Renfu Lu, Ph.D

Renfu Lu

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USDA-ARS Adjunct Professor

Phone:
517-432-8062

Email:

Degrees:
B.S., Engineering, Zhejiang Agric. University (now Zhejiang University), Hangzhou, China
M.S., Agricultural Engineering, Cornell University, Ithaca, NY
Ph.D. in Agricultural Engineering, Pennsylvania State University, University Park, PA

Biography

Dr. Renfu Lu has been a Research Agricultural Engineer with the U.S. Department of Agriculture Agricultural Research Service (USDA-ARS) since 1994. He has 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 served on the graduate guidance committees for advising and mentoring graduate students in Biosystems Engineering and other engineering disciplines.

Research Interest

Dr. Renfu Lu’s research is focused on automation and sensing technologies for harvest and nondestructive quality assessment of horticultural crops. He has authored or co-authored more than 150 peer-reviewed journal articles and 17 book chapters and edited/co-edited two technical books. Dr. Lu has been credited for his pioneering research and outstanding technology transfer efforts in the development and application of hyperspectral imaging technology for food quality and safety inspection, which has been considered one of the most significant emerging technologies in the field for the past 25 years. Dr. Lu has led the development of innovative light scattering, spatially resolved spectroscopy, and structured light imaging technologies for nondestructive assessment of properties and postharvest quality and safety of horticultural and food products. In collaboration with a commercial company, Dr. Lu has led the development of an ASABE award-winning, patented machine-vision based in-field sorting technology and system for grading and sorting apples based on color and size in orchard at up to 12 fruits per second, which enables growers to achieve significant cost savings in postharvest storage and packing as well as reduce postharvest loss. Currently, he is co-leading with a faculty at Michigan State University a research team on the development of an innovative robotic harvesting technology to address the growing shortage and rising cost of labor for the U.S. apple and specialty crop industries.

Awards

ASABE Rain Bird Engineering Concept of the Year Award for the development of a new robotic apple harvesting technology. 2023

ASABE Rain Bird Engineering Concept of the Year Award for the development of an apple harvest and automated in-field sorting technology. 2019

ASABE Superior Paper Award (total of 2). 2019, 2018 (for top 5% of papers published in ASABE journals)

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 the development and application of hyperspectral imaging technology for food quality and safety inspection, 2009

ASAE Superior Paper Award. 2004 (for top 2.5% of papers published in ASAE journals)

ASAE Honorable Mention Paper Award (total of 2). 1997, 1998 (for top 5% of papers published in ASAE journals)

Publications

Google Scholar

Agricultural Research Service

Apple Harvesting Robot

Apple In-field Sorting System