Wang Tianyi

Dr. Tianyi Wang studied and worked at China Agricultural University, Penn State University and Texas A&M University. In 2021, he was introduced by China Agricultural University as an outstanding talent to continue his research in agricultural engineering and smart agriculture. His main research direction is precision agriculture and smart agriculture, and he has obtained professional certification in remote sensing and GIS fields. In the past five years, he had completed 4 international projects as the first accomplisher, and participated in 1 major project of USDA as the backbone, with a total project fund of about 7.4 million US Dolloars. Four of the projects were cooperative projects of the United States Department of Agriculture (3 USDA-ARS projects and 1 USDA-APHIS projects). He has received an Outstanding Contribution Award from the US national Cotton Council for the practical problems he solves and the socio-economic value he provides in cotton production.

Associate Editor of Journal the Transactions of the ASABE 

Associate Editor of Journal Applied Engineering in Agriculture 

Youth Editorial Board of Smart Agriculture Journal 

ASABE Precision Agriculture (MS-54) Committee Member 

Senior member of Chinese Society of Agricultural Engineering 

Member of American Society of Agriculture and Bioengineering (ASABE) 

Member of International Society of Optical Engineering (SPIE) 

Independent reviewer of more than ten SCI academic journals

Precision agriculture 

Smart agriculture 

Agricultural mechanization

Book Chapter:

de Castro Megías, A.I., Pérez-Roncal, C., Thomasson, J.A., Ehsani, R., López-Maestresalas, A., Yang, C., Jarén, C., Wang, T., Cribben, C., Marin, D. and Isakeit, T., 2021. Applications of Sensing for Disease Detection. In Sensing Approaches for Precision Agriculture (pp. 369-398). Springer, Cham.

Article:

Wang, T., Chandra, A., Jung, J. and Chang, A., 2022. UAV remote sensing based estimation of green cover during turfgrass establishment. Computers and Electronics in Agriculture, 194, p.106721. (IF = 5.6)

Wang, T., Mei, X., Thomasson, J.A., Yang, C., Han, X., Yadav, P.K. and Shi, Y., 2022. GIS-based volunteer cotton habitat prediction and plant-level detection with UAV remote sensing. Computers and Electronics in Agriculture, 193, p.106629. (IF = 5.6)

Wang, T., Hardin IV, R.G., Ward, J.K., Wanjura, J.D. and Barnes, E.M., 2022. A smart cotton module tracking and monitoring system for handling logistics and cover damage. Computers and Electronics in Agriculture, 193, p.106620. (IF = 5.6)

Lee, H.S., Shin, B.S., Thomasson, J.A., Wang, T., Zhang, Z. and Han, X., 2022. Development of Multiple UAV Collaborative Driving Systems for Improving Field Phenotyping. Sensors, 22(4), p.1423. (IF = 3.6)

Wang, T.^*, Thomasson, J.A., Isakeit, T., Yang, C. and Nichols, R.L., 2020. A Plant-By-Plant Method to Identify and Treat Cotton Root Rot Based on UAV Remote Sensing. Remote Sensing, 12(15), p.2453. (IF = 4.8)

Wang, T.^*, Thomasson, J.A., Yang, C., Isakeit, T. and Nichols, R.L., 2020. Automatic Classification of Cotton Root Rot Disease Based on UAV Remote Sensing. Remote Sensing, 12(8), p.1310. (IF = 4.8)

Wang, T.^*, Thomasson, J.A., Yang, C., Isakeit, T., Nichols, R.L., Collett, R.M., Han, X. and Bagnall, C., 2020. Unmanned aerial vehicle remote sensing to delineate cotton root rot. Journal of Applied Remote Sensing, 14(3), p.034522. (IF = 1.5; Featured article)

Han, X., Thomasson, J.A., Swaminathan, V., Wang, T., Siegfried, J., Raman, R., Rajan, N. and Neely, H., 2020. Field-Based Calibration of Unmanned Aerial Vehicle Thermal Infrared Imagery with Temperature-Controlled References. Sensors, 20(24), p.7098. (IF = 3.6)

Wang, T. and Liu, J., 2017. Energy Consumption of Herbaceous Biomass Bulk Densification. Innov Ener Res, 6(175), pp.2576-1463. (IF = 1.4)

Wang, T., Chandra, A., Meeks, M. and Genovesi, D., 2021. UAV remote sensing-based phenotyping to evaluate drought stress in turfgrass. In 2021 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.

Wang, T. and Thomasson, J.A., 2021. BRDF effect in UAV remote sensing and empirical improvement methods: A case study of cotton root rot identification. In 2021 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.

Thomasson, J., Wang, T., Wang, X., Isakeit, T., Yang, C., Nichols, R. and Collett, R., 2021. High-precision fungicide application for cotton disease based on UAV remote sensing. In Precision agriculture’21 (pp. 849-858). Wageningen Academic Publishers.

Iqbal, Z., Hardin, R.G., Wang, T., Ward, J.K. and Wanjura, J.D., 2021, January. Round Modules: Handling Logistics and Cover Damage, 2nd Year. In Proceedings of the 2021 Beltwide Cotton Conference, Virtual Meeting (pp. 4-6).

Wang, T., Mei, X., Thomasson, J.A., Han, X. and Yadav, P.K., 2020. Volunteer Cotton Habitat Prediction Model and Detection with UAV Remote Sensing. In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers.

Wang, T. and Thomasson, J.A., 2019, May. Plant-by-plant level classifications of cotton root rot by UAV remote sensing. In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping IV (Vol. 11008, p. 110080N). International Society for Optics and Photonics.

Wang, T., Thomasson, J. A., Yang, C., & Isakeit, T. (2019). Field-region and plant-level classification of cotton root rot based on UAV remote sensing. In 2019 ASABE Annual International Meeting (p. 1). American Society of Agricultural and Biological Engineers.

Thomasson, J.A., Wang, T., Wang, X., Collett, R., Yang, C. and Nichols, R.L., 2018, May. Disease detection and mitigation in a cotton crop with UAV remote sensing. In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III (Vol. 10664, p. 106640L). International Society for Optics and Photonics.

Han, X., Thomasson, J.A., Wang, T. and Swaminathan, V., 2020. Autonomous mobile ground control point improves accuracy of agricultural remote sensing through collaboration with UAV. Inventions, 5(1), p.12.

Han, X., Thomasson, J.A., Wang, T. and Swaminathan, V., 2020, April. Autonomous mobile ground control point for accurate UAV remote sensing in agriculture (Conference Presentation). In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping V (Vol. 11414, p. 1141407). International Society for Optics and Photonics.

Wang, T. and Liu, J., 2014. Energy consumption of biomass bulk densification. In 2014 Montreal, Quebec Canada July 13–July 16, 2014 (p. 1). American Society of Agricultural and Biological Engineers.

Wang, T., Wang, G., Wang, D. and Liu, J., 2014. Investigation of the Densification Performance of Straw under Different Material Surface. In 2014 Montreal, Quebec Canada July 13–July 16, 2014 (p. 1). American Society of Agricultural and Biological Engineers.

Wang, T., Wang, G., Wang, D. and Tabil, L.G., 2012. Investigation of the Compression Characteristics of Leymus chinensis L. In 2012 Dallas, Texas, July 29-August 1, 2012 (p. 1). American Society of Agricultural and Biological Engineers.

The invention relates to a bio-shaped cutting tool for silage forage grass

US National Cotton Ginners-Peary Wilemon Award for Excellence in Cotton Gin-Related Studies