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). Before starting the position in January of 2023, I was a Postdoc scholar with USDA-ARS on the campus of MSU for 2018-2019, focusing on optical imaging for quality evaluation of horticultural products and machine vision-based apple in-field sorting technology development (click here). Thereafter, I joined the Department of Biological and Agricultural Engineering at North Carolina State University, with research on imaging-based high-throughput plant phenotyping and precision agriculture. I was an Assistant Professor in the Department of Agricultural and Biological Engineering at Mississippi State University for 2020-2022.

Welcome to join us at MSU! We are here to innovate in non-destructive sensing (e.g., machine vision, optical imaging, and spectroscopy) and automation/robotics technologies for addressing practical needs/challenges in agricultural systems encompassing production and postharvest processes. Our goal is to research, develop, and transfer engineering solutions for smart and sustainable agriculture & food systems, especially for specalty crop industries. For 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).

Interests

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

Education

  • 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

Projects

Recent Publications

(2024). Design and Preliminary Evaluation of Automated Sweetpotato Sorting Mechanisms. AgriEngineering 6(3), 3058-3069.

PDF Video

(2024). Weed Image Augmentation by ControlNet-Added Stable Diffusion for Multi-class Weed Detection. Computers and Electronics in Agriculture (under review).

(2024). Recognition of catfish fillets using computer vision towards automated singulation. Journal of Food Process Engineering 47, e14726.

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

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(2024). Field Test and Evaluation of an Innovative Vision-Guided Robotic Cotton Harvester. Computers and Electronics in Agriculture 225, 109314.

PDF Dataset Video

(2024). Canopy Image-based Blueberry Detection by YOLOv8 and YOLOv9. Smart Agricultural Technology (under review).

Code

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

PDF

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

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

PDF DOI

(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.

PDF Video DOI

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

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

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

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(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.

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Teaching

2024 Fall: BE 421 Sensors & Robotics for Agricultural Systems (3 credits, lecture), Michigan State University

2024 Spring: BE 815 Experimentation and Instrumentation for Biosystems Engineering (3 credits, lecture/lab), Michigan State University

2023 Fall: BE 491/891 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)

Openings

I am actively looking for motivated PhD (and or MS) graduate students to start in Spring/Fall 2025 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 optical sensing or machine vision for quality assessment, grading, and sorting of horticultural produce and meat, in-orchard sensing & automation of specialty crop production, 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.) or relevant 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.

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