亚洲一区欧美在线,日韩欧美视频免费观看,色戒的三场床戏分别是在几段,欧美日韩国产在线人成

Obtaining chlorophyll content of crops rapidly is of great significance for timely diagnosing the health status of crops and guiding field management. In recent years, the development of unmanned aerial vehicle (UAV) has made it possible to quickly and accurately obtain information at the farm scale. The purpose was to estimate SPAD of summer maize based on UAV multispectral images, especially focusing on whether the hierarchical linear model with meteorological data had high accuracy. SPAD in the jointing stage, the tasseling stage and the filling stage were measured by SPAD-502Plus chlorophyll meter, and the multispectral images were captured by RedEdge mounted on DJI M600 Pro. Firstly, the vegetation indices of 21 experimental plots were extracted by band math and establishing the region of interest. Then, the correlation between the vegetation indices and SPAD was analyzed, and the vegetation indices with high correlation coefficient were selected as the input variables of SPAD estimation model. At last, the SPAD estimation models for the jointing stage, the tasseling stage, the filling stage and the whole growth stage were constructed by using partial least squares (PLS), random forest regression (RF) and hierarchical linear model (HLM), respectively. The results were compared to select the best model, which could provide support for SPAD estimation. It was found that except NRI, other vegetation indices (NDVI, OSAVI, GNDVI, RVI, MCARI, MSR, CIre) were significantly correlated with SPAD, furthermore, OSAVI and NDVI had strong and stable correlation with SPAD. The best model for each growth period was established by RF. For the jointing stage, the tasseling stage, the filling stage and the whole growth period, the R2 of the test set was 0.81, 0.81, 0.73 and 0.61, and the RMSE was 1.24, 2.32, 3.13 and 3.20, respectively. The HLM model, which coupled rainfall and maximum temperature with vegetation index, could improve the accuracy of linear model for estimating SPAD, but its accuracy was lower than that of RF. Therefore, the RF model based on UAV multispectral images could realize the estimation of SPAD of summer maize timely and accurately.