Construction of Color Prediction Model for Damaged Korla Pears during Storage Period

Abstract

In this work, to scientifically predict the color of damaged Korla fragrant pears during the storage period with lower economic loss and improved added value of the fragrant pears, eight pericarp color prediction models of damaged Korla fragrant pears during the storage period were established. These models had different membership functions, which were based on the adaptive neuro-fuzzy inference system (ANFIS). The optimal model was chosen and verified. Finally, the pericarp color of fragrant pears was accurately predicted through the degree of damage and storage time. According to the acquired test results, the pericarp brightness (L*) decreased, while both the red–green (a*) and yellow–blue (b*) values increased as the storage time prolonged. In addition, the pericarp color of the damaged fragrant pears during the storage period could be well predicted by using the ANFIS model. More specifically, the model with a membership function of trimf showed the optimal prediction effects of L*, a*, and b* (RMSE = 0.1089, R2 = 0.9773; RMSE = 0.5894, R2 = 0.9853; and RMSE = 0.2360, R2 = 0.9772). Our work provides valuable insights for the prediction of the quality of Korla fragrant pears during the storage period.