摘要：AbstractThe spectroscopy is one of the efficient methods used in crop monitor. In order to break through the limit of sensitive waveband instability at different growth stages, a full spectrum analysis method was applied in this study. Firstly, the winter wheat canopy reflectance were collected in the range of 325nm ~1075nm by ASD at the setting stage, jointing stage, booting stage and flowering stage respectively. And the corresponding chlorophyll contents were measured by spectrophotometric method. Secondly, the spectral data were pre-processed by wavelet de-noising and multiple scattering correction (MSC). Then, the principal component analysis (PCA) algorithm was used to reduce the dimension of spectra and the correlation coefficient analysis method was used to select the best principal component combinations at different growth stages. Finally, multiple regression models of chlorophyll content were established based on the selected principal component combinations at each growth stage. As a result, the decision coefficients (Rc2) for all the models were above 0.6, of which the maximum reached 0.8385 at the booting stage. The minimum of validation decision coefficient (Rv2) was only 0.4887 at the setting stage, while the maximum reached 0.9063 at the jointing stage. It could provide a technical support for the diagnosis of chlorophyll content during the winter wheat growth process.
