Yuzhen Lu

Yuzhen Lu

Assistant Professor

Michigan State University

I am an Assistant Professor in the Department of Biosystems and Agricultural Engineering at Michigan State University (MSU). My research resolves around the development and deployment of non-destructive sensing (e.g., machine vision, optical imaging, and spectroscopy) and automation/robotics technologies for addressing practical challenges in agricultural systems encompassing production and postharvest processes.

Before joining the faculty at MSU in January of 2023, I was a Postdoc research associate with USDA-ARS on the campus of MSU for 2018-2019, with research focused on optical imaging for quality evaluation of horticultural products and machine vision-based apple in-field sorting technology development (click here). Thereafter, I joined in the Department of Biological and Agricultural Engineering at North Carolina State University, starting the research on imaging-based high-throughput plant phenotyping and precision agriculture. I landed my first faculty position as an Assistant Professor in the Department of Agricultural and Biological Engineering at Mississippi State University in 2020.

Fo prospective students who are determined to work with me, you need to be devoted, proactive, creative, and adaptive, while being willing to go beyond your comfortable zone and embrace challenges. Research is never trivial but a real journey. I am excited to be on this journey with you. My goal is for you as a graduate student/postdoc to grow professionally and enjoy the process of becoming an expert in your discipline. I will strive my best to support you during your academic pursuits and enhance your profession and beyond. If you would like to have a glimpse of my personality, you may read some of my writings (written in Chinese 10+ years ago).


  • Optical Sensing
  • Machine Vision
  • Food Inspection
  • Precision Agriculture
  • Plant/Animal Phenotyping
  • AI & Robotics


  • PhD in Biosystems Engineering, 2018

    Michigan State University

  • MS in Plant Nutrition, 2014

    University of Chinese Academy of Sciences

  • BS in Facility Agriculture Engineering, 2011

    Northwest A&F University


Principal Investigator


Yuzhen Lu

Assistant Professor


Xinyang Mu

Graduate Assistants

Jiaming Zhang

Mingjun Li

Yuyuan Tian

Undergraduate Assistants


Recent Publications

(2024). Field Test and Evaluation of an Innovative Vision-Guided Robotic Cotton Harvester. Computers and Electronics in Agriculture (under review).

Dataset Video

(2024). Canopy Image-based Blueberry Detection by YOLOv8 and YOLOv9. Artificial Intelligence in Agriculture (under review).


(2024). Detection of Woody Breast Condition in Broiler Breast Fillets using Light Scattering Imaging. Journal of the ASABE (under review).


(2024). Automated handling and feeding techniques for skewering operations. Journal of the ASABE (in press).

(2024). Design and Preliminary Evaluation of Automated Sweetpotato Sorting Mechanisms. AgriEngineering (under review).


(2024). Public Computer Vision Datasets for Precision Livestock Farming: A Systematic Survey. Computers and Electronics in Agriculture (under review).


(2024). Design, Prototyping, and Evaluation of A Machine Vision-Based Automated Sweetpotato Grading and Sorting System. Journal of the ASABE (under review).


(2024). Advancing Sweetpotato Quality Assessment with Hyperspectral Imaging and Explainable Artificial Intelligence. Computers and Electronics in Agriculture 220, 108855.


(2024). Recognition of catfish fillets using computer vision towards automated singulation. Journal of Food Process Engineering (under review).

(2024). Prototyping and Evaluation of a Novel Machine Vision System for Real-time, Automated Quality Grading of Sweetpotatoes. Computers and Electronics in Agriculture 219, 108826.


(2024). Beef marbling assessment by structured illumination reflectance imaging with deep learning. Journal of Food Engineering 369, 111936.


(2024). Non-Destructive Assessment of Microbial Spoilage of Broiler Breast Meat Using Structured Illumination Reflectance Imaging with Machine Learning. Food Analytical Methods.


(2023). Deep Data Augmentation for Weed Recognition Enhancement: A Diffusion Probabilistic Model and Transfer Learning Based Approach. Computers and Electronics in Agriculture 216, 108517.


(2023). Non-destructive Assessment of White Striping in Broiler Breast Meat Using Structured Illumination Reflectance Imaging with Deep Learning. Journal of the ASABE 66(6): 1437-1447.


(2023). Online Volume Measurement of Sweetpotatoes by A LiDAR-based Machine Vision System. Journal of Food Engineering 361, 111725.



2024 Spring: BE815 Experimentation and Instrumentation for Biosystems Engineering (3 credits, lecture/lab), Michigan State University

2023 Fall: BE491/891 Sensors & Robotics for Agricultural Systems (3 credits, lecture), Michigan State University

2022 Fall: ABE 4463/6463 Introduction to Imaging in Biological Systems (3 credits, lecture), Mississippi State University

2022 Spring: ABE 4423/6423 Bioinstrumentation II (3 credits, lecture/lab), Mississippi State University

2021 Fall: ABE 4990/6990 Introduction to Imaging in Biological Systems (3 credits, lecture), Mississippi State University

Fall Semester: Problem Solving in Agricultural and Biological Engineering (to be developed for 2022 Fall)



I am actively looking for PhD (and or MS) graduate students to start in Summer/Fall 2024 in the Department of Biosystems & Agricultural Engineering at Michigan State University. The student will be expected to conduct original research within the fields of sensing and automation for agriculture-food systems. Potential research topics include but are not limited to non-destructive optical sensing and quality assessment of horticultural produce and meat, in-orchard sensing & automation of specialty crops, imaging-based high-throughput phenotpyping, and artificial intelligence (AI) and robotics for precision plant/animal production. Students with engineering backgrounds (e.g., agricultural/food engineering, mechanical engineering, electrical engineering, computer science, etc.) and strong experience in computer vision and machine learning are highly welcome to apply. Please email me (luyuzhen@msu.edu) with your CV if you are interested.

See the GRA position (in English). See the GRA position (in Chinese).

In additon, I also have Postdoc positions focusing on real-time machine vision system development for in-orchard and postharvest applications. The position can be started in Spring/Summer/Fall 2024 (for an intial one year with possibility of extension). Qualifications for this position include demonstrated experience in machine/computer vision, sensors and control, software-hardware integration, and strong publication records in engineering journals.

See the Postdoc position.