Meta-analisis Pengaruh Penambahan Bawang Putih terhadap Mutu Mikrobiologi Produk Daging
Date
2023Author
Ramadani, Suci Putri
Kusumaningrum, . Harsi D
Hasanah, Uswatun
Metadata
Show full item recordAbstract
Garlic (Allium sativum) is one of the natural ingredients used in
microbiological quality control of meat products. Various studies have shown that
the addition of garlic to meat products can significantly reduce the number of
microbes, but some studies show a decrease in the number of microbes that is not
significant. Therefore, it is necessary to carry out a thorough and systematic study
using meta-analysis to analyze the effect of adding garlic in various forms on the
microbial content in meat products using meta-analysis, determine the form of
garlic that is most effective in reducing the number of microbes, determine the
type/shape meat products that experienced the highest microbial reduction, and
determining the types of microbes with the highest inhibition through subgroup
analysis of the effect of the addition of garlic on decreasing the number of microbes
in meat products. This meta-analysis study was limited to reducing the number of
microbes in meat products which included the parameters of garlic shape, type of
meat product, and type of microbes tested.
This research was conducted in 6 stages, namely formulation of research
questions, determination of inclusion and exclusion criteria, search and selection
studies, collection of study sources, data extraction, and data analysis. Based on the
search and selection for study sources, 304 data extracted from 10 articles were
analyzed using the Hedges' d method with a random-effect model. Data processing
was done using OpenMEE software. Then an analysis of the overall effect size was
carried out to determine the effect of decreasing the number of microbes in meat
products using a meta-analysis of various studies that have been conducted. This
analysis also tested study heterogeneity, subgroup analysis, and publication bias
analysis. Subgroup analysis was carried out to determine which meat products
experienced the highest microbial reduction, the form of garlic that was most
effective in reducing microbial counts, and the types of microbes that were most
inhibited by the addition of garlic.
The results of the analysis of the overall effect size (SMD/Standardized Mean
Difference) showed a negative value of -1.177 with a confidence interval range
(95% CI) from -1.337 to -1.017. The results of this analysis indicated that the
addition of garlic to meat products significantly reduced the number of tested
microbes (p < 0.05). The resulting heterogeneity value (I2
> 50%) is 54,37%. This
heterogeneity value is quite high for each parameter, so it is necessary to carry out
further analysis, namely subgroup analysis on various moderator variables, namely
the type of sample, the shape of the garlic, and the type of microbe tested. The
addition of garlic significantly decreased the number of microbes (p < 0.05) in 3
types of samples, namely raw meatballs (minced mutton meat), ground beef, and
raw chicken meat. Forms of garlic that reduce the number of microbes higher are
freeze-dried powder, oven-dried powder, and microcapsules essential oil. The
addition of garlic to meat products significantly reduced the 7 tested microbes other
than Staphylococcus aureus with the highest reduction found against Listeria
monocytogenes.
Analysis of publication bias was carried out using the funnel plot method and
validation using Rosenthal's fail-safe-number test. Analysis using the funnel plot
method shows that the distribution of data is symmetrical, indicating that there is
no publication bias. Analysis of publication bias based on Rosenthal's fail-safe number test showed that the results of the meta-analysis carried out avoided the
possibility of publication bias because the Nft value for all observed parameters
was more than 5N+10. So that the results of this analysis can become a new
scientific reference for microbiological quality and microbial control in meat
products.
Collections
- MT - Agriculture Technology [2213]