Abstract: In the field,hyperspectral data and fresh yields in different growth periods of 10 alfalfa (Medicago sativa) varieties were collected and then the reflectance,first derivative spectrum and spectral absorption feature parameters were used as independent variables,to build univariate regression models for estimating the fresh yield of alfalfa. The nonlinear regression equation models,such as quadratic,cubic,compound,power and exponential were better than linear models. Among the spectral parameters of the same type,the parameters which had high coefficient of determinations of the linear model,always had higher coefficients of determination of quadratic,cubic,compound,power and exponential models. Among these estimation models,the compound and exponential estimation models based on the first derivative value at wavelength 747 nm was the most accurate for estimating the fresh yield of alfalfa; The correlation coefficient (r) was 0.852,the root mean square error (RMSE) was 0.466 kg/m²,and the relative error (RE) was 21.14%. The models can be used to estimate the fresh yield of the 10 alfalfa varieties.