Chenchen Kang

Chenchen Kang, Ph.D.

Assistant Professor - Precision Agriculture
Department of Agricultural Science and Engineering
(931) 259-4304 (office)
Otis L. Floyd Nursery Research Center
472 Cadillac Lane, McMinnville, TN
ckang1@tnstate.edu
Tennessee State University

Google Scholar

Education and Experience
The Pennsylvania State University
Postdoctoral Scholar
2023 – 2025

Washington State University
Ph.D., Biological and Agricultural Engineering
August 2018 – May 2023

China Agricultural University
M.S., Agricultural Mechanization Engineering
September 2016 – June 2018

China Agricultural University
B.S., Agricultural Engineering (Outstanding Graduate)
September 2012 – June 2016

Research Interests and Expertise

Precision and autonomous agricultural machinery
AI, computer vision, and field robotics in agriculture
Modeling, simulation, and control of agricultural systems

Teaching Interests
Electrohydraulic systems and control, Machine vision, AI applications in agriculture, Applied data science in
agriculture.

Grant and Proposal Writing
1. Multi-functional and low-cost sensor station for orchard management. 2025. State Horticultural
Association of Pennsylvania. (Co-PI, $9981)
2. A low-cost microclimate monitoring system for orchard disease management. 2024. State
Horticultural Association of Pennsylvania. (Co-PI, $10,983)
3. AgShred: Affordable grape selective harvesting via robotic elimination of defectives. 2023. USDA
Agricultural Marketing Service. (Assisting in proposal writing)
4. Precision crop load management with targeted chemical blossom thinning for apples. 2023. USDA
AFRI. (Assisting in proposal writing, $601,250)

Publications
Journal Articles
1. Kang, C., Krishna Kumar, S ., & He L. (2025) Integrated approach to green fruit thinning:
Combining computer vision and precision sprayers for effective chemical thinning. Precision
Agriculture. (Under review)

2. Kang, C., Mu, X., Seffrin, A. N., Di Gioia, F., & He, L. (2025). A recursive segmentation model
for Bok Choy growth monitoring with Internet of Things (IoT) technology in controlled
enviroment agriculture. Computers and Electronics in Agriculture, 230 10966.
https://doi.org/10.1016/j.compag.2024.109866

3. Kang, C., Diverres, G., Karkee, M., Zhang, Q., & Keller, M. (2024). Assessing grapevine water
status through fusion of hyperspectral imaging and 3D point clouds. Computers and Electronics in
Agriculture, 226, 109488. https://doi.org/10.1016/j.compag.2024.109488

4. Kang, C., He, L., & Zhu, H. (2024). Assessment of spray patterns and efficiency of unmanned
sprayers used in planar growing systems. Precision Agriculture, 1-21.
https://doi.org/10.1007/s11119-024-10166-5

5. Huan, X., Wu, M., Bian, X., Jia, J., Kang, C., Wu, C., . . . Chen, J. (2024). Design and
experiment of ordinary tea profiling harvesting device based on light detection and ranging
perception. Agriculture, 14(7), 1147. https://doi.org/10.3390/agriculture14071147

6. Kang, C., Diverres, G., Achyut, P., Karkee, M., Zhang, Q., & Keller, M. (2023). Estimating soil
and grapevine water status using ground based hyperspectral imaging under diffused lighting
conditions: Addressing the effect of lighting variability in vineyards. Computers and Electronics in
Agriculture, 212, 108175. https://doi.org/10.1016/j.compag.2023.108175

7. Kang, C., Diverres, G., Karkee, M., Zhang, Q., & Keller, M. (2023). Decision-support system
for precision regulated deficit irrigation management for wine grapes. Computers and Electronics in
Agriculture, 208, 107777. https://doi.org/10.1016/j.compag.2023.107777

8. Thapa, S., Kang, C., Diverres, G., Karkee, M., Zhang, Q., & Keller, M. (2022). Assessment of
water stress in vineyards using on-the-go hyperspectral imaging and machine learning algorithms.
Journal of the ASABE, 0. https://doi.org/10.13031/ja.14663

9. Zhou, Z., Diverres, G., Kang, C., Thapa, S., Karkee, M., Zhang, Q., & Keller, M. (2022).
Ground-based thermal imaging for assessing crop water status in grapevines over a growing season.
Agronomy, 12(2), 322. https://doi.org/10.3390/agronomy12020322