The Application of CPLD and ARM in Food Safety Testing Data Fusion

The Center for Disease Control estimates 128,000 people in the U.S. are hospitalized annually due to food borne illnesses. This has created a demand for food safety testing targeting the detection of pathogenic mold and bacteria on agricultural products. This risk extends to medicalCannabisand is of particular concern with inhaled, vaporized and even concentratedCannabisproducts.As a result, third party microbial testing has become a regulatory requirement in the medical and recreationalCannabismarkets, yet knowledge of theCannabismicrobiome is limited. Here we describe the first next generation sequencing survey of the fungal communities found in dispensary basedCannabisflowers by ITS2 sequencing, and demonstrate the sensitive detection of several toxigenicPenicilliumandAspergillusspecies, includingP. citrinum and P. paxilli,that were not detected by one or more culture-based methods currently in use for safety testing.

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Culture-independent Sequence-based Approaches for Diagnostics and Food Safety Testing

Pathogenic Escherichia coli: Evolution, Omics, Detection and Control ◽

10.21775/9781910190777.10 ◽

2018 ◽

Author(s):

Susan R. Leonard ◽

Christopher A. Elkins

Keyword(s):

Food Safety ◽

Independent Sequence ◽

Safety Testing ◽

Culture Independent

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Study on microbial detection technology in food safety

E3S Web of Conferences ◽

10.1051/e3sconf/202123302029 ◽

2021 ◽

Vol 233 ◽

pp. 02029

Author(s):

Xindi Zhang

Keyword(s):

Food Safety ◽

Rapid Development ◽

Enzyme Linked Immunosorbent Assay ◽

Safety Testing ◽

Microbial Detection ◽

Detection Technology ◽

Atp Bioluminescence ◽

Quality Of Food

Economic development has not only led to the steady development of the gross national economy, but also provided a fundamental guarantee for the life of the residents at this stage. However, with the rapid development of economy, people’s attention to hidden safety problems has gradually shifted from big problems to “small details” of food safety. At the same time, in order to reduce the health problems of consumers in the process of eating products, we should start from the source of food, and use microbial technology in the current food safety testing, so as to fundamentally improve the quality of food safety. At present, PCR, impedance, ATP bioluminescence, lamp and enzyme-linked immunosorbent assay are widely used. In this paper, the role of microbial detection technology was described, and the application of microbial detection technology in food safety detection was analyzed in depth, hoping to provide a reference for ensuring food safety through the promotion of microbial detection technology.

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Regional Food Safety Testing Risk Analysis and Early Warning Research

Lecture Notes in Electrical Engineering - Innovative Computing ◽

10.1007/978-981-15-5959-4_139 ◽

2020 ◽

pp. 1135-1142

Author(s):

Guiling Li ◽

Xiaomin Shang ◽

Qiong Liu

Keyword(s):

Food Safety ◽

Risk Analysis ◽

Early Warning ◽

Safety Testing ◽

Regional Food

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Public health impact of foodborne exposure to naturally occurring virulence-attenuated Listeria monocytogenes: inference from mouse and mathematical models

Interface Focus ◽

10.1098/rsfs.2019.0046 ◽

2019 ◽

Vol 10 (1) ◽

pp. 20190046 ◽

Cited By ~ 2

Author(s):

Alison Stout ◽

Anna Van Stelten-Carlson ◽

Hélène Marquis ◽

Michael Ballou ◽

Brian Reilly ◽

...

Keyword(s):

Public Health ◽

Listeria Monocytogenes ◽

Food Safety ◽

Protective Immunity ◽

Health Benefit ◽

Intestinal Barrier ◽

Population Level ◽

T Cell Response ◽

Infection Model ◽

Safety Testing

Listeriosis is a clinically severe foodborne disease caused by Listeria monocytogenes (Lm). However, approximately 45% of Lm isolates in food carry a virulence-attenuating single-nucleotide polymorphism in inlA , which normally facilitates crossing the intestinal barrier during the initial stages of infection. We hypothesized that (i) natural exposure to virulence-attenuated (vA) Lm strains through food can confer protective immunity against listeriosis attributable to fully virulent (fV) strains and (ii) current food safety measures to minimize exposure to both Lm strains may have adverse population-level outcomes. To test these hypotheses, we evaluated the host response to Lm in a mouse infection model and through mathematical modelling in a human population. After oral immunization with a murinized vA Lm strain, we demonstrated the elicitation of a CD8+ T-cell response and protection against subsequent challenge with an fV strain. A two-strain compartmental mathematical model of human exposure to Lm with cross-protective immunity was also developed. If food safety testing strategies preferentially identify and remove food contaminated by vA strains (potentially due to their common occurrence in foods and higher concentration in food compared to fV strains), the model predicted minimal public health benefit to potentially adverse effects. For example, reducing vA exposures by half, while maintaining fV exposures results in an approximately 6% rise in annual incidence.

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Discussion on the Design of Food Safety Subject Database Based on Big Data Testing

E3S Web of Conferences ◽

10.1051/e3sconf/202129202052 ◽

2021 ◽

Vol 292 ◽

pp. 02052

Author(s):

Kai Chen ◽

Heng Tao ◽

Jie Yu ◽

Miao Hao ◽

Hong Yang ◽

...

Keyword(s):

Big Data ◽

Food Safety ◽

High Standard ◽

Safety Testing ◽

Healthy Development ◽

Whole Process ◽

National Importance ◽

Regulatory Approach ◽

Design Idea ◽

Big Data Technology

Food safety is a matter of national importance, and it is important to establish and improve a whole process food safety supervision system with high standard. Along with the advent of the era of big data, to achieve this goal requires not only the reform and optimization of the old regulatory approach needs to establish the idea of information-based supervision, and actively apply big data technology to food safety testing. In this paper, we introduce the current situation of food safety in society, analyse the shortcomings of current food safety supervision and the challenges faced in the era of big data, discuss the feasibility of using big data for food safety testing with big data technology as the core, and give the design idea of establishing a corresponding food safety subject database. This paper takes food safety testing as the foothold and innovatively combines big data with food safety testing, with a view to providing reference for food safety regulatory authorities and promoting the healthy development of the food industry.

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Cannabis microbiome sequencing reveals several mycotoxic fungi native to dispensary grade Cannabis flowers

F1000Research ◽

10.12688/f1000research.7507.1 ◽

2015 ◽

Vol 4 ◽

pp. 1422 ◽

Cited By ~ 16

Author(s):

Kevin McKernan ◽

Jessica Spangler ◽

Lei Zhang ◽

Vasisht Tadigotla ◽

Yvonne Helbert ◽

...

Keyword(s):

Next Generation Sequencing ◽

Food Safety ◽

Food Industry ◽

Agricultural Products ◽

Third Party ◽

Regulatory Requirement ◽

Safety Testing ◽

Food Borne ◽

Generation Sequencing ◽

The U.S

The Center for Disease Control estimates 128,000 people in the U.S. are hospitalized annually due to food borne illnesses. This has created a demand for food safety testing targeting the detection of pathogenic mold and bacteria on agricultural products. This risk extends to medicalCannabisand is of particular concern with inhaled, vaporized and even concentratedCannabisproducts.As a result, third party microbial testing has become a regulatory requirement in the medical and recreationalCannabismarkets, yet knowledge of theCannabismicrobiome is limited. Here we describe the first next generation sequencing survey of the microbial communities found in dispensary basedCannabisflowers and demonstrate the limitations in the culture-based regulations that are being superimposed from the food industry.

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