Journal publications

2017

Zhang, M., C. Li, F. Takeda, and F. Yang. 2017. Detection of internally bruised blueberries using hyperspectral transmittance imaging. Transactions of ASABE, 60(5): 1-14.

Fan, S.X., C. Li, W.Q. Huang, and L.P. Chen. 2017. Detection of blueberry internal bruising over time using NIR hyperspectral reflectance imaging with optimum wavelengths. Postharvest Biology and Technology. In press.

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.

Ozturk, S., Kong, F., Singh, R. K., Kuzy, J. D., & Li, C. 2017. Radio frequency heating of corn flour: Heating rate and uniformity. Innovative Food Science & Emerging Technologies. http://dx.doi.org/10.1016/j.ifset.2017.05.001.

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.

2016

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.

2015

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.

2014

Mustafic, A., Li, C., & Haidekker, M. 2014. Blue and UV LED-induced fluorescence in cotton foreign matter. Journal of Biological Engineering8(1), 29.

Wang, W. and C. Li. 2014. Optical Properties of Healthy and Diseased Onion Tissues in the Visible and Near-Infrared Spectral Region. Transactions of ASABE. 57(6): DOI 10.13031/trans.57.10815.

Mustafic, A., and C. Li. 2014. Classification of cotton foreign matter using color features extracted from fluorescent images. Textile Research Journal. DOI: 10.1177/0040517514561923.

Wang, W. and C. Li. 2014. Size estimation of sweet onions using consumer-grade RGB-depth sensor. Food Engineering. 142: 153–162.

Yu, P., C. Li, F. Takeda, G. Krewer, G. Rains, and T. Hamrita. 2014. Evaluation of rotary, slapper, and sway blueberry mechanical harvesters for potential fruit impact points using a miniature instrumented sphere. Comput. Electron. Agr. 101:84–92.

Yu, P., C. Li, F. Takeda and G. Krewer. 2014. Visual bruise assessment and analysis of mechanical impact measurement in southern highbush blueberry. Applied Engineering in Agriculture. 30(1): 29-37.

2013

Wang, H., C. Li, and M. Wang. 2013. Quantitative determination of onion internal quality using hyperspectral imaging with reflectance, interactance, and transmittance modes. Transactions of ASABE. 56(4): 1623-1635.
https://elibrary.asabe.org/abstract.asp?aid=43967

Takeda, F., G. Krewer, C. Li, D. MacLean , and J. W. Olmstead. 2013. Techniques for increasing machine-harvest efficiency in southern highbush and rabbiteye blueberries. Hort Technology. 23(4): 430-436.
http://horttech.ashspublications.org/content/23/4/430

Li, C., P. Yu, F. Takeda, G. Krewer. 2013. A miniature instrumented sphere to understand impacts created by mechanical blueberry harvesters. HortTechnology . 23(4): 425-429.
http://horttech.ashspublications.org/content/23/4/425

Wang, W. and C. Li. 2013. Measurement of the light absorption and scattering properties of onion skin and flesh at 633 nm. Postharvest Biology and Technology. 86: 494–501.
http://www.sciencedirect.com/science/article/pii/S0925521413002366#

2012

Wang, Weilin, Changying Li, Ernest W. Tollner, and Glen C. Rains. 2012. Development of software for spectral imaging data acquisition using LabVIEW . Computers and Electronics in Agriculture, 84: 68–75.
http://www.sciencedirect.com/science/article/pii/S0168169912000506#

Wang, Weilin, Changying Li, Ernest W. Tollner, Ronald D. Gitaitis, and Glen C. Rains. 2012. Shortwave infrared hyperspectral imaging for detecting sour skin (Burkholderia cepacia)-infected onions. Journal of Food Engineering 109 (1): 38-48
http://www.sciencedirect.com/science/article/pii/S0260877411005292

Li, C., D. Thibodeaux, A. Knowlton and J. Foulk. 2012. Effect of cleaning treatments and cotton variety on fiber and yarn quality. Applied Engineering in Agriculture. 28(6): 1-8.
http://www.researchgate.net/publication/252322035_Effects_of_cleaning_treatment_and_cotton_cultivar_of_cotton_fiber_and_textile_yarn_quality/file/e0b49522db028a99ba.pdf

Wang, Weilin, Changying Li, Ernest W. Tollner, Glen C. Rains, and Ronald D. Gitaitis. 2012. “A liquid crystal tunable filter based shortwave infrared spectral imaging system: Design and integration.” Computers and Electronics in Agriculture 80: 126-134.
http://www.sciencedirect.com/science/article/pii/S016816991100175X

Yu, P., C. Li, F. Takeda, G. Krewer, G. Rains and T. Hamrita. 2012. Quantitative evaluation of a blueberry mechanical harvester using a miniature instrumented sphere. Computers and Electronics in Agriculture. 88: 25-31.
http://www.sciencedirect.com/science/article/pii/S016816991200169X

Wang, Weilin, Changying Li, Ernest W. Tollner, Glen C. Rains, and Ronald D. Gitaitis. 2012. A liquid crystal tunable filter based shortwave infrared spectral imaging system: Calibration and characterization. Computers and Electronics in Agriculture 80: 135-144.
http://www.sciencedirect.com/science/article/pii/S0168169911002067

Wang, H., C. Li, L. Mei, and M. Li. 2012. Integration and Calibration of A Line-Scan Hyperspectral Imaging System. Transactions of the Chinese Society of Agricultural Engineering.  14: 244-249. 

2011

Yu, P., C. Li, G. Rains, and T. Hamrita. 2011. Development of the Blueberry Impact Recording Device sensing system: hardware design and calibration. Computers and Electronics in Agriculture. 79(2):103-111.
http://www.sciencedirect.com/science/article/pii/S016816991100202X

Yu, P., C. Li, G. Rains, and T. Hamrita. 2011. Development of the Berry Impact Recording Device Sensing System: Software. Computers and Electronics in Agriculture. 77(2): 195-203.
http://www.sciencedirect.com/science/article/pii/S0168169911001013

Lin, T., L.F. Rodriguez, C. Li, and S.R. Eckhoff. 2011. An engineering and economic evaluation of wet and dry pre-fractionation processes for dry-grind ethanol facilities. Bioresource Technology. 102(19):9013-9.
http://www.sciencedirect.com/science/article/pii/S0960852411008169

2010

Li, C., J. Luo, and D. MacLean . 2010. A novel instrument to delineate varietal and harvest effect on blueberry fruit texture during storage. Journal of the Science of Food and Agriculture. 91(9): 1653–1658.
http://www.ncbi.nlm.nih.gov/pubmed/21445891

Adedoyin, A., C. Li, and M. Toews. 2010. Characterization of single cotton fibers using a laser diffraction system. Textile Research Journal. 81(4): 355-367.
http://trj.sagepub.com/content/81/4/355

Li, C., A. Knowlton, S. Brown, and G. Ritchie. 2010. A comparative study of a microgin with a lab gin stand and commercial gins in southeast U.S. Applied Engineering in Agriculture. 27(2): 167-175.
https://elibrary.asabe.org/abstract.asp?aid=36488

Rodriguez, L.F., C. Li, M. Khanna, A.D. Spaulding, Tao Lin, and S.R. Eckhoff. 2010. An engineering and economic evaluation of quick germ-quick fiber process for dry-grind ethanol facilities: analysis. Bioresource Technology 101(14): 5275–5281.
http://www.ncbi.nlm.nih.gov/pubmed/20207536

Li, C., L.F. Rodriguez, M. Khanna, A.D. Spaulding, Tao Lin, and S.R. Eckhoff. 2010. An engineering and economic evaluation of quick germ quick fiber process for dry-grind ethanol facilities: model description and documentation. Bioresource Technology 101(14): 5282–5289.
http://www.ncbi.nlm.nih.gov/pubmed/20219358

Li, C., R. Gitaitis, and N. Schmidt. 2010. Detection of onion postharvest diseases by analyses of headspace volatiles using a gas sensor array and GC-MS. LWT – Food Science and Technology. 44: 1019-1025.
http://www.sciencedirect.com/science/article/pii/S0023643810004135

Lee, W. S., V. Alchanatis, C. Yang, M. Hirafuji, D. Moshou, C. Li. 2010. Sensing technologies for precision specialty crop production. Computers and Electronics in Agriculture. 74: 2-33.
http://www.sciencedirect.com/science/article/pii/S0168169910001493

Li, C., G. Krewer, P. Ji, H. Scherm, and S.J. Kays. 2010. Gas sensor array for blueberry fruit disease detection and classification. Postharvest Biology and Technology 55(3): 144-149.
http://www.sciencedirect.com/science/article/pii/S0925521409002373

2009

Li, C., R. Gitaitis, E.W. Tollner, P. Sumner, and D. MacLean . 2009. Onion sour skin detection using a gas sensor array and support vector machine. Sensing and Instrumentation for Food Quality and Safety 3(4): 193-202.

http://link.springer.com/article/10.1007%2Fs11694-009-9085-1

M.R.P. Mosqueda, E.W. Tollner, G.E. Boyhan, C. Li, and R. W. McClendon . 2009. Simulating onion packinghouse product flow for performance evaluation and education. Biosystems Engineering 102(2): 135-142.
http://www.sciencedirect.com/science/article/pii/S1537511008002912

2008

Li, C., P. Heinemann and P. Reed. 2008. Using genetic algorithms (GAs) and CMA evolutionary strategy to optimize electronic nose sensor selection. Transactions of the ASABE 51(1): 321-330.
https://elibrary.asabe.org/abstract.asp?aid=21505

2007

Li, C. and P. Heinemann. 2007. ANN integrated electronic nose system for apple quality evaluation. Transactions of the ASABE 50(6): 2285-2294.
https://elibrary.asabe.org/abstract.asp?aid=24081

Li, C., P. Heinemann and J. Irudayaraj. 2007. Detection of apple defects using an electronic nose and zNose. Transactions of the ASABE. 50(4): 1417-1425.
https://elibrary.asabe.org/abstract.asp?aid=19543

Li, C., P. Heinemann and R. Sherry. 2007. Neural network and Bayesian network fusion models to fuse electronic nose and surface acoustic wave sensor data for apple defect detection. Sensors and Actuators B: Chemical. 125(1): 301-310.
http://www.sciencedirect.com/science/article/pii/S0925400507001153

Li, C. and P. Heinemann. 2007. A comparative study of three evolutionary algorithms for a surface acoustic wave sensor wavelength selection. Sensors and Actuators B: Chemical. 125(1): 311-320.
http://www.sciencedirect.com/science/article/pii/S0925400507001165

2006 and earlier

Wu, C., G. Teng and C. Li. 2005. Application and validation of computer vision based nondestructive measurement system for cucumber seedling growth conditions. Transactions of the Chinese Society of Agricultural Engineering. 21 (4) 109-112.

Li, C., G. Teng, C. Zhao, X. Qiao, and C. Wu. 2003. Implementation of non-contact measurement of the plant growth in greenhouse using computer vision. Transactions of Chinese Society of Agricultural Engineers. 19 (3): 140-144.

Teng, G. and C. Li. 2002. DNCS-A new scheme for the automation of greenhouse environment control. Transactions of the Chinese Society of Agricultural Engineering. 18 (5): 118-122.

Teng, G. and C. Li. 2002. The application of computer vision in industrialized agriculture. Journal of China Agricultural University. 7 (2): 62-67.

Ying, X., G. Teng and C. Li. 2002. The application of distributed network control system in greenhouse environmental control. Transactions of the Chinese Society of Agricultural Engineering. Supplement. 18 (5): 83-86.