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A comprehensive literature search was carried out in the databases of 'Web of Science' and 'Elsevier' to determine the research on the application of natural plant extracts in meat processing and its impact on the quality of meat products. The scope of the included research was expanded by the method of reference tracing. In all databases, the keywords 'natural, plant extract, meat' were used. Between 2020 and 2022, 613 scientific publications were published. Referring to the method of Orzuna-Orzuna et al.[27], these publications were screened in two steps. First, the title and abstract were used for selection, excluding articles that raise animals, reviews, and unmeasured variables of interest. Then the following issues were considered[30,31]: (1) natural plant extracts were used in the processing; (2) pH, color, texture, oxidation index and microbial index were measured; (3) the studies have appropriate control and experimental groups; (4) the publications contain figures for analysis; (5) peer-reviewed journal articles were written in English; (6) experimental design was employed (rotating or continuous); (7) least squares means of the control and experimental groups were measured with variability (standard error or standard deviation); and (8) sample size was used.
Data extraction
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According to the selection criteria, 48 articles were included in the database for final analysis, and the number of articles included in different indicators was different. The response variables extracted for the meta-analysis include pH, L*, a*, b*, antioxidant activity-DPPH, antioxidant activity-AA, antioxidant activity-ABTS, antioxidant activity-FRAP, metal chelating capacity-BHA, peroxide value (PV), total volatile base nitrogen (TVB-N), thiobarbituric acid reactant (TBARS), total bacterial count (TVC), total mesophilic (TMVC), psychrophilic bacteria, lactic acid bacteria, pseudomonas, enterobacteriaceae, yeast and mold , moisture content, moisture activity, water holding capacity (WHC), extrusion loss, cooking loss, hardness, toughness, cohesiveness, elasticity, and chewiness. In addition, in order to investigate which aspects of meat products are more affected by all reported natural plant extracts, the results of different studies are combined through data consolidation.
Other data were collected as much as possible, such as the characteristics of published studies (author, year of publication), the product form of meat, the source of natural extracts, and the number of repetitions. The article references contained in the dataset are listed in Supplemental Table S1. The mean, standard deviation (SD) and number of repetitions of each treatment were extracted from these articles. When the article introduces the SD of each experimental group, these values are directly used in the meta-analysis. If SD is not reported, it is calculated by standard error[32].
Calculation, statistical analysis and heterogeneity test
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The data involved in meta-analysis were analyzed using Review Manager Software (version 5.4.1). Response variables were analyzed through the standardized mean difference (SMD), also called effect size (ES), the difference between the means of the experimental and control groups was standardized using the SD of the groups with and without NPE[33]. The heterogeneity is tested by formula (1) and the model is selected for meta-analysis[34]. i2 represents the proportion of inter study variation observed (due to real heterogeneity rather than accidental observation), Q is the standardized weighted sum of squares of each study variation, and df is the degree of freedom.
$ {i}^{2}=100{\text{%}}\times \frac{Q-df}{Q} $ (1) i2 range from 0 to 100%. Values close to 25% represent low heterogeneity, close to 50% represent moderate heterogeneity, and close to 75% represent high heterogeneity in the study[35]. When i2 is greater than 50%, the random effect model is used to perform the analysis, otherwise, the fixed effect model is used, and Tukey test was used to detect the difference between the treatment groups[32].
Publication bias
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The publication bias was evaluated by funnel plot[36]. When it was asymmetric, it was considered that there was a bias (p < 0.10)[37,38]. However, for the index that the number of articles included in the study is less than ten, the test of publication bias is not carried out, which may lead to false positive statements[39].
In-depth analysis and subgroup analysis
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When the overall effect of a certain type of index is significant (p < 0.05), select an appropriate single index (the number of studies available for analysis is greater than 5) for in-depth analysis, and take the source of meat as the main classification basis for subgroup analysis, which is generally divided into five categories: fish (aquatic products), pork, beef, chicken, lamb[27].
Study attributes and excluded studies
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From 2019 to 2022, online searches using two databases of scientific publications returned 613 publications. After selecting and excluding duplicate papers according to the criteria, 189 full-text articles were evaluated. Finally, 48 articles (Supplemental Table S1) were used to obtain quantitative data for meta-analysis. Descriptive statistics for meta-analysis are shown in Table 1.
Table 1. Descriptive statistical results of all indicators included in MA.
Parameter MPQ N Mean Median Minimum Maximum SD Con NFE Con NFE Con NFE Con NFE Con NFE pH pH 402 6.14 5.85 5.86 6.10 4.62 4.81 6.89 7.54 0.4419 0.3588 Color a* 150 10.43 11.82 9.22 9.58 −0.97 1.61 33.86 45.27 8.6947 8.9012 b* 149 14.76 14.78 12.49 12.64 −0.43 −2.18 38.54 28.20 7.0030 7.3735 L* 158 49.21 47.09 48.87 47.49 20.18 9.33 76.00 78.06 11.7298 11.4085 Texture Chewiness 20 39.11 24.82 67.20 26.14 14.67 15.10 1654.00 1675.00 28.7290 11.0752 Cohesiveness 17 0.63 0.56 0.57 0.49 0.22 0.18 0.77 0.76 0.0996 0.1320 CL, % 36 34.20 34.07 50.70 48.17 3.82 7.74 77.31 79.24 26.5596 26.3236 Elasticity 23 3.67 3.49 3.45 3.99 0.51 0.49 6.61 6.96 2.5301 2.4518 Hardness, N 19 14.17 14.20 20.63 10.24 2.34 4.89 55.35 67.62 21.9327 22.9578 Moisture, % 33 57.34 49.04 64.37 55.54 31.63 29.43 73.69 73.73 13.8881 11.5185 PL, % 10 22.98 1.33 22.98 20.04 22.98 20.04 22.98 20.04 1.0000 0.2700 Water activity 18 0.95 0.93 0.97 0.94 0.88 0.87 1.00 0.99 0.0398 0.0383 WHC, % 9 46.35 40.87 36.70 26.95 36.70 23.30 65.66 72.37 14.4863 23.6829 Antioxidant capacity DPPH, IC50 (μg) 20 41.51 161.12 21.22 48.74 4.84 11.18 45.17 228.03 10.9558 84.4908 Oxidation index Pv, mmol/kg 18 4.51 1.81 1.13 1.03 1.13 0.53 7.11 4.47 2.6571 1.3670 TBARs, mg/kg 402 6.14 5.85 0.72 1.23 0.14 0.18 19.03 21.98 0.4419 0.3588 TVB-N, mg/100g 32.80 21.02 17.10 32.69 10.95 28.57 31.26 55.76 1.8827 7.6660 Microbial index, log10 cfu/g Enterobacteriaceae 34 5.26 3.36 3.48 2.50 1.34 0.99 5.81 4.20 2.4928 1.4109 Enterococcus 3 1.68 0.00 0.84 0.00 0.00 0.00 1.68 0.00 1.3500 0.0000 LAB 33 6.40 5.99 4.98 3.62 4.07 3.00 6.55 6.54 1.9251 1.6709 Micrococcus/
staphylococcus4 5.19 3.98 5.19 3.98 5.19 3.98 5.19 3.98 0.0400 0.0300 Mold and yeast 7 3.61 2.71 3.43 2.59 2.13 1.71 4.72 3.46 1.3863 0.9415 Pseudomonas 24 7.96 6.70 6.38 6.31 6.38 6.31 6.38 6.31 1.7511 0.7401 Psychrotrophic 13 5.81 4.76 5.10 4.19 1.30 0.00 5.37 5.10 2.3713 1.8038 TAC 12 7.15 6.92 7.15 6.92 7.15 6.92 7.15 6.92 0.1100 0.1200 TAMB 12 7.08 7.05 7.08 7.05 7.08 7.05 7.08 7.05 0.0900 0.0400 TMB 9 6.52 5.29 7.05 6.03 5.97 4.40 7.05 6.08 0.7541 2.1113 TPC 21 7.20 5.89 5.48 3.88 3.35 3.24 6.82 5.37 2.7511 1.9788 MPQ: Meat product quality; N: number of comparisons; SD: standard deviation; Con: control; NFE: Natural plant extracts; CL: cooking loss; PL: press loss; WHC: Water holding capacity; DPPH: DPPH radical scavenging activity; Pv: Peroxide value; TBARs: Thiobarbituric acid reactant; TVB-N, Volatile base nitrogen; LAB: lactic acid bacteria; TAC: Total aerobic cryophage; TAMB: Total aerobic mesophilic bacteria; TMB; Total mesophilic bacteria; TPC: Total plate count. The included studies were conducted in 23 different countries (Supplemental Table S1). The sources of raw meat could be divided into six types, of which pork accounts for 40.0%, beef for 30.4%, chicken for 17.4%, fish for 10.9%, and mutton and rabbit meat for 2.2%. On the other hand, the sources of extracts are diverse, including thyme, rosemary, basil and other plants used as spices, as well as blueberries, grapes and other fruits, broccoli, cabbage and other vegetables, and quebracho Colorado wood. The main bioactive substances in different extracts are different, but they could generally be summarized as polyphenols, flavonoids, anthocyanins, tannins and alkaloids.
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Consumers' preference for natural ingredients makes them prefer meat products that use NPE as preservatives and nutritional enhancers rather than synthetic compounds. Therefore, many studies have applied NPE to improve the quality of meat products. The present study indicates that NPE has a positive effect on the quality of meat products. The addition of NPE reduces the pH of meat products, improves antioxidant capacity, delays product oxidation and inhibits microbial reproduction. Specifically, NPE reduce the pH, peroxide value, TBARS and TVB-N value of meat products, inhibit the growth of bacteria such as Enterobacteriaceae, Enterococcus, micrococcus/staphylococcus and Pseudomonas, reduce total microbial cryophase and total plate count, and increase DPPH free radical scavenging activity. NPE effectively protect meat products, reduce the degree of lipid and protein oxidation, and prolong the shelf life without changing the basic properties of meat products, such as color and texture. The results might help to better understand the role of NPE in meat processing and it offers an advantageous method to quantitatively analyze how food components affect food matrix. Given the numerous and intricate sources of NPE, it is essential to classify it based on biochemical makeup and do a thorough investigation. The dose-effect relationship between the addition of NPE and the quality of meat products still need more study. Further investigation should be done in the future on the association between meat products containing NPE and human health from the standpoint of metabolic pathways, taking food safety concerns into consideration.
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About this article
Cite this article
Zhou T, Wu J, Zhang M, Ke W, Shan K, et al. 2023. Effect of natural plant extracts on the quality of meat products: a meta-analysis. Food Materials Research 3:15 doi: 10.48130/FMR-2023-0015
Effect of natural plant extracts on the quality of meat products: a meta-analysis
- Received: 12 December 2022
- Accepted: 16 June 2023
- Published online: 04 August 2023
Abstract: Natural plant extracts (NPE) from some organs of plants are rich in bioactive substances. They have special nutritional characteristics with strong antioxidant and antimicrobial activities. The potential of NPEs to maintain and improve the quality of meat products has attracted attention due to concerns about the safety hazards of synthetic food additives. This paper extensively reviewed the application of NPE in meat processing, and systematically analyzed the comprehensive effects of different NPE using meta-analysis. Fourty-eight articles from 23 countries were studied with standard mean deviation (SMD) using random effect model, and 28 indexes were isolated. Results showed that NPE can reduce the pH value of meat products, improve antioxidant capacity, reduce the degree of oxidation and inhibit microbial growth. In addition, it was found that NPE had a significant impact on the quality of meat products. This meta-analysis provides quantitative evidence to explain how NPE affects meat quality, and helps to better understand the role of NPE in meat processing.
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Key words:
- Meta-analysis /
- Natural plant extracts /
- Meat processing /
- Oxidation resistance /
- Quality