Selected Journal Articles

1.
Validation of a portable near infrared reflectance spectrometer to determine harvest maturity in grass seed crops

Anderson, N., Chastain, T., & Zhou, J.

Crop, Forage & Turfgrass Management, 12, Article e70097. (2025)

2.
Developing a generalized soybean maturity date prediction model using UAV imagery and transfer learning

Zhou, J., Zhou, J., Scaboo, A., Beche, E., Xu, Z., & Zhang, Z.

Frontiers in Plant Science, 16, Article 1720819. (2026)

4.
Pre-harvest estimation and contribution analysis of alfalfa quality traits using multi-type features and machine learning

Yu, T., Xu, Y., Zhou, J., & Zhang, Z.

International Journal of Remote Sensing, 46(13), 4832–4863. (2025)

5.
A new Bayesian semi-supervised active learning framework for large-scale crop mapping using Sentinel-2 imagery

Xu, Y., Zhou, J., & Zhang, Z.

ISPRS Journal of Photogrammetry and Remote Sensing, 209, 17–34. (2024)

6.
Evaluation of the effect of Sentinel-1 SAR and environmental factors in alfalfa yield and quality estimation

Yu, T., Zhou, J., Ranjbar, S., Chen, J., Digman, M. F., & Zhang, Z.

Agronomy, 14(4), Article 859. (2024)

7.
Plot-level maize early stage stand counting and spacing detection using advanced deep learning algorithms based on UAV imagery

Wang, B., Zhou, J., Costa, M., Kaeppler, S. M., & Zhang, Z.

Agronomy, 13(7), Article 1728. (2023)

8.
Developing an image processing pipeline to improve the position accuracy of single UAV images

Feng, A., Vong, C. N., Zhou, J., Conway, L. S., Zhou, J., Vories, E. D., Sudduth, K. A., & Kitchen, N. R.

Computers and Electronics in Agriculture, 206, Article 107650. (2023)

9.
Identification of genomic regions associated with soybean response to off-target dicamba

Canella Vieira, C., Jarquin, D., do Nascimento, E. F., Lee, D., Zhou, J., Smothers, S., Zhou, J., Diers, B., Riechers, D., Xu, D., Nguyen, H., Shannon, J. G., & Chen, P.

Frontiers in Plant Science, 13, Article 1090072. (2022)

10.
A review of remote sensing for precision potato management

Sun, C., Zhou, J., Ma, Y., Xu, Y., Pan, B., & Zhang, Z.

Frontiers in Plant Science, 13, Article 871859. (2022)

11.
IntegrateNet: A deep learning network for maize stand counting from UAV imagery by integrating density and local count maps

Liu, W., Zhou, J., Wang, B., Costa, M., Kaeppler, S., & Zhang, Z.

IEEE Geoscience and Remote Sensing Letters. (2022)

12.
Differential responses of soybean genotypes to off-target dicamba damage

Canella Vieira, C., Zhou, J., Cross, C., Heiser, J. W., Diers, B., Riechers, D., Zhou, J., Hernandez Jarquin, D., Nguyen, H., Shannon, J. G., & Chen, P.

Crop Science. (2022)

13.
Exploring machine learning algorithms to unveil soybean genomic regions associated with resistance to southern root-knot nematode

Canella Vieira, C., Zhou, J., Usovsky, M., Vuong, T., Howland, A. D., Lee, D., & Chen, P.

Frontiers in Plant Science, 13, Article 883280. (2022)

14.
Improve soybean variety selection accuracy using UAV-based high-throughput phenotyping technology

Zhou, J., Beche, E., Vieira, C. C., Yungbluth, D., Zhou, J., Scaboo, A., & Chen, P.

Frontiers in Plant Science, 12, Article 768742. (2021)

15.
Development of an automated plant phenotyping system for evaluation of salt tolerance in soybean

Zhou, S., Mou, H., Zhou, J., Zhou, J., Ye, H., & Nguyen, H. T.

Computers and Electronics in Agriculture, 182, Article 106001. (2021)

16.
Yield estimation of soybean breeding lines under drought stress using unmanned aerial vehicle-based imagery and convolutional neural network

Zhou, J., Zhou, J., Ye, H., Ali, M. L., Chen, P., & Nguyen, H. T.

Biosystems Engineering, 204, 90–103. (2021)

17.
Classification of soybean leaf wilting due to drought stress using UAV-based imagery

Zhou, J., Zhou, J., Ye, H., Ali, M. L., Nguyen, H. T., & Chen, P.

Computers and Electronics in Agriculture, 175, 105576. (2020)

18.
Estimation of the maturity date of soybean breeding lines using UAV-based multispectral imagery

Zhou, J., Yungbluth, D., Vong, C. N., Scaboo, A., & Zhou, J.

Remote Sensing, 11(18), Article 2075. (2019)

19.
Automated segmentation of soybean plants from 3D point cloud using machine learning

Zhou, J., Fu, X., Zhou, S., Zhou, J., Ye, H., & Nguyen, H. T.

Computers and Electronics in Agriculture, 162, 143–153. (2019)

20.
Development of an automated phenotyping platform for quantifying soybean dynamic responses to salinity stress in greenhouse environment

Zhou, J., Chen, H., Zhou, J., Fu, X., Ye, H., & Nguyen, H. T.

Computers and Electronics in Agriculture, 151, 319–330. (2018)

Conference Proceedings

1.
The Grady Sensor: determining seed moisture content in seconds

Zhou, J., Anderson, N. P., Garrett, M. Q., Snell, L. P., & Chastain, T. G.

In 12th International Herbage Seed Group Conference, p. 71. (2025)

Book Chapters

1.
Imaging technology for high-throughput plant phenotyping

Zhou, J., Vong, C. N., & Zhou, J.

In S. Ma, T. Lin, E. Mao, Z. Song, & K. C. Ting (Eds.), Sensing, Data Managing, and Control Technologies for Agricultural Systems (pp. 75–99). Springer International Publishing. (2022)

2.
High-throughput crop phenotyping systems for controlled environments

Zhou, J., Zhou, J., Ye, H., & Nguyen, H. T.

In High-Throughput Crop Phenotyping (pp. 183–208). Springer, Cham. (2021)

Selected Presentations

Bhattarai, P., Zhou, J., & Berry, P. (2026). Hyperspectral sensing for early detection of small broomrape (Orobanche minor) parasitism in red clover. 2026 Western Society of Weed Science Annual Meeting, March 2–5, 2026, Tucson, AZ.

Zhou, J. (2026). Slug and Weather Monitoring for Sustainable Grass and Legume Seed Production Management. Integrated Slug Management Workshop, February 24, 2026, McMinnville, OR.

Zhou, J., Anderson, N., Walenta, D., & Dung, J. (2026). Calibrating the Grady Sensor for rapid seed moisture determination in Kentucky Bluegrass. Union County Seed Growers Association Annual Meeting, February 2026, La Grande, OR.

Zhou, J. & Duan, Q. (2025). A mask-guided dual-encoder with decoupled attention for mapping spectrally similar crop species from satellite image time series. American Geophysical Union Annual Meeting, December 15–19, 2025, New Orleans, LA. (invited)

Zhang, Z., Digman, M., Cherney, J., Mitchell, P., Jung, J., Zhou, J., Gallagher, N., Chen, J., Azimi, F., Yu, T., & Fares, D. (2025). AlfAdvisor: A web-based cyber-platform to estimate alfalfa yield and quality to support harvest scheduling. American Geophysical Union Annual Meeting, December 15–19, 2025, New Orleans, LA. (poster)

Zhou, J., Anderson, N. P., Garrett, M. Q., Snell, L. P., & Chastain, T. G. (2025). The Grady Sensor: determining seed moisture content in seconds. 12th International Herbage Seed Group Conference, November 16–19, 2025, Launceston, Tasmania, Australia.

Zhou, J., Duan, Q., & Anderson, N. P. (2025). Classification of grass seed crop species using spaceborne imagery and artificial intelligence-driven models. 12th International Herbage Seed Group Conference, November 16–19, 2025, Launceston, Tasmania, Australia. (poster)

Eshraghi, M. A., Berry, P., & Zhou, J. (2025). Deployment of instance detection models on edge devices to enable precision weed spot spraying. ASABE Annual International Meeting, July 13–16, 2025, Toronto, Canada.

Nagarajan, A., Chen, B., Snell, L., Underhill, K., Chen, Z., Zhang, K., Curry, D., Di, Y., Li, F., & Zhou, J. (2025). Digitalizing seed purity testing: Identifying species of seeds using low-cost computer vision and artificial intelligence system. ASABE Annual International Meeting, July 13–16, 2025, Toronto, Canada.

Zhou, J. (2025). How AI and precision agriculture enhance farm decision-making and efficiency. ASA Sustainable Agronomy Conference, July 9, 2025, Webinar. (invited)

Zhou, J. (2025). The Grady Seed Moisture Sensor and More. Seminar at Foundation for Arable Research & Seed Industry Research Centre Inc, January 26, 2025, Lincoln, New Zealand. (invited)

Zhou, J. (2025). Supporting Pest Management with Computer Vision and Artificial Intelligence. 2025 Hermiston Farm Fair, December 3–4, 2025, Hermiston, OR.

Berry, P., Eshraghi, M. A., Branka, A., & Zhou, J. (2025). Identifying weed instances in peppermint using aerial imagery and artificial intelligence. 2025 Western Society of Weed Science Annual Meeting, March 10–13, 2025, Seattle, WA.

Iqbal, M. I., Zhou, J., Mallory-Smith, C., & Berry, P. (2025). Spectral discrimination of weed species in grass seed production in the Willamette Valley, OR. 2025 Western Society of Weed Science Annual Meeting, March 10–13, 2025, Seattle, WA.

Iqbal, M. I., Zhou, J., Mallory-Smith, C., & Berry, P. (2025). Identification of Orobanche minor parasitism using hyperspectral remote sensing in red clover cropping systems. 2025 Western Society of Weed Science Annual Meeting, March 10–13, 2025, Seattle, WA. (poster)

Garrett, M., Snell, L., & Zhou, J. (2025). The Grady Sensor: a portable sensor for rapid seed moisture determination. OSU Undergraduate Research Spring Poster Symposium, May 20, 2025, Corvallis, OR. (poster)

Zhou, J. (2025). Exploring New Approaches and Opportunities with Precision Agricultural Technologies. OSU Hermiston Agricultural Research and Extension Center Summer Visit, August 24, 2025, Hermiston, OR.

Seminars

Zhou, J. (2024). High-throughput plant phenotyping (HTPP) technologies towards improving crop breeding efficiency. OSU Crop and Soil Science Department Seminar Series, April 11, 2024, Corvallis, OR.

Zhou, J. (2024). Transfer learning in improving generalizability of deep neural networks. OSU SSMART Forestry Seminar, March 15, 2024, Corvallis, OR.

Zhou, J. (2024). Remote sensing approaches for assessing crop water stress. OSU Water Resources Seminar, January 31, 2024, Corvallis, OR.

Intellectual Property

Zhou, J., Anderson, N., Maliszewski, D., Chastain, T., Garrett, M., & Snell, L. (2025). A portable moisture sensing device for rapid determination of seed moisture content and seed harvest timing (US20260016404A1). Filed July 14, 2025; Published January 15, 2026.