Kross, A.;                     Znoj, E.;                     Callegari, D.;                     Kaur, G.;                     Sunohara, M.;                     Lapen, D.R.;                     McNairn, H.    
        Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields. Remote Sens. 2020, 12, 2230.
    https://doi.org/10.3390/rs12142230
    AMA Style
    
                                Kross A,                                 Znoj E,                                 Callegari D,                                 Kaur G,                                 Sunohara M,                                 Lapen DR,                                 McNairn H.        
                Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields. Remote Sensing. 2020; 12(14):2230.
        https://doi.org/10.3390/rs12142230
    
    Chicago/Turabian Style
    
                                Kross, Angela,                                 Evelyn Znoj,                                 Daihany Callegari,                                 Gurpreet Kaur,                                 Mark Sunohara,                                 David R. Lapen,                                 and Heather McNairn.        
                2020. "Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields" Remote Sensing 12, no. 14: 2230.
        https://doi.org/10.3390/rs12142230
    
    APA Style
    
                                Kross, A.,                                 Znoj, E.,                                 Callegari, D.,                                 Kaur, G.,                                 Sunohara, M.,                                 Lapen, D. R.,                                 & McNairn, H.        
        
        (2020). Using Artificial Neural Networks and Remotely Sensed Data to Evaluate the Relative Importance of Variables for Prediction of Within-Field Corn and Soybean Yields. Remote Sensing, 12(14), 2230.
        https://doi.org/10.3390/rs12142230