Shelf-life Prediction of Chilled Penaeus vannamei Using Grey Relational Analysis and Support Vector Regression

Abstract

ABSTRACT There are some major difficulties when predicting shelf life of chilled Penaeus vannamei in practice, such as numerous prediction indexes, complicated index measurement methods, and low prediction accuracy. In order to overcome these complications, the Grey Relational Analysis (GRA) was first employed to determine the correlation degree between the quality indexes of chilled Penaeus vannamei and the remaining shelf life. The results have revealed that sensory score and pH value are the two most highly relevant quality indicators of the remaining shelf life of chilled Penaeus vannamei, with the relational degree of 0.8567 and 0.8285, respectively. The sensory score, pH value, and the critical environmental index – temperature were selected as the input parameters of Support Vector Regression (SVR) prediction model. The experimental results showed that the prediction accuracy of SVR prediction model based on GRA is 95.66%, which is similar to that of the SVR model based on all indexes (95.5%) and higher than that of the traditional dynamic model (90.08%). By reducing the dimensions of the prediction indexes, simplifying the measurement methods of indexes, and ensuring relatively high prediction accuracy, the SVR shelf-life prediction model for chilled Penaeus vannamei based on GRA is more feasible for practical use.