Salmonella Quantification in Ground Beef

The purpose of this study is to compare the traditional methods (Plating, MPN) with rapid quantification methods (BAX, Gene Up) for Salmonella in ground beef and evaluate the correlation among the methods at different concentrations. Six fresh and frozen ground beef samples with inoculation levels of 1 to 6 Log CFU/g were processed, and analyzed by the Plating, MPN, BAX, and Gene Up quantification methods. The Salmonella counts were transformed into log CFU/ml and statistically analyzed using R Studio and SAS software to determine significant differences between methods at each concentration level. Results provided an overview of Salmonella counts of traditional and rapid methods at 10^1 inoculation level of fresh samples and indicated a statistically significant difference ( p<0.05) between the methods. A 10^1 inoculation level rapid methods quantification is more reliable than traditional methods. Like the 10^1 inoculation level, there is a significant difference between methods with 10^3 inoculation level. In 10^2, 10^4,10^5, and 10^6 inoculation levels of fresh samples, the results did not show statistically significant differences ( p>0.05) between the methods. The results of the 10^1 inoculation level frozen samples indicated a statistically significant difference (p<0.05) between the methods. No significant difference (p>0.05) in the Salmonella level was observed in the frozen samples that were inoculated to the level of 10^2, 10^3, 10^4, 10^5, and 10^6. Rapid methods provide quick results for the quantification of Salmonella, significantly reducing the time required for analysis compared to traditional methods. These rapid methods can even measure lower Salmonella counts in samples, enhancing sensitivity and reliability. Rapid methods facilitate faster decision-making in food safety and public health.

Publication Details

Journal
ThinkTech (Texas Tech University)
Published
2024-12-01
Primary Topic
Advanced Statistical Methods and Models
Type
article
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article

Salmonella Quantification in Ground Beef

ThinkTech (Texas Tech University)
Advanced Statistical Methods and Models
article

Salmonella Quantification in Ground Beef

article en

Abstract

The purpose of this study is to compare the traditional methods (Plating, MPN) with rapid quantification methods (BAX, Gene Up) for Salmonella in ground beef and evaluate the correlation among the methods at different concentrations. Six fresh and frozen ground beef samples with inoculation levels of 1 to 6 Log CFU/g were processed, and analyzed by the Plating, MPN, BAX, and Gene Up quantification methods. The Salmonella counts were transformed into log CFU/ml and statistically analyzed using R Studio and SAS software to determine significant differences between methods at each concentration level. Results provided an overview of Salmonella counts of traditional and rapid methods at 10^1 inoculation level of fresh samples and indicated a statistically significant difference ( p<0.05) between the methods. A 10^1 inoculation level rapid methods quantification is more reliable than traditional methods. Like the 10^1 inoculation level, there is a significant difference between methods with 10^3 inoculation level. In 10^2, 10^4,10^5, and 10^6 inoculation levels of fresh samples, the results did not show statistically significant differences ( p>0.05) between the methods. The results of the 10^1 inoculation level frozen samples indicated a statistically significant difference (p<0.05) between the methods. No significant difference (p>0.05) in the Salmonella level was observed in the frozen samples that were inoculated to the level of 10^2, 10^3, 10^4, 10^5, and 10^6. Rapid methods provide quick results for the quantification of Salmonella, significantly reducing the time required for analysis compared to traditional methods. These rapid methods can even measure lower Salmonella counts in samples, enhancing sensitivity and reliability. Rapid methods facilitate faster decision-making in food safety and public health.

ThinkTech (Texas Tech University)
Openalex Percentile: Top 41%
Advanced Statistical Methods and Models
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