: Calibration and validation of regression model for non-destructive leaf area estimation of saffron (Crocus sativus L.)

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A modeling study with an artificial neural network: developing estimationmodels for the tomato plant leaf area (2016, unknown): “…RMSE = 4.71, MAE = 3.31, and MAPE = 0.08], and that the ANN method provided a better fit to the actual values; therefore, the ANN model can be used as an alternative method in estimating the leaf area. and Demirsoy, 2006; Peksen, 2007; Fallovo et al., 2008; Kumar, 2009; Demirsoy and Lang, 2010).”
A Simple, Cost-Effective Method for Leaf Area Estimation (2011, unknown): “[42]), saffron (Kumar [43]), ginger (Kandiannan et al.”
Allometric models for non-destructive leaf area estimation of Jatropha curcas (2012, background): “The use of simple linear measurement for predicting the LA of horticultural plants eliminates the need for costly leaf area meters [19,22,23].”
Modeling individual leaf area of rose (Rosa hybrida L.) based on leaf length and width measurement (2010, methodology): “…Gyves et al. 2007, Peksen 2007, Rivera et al. 2007, Rouphael et al. 2007, Antunes et al. 2008, Fallovo et al. 2008, Tsialtas et al. 2008, Kandiannan et al. 2009, Kumar 2009, Rouphael et al. 2010, in press) on nondestructive model development for predicting LA using simple linear measurements.”