Estimation of Pennisetum alopecuroides crude protein content in the Jiangsu Dafeng David’s Deer Reserve using hyperspectral remote sensing technology

Crude protein (CP) is an important index for evaluating forage quality. Rapid determination of the crude protein content of forage grass may provide a scientific basis for monitoring forage quality using remote sensing. The canopy reflectance of the dominant species Pennisetum alopecuroides in the semi-captive area of the Jiangsu Dafeng David’s Deer Reserve was measuerd using a back-held Field Spec Pro FR2500 hyperspectrograph, and the crude protein content was determined. Pre-processed spectral reflectance and spectral indices correlating significantly with crude protein content were selected to establish the partial least squares regression (PLSR) and stepwise multiple linear regression (SMLR) models. The PLSR model based on significant bands showed excellent accuracy for predicting crude protein content (R² = 0.897, RMSE = 1.303, RPD = 3.11 in the validation set), whereas the SMLR model had the lowest degree of accuracy in the validation set (R² = 0.17, RMSE = 3.691, RPD = 1.098). The predictive ability was similar between PLSR and SMLR models based on significant spectral indices, with RPD reaching approximately 2. The PLSR model based on significant bands yielded the most accurate model, which can quantitatively predict the crude protein content of P. alopecuroides in a large area in the reserve.