Prediction method for nutritional quality of Korla pear during storage

Abstract

It is difficult to control the quality of Korla pear with different degrees of maturity during storage. Here, a method was proposed for predicting the effects of harvest maturity and cold storage time on the quality indices (soluble solid content (SSC) and Vitamin C (Vc) content) of Korla pear. The generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) were employed to predict the quality changes of Korla fragrant pear fruit during storage. The results demonstrated that during cold storage the SSC in pears with 10%-70% harvest maturity showed continuous increases in the first 90 d of storage and then a slight decline thereafter, while that in pears with 80% and 90% harvest maturity exhibited slow decreases throughout the storage process. With the extension of storage time, the Vc content of pears with 10%-90% harvest maturity showed continuous decreases. The harvest maturity of Korla pear was extremely positively correlated with SSC and Vc content (p < 0.01) in a given storage period. Storage time showed an extremely significant negative correlation with the Vc content (p < 0.01) at the 40%-90% harvest maturity and an significant negative correlation with the Vc content (p < 0.05) at the 10%-30% harvest maturity. At the 10%-70% harvest maturity, storage time showed a significant positive correlation with the SSC (p < 0.05). The trained model could well predict the variation trend of quality indices of pear fruit during storage. The ANFIS with the input membership function of gbellmf had the best performance in predicting the SSC (RMSE=0.175; R2=0.98), and that with the input membership function of trimf exhibited the best performance in predicting Vc content (RMSE=0.075; R2 =0.99). The research findings can provide reference for predicting the fruit nutritional quality at delivery and decision-making on the storage time of Korla fragrant pear. Keywords: Korla fragrant pear, harvest maturity, storage time, nutritional quality, prediction method DOI: 10.25165/j.ijabe.20211403.5990 Citation: Liu Y, Zhang Q, Niu H, Zhang H, Lan H P, Zeng Y, et al. Prediction method for nutritional quality of Korla pear during storage. Int J Agric & Biol Eng, 2021; 14(3): 247–254.