Internal Quality Prediction Method of Damaged Korla Fragrant Pears during Storage

To increase the commercial value of damaged fragrant pears and improve marketing competitiveness, this study explored degree damage effects storage time on internal quality during predicted using an adaptive neural fuzzy inference system (ANFIS). The prediction models with eight membership functions were constructed, optimal model was chosen, allowing for accurate pears. research results demonstrated that hardness soluble solid content (SSC) decrease as increases. Given same time, SSC are negatively correlated to damage. ANFIS modelling technique is feasible predicting storage. best performances pears, respectively, displayed by input function trimf (RMSE = 0.1362, R2 0.9752; RMSE 0.0315, 0.9892). findings can be used predict fruits.