Research Project: Aerial Application Technology for Sustainable Crop Production

Location: Aerial Application Technology Research

Publications (Clicking on the reprint icon will take you to the publication reprint.)

Review of agricultural spraying technologies for plant protection using unmanned aerial vehicle (UAV) - (Peer Reviewed Journal)
Chen, H., Fritz, B.K., Hoffmann, W.C., Lan, Y., Jingfu, Z. 2021. Review of agricultural spraying technologies for plant protection using unmanned aerial vehicle (UAV). International Journal of Precision Agricultural Aviation (IJPAA). 14(1):38-49. https://doi.org/10.25165/j.ijabe.20211401.5714.

Overview of spray nozzles for plant protection from manned aircrafts: Present research and prospective - (Peer Reviewed Journal)
Chen, H., Fritz, B.K., Lan, Y., Sheng, W., Jingfu, Z. 2020. Overview of spray nozzles for plant protection from manned aircrafts: Present research and prospective. International Journal of Precision Agricultural Aviation (IJPAA). 3(2):1-12. https://doi.org/10.33440/j.ijpaa.20200302.76.

Automatic classification of cotton root rot disease based on UAV remote sensing - (Peer Reviewed Journal)
Wang, T., Thomasson, J.A., Yang, C., Isakeit, T., Nichols, R.L. 2020. Automatic classification of cotton root rot disease based on UAV remote sensing. Remote Sensing. 12, 1310. https://doi.org/10.3390/rs12081310.

Segmenting purple rapeseed leaves in the field from UAV RGB imagery using deep learning as an auxiliary means for nitrogen stress detection - (Peer Reviewed Journal)
Zhang, J., Xie, T., Yang, C., Song, H., Jiang, Z., Zhou, G., Zhang, D., Feng, H., Xie, J. 2020. Segmenting purple rapeseed leaves in the field from UAV RGB imagery using deep learning as an auxiliary means for nitrogen stress detection. Remote Sensing. 12, 1403. https://doi.org/10.3390/rs12091403.

Measurement and analysis methods for determination of effective swath width from unmanned aerial systems - (Peer Reviewed Journal)
Fritz, B.K., Martin, D.E. 2020. Measurement and analysis methods for determination of effective swath width from unmanned aerial vehicles. In: Elsik, C.M., editor. Pesticide Formulation and Delivery Systems: 40th Volume, Formulation, Application and Adjuvant Innovation. West Conshohocken, PA: ASTM International. p. 62-85. https://doi.org/10.1520/STP162720190132.

Evaluation of a UAV-mounted consumer grade camera with different spectral modifications and two handheld spectral sensors for rapeseed growth monitoring: Performance and influencing factors - (Peer Reviewed Journal)
Zhang, J., Wang, C., Yang, C., Jiang, Z., Zhou, G., Wang, B., Shi, Y., Zhang, D., You, L., Xie, J. 2020. Evaluation of a UAV-mounted consumer grade camera with different spectral modifications and two handheld spectral sensors for rapeseed growth monitoring: Performance and influencing factors. Precision Agriculture. https://doi.org/10.1007/s11119-020-09710-w.

It's time to spray, is your system ready? - (Popular Publication)
Fritz, B.K. 2020. It's time to spray, is your system ready?. Agricultural Aviation. No. 2. pp. 54-57.

Identification of cotton fields using Sentinel-2 satellite imagery for boll weevil eradication - (Proceedings)
Yang, C., Suh, C.P. 2020. Identification of cotton fields using Sentinel-2 satellite imagery for boll weevil eradication. National Cotton Council Beltwide Cotton Conference. p. 128-133.

Particle drift potential of glyphosate plus 2,4 D choline pre-mixture formulation in a low-speed wind tunnel - (Peer Reviewed Journal)
Viera, B., Butts, T., Rodrigues, A., Schleier, J., Fritz, B.K., Kruger, G. 2020. Particle drift potential of glyphosate plus 2,4 D choline pre-mixture formulation in a low-speed wind tunnel. Weed Technology. https://doi.org/10.1017/wet.2020.15.

Integrating growth and environmental parameters to discriminate powdery mildew and aphid of winter wheat using bi-temporal Landsat-8 imagery - (Peer Reviewed Journal)
Ma, H., Huang, W., Jing, Y., Yang, C., Han, L., Dong, Y., Ye, H., Shi, Y., Zheng, Q., Liu, L., Ruan, C. 2019. Integrating growth and environmental parameters to discriminate powdery mildew and aphid of winter wheat using bi-temporal Landsat-8 imagery. Remote Sensing. 11:846. https://doi.org/10.3390/rs11070846.

Airborne remote sensing systems for precision agriculture - (Peer Reviewed Journal)
Yang, C. 2020. Airborne remote sensing systems for precision agriculture. Smart Agriculture. 2(1):1-22.

Effect of application height and ground speed on spray pattern and droplet spectra from remotely piloted aerial application systems - (Peer Reviewed Journal)
Martin, D.E., Woldt, W., Latheef, M.A., Kruger, G. 2019. Effect of application height and ground speed on spray pattern and droplet spectra from remotely piloted aerial application systems. Drones. 3:83. https://doi.org/10.3390/drones3040083.

How to set up your system to meet the label - (Popular Publication)
Fritz, B.K. 2019. How to set up your system to meet the label. Agricultural Aviation. pp. 53-59.

Western corn rootworm pyrethroid resistance confirmed by aerial application simulations of commercial insecticides - (Peer Reviewed Journal)
Souza, D., Vieira, B., Fritz, B.K., Hoffmann, W.C., Peterson, J., Kruger, G., Meinke, L. 2019. Western corn rootworm pyrethroid resistance confirmed by aerial application simulations of commercial insecticides. Scientific Reports. https://doi.org/10.1038/s41598-019-43202-w.

Remote sensing of woolly croton using manned and unmanned aerial imaging systems - A feasibility study - (Proceedings)
Yang, C., Suh, C.P., Eyster, R.S., Hong, J., Hamons, K. 2019. Remote sensing of woolly croton using manned and unmanned aerial imaging systems - A feasibility study. National Cotton Council Beltwide Cotton Conference. pp. 250.254.

Aerial remote sensing surveys of Fusarium wilt of cotton near El Paso, Texas - (Proceedings)
Yang, C., Isakeit, T., Nichols, R. 2019. Aerial remote sensing surveys of Fusarium wilt of cotton near El Paso, Texas. National Cotton Council Beltwide Cotton Conference. pp. 246-249.

Examining aerial application swath pattern evaluations under in-wind and cross-wind conditions - (Peer Reviewed Journal)
Fritz, B.K., Gill, M., Bretthauer, S. 2019. Examining aerial application swath pattern evaluations under in-wind and cross-wind conditions. Journal of ASTM International. https://doi.org/10.1520/STP161920180123.

UAAS test protocol and comparison of commercially available systems - (Other)
Martin, D.E., Woldt, W. 2019. UAAS test protocol and comparison of commercially available systems. World Wide Web. http://www.hse-uav.com/data-USDA-research-on-spraying-drones/

Modeling aerially applied sprays: An update to AGDISP model development - (Peer Reviewed Journal)
Teske, M., Thistle, H., Fritz, B.K. 2019. Modeling aerially applied sprays: An update to AGDISP model development. Transactions of the ASABE. 62(2):343-354. https://doi.org/10.13031/trans.13129.

A shadow-eliminated vegetation index (SEVI) for removal of self and cast shadow effects on vegetation in rugged terrains - (Peer Reviewed Journal)
Jiang, H., Wang, S., Cao, X., Yang, C., Zhang, Z., Wang, X. 2019. A shadow-eliminated vegetation index (SEVI) for removal of self and cast shadow effects on vegetation in rugged terrains. International Journal of Digital Earth. 12(9):1013-1029.

Rapeseed seedling stand counting and seeding performance evaluation at two early growth stages based on unmanned aerial vehicle imagery - (Peer Reviewed Journal)
Zhao, B., Zhang, J., Yang, C., Zhou, G., Ding, Y., Yeyin, S., Zhang, D., Xie, J., Liao, Q. 2018. Rapeseed seedling stand counting and seeding performance evaluation at two early growth stages based on unmanned aerial vehicle imagery. Frontiers in Plant Science. 9:1362. https://doi.org/10.3389/fpls.2018.01362.

Image dehazing based on dark channel prior and brightness enhancement for agricultural remote sensing images from consumer-grade cameras - (Peer Reviewed Journal)
Zhang, J., Wang, X., Yang, C., Jian, Z., He, D., Song, H. 2018. Image dehazing based on dark channel prior and brightness enhancement for agricultural remote sensing images from consumer-grade cameras. Computers and Electronics in Agriculture. 151:196-206. https://doi.org/10.1016/j.compag.2018.06.010.

An index of non-sampling error in area frame sampling based on remote sensing data - (Peer Reviewed Journal)
Wu, M., Peng, D., Qin, Y., Niu, Z., Yang, C., Li, W., Hao, P., Zhang, C. 2018. An index of non-sampling error in area frame sampling based on remote sensing data. PeerJ. 6:e5824. https://doi.org/10.7717/peerj.5824.