Synthetic Biology - New Interdisciplinary Science 2020
DOI: 10.5772/intechopen.84532
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Real-Time Quantitative PCR as a Tool for Monitoring Microbiological Quality of Food

Abstract: Microbiological parameters of food provide quality information regarding the processing, storage, and distribution conditions, shelf life, as well as whether the food poses a health risk to the population. In this context, the concern with food safety is a competitive advantage, as the pressure of consumers, who are increasingly interested and concerned about what they are consuming, directs the trade to reach the quality of products and services offered. With regard to microbiological analyses, researchers ha… Show more

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Cited by 4 publications
(2 citation statements)
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References 65 publications
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“…Real-time PCR has been recognized as a powerful tool for quantitative bacterial detection from food materials that is highly sensitive and specific (Kimura et al, 2001;Rodríguez-Lázaro et al, 2004;Mafu et al, 2009;Liu et al, 2019). Several studies have compared the application of real-time PCR to plate counting, optical density, and other methods (Reichert-Schwillinsky et al, 2009;Macé et al, 2013;Ilha et al, 2016;Ricchi et al, 2017;Lopes and Maciel, 2019). However, no study has utilized real-time PCR quantification to generate bacterial growth data from food materials for the construction of growth prediction models in comparison with other methods.…”
Section: Introductionmentioning
confidence: 99%
“…Real-time PCR has been recognized as a powerful tool for quantitative bacterial detection from food materials that is highly sensitive and specific (Kimura et al, 2001;Rodríguez-Lázaro et al, 2004;Mafu et al, 2009;Liu et al, 2019). Several studies have compared the application of real-time PCR to plate counting, optical density, and other methods (Reichert-Schwillinsky et al, 2009;Macé et al, 2013;Ilha et al, 2016;Ricchi et al, 2017;Lopes and Maciel, 2019). However, no study has utilized real-time PCR quantification to generate bacterial growth data from food materials for the construction of growth prediction models in comparison with other methods.…”
Section: Introductionmentioning
confidence: 99%
“…First, you create a standard curve; then you compare unknowns to the standard curve and extrapolate a value. It relies on an internal or external calibration curve, and these standard curves are used to derive the input template copy number and to ensure that the exact transcript copy number is determined [ 15 , 17 ]. Absolute quantitative methods have been found to be more sensitive to gene expression variations caused by factors such as developmental and environmental variation [ 18 , 19 ].…”
Section: Introductionmentioning
confidence: 99%