Xincheng Li | Agricultural Engineering | Best Researcher Award

Prof Xincheng Li |  Agricultural Engineering |  Best Researcher Award

Associate Professor at  College of Electrical and Mechanical Engineering,Qingdao Agricultural University, China

Xingcheng Li is a Research Assistant at the College of Electrical and Mechanical Engineering, Qingdao Agricultural University. His research focuses on agricultural information technology, sensor development, intelligent agricultural machinery control, and automation technology in livestock and poultry farming. He has published over 10 academic papers, secured 5 national invention patents, and led key research projects at both provincial and national levels. With experience in teaching and developing innovative solutions in agricultural engineering, Li contributes to advancing technological applications in agriculture.

 

Publication Profile

Academic and Professional Background:

Xingcheng Li is a Research Assistant at Qingdao Agricultural University, specializing in agricultural engineering and information technology. He has taught various courses at both undergraduate and graduate levels, including Principles and Applications of Sensors, Agricultural Sensing, and Operations Research. His primary research interests include agricultural information technology, sensor development, intelligent agricultural machinery control, and automation in livestock and poultry farming.

Research and Innovations:

Prof. Li has contributed significantly to the development of agricultural technologies. He has published over 10 research papers and secured 5 national invention patents. His ongoing research includes projects on livestock and poultry disease prevention, as well as participation in key national and provincial R&D programs. Notably, he has led the Shandong Province Agricultural Major Application Technology Innovation Project and the Natural Science Foundation of Shandong Province.

Research Areas:

  • Agricultural Engineering
  • Mechanical Engineering
  • Agricultural Machinery and Equipment Engineering
  • Agricultural Engineering and Information Technology

Publication Top Notes

  1. A seed-epidermis-feature-recognition-based lightweight peanut seed selection method for embedded systems
    Li, D., Huang, J., Li, X., Xu, P., Yun, Y.
    Measurement and Control (United Kingdom), 2024.
    This paper introduces a lightweight peanut seed selection method based on seed-epidermis feature recognition, suitable for embedded systems in agricultural automation.
  2. Optimization Design and Experiment of Automatic Leveling System for Orchard Operating Platform in Hilly and Mountainous Areas
    Shang, H., Li, X., Zhang, C., Hou, Y., Jia, M.
    INMATEH – Agricultural Engineering, 2024, 73(2), pp. 364–374.
    Focuses on optimizing the design and conducting experiments on an automatic leveling system for orchard platforms in challenging terrains.
  3. Domestic Conflicts and Trade Protectionism: Evidence from Tweets
    Kun, L., Xincheng, L., Ming, F.
    China Journal of Economics, 2022, 9(1), pp. 56–84.
    Analyzes the relationship between domestic conflicts and trade protectionism, based on Twitter data analysis.
  4. Grain Yield Data Collection and Service for Heterogeneous Platforms
    Zheng, L., Guo, X., Li, M., Chen, Y., Xiao, C.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(9), pp. 142–149.
    This work discusses systems for collecting and providing grain yield data across different agricultural platforms.
  5. Test and Optimization of Sampling Frequency for Yield Monitor System of Grain Combine Harvester
    Li, X., Li, M., Zheng, L., Wang, X., Sun, M.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2015, 46, pp. 74–78.
    Examines the optimization of sampling frequency for a grain yield monitor in combine harvesters.
  6. Modeling Algorithm for Yield Monitor System of Grain Combine Harvester
    Li, X., Sun, M., Li, M., Zhang, M., Wang, X.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(7), pp. 91–96.
    Proposes a modeling algorithm for improving the yield monitor system of grain combine harvesters.
  7. Development and Denoising Test of Grain Combine with Remote Yield Monitoring System
    Li, X., Li, M., Wang, X., Sun, M., Sun, H.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(2), pp. 1–8.
    This paper focuses on the development and testing of a grain combine equipped with a remote yield monitoring system.
  8. Structure Design and Signal Processing of a New Grain Flow Sensor
    Li, X., Li, M., Zheng, L., Yang, W., Sun, H.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2014, pp. 4330–4336.
    Presents the design and signal processing methods for a new grain flow sensor.
  9. A Remote Monitoring System of Automatic Soil Sampler Based on ZigBee WSN
    Yang, W., Li, M., Zheng, L., Li, X., Zhang, M.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2013, pp. 4023–4028.
    Describes a remote monitoring system for an automatic soil sampler based on ZigBee wireless sensor networks (WSN).
  10. A Remote Operating System of Grain Yield Monitor
    Li, X., Li, M., Zheng, L., Yang, W., Zhang, M.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2013, pp. 4091–4096.
    Introduces a remote operating system for monitoring grain yield during harvesting.