Abstract：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.
Key words：Reflection spectra;Backward interval partial least squares;Genetic algorithm;Successive projections algorithm;Radial basis function neural network;Extreme learning machine
[1] Andrews M, Raven J A, Lea P J. Annals of Applied Biology, 2013, 163(2): 174. [2] Abdel-Rahman E M, Ahmed F B, van den Berg M. International Journal of Applied Earth Observation and Geoinformation, 2010, 12: S52. [3] Bell G E, Howell B M, Johnson G V, et al. HortScience, 2004, 39(5): 1130. [4] TIAN Yong-chao, ZHU Yan, YAO Xia, et al(田永超, 朱 艳, 姚 霞, 等). Chinese Journal of Ecology(生态学杂志), 2007, 26(9): 1454. [5] Miphokasap P, Honda K, Vaiphasa C, et al. Remote Sensing, 2012, 4(6): 1651. [6] Ulissi V, Antonucci F, Benincasa P, et al. Sensors, 2011, 11(6): 6411. [7] Bajwa S G, Mishra A R, Norman R J. Precision Agriculture, 2010, 11(5): 488. [8] GUO Zhi-ming, HUANG Wen-qian, PENG Yan-kun, et al(郭志明, 黄文倩, 彭彦昆, 等). Chinese Journal of Analytical Chemistry(分析化学), 2014, 42(4): 513. [9] ZHANG Xiao-dong, MAO Han-ping, NI Jun, et al(张晓东, 毛罕平, 倪 军, 等). Transactions of the Chinese Society for Agriculture Machinery(农业机械学报), 2009, 40(9): 164. [10] Galvao R K H, Ara jo M C U, Jose G E, et al. Talanta, 2005, 67: 736. [11] TAN Chao(谭 超). Transducer and Microsystem Technologes(传感器与微系统)，2007, 26(5): 57. [12] Leardi R, Lupiáez González A. Chemometrics and Intelligent Laboratory Systems, 1998, 41(2): 195. [13] Araujo M C U, Saldanha T C B, Galvao R K H , et al. Chemometrics and Intelligent Laboratory Systems, 2001, 57: 65. [14] Huang G B, Zhu Q Y, Siew C K. Neurocomputing, 2006, 70(1): 489. [15] Huang G B, Wang D H, Lan Y. International Journal of Machine Learning and Cybernetics, 2011, 2(2): 107.
