Dr. Renfu Lu has been a research agricultural engineer with U.S. Department of Agricultural Research Service (USDA-ARS) since 1994. He served as Research Leader for the USDA-ARS research unit at Michigan State University since 2007 and location coordinator since 2015. Prior to joining USDA-ARS, he was a research assistant professor (1994) and research associate (1990-1993) with the Department of Biological and Agricultural Engineering at University of Arkansas. As an adjunct faculty since 1999, Dr. Lu has supervised and mentored graduate students in the MSU Biosystems Engineering.
Lu currently leads a research team to develop an innovative robotic technology for automated harvesting of apples and a new generation of imaging technology with enhanced capabilities for quality inspection of fruits and vegetables during postharvest handling. He has made many original contributions in the development and application of acoustics, near-infrared spectroscopy, hyperspectral imaging, light scattering, mechanical and optical property measurement, structured-light imaging, and apple robotic harvesting and infield sorting technologies. He has authored or co-authored 141 peer-reviewed journal papers, 17 book chapters, 105 conference proceeding papers and 33 other publications (as of April 2021). Lu has edited two technical books and served as a guest editor for three special issues for two international journals. He has held numerous leadership positions with the American Society of Agricultural and Biological Engineers (ASABE), including chair of Publications Council (2016-2018), Refereed Publications Committee (2014-2016), and Food and Process Engineering Division (2012-2013). He has served as an editor (2009-2015) and associate editor (2002-2009) for Transactions of the ASABE and the journal of Applied Engineering in Agriculture, and on the editorial board of two international journals.
ASABE Superior Paper Award (total of two). 2019, 2018
ASABE Rain Bird Engineering Concept of the Year Award for the development of an apple harvest and automated infield sorting technology. 2019
ASABE ITSC Select Paper Award (total of 5). 2018, 2010, 2009, 2008, 2004 (for top 10% of papers presented at ASABE ITSC technical sessions)
ASABE Fellow, 2013
Outstanding Alumni Award, College of Agricultural Sciences, Pennsylvania State University, 2011
Federal Laboratory Consortium (FLC) Technology Transfer Award for hyperspectral imaging for food quality and safety inspection, 2009
ASABE Superior Paper Award, 2004
ASABE Honorable Mention Paper Award (total of 2), 1998, 1997
Lu, Y., Saeys, W., Kim, M., Peng, Y., and Lu, R. Hyperspectral imaging technology for quality and safety evaluation of horticultural products: A review and celebration of the past 20-year progress. Postharvest Biology and Technology 170:111318, 19 pages. 2020.
Lu, R., Van Beers, R., Saeys, W., Li, C., and Cen, H. Measurement of optical properties of fruits and vegetables: A review. Postharvest Biology and Technology 159:111003, 17 pages. 2020.
Zhang, Z., Pothula, A. K., and Lu, R. Improvements and evaluation of an in-field bin filler for apple bruising and distribution. Transactions of the ASABE 62(2):271-280. 2019.
Lu, Y. and Lu, R. Detection of surface and subsurface defects of apples using structured-illumination reflectance imaging with machine learning algorithms. Transactions of the ASABE 61(6):1831-1842. 2018
Huang, Y., Lu, R. and K. Chen. Development of a multichannel hyperspectral imaging probe for property and quality assessment of horticultural products. Postharvest Biology and Technology 133:88-97. 2017.
Lu, Y., R. Li, and Lu, R. Structured-illumination reflectance imaging (SIRI) for enhanced detection of fresh bruises in apples. Postharvest Biology and Technology 117:89-93. 2016.
Lu, R. (ed.). Light Scattering Technology for Food Property, Quality and Safety Assessment, 459pp. CRC Press, Taylor & Francis Group. 2016 (Book)
Park, B. and Lu, R. (ed.). Hyperspectral Imaging Technology in Food and Agriculture, 403pp. Springer. 2015. (Book)
Cen, H., Lu, R., Ariana, D. P., and Mendoza, F. Hyperspectral imaging-based classification and wavebands selection for internal defect detection of pickling cucumbers. Food and Bioprocess Technology. 7(6):1689-1700. 2014.
Leiva-Valenzuela, G. A., Lu, R., and Aguilera, J. M. Assessment of internal quality of blueberries using hyperspectral transmittance and reflectance images with whole spectra or selected wavelengths. Innovative Food Science and Emerging Technologies. 24(SI):2-13. 2014.
Mendoza, F., Lu, R., and Cen, H. Grading of apples based on firmness and soluble solids content using VIS/SWNIR spectroscopy and spectral scattering techniques. Journal of Food Engineering 125(3):59-68. 2014.