Li, Changying - The University of Georgia - School of Chemical, Materials, and Biomedical Engineering

个人简介

Dr. Li is developing innovative sensing and automation technologies to help provide safe and high-quality food, fiber, feed and fuel to sustain the world’s growing population. Learn more about Dr. Li's teaching and research in Focus on Faculty. One of Dr. Li's recent research projects is the development of the Berry Impact Recording Device, or "BIRD." The device rides along with berries in packing plants while its sensors record the bumps and bruises inflicted on the fruit. The data gathered by BIRD helps engineers design gentler harvesting and packing methods so more high-quality fruit makes its way to grocery stores. Ph.D., Agricultural and Biological Engineering, Pennsylvania State University, 2006

研究领域

Sensing and automation for food, agricultural and biological systems.

近期论文

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Zhang, M., C. Li and F. Yang. 2017. Classification of Foreign Matter Embedded inside Cotton Lint using Short Wave Infrared (SWIR) Hyperspectral Transmittance Imaging. Computers and Electronics in Agriculture. 10.1016/j.compag.2017.05.005. In press. Takeda, F., W. Yang , C. Li, A. Freivalds, K. Sung , R. Xu, B. Hu, J. Williamson and S. Sargent. 2017. Applying New Technologies to Transform Blueberry Harvesting. Agronomy, 7, 33; doi:10.3390/agronomy7020033. Sun, S., C. Li, and A. H. Paterson. 2017. In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR. Remote Sensing, 9, 377; doi:10.3390/rs9040377. Kuzy, J. and Li, C., 2017. A Pulsed Thermographic Imaging System for Detection and Identification of Cotton Foreign Matter. Sensors, 17(3), p.518. Patrick, A., S. Pelham, A. Culbreath, C. Holbrook, I.J.d. Godoy, and C. Li. 2017. High Throughput Phenotyping of Tomato Spot Wilt Disease in Peanuts Using Unmanned Aerial Systems and Multispectral Imaging. IEEE Instrumentation & Measurement Magazine. June 1-10. Jiang, Y., C. Li, and F. Takeda. 2016. Nondestructive detection and quantification of blueberry bruising using near-infrared (NIR) hyperspectral reflectance imaging. Scientific Reports. 6: srep35679. Jiang, Y., C. Li., and A. Paterson. 2016. High-throughput phenotyping of cotton plant height using depth images under field conditions. Computers and Electronics in Agriculture. 130 (2016): 57-68. Zhang, R., C. Li, M. Zhang, and J. Rodgers. 2016. Shortwave infrared hyperspectral reflectance imaging for cotton foreign matter classification. Computers and Electronics in Agriculture. 127: 260-270. Jiang, Y. and C. Li. 2015. mRMR-based feature selection for classification of cotton foreign matter using hyperspectral imaging. Computers and Electronics in Agriculture. 10.1016/j.compag.2015.10.017. Chugunov, S. and C. Li. 2015. Monte Carlo simulation of light propagation in healthy and diseased onion bulbs with multiple layers. Computers and Electronics in Agriculture. 117: 91-101. DOI:1016/j.compag.2015.07.015. Xu, R., F. Takeda, G. Krewer, and C. Li. 2015. Measure of mechanical impacts in commercial blueberry packing lines and potential damage to blueberry fruit. Postharvest Biology and Technology. DOI: 10.1016/j.postharvbio.2015.07.013. Wang, W. and C. Li. 2015. A multimodal machine vision system for quality inspection of onions. Journal of Food Engineering. DOI: 10.1016/j.jfoodeng.2015.06.027. Mustafic, A., Y. Jiang, and C. Li. 2015. Cotton contamination detection and classification using hyperspectral fluorescence imaging. Textile Research Journal. DOI: 10.1177/0040517515590416. Jiang Y, Li C. 2015. Detection and Discrimination of Cotton Foreign Matter Using Push-Broom Based Hyperspectral Imaging: System Design and Capability. PLoS ONE 10(3): e0121969. doi: 10.1371/journal.pone.0121969. Konduru, T., G. Rains, and C. Li. 2015. Detecting sour skin infected onions using a customized gas sensor array. Journal of Food Engineering. 160: 19-27. DOI: 10.1016/j.jfoodeng.2015.03.025. Chugunov, S. and C. Li. 2015. Parallel implementation of inverse adding-doubling and Monte Carlo multi-layered programs for high performance computing systems with shared and distributed memory. Computer Physics Communications. DOI: 10.1016/j.cpc.2015.02.029. Xu, R. and C. Li. 2015. Development of the Second Generation Berry Impact Recording Device (BIRD II). Sensors 15, no. 2: 3688-3705. Konduru, T., G. Rains, and C. Li. 2015. A customized metal oxide semiconductor-based gas sensor array for onion quality evaluation: system development and characterization. Sensors. 15, 1252-1273.