For the purpose of optimizing near infrared spectroscopy model,and improving the prediction result,Genetic Algorithm (GA) was used to select wavelength variables of near infrared spectroscopy for fishmeal adulterated with meat and bone meal. 310 wavelengths are selted in genetic algorithm. By contrast with all wavelengths based partial least squares(PLS),GA based PLS reduced 80% of the wavelengths,and gained much better cross validation and prediction results. Related coefficient of cross-validation RCV was improved from 0.80 to 0.90,while the value of root mean square error of cross- validation (RMSECV) was reduced from 5.22% to 3.62%. The related coefficient of prediction RV was improved from 0.91 to 0.96,while the value of root mean square error of prediction (RMSEP) was reduced from 3.85% to 2.95%. GA improved the robustness and predictability of the model. It’s indicated that GA was an effective method for variable selection and could improve the prediction result of the meat and bone meal content in fishmeal by near infrared spectroscopy.