Yuzhen Lu

Lu, Y., Young, S., Linder, E., Whipker, B., & Suchoff, D. (2022). Hyperspectral Imaging With Machine Learning to Differentiate Cultivars, Growth Stages, Flowers, and Leaves of Industrial Hemp (Cannabis sativa L.). FRONTIERS IN PLANT SCIENCE, 12. https://doi.org/10.3389/fpls.2021.810113

Lu, Y., Li, X., Young, S., Li, X., Linder, E., & Suchoff, D. (2022). Hyperspectral imaging with chemometrics for non-destructive determination of cannabinoids in floral and leaf materials of industrial hemp (Cannabis sativa L.). COMPUTERS AND ELECTRONICS IN AGRICULTURE, 202. https://doi.org/10.1016/j.compag.2022.107387

Lu, Y., Young, S., Wang, H., & Wijewardane, N. (2022). Robust plant segmentation of color images based on image contrast optimization. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 193. https://doi.org/10.1016/j.compag.2022.106711

Lu, Y., Payn, K. G., Pandey, P., Acosta, J. J., Heine, A. J., Walker, T. D., & Young, S. (2021). HYPERSPECTRAL IMAGING WITH COST-SENSITIVE LEARNING FOR HIGH-THROUGHPUT SCREENING OF LOBLOLLY PINE (PINUS TAEDA L.) SEEDLINGS FOR FREEZE TOLERANCE. TRANSACTIONS OF THE ASABE, 64(6), 2045–2059. https://doi.org/10.13031/trans.14708

Lu, Y., Walker, T. D., Acosta, J. J., Young, S., Pandey, P., Heine, A. J., & Payn, K. G. (2021). Prediction of Freeze Damage and Minimum Winter Temperature of the Seed Source of Loblolly Pine Seedlings Using Hyperspectral Imaging. FOREST SCIENCE, 67(3), 321–334. https://doi.org/10.1093/forsci/fxab003

Zhang, Z., Igathinathane, C., Li, J., Cen, H., Lu, Y., & Flores, P. (2020). [Review of Technology progress in mechanical harvest of fresh market apples]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 175. https://doi.org/10.1016/j.compag.2020.105606