Journals

Pandey, P., Veazie, P., Whipker, B., & Young, S. (2023). Predicting Foliar Nutrient Concentrations and Nutrient Deficiencies of Hydroponic Lettuce Using Hyperspectral Imaging. Biosystems Engineering, 230, 458-469. doi.org/10.3390/rs13183595.

Pandey, P., Payn, K.G., Lu, Y., Heine, A.J., Walker, T.D., Acosta, J.J., & Young, S. (2021). Hyperspectral Imaging Combined with Machine Learning for the Detection of Fusiform Rust Disease Incidence in Loblolly Pine Seedlings. Remote Sensing.; 13(18):3595. doi.org/10.3390/rs13183595.

Pandey, P., Dakshinamurthy, H. N., & Young, S. N. (2021). Frontier: Autonomy in Detection, Actuation, and Planning for Robotic Weeding Systems. Transactions of the ASABE, 64(2), 557-563. doi. org/10.13031/trans.14085.

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.) Seedling for Freeze Tolerance. Transactions of the ASABE, 64(6), 2045-2059. 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. doi.org/10.1093/forsci/fxab003.

Liang, Z., Pandey, P., Stoerger, V., Xu, Y., Qiu, Y., Ge, Y., & Schnable, J. C. (2018). Conventional and hyperspectral time-series imaging of maize lines widely used in field trials. Gigascience, 7(2), gix117. doi.org/10.1093/gigascience/gix117.

Pandey, P., Ge, Y., Stoerger, V., & Schnable, J. C. (2017). High throughput in vivo analysis of plant leaf chemical properties using hyperspectral imaging. Frontiers in plant science, 8, 1348. doi.org/10.3389/fpls.2017.01348.

Conferences

Pandey, P., Acosta, J. J., Payn, K. G., & Young, S. N. (2022). Towards Aerial Robotic Pollination for Controlled Crosses in Pinus taeda. In 2022 ASABE Annual International Meeting (p. 1). American Society of Agricultural and Biological Engineers. doi.org/10.13031/aim.202200677.

Pandey, P., Payn, K. G., Lu, Y., Heine, A. J., Walker, T. D., & Young, S. (2020). High Throughput Phenotyping for Fusiform Rust Disease Resistance in Loblolly Pine Using Hyperspectral Imaging. In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers. doi.org/10.13031/aim.202000872.

Lu, Y., Payn, K. G.,Pandey, P., Acosta, J. J., Heine, A. J., Walker, T. D., & Young, S. (2020). Hyperspectral Imaging-Enabled High-Throughput Screening of Loblolly Pine (Pinus taeda) Seedlings for Freeze Tolerance. In 2020 ASABE Annual International Virtual Meeting (p. 1). American Society of Agricultural and Biological Engineers. doi.org/10.13031/aim.202001072.

Ge, Y., Pandey, P., & Bai, G. (2016). . Estimating Fresh Biomass of Maize Plants from their RGB Images in Greenhouse Phenotyping.In Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping (Vol. 9866, p. 986605).International Society for Optics and Photonics. SPIE Digital Library. doi.org/10.1117/12.2228790.