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Prediction of relationship between surface area, temperature, storage time and ascorbic acid retention of fresh-cut pineapple using adaptive neuro-fuzzy inference system (ANFIS)

journal contribution
posted on 2024-11-02, 00:03 authored by Zhengdong Jiang, Hong Zheng, Nitin MantriNitin Mantri, Zhechen Qi, Xiaodan Zhang, Zhuoni Hou, Jiadong Chang, Hongfei Lu, Zongsuo Liang
Adaptive neuro-fuzzy inference system (ANFIS) was developed for the prediction of ascorbic acid (AA) retention during storage of fresh-cut pineapple as a function of surface area, storage temperature and time. Our results demonstrate that surface area and temperature are the two most important factors influencing the degradation of AA in fresh-cut pineapple during storage. The AA in fresh-cut pineapple with a high surface area is more easily destroyed than that with a low surface area at the same storage temperature. In addition, the ANFIS model with triangular-shaped membership function (trimf) (RMSE=7.88%; R2=0.95) provides the best prediction accuracy than models with other membership functions (RMSE=8.97-10.19%; R2=0.91-0.93). Therefore, the high-surface-area fresh-cut fruit should be stored at a relatively low temperature as compared with the low-surface-area produce. The ANFIS model with trimf is an adequate model for the prediction of AA retention during storage of fresh-cut pineapple.

History

Journal

Postharvest Biology and Technology

Volume

113

Start page

1

End page

7

Total pages

7

Publisher

Elsevier

Place published

Netherlands

Language

English

Copyright

© 2015 Elsevier B.V. All rights reserved.

Former Identifier

2006059727

Esploro creation date

2020-06-22

Fedora creation date

2016-03-23

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