Lipid oxidation in muscle foods is a complex phenomenon that takes place depending on numerous intrinsic and extrinsic factors. The oxidative stability of meat is related to the balance of antioxidant and prooxidants as well as the concentration and characteristics of oxidizable substrates such as polyunsaturated fatty acids (PUFAs), cholesterol, proteins, and pigments (Grotta et al. 2017). In addition, curing of meat has a big influence on lipid oxidation rate since sodium nitrite as the major curing agent not only indicates an antimicrobial effect specifically against Clostridium botulinum but also plays a strong antioxidant role (Bonifacie et al. 2021). Taking all these facts into consideration, in the current study we evaluated the effects of curing and introducing ZX and FI to the cured systems to better understand the changes in MDA concentration when detected by different assays.
3.1.1. General remarks on MDA concentrations of different meat systems and overestimation
The effects of different analytical methods, different formulations, storage time, and their interactions on MDA concentrations of the model meat system samples are presented in Table 2. As is seen from the table, all the factors analyzed were found to be significantly effective on MDA levels (P < 0.05). Relatedly, single (A, B, C) or several two-factor interactions (A × B, A × C, B × C) as well as three-factor interaction (A × B × C) all yielded significant variations on MDA concentrations. For this reason, they were then analyzed individually to better discuss the effects of treatments and storage time on MDA concentrations detected by different methods.
Table 2
Factorial ANOVA table indicating the statistical significance of the method types, treatments, storage time, and their interactions on MDA concentrations of model meat systems.
Source of variation1
|
Type III Sum of Squares (SS)
|
Degree of freedom (df)
|
Mean Squares (MS)
|
F
|
P value
|
A
|
11.64
|
2
|
5.82
|
14743.89
|
0.00
|
B
|
5.20
|
3
|
1.73
|
4391.90
|
0.00
|
C
|
1.30
|
4
|
0.33
|
824.80
|
0.00
|
A × B
|
7.74
|
6
|
1.29
|
3264.71
|
0.00
|
A × C
|
1.44
|
8
|
0.18
|
456.28
|
0.00
|
B × C
|
1.05
|
12
|
0.09
|
222.43
|
0.00
|
A × B × C
|
1.95
|
24
|
0.08
|
205.60
|
0.00
|
Error
|
0.071
|
180
|
0.00
|
-
|
-
|
Total
|
43.068
|
240
|
-
|
-
|
-
|
1A represents the methods (M1, M2 and M3) applied for the determination of MDA concentrations, B represents the treatments (C, CR, CRA and CRP), and C represents the storage time (0., 3., 7., 12. and 15. days). |
MDA concentrations of the model meat systems recorded with different analytical methods M1, M2 and M3 during storage are presented in Fig. 2. Initial MDA concentrations recorded on Day-0 (immediately after production) ranged between 0.116–0.409, 0.013–0.082 and 0.002–0.018 mg MDA/kg sample whereas final concentrations recorded on Day-15 ranged between 0.243–1.935, 0.06–0.116 and 0.024–0.143 mg MDA/kg sample for M-1, M-2 and M-3, respectively. Those ranges pointed out that using the conventional method (M-1) to detect MDA content resulted in significant higher ranges of MDA compared with test kit (M-2) and chromatography (M-3) (P < 0.05). These remarkably high values recorded by M-1 were regardless of either the formulation or the storage time. As also mentioned in Section 1, the biggest disadvantage of the conventional TBARS analysis is that TBA, the main reagent in the assay, reacts not only with MDA but also with several other carbonyl compounds resulting from lipid peroxidation such as alkenals, alkadienals, ketones and other aldehydes (Díaz et al. 2014; Reitznerová et al. 2017). Furthermore, TBA may react with various other compounds such as carbohydrates, amino acids, fatty acids, nitrites and nitrates, pyridines, pigments, metal chelators and other additives present in the meat system (Mendes et al. 2009; Díaz et al. 2014) that could lead to the generation of yellow or orange colored complexes (Díaz et al. 2014). Those complexes form chromogens that absorb at similar wavelengths (530–535 nm) to the MDA-TBA complex which results in overestimation of the values (Bertolín et al. 2019). In addition, Mendes et al. (2009) emphasized that high temperatures (95–100°C) and strong acidic conditions (pH 1.5–3.5) which are required for MDA-TBA reaction could cause an artifactual peroxidation of sample constituents. The major reason for higher MDA concentrations recorded in M-1 compared with M-2 and M-3 is thought to be the overestimation of the data due to the combined effects of all those emphasized facts. Previously, MDA levels in raw meat and processed meat products were evaluated by Bertolín et al. (2019). In their study, MDA concentrations were overestimated by using the spectrophotometric method when compared with the chromatographic methods, where specifically in processed meat products, the difference was between 54% and 2068%. Concordant data was also found by Papastergiadis et al. (2012) who reported that in processed meats and cooked fish, spectrophotometric measurements of MDA resulted in an overestimation up to a factor of more than 10 when compared with HPLC measurements. Specifically processed meat samples indicated those behavior when compared with uncooked meats that confirms the interactions of TBA with other additives and ingredients present in the formulation. In our study, on different storage days, the overestimation of MDA concentrations for the conventional method ranged between 2 to 53-fold when compared with the chromatographic method whereas this range differed from 2 to 29-fold between conventional and test kit methods. This overestimation of MDA could be decreased when test kits were used and, in this way, MDA levels obtained with M-2 were 0.4 to 8 folds higher than the MDA levels obtained with M-3. Despite of those reports, the trends of MDA change in different assays throughout the storage followed a similar pattern thus leading to high correlations among them. These correlations evaluated among different methodologies would be further discussed in the following sections.
3.1.2. Curing of model meat systems and changes in MDA levels
The expected impact of curing on retarding lipid oxidation was clearly followed by all analytic methods (Fig. 2): At all storage days, CR samples in which curing was included yielded significantly lower MDA concentrations compared with C samples in which no curing was included (P < 0.05). Values in C samples were almost 5 times higher than the cured samples after 3 days of storage. In the absence of nitrites, free iron is released and it promotes lipid oxidation via Fenton reaction in which oxygenated free radicals are formed by the reaction with lipoperoxides (Bonifacie et al. 2021). Nitrite, as a very typical agent in curing, has the ability to bind both heme and non-heme iron which prevents the further release of this catalytic iron and thereby acts against oxidation (Karwowska et al. 2020). In addition, ascorbic acid, a highly effective reducing agent that promotes curing reactions, also serves as an oxygen scavenger that improves antioxidant protection (Terns et al. 2011). Therefore, lower MDA concentrations of the cured samples most probably arise from the combined effects of nitrite and ascorbate. Our results were in agreement with Bonifacie et al. (2021) who reported that cured and cooked meat models containing sodium nitrite had much lower lipid oxidation than the meat models without nitrite, besides, no additional effect of ascorbates to retard oxidation was recorded. According to another approach, lower MDA concentrations of meat models containing nitrite could be because of the reaction of nitrites with MDA under acidic conditions causing the underestimation of MDA (Jung et al. 2016). Since strong acids like TCA and perchloric acid are used for extraction of MDA in standard spectrophotometric TBARS assays, this statement could be prevailing; however, in our study, lower MDA concentrations in meat systems with nitrite were still observable in the chromatographic technique where acid extraction was not employed. Therefore, at this point, it is thought that the antioxidant effects of curing agents were the major reason for lower oxidation rather than interferences of the nitrite with MDA.
3.1.3. The effects of antioxidant addition on MDA concentrations
Even though the curing process seemed eminently effective to control the oxidation rate, introducing ZX to the cured meat models led to further decrements in MDA levels (Fig. 2): TBARS values detected by M-1 showed that the lowest MDA content on Day-12 and Day-15 belonged to CRA samples containing ZX (P < 0.05). This result indicated that ZX was effective to decrease the oxidation rate particularly on the last days of storage although it did not lead to any considerable changes on the earlier days. These results corroborate the findings of Sellimi et al. (2017) who recorded lower TBARS contents after 10 days of refrigerated storage in sausages containing fucoxanthin, which further provided evidence that carotenoids are potent antioxidants for ensuring lipid stability in meat systems. In this respect, Domínguez et al. (2019) stated that carotenoids act as important antioxidants since they scavenge proxy radicals that lead to the formation of a stabilized carbon-centered radical. Right along with the data from M-1, lower MDA levels in CRA samples were detected by M-2 and M-3. According to M-2 data, MDA concentrations of CRA samples were the lowest among other samples on Day-0, Day-3 and Day-15 (P < 0.05). Similarly, according to M-3, the lowest MDA concentrations belonged to CRA samples on Day-3, Day-12 and Day-15 (P < 0.05). Therefore, the last two methods (M-2 and M-3) revealed that the addition of ZX to cured meat model systems resulted in lower oxidation rates at both the beginning and the end of the storage.
3.1.4. The effects of prooxidant addition on MDA concentrations
It is well-known that the presence of iron plays a considerable role in triggering lipid oxidation chain reactions. Although catalysis of lipid oxidation was ascribed to myoglobin and other heme compounds previously, it was later understood that in cooked meats, non-heme iron was a more active catalyst of oxidation when compared to heme iron (Baron and Andersen, 2002). Gheisari et al. (2010) stressed that iron released from heme pigments during cooking of meat could lead to an increase in non-heme iron that is responsible for accelerating the oxidation rate. This data was a reason behind the selection of the prooxidant included in the cured meat models in the current study. Indeed, different methods selected to determine the oxidation rate resulted in pretty much similar trends (Fig. 2): For M-1, utilization of iron in ferric form (FeCl3) gave a rise to MDA concentrations of cured meat models on most of the storage days. In this traditional method, CRP samples containing prooxidant had higher MDA concentrations than CRA samples containing antioxidant on Day-0, Day-12 and Day-15 (P < 0.05), which indicated that the impact of iron in triggering oxidation reactions was visible. On the side, C treatment without curing showed higher TBARS values than CRP treatments for all the storage days (P < 0.05). This was presumably due to the abnormal increase in oxidation without curing; thus, when curing was applied to the meat systems, even if prooxidant is present the samples showed a lower oxidation trend than the samples in which curing was not involved. Indeed, as previously emphasized in Section 3.1.2, as the effective antioxidant, nitrite is offered to favor iron chelation and thereby stabilization of unsaturated lipids (Skibsted, 2011). Based on this fact, in the cured samples the probable effects of the prooxidant material might be suppressed.
Although the traditional method (M-1) showed a rising trend for oxidation by the action of prooxidant materials, this effect was much obvious when detected with other methods. For M-2, CRP samples had higher TBARS values than both CR and CRA samples on all the storage days (P < 0.05). Similarly, for M-3, CRP samples had higher MDA concentrations when compared with CR and CRA on Day-0, Day-3, Day-12 and Day-15 (P < 0.05). Those data pointed out that rapid kits and chromatographic methods could be more useful to better specify the effects of introducing pro- or antioxidative compounds on lipid oxidation rate of meat systems.
3.2. The effects of storage time on MDA concentrations of model meat systems evaluated by different methods
Storage time has an indisputable influence on the progress of lipid oxidation in muscle foods due to the possibility that radicals cause damage to lipids increases with time (Domínguez et al. 2019). As shown in Table 2, both storage time itself and its interactions with type of the method and the treatments were all significant on MDA contents of the model meat systems (P < 0.05). Evaluating the progress of different treatments during storage (Fig. 3), it was found that for M-1, C samples produced without curing had the maximum TBARS value at the end of the storage (Day-15) (P < 0.05). However, the maximum MDA content in C treatment belonged to Day-7 for M-2 and to Day-3 for M-3 (P < 0.05), which showed that the rising trend of oxidation was not stable throughout the storage. In CR samples in which curing was involved, a significant decrease in MDA level was recorded by M-1 and M-3 after 12 days of storage (P < 0.05). Similar to this, in CRA samples containing ZX, there was an increase in the oxidation rate in earlier stages of storage, however, after 7 days, MDA content of these samples showed a decreasing trend which was both detected by M-1 and M-3 (P < 0.05). The variations in MDA content during chilled storage could be due to the balance between the formation and destruction reactions according to Mendes et al. (2009). The initial increase of MDA concentrations highlights the proceeding of oxidation reactions, the intermediate declines might arise from the decomposition of MDA and/or reactions of MDA with other polymers such as proteins, and the thereafter increase in some of the samples could be related with a markedly high rate of MDA formation after several storage days (Mendes et al. 2009; Öztürk-Kerimoğlu et al. 2019).
On contrary to the other methods, the data obtained from M-2 indicated that there was a continuous increase in TBARS values of all cured meat models (CR, CRA and CRP) after 7 days of storage (P < 0.05). This data demonstrated that when compared with traditional and chromatographic assays, rapid test kits yielded a more different trend for oxidation rate during storage. Nevertheless, the results indicated that MDA concentrations of all the meat model systems including control samples without curing did not exceed the threshold level (< 2 mg MDA/kg sample) suggested for bovine muscles (Campo et al. 2006). On the side, the relationship between the perception of rancidity and MDA levels should also be considered since it was previously reported that oxidized flavor could be detected from 0.6 to 2.0 mg MDA/kg in beef (Greene and Cumuze, 1981). Thus, rancid notes might be perceived in some of the samples that had TBARS values higher than 0.6 mg MDA/kg. A noticeable point is that the limit values for MDA could be modified based on the determination assay. For instance, Zhang et al. (2019) suggested that sensory quality of beef muscles was acceptable when their TBARS values reached up to 2.5 mg MDA/kg detected by test kits whilst TBARS values up to 10.0 mg MDA/kg detected by spectrophotometric assay could be sensorially tolerable. Those findings are remarkable in terms of the necessity of designating different limit values for MDA concentrations of meat and meat products which are determined by different assays.
3.3. Correlations evaluated between different MDA detection assays
As highlighted earlier in both Table 2 and Fig. 2, the results of this study indicated that the application of three different analytical methods used to determine MDA concentrations in model meat systems resulted in significant variations (P < 0.05). The interrelationships between the assays used in the present study were further evaluated with correlation analysis. The correlation matrices indicating those interrelationships on different storage days are presented in Fig. 4. At each storage day, at least one significant positive correlation (r > 0.5) was detected between the methods (P < 0.05). M-1 had a significant positive correlation with M-3 through the storage (P < 0.05) and specifically at the beginning and the end of this period. The strong correlations between M-1 and M-3 indicated that the traditional spectrophotometric method showed good compatibility with the chromatographic method even if the numerical MDA concentrations were different as mentioned in the previous sections. Since the TBA reagent is not used in the HPLC method, no condensing TBA compounds were present which might have interfered with other substances (Karatas et al. 2002). Therefore, MDA concentrations detected by the HPLC method were much lower than those detected by the traditional method. Despite this, the overall trends of both spectrophotometric and chromatographic methods were in a similar line thus presenting positive correlations. The interactions between classical spectrophotometric and chromatographic methods for MDA detection were formerly investigated by Reitznerová et al. (2017) in different meat products. Similar to our findings, they recorded an overestimation with spectrophotometry, however, the results of the traditional assay correlated in all meat samples with the results of the RP-HPLC method. For this reason, the authors suggested that traditional methods could be used to determine the lipid oxidation level if no legislative limit is stated. Nonetheless, in the case of implementation of oxidation limits, specific chromatographic methods would be necessary, and preferentially the specificity of MDA determination could be increased by utilizing correlation factors among different assays. On the other hand, those outcomes were contrary to that of Mendes et al. (2009) who reported that correlation coefficients between spectrophotometric and chromatographic MDA concentrations of fish samples were low although the coefficient between two different HPLC separation methods (MDA-TBA or MDA-DNPH) was higher. Depending on their findings, the authors declared a greater uncertainty in the traditional method without HPLC separation. The conflicting results of those findings with our study are presumably due to the different separation techniques used in the HPLC method where MDA-protein interactions could possibly take place.
Data from the test kit assay (M-2) was also coherent with the HPLC method (M-3), where it yielded strong positive correlations with M-3 on most of the storage days (Day-0, Day-3, Day-7 and Day-12) (P < 0.05). Despite this, M-2 had much weaker correlations with M-1, specifically on Day-12 and Day-15. In accordance with this, Zhang et al. (2019) found no significant relationship between spectrophotometric and test kit assays of TBARS determination in beef muscles, which was probably due to the differences in the sample extraction conditions and the reagents used. On the side, our outputs revealed that the rapid test kit assay gave more consistent results with the chromatographic assay when compared with the traditional spectrophotometric assay. Those strong correlations evaluated between M-2 and M-3 were promising, and the results highlighted that test kits could be a good alternative to HPLC in case of simplification and enhancing their specificity for meat products since the overestimation of MDA was also lower than the traditional method.