Sierra Young

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. https://doi.org/10.1016/j.biosystemseng.2023.05.005

Nguyen, A. H., Holt, J. P., Knauer, M. T., Abner, V. A., Lobaton, E. J., & Young, S. N. (2023). Towards rapid weight assessment of finishing pigs using a handheld, mobile RGB-D camera. BIOSYSTEMS ENGINEERING, 226, 155–168. https://doi.org/10.1016/j.biosystemseng.2023.01.005

Kendler, S., Aharoni, R., Young, S., Sela, H., Kis-Papo, T., Fahima, T., & Fishbain, B. (2022). Detection of crop diseases using enhanced variability imagery data and convolutional neural networks. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 193. https://doi.org/10.1016/j.compag.2022.106732

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

Veazie, P., Pandey, P., Young, S., Ballance, M. S., Hicks, K., & Whipker, B. (2022). Impact of Macronutrient Fertility on Mineral Uptake and Growth of Lactuca sativa 'Salanova Green' in a Hydroponic System. HORTICULTURAE, 8(11). https://doi.org/10.3390/horticulturae8111075

Young, S., Lu, Y., Li, X., Li, X., Linder, E., & Suchoff, D. (2022, October 5). NAPPN Annual Conference Abstract: Hyperspectral imaging for non-destructive determination of cannabinoids in floral and leaf materials of industrial hemp. https://doi.org/10.22541/au.166497079.98875901/v1

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

Saia, S., Nelson, N., Young, S., Parham, S., & Vandegrift, M. (2022, January 31). Ten Simple Rules for Researchers Who Want to Develop Web Apps (Vol. 1). Vol. 1. https://doi.org/10.31223/X57P6R

Saia, S. M., Nelson, N. G., Young, S. N., Parham, S., & Vandegrift, M. (2022). Ten simple rules for researchers who want to develop web apps. PLOS COMPUTATIONAL BIOLOGY, 18(1). https://doi.org/10.1371/journal.pcbi.1009663

Linder, E. R., Young, S., Li, X., Inoa, S. H., & Suchoff, D. H. (2022). The Effect of Harvest Date on Temporal Cannabinoid and Biomass Production in the Floral Hemp (Cannabis sativa L.) Cultivars BaOx and Cherry Wine. HORTICULTURAE, 8(10). https://doi.org/10.3390/horticulturae8100959

Linder, E. R., Young, S., Li, X., Inoa, S. H., & Suchoff, D. H. (2022). The Effect of Transplant Date and Plant Spacing on Biomass Production for Floral Hemp (Cannabis sativa L.). AGRONOMY-BASEL, 12(8). https://doi.org/10.3390/agronomy12081856

Pandey, P., Narayan, H. D., & Young, S. N. (2021). FRONTIER: AUTONOMY IN DETECTION, ACTUATION, AND PLANNING FOR ROBOTIC WEEDING SYSTEMS. TRANSACTIONS OF THE ASABE, 64(2), 557–563. https://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.) SEEDLINGS FOR FREEZE TOLERANCE. TRANSACTIONS OF THE ASABE, 64(6), 2045–2059. https://doi.org/10.13031/trans.14708

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). https://doi.org/10.3390/rs13183595

Barnes, E., Morgan, G., Hake, K., Devine, J., Kurtz, R., Ibendahl, G., … Holt, G. (2021, June). Opportunities for Robotic Systems and Automation in Cotton Production. AGRIENGINEERING, Vol. 3, pp. 339–362. https://doi.org/10.3390/agriengineering3020023

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

Aharoni, R., Klymiuk, V., Sarusi, B., Young, S., Fahima, T., Fishbain, B., & Kendler, S. (2021). Spectral light-reflection data dimensionality reduction for timely detection of yellow rust. Precision Agriculture, 22(1), 267–286. https://doi.org/10.1007/s11119-020-09742-2

Young, S. N., Lanciloti, R. J., & Peschel, J. M. (2021, April 8). The Effects of Interface Views on Performing Aerial Telemanipulation Tasks Using Small UAVs. INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS, Vol. 4. https://doi.org/10.1007/s12369-021-00783-9

A process‐based approach to attribution of historical streamflow decline in a data‐scarce and human‐dominated watershed. (2020). Hydrological Processes. https://doi.org/10.1002/hyp.13707

Lu, Y., & Young, S. (2020). A survey of public datasets for computer vision tasks in precision agriculture. Computers and Electronics in Agriculture, 178, 105760. https://doi.org/10.1016/j.compag.2020.105760

Young, S. N., & Peschel, J. M. (2020). Review of Human–Machine Interfaces for Small Unmanned Systems With Robotic Manipulators. IEEE Transactions on Human-Machine Systems, 50(2), 131–143. https://doi.org/10.1109/THMS.2020.2969380

Young, S. N. (2019). A Framework for Evaluating Field-Based, High-Throughput Phenotyping Systems: A Meta-Analysis. SENSORS, 19(16). https://doi.org/10.3390/s19163582

Young, S. N., Kayacan, E., & Peschel, J. M. (2019). Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum. Precision Agriculture, 20(4), 697–722. https://doi.org/10.1007/s11119-018-9601-6

Young, S., Peschel, J., Penny, G., Thompson, S., & Srinivasan, V. (2017). Robot-Assisted Measurement for Hydrologic Understanding in Data Sparse Regions. Water, 9(7), 494. https://doi.org/10.3390/w9070494

Kayacan, E., Young, S. N., Peschel, J. M., & Chowdhary, G. High-precision control of tracked field robots in the presence of unknown traction coefficients. Journal of Field Robotics, 0(0). https://doi.org/10.1002/rob.21794