Predicting partition coefficients of migrants in food simulant/polymer systems using Adaptive Neuro-Fuzzy Inference System

Food contaminations by migration of low molecular weight additives into foodstuffs can be resulted of direct contact between packaging materials and food. The amount of migration is related to the structural properties of the additive as well as to the nature of packaging material. The goal of this study is development of a quantitative structure- roperty relationship (QSPR) model by the adaptive neuro-fuzzy inference system (ANFIS) for prediction of the partition coefficient in food/packaging system. The partition coefficients of a set of 44 various systems consisted of 4 food simulants, 6 migrants and 2 packaging materials were investigated. A set of 6 molecular descriptors representing various structural characteristics of food simulants, migrants and polymers was used as data set. ANFIS as a new modeling technique was applied for the first time in this filed. The resulted model had a correlation coefficient (R2) of 0.9920 for the prediction set.

کلیدواژه ها:

Quantitative Structure-Property Relationship (QSPR) ، Adaptive Neuro-Fuzzy Inference System (ANFIS) ، Partition Coefficients ، Migration