Petya Veleva | Agricultural Science | Best Researcher Award

Assoc. Prof. Dr Petya Veleva |  Agricultural Science |  Best Researcher Award

Assoc. Professor at  Department of Agricultural Engineering, Faculty of Agriculture, Trakia University, Stara Zagora, Bulgaria.

Assoc. Prof. Dr. Petya Marinova Veleva is an expert in automated systems, artificial intelligence, and precision agriculture. She holds a Master’s degree in Mechanical Engineering Technology and Machine Tools and a PhD in Automation of Engineering Labor and Systems for Automated Design. Dr. Veleva’s research focuses on intelligent data analysis, agricultural safety, and the application of artificial neural networks and Near Infrared Spectroscopy in agriculture and food safety. She has collaborated with renowned institutions, including Kobe University (Japan) and Karlsruhe Institute of Technology (Germany), and has published 34 journal articles and 6 books.

Profile:

Academic & Professional Background:

Assoc. Prof. Dr. Petya Veleva holds a Master’s degree in “Mechanical Engineering Technology and Machine Tools” and a PhD in “Automation of the Engineering Labor and Systems for Automated Design.” Her research focuses on automated systems for data analysis, artificial intelligence in precision agriculture, intelligent animal husbandry, and food safety evaluation, with specializations in artificial neural networks, Near Infrared Spectroscopy, and Aquaphotomics. She has gained valuable international experience through JSPS Fellowship in Japan, and research mobility at the Karlsruhe Institute of Technology (Germany) and the University of Agronomic Sciences and Veterinary Medicine of Bucharest (Romania).

Research & Innovations:

Dr. Veleva has completed 39 research projects and is currently involved in 6 ongoing projects. Her work has resulted in 34 journal publications (SCI, Scopus), 6 books, and 1 patent. She collaborates with prestigious institutions like Kobe University (Japan), Karlsruhe Institute of Technology (Germany), and the University of Agronomic Sciences and Veterinary Medicine of Bucharest (Romania). She is also a member of the editorial board of the journal SLOVJANI.info and has an h-index of 5 in Scopus.

Contributions:

Dr. Veleva’s research contributes to advancements in sustainable agriculture, smart crop production, and intelligent animal husbandry. Her work supports human health, bioeconomy, and quality of life through innovative applications of digital technologies and artificial intelligence in agriculture.

Publication Top Notes:

  • Impact of Different Sugar Syrups on the Development of the Fat Body in Worker Bees (Apis mellifera macedonica)
    Agriculture (2025-01-02)
    DOI: 10.3390/agriculture15010083
  • Exploring Microelement Fertilization and Visible–Near-Infrared Spectroscopy for Enhanced Productivity in Capsicum annuum and Cyprinus carpio Aquaponic Systems
    Plants (2024-12-20)
    DOI: 10.3390/plants13243566
  • Differentiation of Amaranthus Species and Estimation of Their Polyphenolic Compounds and Antioxidant Potential Using Near-Infrared Spectroscopy
    Plants (2024-11-30)
    DOI: 10.3390/plants13233370
  • Assessment of Tomato Quality through Near-Infrared Spectroscopy—Advantages, Limitations, and Integration with Multivariate Analysis Techniques
    Conference Paper (2024-08-08)
    DOI: 10.3390/engproc2024070034
  • Indirect Determination of Basic Tomato Quality Parameters Using Color Digital Images
    Conference Paper (2024-08-06)
    DOI: 10.3390/engproc2024070024
  • Near-Infrared Spectroscopy for Rapid Differentiation of Fresh and Frozen–Thawed Common Carp (Cyprinus carpio)
    Sensors (2024-06-04)
    DOI: 10.3390/s24113620
  • Evaluating the Performance and Practicality of a Multi-Parameter Assessment System with Design, Comparative Analysis, and Future Directions
    Sustainability (2024-05-14)
    DOI: 10.3390/su16104124
  • Detection of Fungal Diseases in Lettuce by VIR-NIR Spectroscopy in Aquaponics
    Microorganisms (2023)
    DOI: 10.3390/MICROORGANISMS11092348
  • Non-Destructive Determination of Plant Pigments Based on Mobile Phone Data
    TEM Journal-Technology Education Management Informatics (2023)
    DOI: 10.18421/TEM123-23
  • An Aquaphotomics Approach for Investigation of Water-Stress-Induced Changes in Maize Plants
    Sensors (2023-12-07)
    DOI: 10.3390/s23249678
  • Influence of Some Environmental Factors on Summer Phytoplankton Community Structure in the Varna Bay, Black Sea (1992–2019)
    Water (2023-04-25)
    DOI: 10.3390/w15091677