Cite
Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data.
MLA
Smith, Chaya, et al. “Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data.” Remote Sensing, vol. 12, no. 6, Mar. 2020, p. 928. EBSCOhost, https://doi.org/10.3390/rs12060928.
APA
Smith, C., Karunaratne, S., Badenhorst, P., Cogan, N., Spangenberg, G., & Smith, K. (2020). Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data. Remote Sensing, 12(6), 928. https://doi.org/10.3390/rs12060928
Chicago
Smith, Chaya, Senani Karunaratne, Pieter Badenhorst, Noel Cogan, German Spangenberg, and Kevin Smith. 2020. “Machine Learning Algorithms to Predict Forage Nutritive Value of In Situ Perennial Ryegrass Plants Using Hyperspectral Canopy Reflectance Data.” Remote Sensing 12 (6): 928. doi:10.3390/rs12060928.