Eupatorium adenophorum has caused tremendous ecological and economic losses in China since the 1940s. Although a great deal of money has been expended on the prevention and control of the weed, the situation is still deteriorating. To identify its crucial environmental constraints, an ecological niche factor analysis was employed. The distribution of the weed was predicted by the maximum entropy model. The results indicate that the temperature in winter is more influential than that in other quarters of a year, and the maximum temperature in March restricts the spread of E. adenophorum most. Currently, the weed is mainly distributed in four provinces of southwest China. From the present to the 2080s, the center of L3, which has a potential distribution probability of 0.7 to 1.0, will move 53 km to the southwest. Accordingly, the area of L3 will expand by 16.04%. To prevent its further expansion, we suggest differentiating the prevention and control measures according to the potential distribution levels predicted. Meanwhile, the integration of various means of removal and comprehensive utilization of E. adenophorum is highly encouraged. Additionally, precautions should be taken in regions that have not yet, or have been only slightly, invaded by the E. adenophorum.
This paper illustrates how supply chain (SC) analytics could provide strategic and operational insights to evaluate the risk-based allocation of regulatory resources in food SCs, for management of food safety and adulteration risks. This paper leverages data on 89,970 tests of aquatic products extracted from a self-constructed data set of 2.6 million food safety tests conducted by the China Food and Drug Administration (CFDA) organizations. The integrated and structured data set is used to conduct innovative analysis that identifies the sources of adulteration risks in China’s food SCs and contrasts them with the current test resource allocations of the CFDA. The analysis highlights multiple strategic insights. Particularly, it suggests potential gaps in the current CFDA testing allocation by SC location, which is heavily focused on retail and supermarkets. Instead, the analysis indicates that high-risk parts of the SC, such as wholesale and wet markets, are undersampled. Additionally, the paper highlights the impact that SC analytics could have on policy-level operational decision making to regulate food SCs and manage food safety. The hope is that the paper will stimulate the interest of academics with expertise in these areas to conduct more work in this important application domain. This paper was accepted by Charles Corbett, operations management.
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