Neuro-fuzzy modeling to predict physicochemical and microbiological parameters of partially dried cherry tomato during storage: effects on water activity, temperature and storage time

文献类型： 外文期刊

第一作者： Tao, Yang

作者： Tao, Yang;Li, Yong;Zhou, Ruiyun;Su, Lijuan;Han, Yongbin;Dinh-Toi Chu;Dinh-Toi Chu;Zhou, Jianzhong

作者机构：

关键词： Cherry tomato;Partially dried;ANFIS;Lycopene;Phenolics;Microbiological analysis

期刊名称：JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE （ 影响因子：2.701； 五年影响因子：3.574 ）

ISSN：

年卷期：

页码：

收录情况： SCI

摘要： In the study, osmotically dehydrated cherry tomatoes were partially dried to water activity between 0.746 and 0.868, vacuum-packed and stored at 4-30 A degrees C for 60 days. Adaptive neuro-fuzzy inference system (ANFIS) was utilized to predict the physicochemical and microbiological parameters of these partially dried cherry tomatoes during storage. Satisfactory accuracies were obtained when ANFIS was used to predict the lycopene and total phenolic contents, color and microbial contamination. The coefficients of determination for all the ANFIS models were higher than 0.86 and showed better performance for prediction compared with models developed by response surface methodology. Through ANFIS modeling, the effects of storage conditions on the properties of partially dried cherry tomatoes were visualized. Generally, contents of lycopene and total phenolics decreased with the increase in water activity, temperature and storage time, while aerobic plate count and number of yeasts and molds increased at high water activities and temperatures. Overall, ANFIS approach can be used as an effective tool to study the quality decrease and microbial pollution of partially dried cherry tomatoes during storage, as well as identify the suitable preservation conditions.

分类号： TS2

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