Food safety risk intelligence early warning based on support vector machine

2020 ◽  
Vol 38 (6) ◽  
pp. 6957-6969
Author(s):  
Yu Zhang
Keyword(s):  
Support Vector Machine ◽  
Food Safety ◽  
Early Warning ◽  
Support Vector ◽  
Safety Risk ◽  
Risk Intelligence ◽  
Food Safety Risk

Research on the architecture of food safety risk intelligence early warning system

2021 ◽  
pp. 1-11
Author(s):  
Yu Zhang ◽  
Yarui Zhang ◽  
Xiaocui Li
Keyword(s):  
Decision Support ◽  
Food Safety ◽  
Early Warning ◽  
Early Warning System ◽  
System Development ◽  
Warning System ◽  
Risk Identification ◽  
Functional Modules ◽  
Safety Risk ◽  
Food Safety Risk

Food safety supervision involves all aspects of production, processing and sales. True, reliable and complete intelligence can realize the traceability of the entire process of food safety production, thereby ensuring that food safety incidents are controllable from the source. However, most studies only analyze the food safety risk identification and early warning from the perspective of information flow from the theoretical level, and lack specific applications at the practical level. Therefore, this study analyzes the system requirements and the overall business process of the system, expounds the goals and principles of system design, designs the overall framework of the system, and finally elaborates on the realization of its functions of the different functional modules of the system, so as to provide the early warning system development provides decision support and reference. Finally elaborates the realization of its functions according to the different functional modules of the system, so as to provide decision support and reference for the development of early warning system.

Early warning and control of food safety risk using an improved AHC-RBF neural network integrating AHP-EW

2021 ◽  
Vol 292 ◽  
pp. 110239 ◽  
Author(s):  
Zhiqiang Geng ◽  
Fenfen Liu ◽  
Dirui Shang ◽  
Yongming Han ◽  
Ying Shang ◽  
...  
Keyword(s):  
Neural Network ◽  
Food Safety ◽  
Early Warning ◽  
Rbf Neural Network ◽  
Safety Risk ◽  
Food Safety Risk ◽  
And Control

Risk early warning of food safety using novel long short-term memory neural network integrating sum product based analytic hierarchy process

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhiqiang Geng ◽  
Lingling Liang ◽  
Yongming Han ◽  
Guangcan Tao ◽  
Chong Chu
Keyword(s):  
Food Safety ◽  
Early Warning ◽  
Short Term Memory ◽  
Short Term ◽  
Analytic Hierarchy ◽  
Safety Risk ◽  
Content Type ◽  
Long Short Term Memory ◽  
Food Safety Risk ◽  
Hierarchy Process

PurposeFood safety risk brought by environmental pollution seriously threatens human health and affects national economic and social development. In particular, heavy metal pollution and nutrient deficiency have caused regional diseases. Thus, the purpose of this paper is to present a risk early warning method of food safety considering environmental and nutritional factors.Design/methodology/approachA novel risk early warning modelling method based on the long short-term memory (LSTM) neural network integrating sum product based analytic hierarchy process (AHP-SP) is proposed. The data fuzzification method is adopted to overcome the uncertainty of food safety detection data and the processed data are viewed as the input of the LSTM. The AHP-SP method is used to fuse the risk of detection data and the obtained risk values are viewed as the expected output of the LSTM. Finally, the proposed method is applied on one group of sterilized milk data from a food detection agency in China.FindingsThe experimental results show that compared with the back propagation and the radial basis function neural networks, the proposed method has higher accuracy in predicting the development trend of food safety risk. Moreover, the causal factors of the risk can be figured out through the predicted results.Originality/valueThe proposed modelling method can achieve accurate prediction and early warning of food safety risk, and provide decision-making basis for the relevant departments to formulate targeted risk prevention and control measures, thereby avoiding food safety incidents caused by environmental pollution or nutritional deficiency.

Comparing the Microbiological Status of Pre- and Postharvest Produce from Small Organic Production

2015 ◽  
Vol 78 (6) ◽  
pp. 1072-1080 ◽  
Author(s):  
AIXIA XU ◽  
DONNA M. PAHL ◽  
ROBERT L. BUCHANAN ◽  
SHIRLEY A. MICALLEF
Keyword(s):  
Food Safety ◽  
Organic Production ◽  
Wash Water ◽  
Small Scale ◽  
Organic Farms ◽  
Production Scale ◽  
Safety Risk ◽  
Leafy Greens ◽  
Postharvest Handling ◽  
Food Safety Risk

Consumption of locally, organically grown produce is increasing in popularity. Organic farms typically produce on a small scale, have limited resources, and adopt low technology harvest and postharvest handling practices. Data on the food safety risk associated with hand harvesting, field packing, and packing-house handling with minimal treatment, at this production scale, are lacking. We followed produce from small organic farms from the field through postharvest handling and packing. Pre- and postharvest produce (177 samples) and water (29 samples) were collected and analyzed quantitatively for Escherichia coli, total coliforms (TC), aerobic bacteria (APC), yeasts, molds (M), and enteric pathogens. No pathogens were recovered. E. coli was detected in 3 (3.6%) of 83 preharvest produce samples, 2 (6.3%) of 32 unwashed and 0 of 42 washed postharvest produce samples, and 10 (34.5%) of 29 water samples. No correlation was found between bacterial levels in irrigation water and those on produce. Postharvest handling without washing was a factor for APC and M counts on tomatoes, with lower frequencies postharvest. Postharvest handling with washing was a factor for leafy greens for TC counts, with higher frequencies postharvest. APC (P = 0.03) and yeast (P = 0.05) counts were higher in preharvest than in unwashed postharvest tomatoes. Washed postharvest leafy greens had higher M counts (P = 0.03) and other washed produce had higher TC counts (P = 0.01) than did their preharvest counterparts. Barriers were found to the use of sanitizer in wash water for leafy greens among small farms using organic practices. Hand harvesting and dry handling did not appear to be associated with a significant food safety risk, but washed leafy greens carried higher levels of some microbial indicators, possibly because of the lack of sanitizer in the wash water. The development of resources and materials customized for this sector of growers could enhance dissemination of information on best practices for handling of leafy greens.

Microbiological Safety of Commercial Prime Rib Preparation Methods: Thermal Inactivation of Salmonella in Mechanically Tenderized Rib Eye†

2015 ◽  
Vol 78 (12) ◽  
pp. 2126-2135 ◽  
Author(s):  
ALEXANDRA CALLE ◽  
ANNA C. S. PORTO-FETT ◽  
BRADLEY A. SHOYER ◽  
JOHN B. LUCHANSKY ◽  
HARSHAVARDHAN THIPPAREDDI
Keyword(s):  
Food Safety ◽  
Low Temperatures ◽  
Thermal Inactivation ◽  
Medium Size ◽  
Preparation Methods ◽  
Safety Risk ◽  
Microbiological Safety ◽  
Pathogen Populations ◽  
Food Safety Risk ◽  
Midwestern City

Boneless beef rib eye roasts were surface inoculated on the fat side with ca. 5.7 log CFU/g of a five-strain cocktail of Salmonella for subsequent searing, cooking, and warm holding using preparation methods practiced by restaurants surveyed in a medium-size Midwestern city. A portion of the inoculated roasts was then passed once through a mechanical blade tenderizer. For both intact and nonintact roasts, searing for 15 min at 260°C resulted in reductions in Salmonella populations of ca. 0.3 to 1.3 log CFU/g. For intact (nontenderized) rib eye roasts, cooking to internal temperatures of 37.8 or 48.9°C resulted in additional reductions of ca. 3.4 log CFU/g. For tenderized (nonintact) rib eye roasts, cooking to internal temperatures of 37.8 or 48.9°C resulted in additional reductions of ca. 3.1 or 3.4 log CFU/g, respectively. Pathogen populations remained relatively unchanged for intact roasts cooked to 37.8 or 48.9°C and for nonintact roasts cooked to 48.9°C when held at 60.0°C for up to 8 h. In contrast, pathogen populations increased ca. 2.0 log CFU/g in nonintact rib eye cooked to 37.8°C when held at 60.0°C for 8 h. Thus, cooking at low temperatures and extended holding at relatively low temperatures as evaluated herein may pose a food safety risk to consumers in terms of inadequate lethality and/or subsequent outgrowth of Salmonella, especially if nonintact rib eye is used in the preparation of prime rib, if on occasion appreciable populations of Salmonella are present in or on the meat, and/or if the meat is not cooked adequately throughout.

Salmonella enterica in Superficial Cervical (Prescapular) and Ileocecal Lymph Nodes of Slaughtered Pigs

2006 ◽  
Vol 69 (4) ◽  
pp. 925-927 ◽  
Author(s):  
PETER B. BAHNSON ◽  
CLAUDIA SNYDER ◽  
LATIFA M. OMRAN
Keyword(s):  
Food Safety ◽  
Confidence Interval ◽  
Lymph Nodes ◽  
Salmonella Enterica ◽  
Food Products ◽  
Safety Risk ◽  
Bacterial Cultures ◽  
Limited Food ◽  
Food Safety Risk ◽  
Slaughtered Pigs

Because certain lymph nodes may be incorporated in food products, the presence of Salmonella enterica in these tissues could pose a food safety risk. We designed this two-part study to assess the prevalence of Salmonella in prescapular lymph nodes from normal slaughtered swine. Prescapular lymph nodes were collected from 300 systematically selected pigs in study 1 and, in study 2, from 75 pigs distributed among 10 herds. For study 2, pooled bacterial cultures were also completed on ileocecal lymph nodes, combining tissue from five pigs per pool (n = 60 pools). No Salmonella was detected in study 1 among prescapular lymph nodes (95% confidence interval, 0.0 to 1.16%). Salmonella was not detected in 75 prescapular lymph nodes from study 2, although Salmonella was detected in 5 of 10 herds in ileocecal lymph nodes. We conclude that prescapular lymph nodes posed a limited food safety risk in this population of pigs.

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