[Measurement of Nitrogen Content in Lettuce Canopy Using Spectroscopy Combined with BiPLS-GA-SPA and ELM]

Nitrogen fertilizer is necessary to improve yield and quality of lettuce. Spectroscopy is one of the most effective techniques used to detect crop nitrogen content. In this study, canopy reflectance spectra were acquired under five levels of nitrogen, and then were Savitzky-Golay smoothed, the first-order derivative spectra were calculated from the smoothed spectra to eliminate noise effects. Backward interval partial least squares (BiPLS), genetic algorithm (GA) and successive projections algorithm (SPA) were combined to select the efficient wavelengths. The number of variables was decreased from 2,151 to 8. The optimal intervals or variables were used to build multivariable linear regression (MLR) model, radial basis function neural network (RBFNN) models and extreme learning machine (ELM) models. This work proved that the results of BiPLS-GA-SPA-ELM model was superior to others with RMSEC was 0.241 6%, Rc was 0.934 6, RMSEP was 0.284 2% and Rp was 0.921 8. Our research results may provide a foundation for nutrition regulation and developing instrument.