Yuzhen Lu

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Photo of Yuzhen Lu
Current Standing: 
PhD
Last Degree: 
MS, 2014, University of Chinese Academy of Sciences
Curriculum Vitae: 
Entered Program in: 
2014
Academic Background: 

BS in Facility Agriculture Science and Engineering, College of Horticulture, Northwest Agriculture & Forestry University, Yangling, Shaanxi, China (2007-2011)

MS in Plant Nutrition, Institute of Soil Science, University of Chinese Academy of Sciences, Nanjing, Jiangsu, China (2011-2014)

Current Research Interests / Thesis Topic: 

Spatial frequency-domain hyperspectral imaging, structured illumination imaging, machine vision, image processing, spectroscopy and imaging, facility horticulture

Publications / Journal Articles: 
  • Lu Yuzhen, Du Changwen, Yu Changbing, Zhou Jianmin.  Use of FTIR-PAS combined with chemometrics to estimate nutritional information in rapeseeds. The Journal of Plant Nutrition and Soil Science, 2014, 117, 927-933.
  • Lu Yuzhen, Du Changwen, Yu Changbing, Zhou Jianmin. Classifying rapeseed varieties using Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS). Computers and Electronics in Agriculture, 2014, 107, 58-63.

Peer-Reviewed Articles 

  • Y. Lu, R. Lu and R. Li. 2017. Structured-illumination reflectance imaging coupled with phase analysis techniques for surface profiling of apples. Journal of Food Engineering (under review).
  • Y. Lu and R. Lu, 2017. Non-destructive defect detection of apples by spectroscopic and imaging technologies: a review. Transactions of the ASABE (under review).
  • R. Li, Y. Lu and R. Lu, 2017. Structured illumination reflectance imaging for enhanced detection of subsurface tissue bruising in apples. Transactions of the ASABE (under review).
  • Y. Lu and R. Lu, 2017. Histogram-based automatic thresholding methods for bruise detection of apples by structured-illumination reflectance imaging. Biosystems Engineering (in press).
  • Y. Lu and R. Lu, 2017. Development of a multispectral structured-illumination reflectance imaging (SIRI) system and its application to bruise detection of apples. Transactions of the ASABE (in press).
  • Y. Lu, Y. Huang and R. Lu, 2017. Innovative hyperspectral imaging-based techniques for quality evaluation of fruits and vegetables: a review. Applied Science 7, 189.
  • Y. Lu and R. Lu, 2017. Using composite sinusoidal patterns in structured-illumination reflectance imaging (SIRI) for enhanced detection of apple bruise. Journal of Food Engineering 199, 54-64.
  • Y. Lu, R. Li and R. Lu, 2016. Gram-Schmidt orthonormalization for retrieval of amplitude images under sinusoidal patterns of illumination. Applied Optics 55(25): 6866-6873.
  • Y. Lu, R. Li and R. Lu, 2016. Fast amplitude demodulation by spiral phase transform (SPT) in structured-illumination reflectance imaging (SIRI) for detection of bruises in apples. Computers and Electronics in Agriculture 127, 652-658.
  • Y. Lu, R. Li and R. Lu, 2016. Structured-illumination reflectance imaging (SIRI) for enhanced detection of fresh bruises in apples. Postharvest Biology and Technology 117, 89-93.

Book Chapters

  • Y. Lu and R. Lu., 2016. Quality evaluation of apple by computer vision. In: D.W. Sun, Computer Vision Technology for Food Quality Evaluation, 2nd edition, Academic Press, pp. 273-304.
  • C. Du, F. Ma, Y. Lu and J. Zhou. 2015. Soil fertility assessed by infrared spectroscopy. In: R. Lal and B.A. Steward, Specific Farming: Precision Agriculture, CRC Press, pp. 155-184.
Biography (Personal Interest): 

I enjoy working with the challenges in the fruit and vegetable domain. My focus is to develop nondestructive sensing techniques like computer vision for automated food quality and safety assessment. During my spare time, I like to do some sports like running, or watch movies.

Awards: 
  • Scholar award of international plant nutrition institute (NIPI), 2013
  • Wu Yee-sun scholarship of Nanjing branch, Chinese Academy of Sciences, 2014
  • Di-ao Scholarship of Chinese Academy of Sciences, 2014
  • Galen and Ann Brown Scholarship, 2016
  • Galen and Ann Brown Scholarship, 2017
  • Engineering Graduate Research Symposium Poster Award (1st place), 2017