Estimation of Nitrogen Contents in Rice Plant at the Panicle Initiation Stage Using Ground-Based Hyperspectral Remote Sensing

Abstract

In this study, ground-based hyperspectral remote sensing was used for estimating the nitrogen content of rice plants (Kinu-hikari) at the panicle initiation stage. The resulting images were separated into two parts: (1) the rice plant and (2) others (irrigation water, soil background) using the equation of “GreenNDVI-NDVI„. RRICE was calculated as the ratio of the reflectance for the rice plant to that for the reference board. Partial least square regression models were constructed based on the association between the reflectance of the rice plant and its nitrogen content. The precision and accuracy of the 2007 model was evaluated using the full-cross validation method, as the following results: R2 = 0.846, RMSEP = 1.244 g/m2, and REP = 19.9%. The precision and accuracy of the 2008 model was evaluated as the following results: R2 = 0.846, RMSEP = 1.049 g/m2, and REP = 20.2%. The 2007 model predicted RMSEP and REP values as 1.244 g/m2 and 24.0%, respectively, for the 2008 data. Similarly, the 2008 model predicted RMSEP and REP values as 1.694 g/m2 and 27.1%, respectively, for the 2007 data. Because of similarities in the regression coefficients of both models, in terms of precision, no considerable differences between validation and prediction results were observed. The following results were determined when precision and accuracy were estimated using full-cross validation based on two years’ data: R2 = 0.867, RMSEP = 1.084 g/m2, and REP = 18.9%.