An Evaluation of Food Safety Performance in Wineries

Assessing wineries' performance in managing critical control points for arsenic, lead, and cadmium contamination risk in the wine-making industry: A survey-based analysis utilizing performance indicators as a results tool

Human health hazards appear in wine production. Wineries have implemented food safety management systems to control food hazards through Hazard Analysis Critical Control Point (HACCP). Wine-making industry applies HACCP by evaluating Critical Control Points (CCPs). One of the CCPs that exhibits inadequate control is the potential contamination risk of arsenic, cadmium, and lead throughout the winemaking procedure. Wineries performance level about controlling CCPs related to contamination risk by arsenic, cadmium and lead in the winemaking were analyzed. A sixteen-question questionnaire was made to achieve this research. Three indicators were calculated for training, legislation, and analysis performance components in CCPs control. Results revealed that wineries fault in analysis and legislation components. Identification and updating of legislation about As, Cd and Pb contamination risk is in starting performance level for wineries that produce less than 250,000 L/year wineries. Analysis performance level is even lower than legislation. Only one out of every three wineries possess information regarding the concentrations of arsenic, cadmium, and lead in the soils of vineyards where grapes are cultivated. Furthermore, the availability of data on their available concentrations in the soil solution is even more limited. Those wineries that controlled As, Cd and Pb concentrations make it according to official recommendations using techniques based on atomic absorption spectrometry. However, there is a lack of this spectrometry equipment in the wineries own laboratories.

Elemental Profile and Health Risk of Fruška Gora Wines

The elemental composition of wine is influenced by endogenous sources and interventions from winemakers. The ICP-MS analysis of Fruška Gora wines (113) from vintages spanning across a decade (2011-2020), produced by 30 wineries and representing 18 autochthonous and international wine varieties, allowed a comprehensive insight into their elemental composition. Based on the mean concentrations of 23 investigated elements, B, Fe, and Mn, which were determined in mg per L of wine regardless of its colour or origin, were the most abundant. Red and white wines showed significant concentration differences in the case of B, Mn, and Sr (higher in red) as well as Be, Al, V, As, Mo, and Pb (higher in white). The elements of the highest toxicological concern were found in all (Pb and As) or almost all of the samples (Cd and Hg). Pb levels (maximum 47.1, 61.6, and 73.2 μg/L in red, rose, and white, respectively) were well below the legal limit. The applied risk assessment approaches (hazard quotient and index, margin of exposure) revealed no health concerns associated with consumption of Fruška Gora wines, except for a slightly increased lifetime cancer risk in the case of high wine consumption, and thus supported the promotion of Fruška Gora wines in the highly competitive international market.

A Rice Hazards Risk Assessment Method for a Rice Processing Chain Based on a Multidimensional Trapezoidal Cloud Model

Rice is common in the human diet, making rice safety issues important. Moreover, rice processing safety is key for rice security, so rice processing chain risk assessment is critical. However, methods proposed to assess the rice processing chain risk have issues, such as the use of unreasonable thresholds for the rice processing chain and fixed weight. To solve these problems, we propose a risk assessment method for the rice processing chain based on a multidimensional trapezoidal cloud model. First, an evaluation model based on a multidimensional trapezoidal cloud model was established. Based on the historical evaluation results, Atanassov’s interval-valued intuition language numbers (AIVILNs) were introduced to determine the cloud model’s parameters. Second, the concept of dynamic weight was introduced to integrate the static and dynamic weights. An exponential function was used to construct dynamic weighting mechanisms, and the analytic hierarchy stage (AHP) was used to construct a static weight. The proposed method was validated by 104 sets of rice processing chain data, and the results show that the method could evaluate the risk level of the rice processing chain more accurately and reasonably than other methods, indicating that it can provide a sound decision-making basis for food safety supervision authorities.