Prof. Yankun Peng, China Agricultural University, China
Dr. Peng is a distinguished researcher and professor in the field of Agricultural Engineering with a focus on intelligent detection systems and automated devices for evaluating agricultural product quality and safety. He holds a Ph.D. in Biological and Agricultural Engineering from Tokyo University of Agriculture and Technology, Japan, and has extensive academic and professional experience in both China and the United States. Since 2007, Dr. Peng has served as a Professor and PhD supervisor at the College of Engineering, China Agricultural University (CAU), where he also holds key leadership roles including Director of the National R&D Center for Agro-Processing Technology and Equipment and the National Technical Center for Nondestructive Evaluation, Identification, Instrument, and Equipment of Famous Agro-foods.
Professional Profile:
Summary of Suitability for Best Researcher Award
Dr. Peng has authored 293 peer-reviewed journal articles and 257 conference proceedings, showcasing his prolific research output.He holds 107 patents (including a US patent), with 22 patents industrialized, reflecting his significant contributions to applied science and technology. Additionally, he has developed 18 series of equipment for agro-food quality inspection and grading. Dr. Peng has established 14 standards and authored 4 books and 17 book chapters, demonstrating his leadership in setting benchmarks and contributing to scientific literature.
Education
- Ph.D. in Biological and Agricultural Engineering
Tokyo University of Agriculture and Technology, Tokyo, Japan
Apr. 1993 – Mar. 1996
Major: Agricultural Engineering, Specialty in Biological Production Science
Dissertation Title: Active Noise Control on Agricultural/Biological Production Machinery
- Developed and designed a new type of Active Noise Control (ANC) system/equipment.
- Proposed a Recurrent Least Squares (RLS) algorithm for noise reduction.
- Conducted computer simulations of noise reduction effects using C/C++ programming language.
- Constructed an Adaptive Digital Filter (ADF) system with digital signal processors (DSP) and C/C++ programming.
- Evaluated the control system on actual machinery and simplified the control algorithm using matrix theory.
- M.S. in Engineering in Agricultural Electrification & Automation
Graduate School of Northeast Agricultural University, Harbin, China
Sep. 1985 – Dec. 1988
Major: Agricultural Electrification & Automation
Thesis Title: A Microcomputer Control System for Livestock Granulated Feed Processing
- Developed a PID feedback control system using a microcomputer.
- Proposed a new control method for the rotation speed of a servomechanism.
- Designed a controller using a microcomputer and assembly programming language.
- Invented a grain flow sensor and applied the control system to livestock feed production.
- Proposed a method for judging the stability of linear time-invariant systems.
Professional Experience
- Professor and Ph.D. Supervisor
Department of Agricultural Engineering, College of Engineering, China Agricultural University (CAU)
Beijing, China
Mar. 2007 – Present
- Research in nondestructive measurement and instrumentation for agricultural product quality and safety.
- Development of hyperspectral/multispectral and Raman spectral imaging methods for meat microbial contamination detection.
- Development of rapid real-time inspection/detection systems and NIR optical instruments for agricultural product contaminants.
- Teaching courses on nondestructive measurement technology and hyperspectral imaging techniques for agro-food quality attributes.
- Supervised over 60 graduate students in agricultural engineering research.
- Director, National R&D Center for Agro-Processing Technology and Equipment
Ministry of Agriculture and Rural Affairs, China
Nov. 2009 – Present
- Oversight of national research and development projects related to agro-processing technology and equipment.
- Director, National Technical Center for Nondestructive Evaluation, Identification, Instrument and Equipment of Famous, Special, Excellent and New Agro-foods
Ministry of Agriculture and Rural Affairs, China
Dec. 2019 – Present
- Leadership in the development and evaluation of nondestructive techniques and equipment for agro-food quality assessment.
Publication top Notes:
Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control
Tailored Au@Ag NPs for rapid ractopamine detection in pork: Optimizing size for enhanced SERS signals
Optimization of Online Soluble Solids Content Detection Models for Apple Whole Fruit with Different Mode Spectra Combined with Spectral Correction and Model Fusion
SERS characterization and concentration prediction of Salmonella in pork
Rapid Quantitative detection of Ractopamine using Raman scattering features combining with Deep Learning
Non-destructive detection of TVC in pork by machine learning techniques based on spectral information