An improved ISM method based on GRA for hierarchical analyzing the influencing factors of food safety
Introduction
Food safety affects people's health, which has profound social significance. In recent years, food safety accidents have happened frequently all around the world (Chiou et al., 2015, Lam et al., 2013). The outbreak of toxic eggs in Europe in 2017 has been reported in nearly 20 countries and regions, including the Netherlands, Belgium and Germany (Liu, 2017). And a series of food safety incidents have happened in China, such as Sudan red (Liu, Hei, He, & Li, 2011), melamine (Xiu & Klein, 2010) and gutter oil (Lu & Wu, 2014). The accidents happened have hampered social stability and economic development. The national food unqualified situation report of 2012–2017 is issued by the China State Bureau of Technical Supervision as shown in Fig. 1, which shows that the number and proportion of unqualified food batches in China are on the rise from 2012 to 2017 with a small fluctuation. Hence, it is critical to find the major factors affecting food safety and food safety problems in advance.
By analyzing the influencing factors of food safety, the source control of major factors can be realized. Consider the grim situation of dairy food safety in China (Yan, 2012), a new interpretative structural modeling (ISM) method based on the grey rational analysis (GRA) (GRA-ISM) for hierarchical analyzing the influencing factor of food safety is proposed in this paper. Firstly, the correlation coefficient between influencing factors is calculated by the GRA, and the strength and weakness of the mutual relations between the factors is quantified simultaneously. Then the ISM is used to stratify the influencing factors of food safety, and the main influencing factors are obtained. Finally, the infant formula data and the sterilized milk data of food safety in China are hierarchical analyzed by the GRA-ISM. Though the Student's t-test (t-test), the validity of the threshold selection and the result of the GRA-ISM is verified. Meanwhile, the experimental results show that the GRA-ISM can analyze the factors affecting food safety better.
The organizational structure of this paper is as follows. The current research of the ISM method and the GRA are introduced in section2. Section 3 is the detailed description of the GRA-ISM method. Section 4 is the case study for hierarchical analyzing the influencing factors of the infant formula and the sterilized milk. Section 5 is the discussion of the experiment results and the proposed method. Finally, the conclusion is given in Section 6.
Section snippets
Relate work
Due to food safety incidents occur frequently, food safety research has become the focus of the global research (Perrot, Trelea, Baudrit, Trystram, & Bourgine, 2011). At present, the Artificial Neural Network (ANN) (Geng, Shang, Han, & Zhong, 2019) and the Bayesian Network (BN) (Greco, Landoni, Biondi-Zoccai, D'Ascenzo, & Zangrillo, 2016) are the most mature research methods on food safety. The ANN is an effective computing model and widely used in classification of food species (da Silva,
The grey relational analysis (GRA)
Correlation coefficient can measure the degree of linear correlation between two random factors (Puth, Neuhäuser, & Ruxton, 2014). Generally, the more consistent the change tendency of the two variables, the higher the degree of correlation between the two variables. On the contrary, the degree is low. The correlation coefficient matrix is established by using the GRA.
Let the reference sequence be = { (1), (2), …,()}, where is the number of samples, and the comparison sequence is
Case study: the influencing factors analysis of food safety
This paper analyzes the influencing factors of food safety. The used data is from a food inspection agency in a province in China. Firstly, the GRA is used to establish the correlation coefficient matrix of each factor. Then the ISM is used to stratify the influencing factors, and the multilevel hierarchical structure of the factors affecting the food safety is established. The inspection data of infant formula and sterilized milk are used in this paper.
Discussion
First, The GRA-ISM is proposed. The correlation coefficient matrix of the non-linear data is calculated by using the GRA. Then major factors affecting food safety can be found based on the ISM. By focusing on major factors, the proposed method can guide relevant departments to strengthen supervision and urge enterprises to work safely.
Second, this proposed method is used for effectively analyzing the major factors affecting the safety of infant formula and sterilized milk. The t-test is used to
Conclusion
The improved GRA-ISM method for hierarchical analyzing the influencing factor of food safety is proposed in this paper. Taking the inspection data of infant formula and sterilized milk as examples, the correlation coefficient matrix of the factors is calculated by using the GRA. And then the ISM method is used to stratify the influencing factors and establish the multi-hierarchical structure of the influencing factors of infant formula and sterilized milk. The t-test is used to verify the
Acknowledgement
This work is partly financial supported by National Key Research and Development Program of China (2017YFC1601800), National Natural Science Foundation of China (61673046 and 61374166), and Fundamental Research Funds for the Central Universities (XK1802-4).
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2021, EnergyCitation Excerpt :Grey relational analysis (GRA), on the other hand, has been used to address complex problems that contain incomplete information and the convoluted interrelationship between a given list of criteria [61]. It is one of the most widely used grey system theory [62], which has extended its utility to various fields such as the manufacturing industry [63], logistics companies [64], food security [65], etc. Recently, integration between TOPSIS and GRA (or GRA-based TOPSIS) have been proposed to overcome the accuracy issues on the approximation of the geometric relationship between a given solution to the respective PIS and NIS [38].