# Design of Safety Evaluation and Risk Traceability System for Agricultural Product Quality
## 2 Design of Agricultural Product Quality and Safety Evaluation System
### Construction of Evaluation Model  
In the process of constructing the evaluation model, the standard deviation statistical method was used to conduct a statistical analysis of the obtained agricultural product sample testing data. The sample information and statistical results obtained are shown in Table 3. Using the CRITIC method [20] to solve the correlation between the average value and standard deviation of the obtained sample data, the coefficients of the fitting indicators were further optimized through the comprehensive expert survey method. Due to the close relationship between indicators of the designed risk assessment system within the same main category, while the relationship between indicators of different main categories is not closely related, the commonly used addition and multiplication mixed method is used to construct the model [21]. \begin{table}
\begin{tabular}{c c c} \hline
The sources of heavy metals in agricultural products are mainly their absorption of heavy metals in soil and in the environment or inputs except soil. Through multi-factor nonlinear response analysis, the response model of quality and safety risk assessment can be simplified as the following Equation (1) after the coefficient is eliminated:  
\[EM=Acs\times Ac+Os \tag{1}\]  
In Equation (1): \(EM\): score value of agricultural product quality and safety risk assessment; \(Acs\): available content of heavy metals in soil; \(Ac\): absorption coefficient of heavy metals in crops; \(Os\): heavy metal content from other sources. In this paper, the method of assigning points is used to optimize the fitting of the model. The total content of heavy metals in soil was an important factor affecting the existence of heavy metals in soil, while the available state coefficient of heavy metals in soil was a state factor affecting the existence of heavy metals in soil, mainly including soil pH value, soil organic matter content, and soil redox potential. After the principal component linear analysis equation and Bayesian classification, the weight coefficients of the total content of soil heavy metals, soil pH, soil organic matter, and soil redox potential were obtained by the expert scoring method. After the standardization coefficient, Equation (2) of the risk assessment model was obtained as follows:  
\[Acs=a\times(5b+3c+2d) \tag{2}\]  
In Equation (2): \(a\): total content of heavy metals in soil; \(b\): risk level of soil pH; \(c\): risk level of soil organic matter; and \(d\): risk level of soil redox potential. When the content of heavy metals in soil exceeds the standard, the effective content score of heavy metals in soil will exceed the warning score of 60 points under the condition that the influencing factors of the effective coefficient of heavy metals in soil have great effects. The absorption coefficient of heavy metals by crops is closely related to crop varieties, cultivation, and irrigation methods. After the same scoring and regression analysis, the weight coefficients of crop varieties, crop nutrition, and crop cultivation measures were obtained by the expert scoring method. The final risk assessment model Equation (3) is as follows:  
\[Ac=0.6e+0.2f+0.2g \tag{3}\]  
In Equation (3): \(e\): risk level of crop varieties; \(f\): risk level of crop nutritional status; \(g\): risk level of crop cultivation measures. According to Equation (3) and the scoring analysis, the maximum absorption coefficient score is four and the minimum is one, which means that under normal circumstances, only when there is a risk warning of heavy metals in the external environment can the heavy metals in agricultural products exceed the standard. If the absorption coefficient of crops increases due to their own varieties, nutritional status, or improper farming, the heavy metals in the environment may also exceed the standard. Through a literature review and sample detection, four secondary indicators of heavy metals from other sources were set: heavy metal content in pesticides, heavy metal content