Jian Jin, Professor

Department Agricultural and Biological Engineering
Purdue University

Research Website

LeafSpec LLC is the ONLY company Dr. Jin works with for the commercialization of Purdue's handheld leaf imaging technologies.

Iowa State to DuPont Pioneer to Purdue

Professional Preparation 

Zhejiang University                  Hangzhou, China          Computer engineering               B.S. 2003

Denmark Technical University  Copenhagen, Denmark  Computer Engineering              M.S. 2005

Iowa State University               Ames, IA                      Agricultural Engineering           Ph.D. 2009 

Iowa State University               Ames, IA                     Agricultural Engineering           Postdoc 2010

Research and Professional Experience

2026- present           Professor, Agriculture & Biological Engineering, Purdue University

2022- 2026           Associate Professor, Agriculture & Biological Engineering, Purdue University

2015- 2022           Assistant Professor, Agriculture & Biological Engineering, Purdue University

04/2018-present        President, LeafSpec LLC, West Lafayette. IN 

2010-2015    Research Scientist/Technology Leader, DuPont Pioneer, Johnston, IA

 

Awards, Honors, Honorary Service

Davidson Prize, AEM & ASABE, 2021

AE50 Outstanding Innovation Award, ASABE, 2021

College of Engineering’s Most Impactful Inventors Awards, Purdue University, 2 times in 2019 and 2020

College of Agriculture Millionaire’s Club, Purdue University, 2 times in 2018 and 2020 

University Seed for Success Award, Purdue University, 2019

Outstanding Engineering Teachers, Purdue University, 2019

University Research Excellence Award, Iowa State University, 2009

Outstanding Leadership Award, Iowa State University, 2008

Community Leadership Award, Certificate of Recognition from Iowa Governor Chester J. Culver, 2007

Synergistic Activities and Projects

Inaugural Executive Board of the North American Plant Phenotyping Network (NAPPN), 2018-

Invited reviewer for Computers and Electronics in Agriculture, Biosystems Engineering, Transactions of ASABE, Field Robotics.

Vice President of IET-348 Electromagnetics and Spectroscopy Committee, American Society of Agricultural and Biological Engineers, 2012-2013

Vice President of IET-318 Mechatronics and Biorobotics Committee, American

Society of Agricultural and Biological Engineers, 2011-2012

Publications in Refereed Journals (Last Four Years) 

1.      D. Ma, N. Carpenter, T. Rehman, H. Maki, M. Tuinstra, and J. Jin. 2019. Greenhouse Environment Modeling and Simulation for Microclimate Control. Computers and Electronics in Agriculture, Vol 162, July 2019, Pages 134-142 

2.      L. Zhang, H. Maki, D. Ma, J.A. Sánchez-Gallego, M.V. Mickelbart, L. WangPD, and J. Jin. 2019. Optimized angles of the swing hyperspectral imaging system for single corn plant. Computers and Electronics in Agriculture 156, 349-359

3.      T.U. Rehman, M.S. Mahmud, Y.K. Chang, J. Jin, and J. Shin. 2019. Current and future applications of statistical machine learning algorithms for agricultural machine vision systems. Computers and Electronics in Agriculture 156, 585-605

4.      T. Wang, M. Rostamza, Z. Song, L. Wang, G. McNickle, A.S. Iyer-Pascuzzi, Z. Qiu, and J. Jin. 2019. SegRoot: A high throughput segmentation method for root image analysis. Computers and Electronics in Agriculture 162, 845-854

5.      D. Ma, N. Carpenter, S. Amatya, H. Maki, L. Wang, L. Zhang, S. Neeno, M.R. Tuinstra, and J. Jin. 2019. Removal of greenhouse microclimate heterogeneity with conveyor system for indoor phenotyping. Computers and Electronics in Agriculture 166, 104979.

6.      L. Zhang, L. Wang, J. Wang, Z. Song, T.U. Rehman, T. Bureetes, D. Ma, Z. Chen, S. Neeno, and J. Jin. 2019. Leaf Scanner: A portable and low-cost multispectral corn leaf scanning device for precise phenotyping. Computers and Electronics in Agriculture 167, 105069 

7.      L. Wang, J. Jin, Z. Song, J. Wang, L. Zhang, T.U. Rehman, D. Ma, N.R. Carpenter, and M.R. Tuinstra. 2020. LeafSpec: An accurate and portable hyperspectral corn leaf imager. Computers and Electronics in Agriculture. Volume 169, 105209

8.      L. Zhang, J. Jin, L. Wang, P. Huang, and D. Ma. 2020. A 3D White Referencing Method for Soybean Leaves Based on Fusion of Hyperspectral Images and 3D Point Clouds. Precision Agriculture. https://doi.org/10.1007/s11119-020-09713-7

9.      L. Wang, Y. Duan, L. Zhang, J. Wang, Y. Li, and J. Jin. 2020. LeafScope: A Portable High-resolution Multispectral Imager for In Vivo Imaging Soybean Leaf. Sensors. 2020, 20, 2194. Doi:10.3390/s20082194

10.  L. Wang, Y. Duan, L. Zhang, T.U. Rehman, D. Ma, and J. Jin. 2020. Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants. Sensors. 2020, 20(11), 3208 

11.  D. Ma, L. Wang, L. Zhang, Z. Song, T.U. Rehman, and J. Jin. 2020. Stress Distribution Analysis on Hyperspectral Corn Leaf Images for Improved Phenotyping Quality. Sensors 2020, 20(13), 3659

12.  T.U. Rehman, L. Zhang, L. Wang, D. Ma, H. Maki, J.A. Sánchez-Gallego, M.V. Mickelbart, and J. Jin. 2020. Automated leaf movement tracking in time-lapse imaging for plant phenotyping. Computers and Electronics in Agriculture. Volume 175, 105623

13.  T.U. Rehman, L. Zhang, D. Ma, L. Wang, and J. Jin. 2020. Calibration transfer across multiple hyperspectral imaging-based plant phenotyping systems: I – Spectral Space Adjustment. Computers and Electronics in Agriculture. Volume 176, 105685

14.  T.U. Rehman, D. Ma, H. Maki, L. Wang, L. Zhang, M.M. Crawford, J. Jin. 2020. Predictive spectral analysis using an end-to-end deep model from hyperspectral images for plant phenotyping. Computers and Electronics in Agriculture. Volume 177, 105713

15.  D. Ma, H. Maki, S. Neeno, L. Zhang, L. Wang, and J. Jin. 2020. Application of non-linear partial least squares analysis on prediction of biomass of corn plants using hyperspectral images. Biosystems Engineering, Volume 200, Pages 40-54

16.  Ziling Chen, Jialei Wang, Tao Wang, Zhihang Song, Yikai Li, Yuanmeng Huang, Liangju Wang, Jian Jin. 2021. Automated In-Field Leaf-Level Hyperspectral Imaging of Corn Plants Using a Cartesian Robotic Platform. Computers and Electronics in Agriculture. Volume 183, 105996 

17.  D. Ma, T.U. Rehman, L. Zhang, H. Maki, M. R. Tuinstra, and J. Jin. 2021. Modeling of diurnal changing patterns in airborne crop remote sensing images. Remote Sens. 2021, 13, 1719. https://doi.org/10.3390/ rs13091719

18.  C.D. Cruz, Y. Huang, M.R. Jahanshahi, C. Gongora-Canul, J. Jin, T. Wang, and M. Fernandez-Campos. 2021. Wheat spike blast image classification using deep convolutional neural networks. Frontiers in Plant Science. Volume 12, page 1054, DOI=10.3389/fpls.2021.673505

19.  D. Ma, T.U. Rehman, L. Zhang, H. Maki, M. R. Tuinstra, and J. Jin. 2021. Modeling of environmental impacts on aerial hyperspectral images for corn plant phenotyping. Remote Sens. 2021, 13(13), 2520. https://doi.org/10.3390/rs13132520

20.  Z. SongG*, W. QiuVS*, and J. Jin*. 2021. MISIRoot: A Robotic Minimum Invasion In-Situ Imaging System for Plant Root Phenotyping. Accepted by Transactions of the ASABE in May 2021. ITSC-14306-2020

21.  T.U. Rehman, L. Zhang, D. Ma, and J. Jin. 2022. Common Latent Space Exploration for Calibration Transfer across Hyperspectral Imaging-Based Phenotyping Systems. Remote Sensing. 14(2), 319

22.  M. Lin, V. Lynch, D. Ma, H. Maki, Jian Jin, Mitch Tuinstra. 2022. Multi-Species Prediction of Physiological Traits with Hyperspectral Modeling. Plants. 11(5), 676