions for the prediction of the dry bulk density of cultivated soils in a semiarid environment. Communications in Soil Science and Plant Analysis.
Cited: 25 times

5. Alaboz, P., Demir, S., & Dengiz, O. (2020). Determination of spatial distribution of soil moisture constant using different interpolation model case study, Isparta Atabey Plain. Journal of Tekirdag Agricultural Faculty.
Cited: 23 times

 

Dr. Jinzhu Lu – Artificial Intelligence – Best Researcher Award

Dr. Jinzhu Lu - Artificial Intelligence in Agriculture - Best Researcher Award

Xihua University - China

AUTHOR PROFILE

Scopus

ORCID

SUMMARY

Dr. Jinzhu Lu is a dedicated scholar in Agricultural Engineering, specializing in agricultural robotics, non-destructive testing, and precision equipment for crops like potatoes and tea. She serves as Associate Professor and lab head at Xihua University, leading innovative agricultural automation projects. Her academic exposure includes a doctorate from Zhejiang University and a visiting term at the University of Florida. With an impactful record of publications, awards, and professional contributions, Dr. Jinzhu Lu represents a blend of research excellence and applied technological innovation in modern agriculture.

EDUCATION

Dr. Jinzhu Lu earned her Doctor of Engineering in Agricultural Engineering from Zhejiang University, focusing her thesis on spectral imaging for leaf disease detection. She was mentored by Prof. Huanyu Jiang and Dr. Reza Ehsani. Additionally, she pursued academic exchange as a visiting student at the University of Florida under the China Study Abroad Council. Her foundational training includes a Bachelor’s degree in Agricultural Electrification and Automation, setting the stage for her specialization in robotics and sensor-based agricultural systems.

PROFESSIONAL EXPERIENCE

Since January 2019, Dr. Jinzhu Lu has served as Associate Professor and head of the Agricultural Robot Laboratory at Xihua University’s School of Mechanical Engineering. Previously, She was a lecturer in the same institution. She also undertook a visiting scholar position at the University of Aberdeen in 2024. Her leadership has been pivotal in guiding student innovation, contributing significantly to national and international competitions. Her involvement in various research and academic committees reflects her active engagement in the broader agricultural engineering community.

RESEARCH INTEREST

Dr. Lu’s research focuses on agricultural robotics, non-destructive testing, and precision agriculture. She is particularly interested in machine vision applications for tea bud detection, disease identification, and robotic operations in orchards and tea gardens. Her work integrates sensor technology, artificial intelligence, and automation to enhance crop monitoring and productivity. She has recently led projects on hyperspectral imaging for fruit phenotyping and precision seeding in potatoes, showcasing her ability to merge practical field challenges with advanced technological solutions.

AWARD AND HONOR

Dr. Jinzhu Lu received the Best Paper Award from Agriculture Journal in 2021 and her students have achieved top ranks in national robotics and innovation competitions. These include CSAE 2023, CRAIC 2023, and various agricultural equipment design contests from 2018 to 2022. She was recognized as a young scientific talent by Sichuan Province and holds a senior membership in the Chinese Society of Agricultural Engineering. Her editorial contributions to peer-reviewed journals further reflect her standing in the scientific community.

RESEARCH SKILL

Dr. Jinzhu Lu possesses strong expertise in machine vision, hyperspectral imaging, deep learning, and robotics for agricultural applications. She designs and implements intelligent systems for crop inspection, disease classification, and harvesting precision. Her technical acumen includes using YOLO models, convolutional neural networks, and spectral analysis. With experience in prototyping, sensor integration, and AI algorithm deployment, she bridges engineering and agriculture effectively. Her laboratory leadership has advanced hands-on experimentation and field-ready agricultural automation systems.

PUBLICATIONS

Dr. Jinzhu Lu has authored numerous influential research papers in top journals such as Agriculture, Computers and Electronics in Agriculture, and Frontiers in Plant Science. Her works cover topics like hyperspectral phenotyping, tea bud detection using YOLO algorithms, and nondestructive ripeness assessment in citrus. Notably, she has co-developed several patents and submitted further applications, reinforcing the applied nature of her research. Her studies often include interdisciplinary collaborations and have gained relevance across plant science, AI, and engineering domains.

  • Title: Phenotyping of navel orange based on hyperspectral imaging technology
    Author(s): Qi Wang, Jinzhu Lu, Yuanhong Wang, Kaiqian Peng, Zongmei Gao
    Journal: Computers and Electronics in Agriculture

  • Title: In situ nondestructive identification of citrus fruit ripeness via hyperspectral imaging technology
    Author(s): Qi Wang, Jinzhu Lu, Yuanhong Wang, Fajun Miao, Senping Liu, Qiyang Shui, Junfeng Gao, Yingwang Gao
    Journal: Plant Methods

  • Title: A method of identification and localization of tea buds based on lightweight improved YOLOV5
    Author(s): Yuanhong Wang, Jinzhu Lu, Qi Wang, Zongmei Gao
    Journal: Frontiers in Plant Science

  • Title: Research on Device and Sensing Technology for Precision Seeding of Potato
    Author(s): Jinzhu Lu, Senping Liu, Qi Wang, Min Liao
    Journal: Agriculture

CONCLUSION

Dr. Jinzhu Lu stands out as an innovative researcher whose work bridges technology and agricultural sciences. Her contributions to robotics, plant imaging, and AI-driven diagnostics have advanced both academic inquiry and practical farming solutions. With a clear vision for intelligent agriculture and a strong track record of mentorship, patents, and publications, she is shaping the future of smart farming. Her ongoing engagements and recognitions affirm her leadership and continued potential in agricultural engineering research and innovation.