［［Objective ］］ To improve the classification accuracy of edible vegetable oils,an identification model based on three -dimensional fluorescence spectroscopy and ISSA -SVM was established.［［Methods ］］ Combining the feature information of three -dimensional fluorescence spectroscopy,an improved sparrow search algorithm was used to optimize the parameters of the SVM model,constructing an edible vegetable oil identification method that integrates the characteristics of three -dimensional fluorescence spectroscopy information and the ISSA -SVM model.［［Results］］ Compared with the SVM model,GA -SVM model,PSO -SVM model,and SSA -SVM model,the classification accuracy of the ISSA -SVM model for edible vegetable oils reached 100%.［［Conclusion ］］ The ISSA -SVM model has higher convergence efficiency,system stability,and the ability to avoid local optimal solutions,which can effectively cope with complex and variable sample classification tasks.