Company: University of Florida
Position: Postdoctoral Research Associate
Dr. Bantchina is a consultant and researcher specializing in precision agriculture. He is dedicated to enhancing water and fertilizer use efficiency through the integration of smart farming technologies. His academic pursuits focus on advancing this field by utilizing and developing innovative tools and techniques to sustain agriculture and conserve natural resources. Dr. Bantchina's research aims to generate scientific knowledge that translates into practical solutions for environmental challenges in agriculture, from local fields to global scales. He emphasizes collaboration, innovation, and mentorship, striving to promote cross-disciplinary scientific progress. By fostering partnerships and mentoring the next generation of scientists, Dr. Bantchina seeks to facilitate creative and resourceful applications of scientific principles, ultimately benefiting communities and advancing sustainable agricultural practices.
Peer-Reviewed Journals Articles
Bantchina, B. B., Qaswar, M., Arslan, S., Ulusoy, Y., Gündoğdu, K. S., Tekin, Y., & Mouazen, A. M. (2024). Corn yield prediction in site-specific management zones using proximal soil sensing, remote sensing, and machine learning approach. Computers and Electronics in Agriculture, 225, 109329. DOI
Bantchina, B. B., & Gündoğdu, K. S. (2024). Machine learning-based maize (Zea mays L.) extraction at parcel level using Sentinel 2A-derived spectral indices. Journal of Applied Remote Sensing. 18(3), 034515. DOI
Bantchina, B. B., & Gündoğdu, K. S. (2024). Crop type classification using Sentinel 2A-derived Normalized Difference Red Edge Index (NDRE) and machine learning approach. Journal of Agricultural Faculty of Bursa Uludag University, 38(1), 89–105. DOI
Bantchina, B. B., Gündoğdu, K. S., Arslan, S., Ulusoy, Y., Tekin, Y., Pantazi, X. E., Dolaptsis, K., Paraskevas, C., Tziotzios, G., Qaswar, M., & Mouazen, A. M. (2024). spatiotemporal modeling of soil water dynamics for site-specific variable rate irrigation in maize. Soil Systems, 8(1), 19.DOI
Dolaptsis, K., Pantazi, X. E., Paraskevas, C., Arslan, S., Tekin, Y., Bantchina, B. B., Ulusoy, Y., Gündoğdu, K. S., Qaswar, M., Bustan, D., & Mouazen, A. M. (2024). A hybrid LSTM approach for irrigation scheduling in maize crop. Agriculture, 14(2), 210. DOI
Bantchina, B. B., & Gündoğdu, K. S. (2022). Watershed characteristics and synthetic unit hydrographs determination using geographical information systems. Journal of Biological and Environmental Sciences (JBES), 15(45), 27–34.
Gündoğdu, K. S., & Bantchina, B. B. (2018). Parcel-based evaluation of NDVI values distribution from Landsat satellite images. A case study of Uludağ University, Faculty of Agriculture Farm. Journal of Agricultural Faculty of Bursa Uludag University, 32(2), 45–53.
International Peer-Reviewed Conference Contributions
Bantchina, B. B. (2024). Land cover and crop types classification using Sentinel 2A-derived vegetation indices and an artificial neural network. In Proceedings of the 16th International Conference on Precision Agriculture. 21–24 July 2024, Manhattan, Kansas, USA; International Society of Precision Agriculture.
Arslan, S., Bantchina, B. B., Taşdelen M. K., Salı, N., Tekin Y., & Mouazen, A. M. (2023). Water distribution uniformity of nozzles for a hose reel irrigation machine. In Proceedings of 5th International Congress on Agricultural Mechanization and Energy in Agriculture, Abstract Book, p51, October 29 – November 1, 2023, Antalya, Turkey.
Bantchina, B. B., Mucan, U., & Gündoğdu, K. S. (2017). Land availability analysis in Bursa using geographic information systems. In Proceedings Book, Proceedings of 5th International Participation Soil and Water Resources Congress, Kırklareli, Turkey, 12–15 September 2017; Atatürk Soil Water and Agricultural Meteorology Research Institute Kırklareli Merkez, Turkey, 2017; Volume 1, pp. 65–74.
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PhD in Biosystems Engineering | Bursa Uludağ University (Turkey)
M.Sc. in Biosystems Engineering | Bursa Uludağ University (Turkey)
B.Sc. in Agricultural Engineering | Université de Parakou (Benin)
Dr. Bantchina is a researcher with over 5 years of experience as an agricultural development consultant. His current research interests include climate-smart agriculture, precision agriculture, precision water management, soil fertility, soil proximal sensing, variable rate technology, digital soil mapping, precision irrigation, site-specific fertigation, hyperspectral remote sensing and GIS applications for agriculture, crop modelling, numerical modelling and data fusion, AI, machine learning, and deep learning applications in agriculture.