Education

• Ph.D. 2015, Agricultural and Biological Engineering, Purdue University
• M.S. 2011, Biological and Agricultural Engineering, North Carolina State University
• B.S. 2008, Bioenvironmental Systems Engineering, National Taiwan University

Certifications

  • Ph.D.

Funding

“Building Artificial Intelligence (AI)/Machine Learning Capacity for Digital Agriculture and Plant Phenotyping Technologies Research, Education, and Extension at Florida A&M University”.  USDA-CBG. 2024-2027. PI: Chen, J.; Co-PIs: Liang, W.-Z. (UNL lead), Qiao, X, and Jin, J. (Purdue). Amount: $750,000. UNL: $180,000.
 

“Partnership: Growing Precision Engineering Systems for Muscadine Grape Vineyard and Water Management”.  USDA-AFRI. 2023-2026. PI: Chen, J.; Co-PIs, Liang, W.-Z. (UNL lead), Qiao, X. Amount: $760,000. UNL: $372,333. 
 

 “Beginnings: Experiential Learning on Digital Agriculture and Plant Phenotyping Technologies (DAPPT)”. NSF-ExLENT. 2023-2026. PI: Chen, J.; Co-PIs: Liang, W.-Z. (UNL lead), Qiao, X., and Jin, J. (Purdue). Amount: $1,000,000, UNL: $272,597.

“Developing Education, Research, and Extension Training on Precision Agriculture Phenotyping Tool at HBCU”. Agricultural Genome to Phenome Initiative (AG2PI). 2022 – 2023. PI: Chen, J.; CO-PIs: Liang, W.-Z. (UNL), and Jin, J. (Purdue). Amount: $100,000. UNL: $20,000.

Selected Publications

Liang, W.-Z., Oboamah, J., Qiao, X., Ge, Y., Harveson, B., Heeren, D., Rudnick, D.R., Wang, J. (2023). CanopyCAM-an edge-computing sensing unit for continuous measurement of canopy cover percentage of dry edible beans. Computers and Electronics in Agriculture, 204:107498.

Liu, L, Qiao, X., Liang, W.-Z., Oboamah, J., Wang, J., Rudnick, D.R., Yang, H., Katimbo, A., and Shi, Y. (2023). An Edge-computing flow meter reading recognition algorithm optimized for agricultural IoT network, Smart Agricultural Technology, 5:100236.

Nakabuye, H. N., Rudnick, D. R., DeJonge, K. C., Ascough, K., Liang, W.-Z., Lo, T. H., Franz, T. E., Qiao, X., Katimbo, A., & Duan, J. (2023). Weather data-centric prediction of maize non-stressed canopy temperature in semi-arid climates for irrigation management. Irrigation Science. https://doi.org/10.1007/s00271-023-00863-w 

Katimbo, A., Rudnick, D.R., Zhang, J., Ge, Y., DeJonge, K.C., Franz, T.E., Shi, Y., Liang, W.-Z.,  Qiao, X., Heeren, D.M., Kabenge, I., Nakabuye, H., and Duan, J. (2023). Evaluation of artificial intelligence algorithms with sensor data assimilation in estimating crop evapotranspiration and crop water stress index for irrigation water management. Smart Agriculture Technology 4.

Katimbo, A., Rudnick, E.R., Liang, W.-Z., DeJonge, K.C., Lo, T.-Z., Franz, T.E., Ge, Y., Qiao, X., Kabenge, I., Nakabuye, H.N., Duan, J. (2022). Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions. Agricultural Water Management, 274:107972.

Liang, W.-Z., X. Qiao, I. Possignolo, K. DeJonge, S. Irmak, D. Heeren, and D. Rudnick. (2021). Utilizing digital image processing and two source energy balance model for the estimation of evapotranspiration of dry edible beans in western Nebraska. Irrigation Science. https://doi.org/10.1007/s00271-021-00721-7

Rudnick, D.R., M. Stockton, S. Taghvaeian, J. Warren, M.D. Dukes, A. Kremen, C.G. Henry, J. Aguilar, B. Ortiz, A. Andales, C.A. Burr, X. Qiao, W.-Z. Liang, S. Walthour, and S.H. Amosson. (2020). Innovative extension methods in the US to promote irrigation water management. Transaction of ASABE, 63(5): 1549-1558.

Liu, S, J.-Q. Ni, A.J. Heber, and W.-Z. Liang. (2019). Modeling of dynamic ammonia concentrations in two commercial layer hen houses. Environmental Informatics, 33(1):56-67.

Liang, W.-Z., K.R. Kirk, and J.K. Greene. (2018). Soybean leaf area, edge, and defoliation estimation using color image analysis. Computers and Electronics in Agriculture, 150:41-51.

Li, B., A.R. Pales, H.M. Clifford, S. Kupis, S. Hennessy, W.-Z. Liang, S. Moysey, B. Powell, K.T. Finneran, and C.J.G. Darnault. (2017). Preferential flow in the vadose zone and interface dynamics: impact of microbial exudates. Journal of Hydrology, 558:72-89.

Pales, A.R., B. Li, H.M. Clifford, S. Kupis, N. Edayilam, D. Montgometry, W.-Z. Liang, M. Dogan, N. Tharayil, N. Martinez, S. Moysey, B. Powell, and C.J.G. Darnault. (2017). Preferential flow systems amended with biogeochemical components: Imaging of a two-dimensional study. Hydrology and Earth System Sciences, 22:2487-2509.

Bai, L., C. Li, C. Korte, B.M.J. Huibers, A.R. Pales, L. Mu, W.-Z. Liang, D. Ladner, H. Daigle, and C.J.G. Darnult. (2017). Effects of silica-based nanofluids and surfactant on the interfacial befavior of light, medium, and heavy cuide oils at oil-aqueous interfaces. Applied Nanoscience, 7(8):947-972.

Li, B., W.-Z. Liang, L. Mu, W.C. Bridges, A.R. Jacobson, and C.J.G. Darnault. (2017). Influence of cerium oxide nanoparticles on the soil enzyme activities in a soil-grass microcosm system. Geoderma, 299:54-62.

Wang, K.-Y., Q.-F. Li, L. Wang-Li, E. Cortus, B.W. Bogan, I. Kilic, W.-Z. Liang, C.-H. Xiao, L.-L. Chai, J.-Q. Ni, , and A. J. Heber. (2016). National air emission monitoring study’s southeast layer site: part V. Hydrogen sulfide and volatile organic compounds. Transactions of ASABE, 59(2):681-693.

Liang, W.-Z., S.B. Shah, J.J. Classen, and R.R. Sharma-Shivappa. (2014). Drying temperature-duration impacts on moisture, carbon, and nitrogen losses from broiler litter. CIGR Journal, 16(4).

Liang, W.-Z., J.J. Classen, S.B. Shah, and R.R. Sharma-Shivappa. (2013). Ammonia fate and transport mechanisms in broiler litter. Water, Air, & Soil Pollution 225:1812.

Liang, W.-Z., S.B. Shah, J.J. Classen, and R.R. Sharma-Shivappa. (2013). Modeling ammonium adsorption on broiler litter and cake. Water, Air, & Soil Pollution 224:1405.

Professional Memberships:

• American Society of Agricultural and Biological Engineers