Prof. Dr. László Baranyai - MATE Research
Overview
Prof. Dr. László Baranyai is full professor at the Department of Food Measurement and Process Control, Institute of Food Escience and Technology, Hungarian University of Agriculture and Life Sciences. He serves as head of the department and the chair of the Center of Bioengineering and Process Control.
His research focuses on application of computer vision and digital tools in agriculture. His expertise lies primarily in laser induced diffuse reflectance imaging, as well as data analysis and advanced statistics.
Prof. Dr. László Baranyai’s work contributes to questions of how non-destructive methods can be used for quality assessment of raw materials and food. He develops methods for quality control using rapid biophysical techniques. His research interest also includes development of artificial intelligence solutions.
His theoretical work examines the interaction between photons of a laser beam and biological tissues. His empirical work has assessed these theories in settings ranging from grading fruits and vegetables (kiwifruit, tomato) to detection of wine and fruit juice adulteration.
Across his research, he uses free software tools of R, RStudio for statistics, data analysis and visualization, and Scilab for computer vision.
Prof. Dr. László Baranyai pioneered the development of free software toolboxes like ampelography (GRALED software), surface patter analysis of leaves (LeafLaminaMap), and R package for backscattering simulation (MCBackscattering). His developed software tools are freely available from the university website, open repository (GitHub), or as official R package. He has developed logical games for the national open university project website (called Mindentudás Egyeteme).
His findings are utilized in submitted patent application related to meat marbling classification with color imaging. He made significant contributions in sunburn risk assessment as delivered AI model for the mobile application called SHEET.
He authored and co-authored 70 research articles in high-impact scientific journals, and 9 book chapters (including edited conference books). His h-index is 14 according to Scopus. He made 225 verified peer review according to Web of Science.
Prof. Dr. László Baranyai has collaborated with research groups across Europe/worldwide, and he has successfully applied for research grants nationally (OTKA) and internationally (ICT-AGRI-FOOD). He won the prestigious CIGR Recognition Award for his section editor work at CIGR ejournal.
Research keywords:
Publications
Gianluca, A., Filippetti, I., Pastore, C., Sangiorgio, D., Valentini, G., Bortolotti, G., ... & Baranyai, L. (2025). Prediction of berry sunburn damage with machine learning: Results on grapevine (Vitis vinifera L.). Biosystems Engineering, 250, 62-67. https://doi.org/10.1016/j.biosystemseng.2024.12.006
Pham, T. T., Baranyai, L., Sao Dam, M., Ha, N. T. T., Nguyen, L. L. P., Varga-Toth, A., ... & Friedrich, L. (2023). Evaluation of shelf life of egg treated with edible coating by means of NIR spectroscopy and laser induced diffuse reflectance imaging. Journal of Food Engineering, 358, 111688. https://doi.org/10.1016/j.jfoodeng.2023.111688
Le Nguyen, L. P., Zsom, T., Sao Dam, M., Baranyai, L., & Hitka, G. (2019). Evaluation of the 1-MCP microbubbles treatment for shelf-life extension for melons. Postharvest Biology and Technology, 150, 89-94. https://doi.org/10.1016/j.postharvbio.2018.12.017
Mussadiq, Z., Laszlo, B., Helyes, L., & Gyuricza, C. (2015). Evaluation and comparison of open source program solutions for automatic seed counting on digital images. Computers and Electronics in Agriculture, 117, 194-199. https://doi.org/10.1016/j.compag.2015.08.010
Reichart, O., Szakmár, K., Jozwiak, Á., Felföldi, J., & Baranyai, L. (2007). Redox potential measurement as a rapid method for microbiological testing and its validation for coliform determination. International journal of food microbiology, 114(2), 143-148. https://doi.org/10.1016/j.ijfoodmicro.2006.08.016
Projects
Sunburn and HEat prediction in canopies for Evolving a warning Tech solution
Purpose of SHEET was to develop risk prediction models for heat damage in the fruit production and transfer the model in a functional mobile application on the smart phone. Global radiation and temperature rise cause huge risks for the fruit production already affecting the fruit quality, storability, and increasingly results in food waste. Experimental data captured apple and grape production in varying elevation, global radiation, and precipitation.
TRL7 (fruit detection and thermal imaging solution - fruit assessment, case specific temperature distribution model and mobile App as warning solution)
TRL5 (temperature distribution model for varying canopies)
https://ictagrifood.eu/node/44656
CA24145 - International Food Techno-functionality - Data (INFOTECH-DATA)
INFOTECH-DATA (INternational FOod TECHno-functionality – DATA) aims to create a network and facilitate the creation of open-access databases with comparable techno-functionality data of food ingredients. The Action will create methodologies with the whole EU food science community to achieve this. The methodologies will consist of 1) standardised techno-functionality method and 2) blueprints from database architecture and data management strategies. https://www.cost.eu/actions/CA24145/
