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Article

Comparative Assessment of Quality Deterioration in Various Vegetable Oils During Deep-Fat Frying of Crispy Meat

by
Zelong Wang
1,
Yinuo Liu
1,
Qiuxiao Li
1,
Ruijia Liu
1,
Ming Cai
2 and
Shuna Zhao
1,*
1
Key Laboratory of Geriatric Nutrition and Health, School of Food and Health, Ministry of Education, Beijing Technology and Business University, Beijing 100048, China
2
Department of Food Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China
*
Author to whom correspondence should be addressed.
Foods 2026, 15(4), 771; https://doi.org/10.3390/foods15040771
Submission received: 16 January 2026 / Revised: 10 February 2026 / Accepted: 14 February 2026 / Published: 20 February 2026
(This article belongs to the Special Issue Nutrients and Flavor in Food Processing—Innovating for Healthier and Tastier Foods)
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Abstract

Deep-fat frying is widely used, but high temperatures and complex food matrices promote oil deterioration and harmful substance formation, posing risks to food safety and oil quality. This study evaluated five vegetable oils—sunflower oil (SFO), canola oil (CNO), palm oil (PO), cottonseed oil (CSO), and soybean oil (SBO)—during deep-fat frying of crispy meat to elucidate oil deterioration and contaminant formation patterns. After 32 h of frying, total polar compounds (TPCs) of PO and CNO were 29.8% and 32.6%, significantly lower than the other oils. Similar trends were observed for total oxidation value (TOTOX), carbonyl value (CV), and polar polymers, suggesting higher oxidative stability of PO and CNO, as confirmed by principal component analysis (PCA). Initial monochloro-1,2-propanediol esters (MCPDEs) and glycidyl ester (GE) in PO were relatively high (e.g., 3-MCPDE: 3630 μg/kg) but decreased over time during frying, whereas levels in SFO, CSO, and SBO remained low. Pearson’s correlation analysis indicated diacylglycerols (DAG) and monoacylglycerols (MAG) were positively correlated with MCPDEs and GE (p < 0.05). L* and b* values were positively correlated with polar polymers and contaminants, indicating that color parameters may serve as rapid, non-invasive auxiliary indicators of oil quality but should be combined with other indices for accurate evaluation.

Graphical Abstract

1. Introduction

Deep-fat frying is a prevalent cooking technique favored for its efficient heat transfer and operational simplicity. During a typical frying process, food is submerged in oil heated to 150–200 °C [1]. While heat penetrates the food’s interior, surface moisture evaporates rapidly into the surrounding oil, forming the crispy outer layer that defines the characteristic texture [2]. However, this intense thermal environment accelerates oil deterioration, posing potential safety risks. Specifically, exposure of oils to oxygen and moisture at elevated temperatures triggers a complex series of degradative reactions, including oxidation, hydrolysis, and polymerization [3,4]. To ensure the safe application of frying oils, many countries have set strict limits on frying oil quality. For example, according to the Chinese National Food Safety Standard (GB 2716-2018) [5], the maximum levels are set at 27% for total polar compounds (TPCs) and 5 mg/g for acid value (AV). Other countries, including Chile, Italy, France, Poland, the UK, and Japan, set the TPC limit at 25% or lower. Recent studies, however, have challenged the conventional reliance on traditional physicochemical indicators, showing that free fatty acid (FFA) content does not consistently correlate with lipid degradation during prolonged heating [6,7]. Conventional quality indices may insufficiently capture the comprehensive safety risks associated with thermally deteriorated oils.
In addition to the physicochemical parameters, some contaminants formed during the refining of edible oils—such as glycidyl ester (GE), 2-monochloro-1,3-propanediol ester (2-MCPDE), and 3-monochloro-1,2-propanediol ester (3-MCPDE)—have attracted global attention [8,9]. The International Agency for Research on Cancer (IARC) classified glycidol (GD), the hydrolyzed form of GE, as Group 2A, “probably carcinogenic to humans,” in 2000, and 3-monochloro-1,2-propanediol (3-MCPD) as Group 2B, “possibly carcinogenic to humans,” in 2013. Although these contaminants have been extensively studied during oil refining, their behavior and impact under frying conditions remain poorly understood. Crucially, the introduction of the food matrix incorporates exogenous constituents—such as moisture, carbohydrates, and metal ions—that substantially enhance the complexity of lipid degradation reactions [10]. This multifaceted environment not only facilitates conventional degradation reactions but may also promote the accumulation of specific process-induced contaminants. For example, Xu et al. [11] reported significant correlations between MCPDE levels and both peroxide value (POV) and p-anisidine value (p-AV) during frying. Quek et al. [12] noted that the accumulation of 3-MCPDE could be affected by the degree of fatty acid unsaturation and the acidity of the frying oil. Therefore, systematically evaluating physicochemical changes in conjunction with 2-MCPDE, 3-MCPDE, and GE across different oils during actual frying is essential for a comprehensive safety assessment.
Meanwhile, French fries are the most commonly used model food for assessing frying oil quality changes [13,14,15], and some meat products, such as chicken breast and beef nuggets, have also been examined [3,16]. However, due to its unique composition and moisture-release behavior, crispy meat (a batter-coated product) exhibits oil–food interactions distinct from those of traditional model foods. Given its widespread consumption in Chinese commercial catering, the thermal degradation of different oils used for crispy meat has not been systematically characterized.
Compared with previous studies, this study used crispy meat as a model food to capture the more complex and realistic oil–food interactions and selected five vegetable oils—sunflower oil (SFO), canola oil (CNO), palm oil (PO), cottonseed oil (CSO), and soybean oil (SBO)—as the research subjects. To simulate actual restaurant operations, an intermittent frying schedule was applied (8 h/day for 4 days). Throughout the frying process, key physicochemical parameters, glycerides, and refining-related contaminants (2-MCPDE, 3-MCPDE, and GE) were monitored and systematically compared among the different oils. Therefore, this study aimed to elucidate the deterioration patterns and contaminant formation characteristics of different oils during the deep-fat frying of crispy meat and provide scientific guidance for oil selection and food safety risk management in the catering industry.

2. Materials and Methods

2.1. Materials and Chemicals

Crispy meat was obtained from Henan Lianduoduo Supply Chain Management Co., Ltd., Hebi, China. Its primary ingredients consist of chicken, starch, edible salt, and other additives, with a nutritional profile of 15.0% fat, 8.0% protein, and 457 mg/100 g sodium. SFO, CNO, PO, CSO, and SBO were purchased from a Yonghui Superstores, Beijing, China. HPLC-grade solvents and standards, including benzene, ethanol, p-anisidine, n-hexane, tetrahydrofuran, 1,2-dipalmitoyl-3-chloropropanediol, its deuterated analog (d5), 1,3-dipalmitoyl-2-chloropropanediol, glycidyl palmitate, and glycidyl palmitate-d5, were obtained from J&K Scientific Co., Ltd., Beijing, China. Analytical-grade reagents including cyclohexane, diethyl ether, potassium hydroxide, chloroform, potassium iodide, phenolphthalein, glacial acetic acid, isooctane, sodium hydroxide, 2,4-dinitrophenylhydrazine, trichloroacetic acid, and soluble starch were supplied by Sinopharm Chemical Reagent Co., Ltd., Shanghai, China. Wade’s reagent and sodium thiosulfate solution were provided by Northern Weiye Metrology Group Co., Ltd., Girraween, Australia.

2.2. Frying Experimental Conditions

Frying trials were conducted using stainless-steel fryers. Five liters of fresh oil were heated to 185 ± 5 °C prior to frying. Batches of 50 g of crispy meat were fried for 3 min at 20 min intervals, for 8 h per day over four consecutive days, totaling 32 h of frying. The product-to-oil ratio was adjusted based on the daily frying consumption in actual commercial stores, thereby enhancing the practicality and relevance of the experimental outcomes without introducing operational complexity. During frying, the amount of crispy meat per batch was proportionally adjusted to compensate for sampling loss, maintaining an approximately constant product-to-oil ratio. Oil samples (100 mL) were collected every 4 h and stored under refrigeration for further analysis. Oil loss due to volatilization and absorption by the food matrix was not quantified; therefore, a fixed oil turnover rate was not applied in this study. During frying, the fryer remained uncovered, and the oil was not replenished. Between daily sessions, the fryer was kept at room temperature in the dark and covered with plastic wrap.

2.3. Determination of the Fatty Acid Composition

The fatty acid composition of the oils was analyzed with reference to the third normalization procedure specified in GB 5009.168-2016 [17,18]. Oil samples were saponified and methylated under alkaline conditions to obtain fatty acid methyl esters (FAMEs). Analyses were performed on an Agilent 8890 GC system coupled with a 5977B mass selective detector (MSD) (Agilent Technologies, Santa Clara, CA, USA) and equipped with a DB-WAX capillary column (30 m × 0.25 mm × 0.25 μm). The injector temperature was set at 250 °C, and a 1.0 μL aliquot was injected in splitless mode. The oven temperature was programmed as follows: 40 °C (held for 3 min), ramped to 50 °C at 5 °C/min, to 230 °C at 6 °C/min (held for 12 min), and finally to 250 °C at 10 °C/min (held for 6 min). Helium was used as the carrier gas at 1.0 mL/min. Fatty acids were preliminarily identified by comparison with the NIST-14 library and confirmed using a 37-component FAME standard mixture. The chromatogram of the 37-component FAME standard mixture is shown in Figure S1. Relative contents were quantified using the area normalization method.

2.4. Determination of Physical and Chemical Indicators

2.4.1. Determination of Color

A colorimeter (Guangdong 3nh Technology Co., Ltd., Guangzhou, China) was used to measure the oil’s lightness (L*), red/green axis (a*), and yellow/blue axis (b*), and Equation (1) was used to compute the total color difference (ΔE) [19].
∆ E = L ∗ − L 0 ∗ 2 + a ∗ − a 0 ∗ 2 + b ∗ − b 0 ∗ 2
Note: Subscript 0 indicates the L 0 ∗ , a 0 ∗ and b 0 ∗ values for unheated oil.

2.4.2. Determination of Regular Indicators

Total Polar Compounds
The TPC percentage was measured using a Testo 270 tester (Testo SE & Co. KGaA, Lenzkirch, Germany) [20,21,22]. For each measurement, the probe was immersed in temperature-stabilized oil within the designated depth range, and values were recorded after stabilization. The instrument determines TPC based on the dielectric constant of the oil, which correlates directly with the weight percentage of polar compounds, with a measurement accuracy of ±2.0%, and its results have been reported to correlate well with those obtained by chromatographic methods [23].
Acid Value
AV was determined per GB 5009.229-2016 [24,25]. A 10–20 g oil sample was dissolved in 50 mL ethyl ether–isopropanol (1:1, v/v) and titrated with 0.1 mol/L KOH using phenolphthalein as the indicator. AV was expressed as mg KOH required to neutralize free fatty acids per gram of oil.
Iodine Value (IV)
IV was determined per GB/T 5532-2022 [26,27]. A 0.2–0.3 g oil sample was reacted with 20 mL of cyclohexane–acetic acid (1:1, v/v) and 25 mL of Wijs reagent in the dark for 1 h. After adding 20 mL of KI and 150 mL of water, the mixture was titrated with 0.1 mol/L Na2S2O3 until the yellow color nearly disappeared. Starch indicator was then added, and titration continued until the blue color disappeared. IV was expressed as grams of iodine absorbed per 100 g oil.
Carbonyl Value (CV)
CV was determined per GB 5009.230-2016 [28,29]. A 0.025–0.5 g oil sample was dissolved in 5 mL benzene, mixed with 3 mL trichloroacetic acid and 5 mL 2,4-dinitrophenylhydrazine, and shaken for 20 s. After incubation at 60 °C for 30 min and cooling, 10 mL KOH-ethanol (4 g/100 mL) was added and left for 10 min. Absorbance at 440 nm was measured using a UV–visible spectrophotometer with a blank. CV was expressed as milliequivalents of carbonyl compounds per kilogram of oil (meq/kg).
Peroxide Value
POV was determined per GB 5009.227-2016 [30] and expressed as mmol/kg [31]. A 2–3 g oil sample was mixed with 30 mL of trichloromethane–acetic acid (2:3, v/v) and 1 mL saturated KI, kept in the dark for 3 min, then diluted with 100 mL water. The mixture was titrated with 0.002 mol/L Na2S2O3 until light yellow, followed by starch indicator, and continued until the blue color disappeared. POV was expressed as mmol of peroxide per kilogram of oil.
P-Anisidine Value
P-AV was determined according to GB/T 24304-2009 [32] and calculated using Equation (2), where *m* is the sample mass (g) [33]. A 0.0025 g/mL p-anisidine reagent was prepared in glacial acetic acid. Oil samples (1.0–2.0 g) were dissolved in iso-octane. For A0, 5 mL of test solution and 1 mL of acetic acid were mixed, and absorbance was recorded at 350 nm after 8 min. Then, 1 mL of p-anisidine reagent was added to 5 mL of test solution, and A1 (sample) and A2 (blank) were measured within 2 min, keeping absorbance between 0.2 and 0.8. P-AV was expressed as the concentration of aldehydic secondary oxidation products in the oil.
P - A V = 30 × A 1 − A 2 − A 0 m
Total Oxidation Value (TOTOX)
TOTOX, an essential indicator of the overall oxidation state of oils, is calculated using Equation (3) [33]. POV was expressed in mmol per kilogram of oil (mmol/kg).
T O T O X = 4 × P O V m m o l k g + p - A V

2.4.3. Determination of Degradation and Polymerization Products Formed from Triacylglycerols (TAGs)

Analysis of TAG degradation and polymerization products was performed according to GB/T 26636-2011/IS0 16931:2001 [34], with slight modifications [35]. HPLC analysis was conducted using an Agilent 1100 system with a PLgel 5 μm 100 Å (300 × 7.5 mm) column and a refractive index detector. Samples were filtered through a 0.22 μm membrane and 50 µL was injected. Tetrahydrofuran served as the mobile phase at 0.9 mL/min flow rate. Glyceride percentages were calculated by the area normalization method.

2.4.4. Determination of 3-MCPDE, 2-MCPDE, and GE

The contents of 3-MCPDE, 2-MCPDE, and GE in frying oils were determined with reference to the first method of Title II in GB 5009.191-2024 [36,37]. Oil samples were accurately weighed, spiked with isotopically labeled standards, and subjected to purification by acidification, liquid–liquid extraction, ether–ethyl acetate extraction, and subsequent derivatization with phenylboronic acid. Analyses were performed on a GCMS-TQ8050NX system (Shimadzu, Kyoto, Japan) equipped with an SH-5MS capillary column (30 m × 0.25 mm × 0.25 μm). Quantification of esters was achieved using the isotopic internal standard method. Instrumental conditions included a 1 μL injection volume, helium as the carrier gas at 1.00 mL/min in non-split mode, and operation in EI-MRM mode at 200 °C. The calibration curves for 2-MCPDE, 3-MCPDE, and GE are shown in Table S1. The limits of detection (LOD) for GE and MCPDEs were both 100 μg/kg.

2.5. Statistical Analysis

All analyses were carried out in triplicate as analytical replicates from the same fryer for each oil, and data are reported as mean ± standard deviation (SD). For TPC, AV, ΔE, L*, a*, b*, POV, p-AV, TOTOX, IV, CV, MCPDEs, and GE, two-way ANOVA was performed with oil type and frying time as fixed factors, and their interaction effects were examined; post hoc comparisons were conducted using Tukey’s multiple comparison test [16,38]. One-way ANOVA was applied to the fatty acid composition of fresh vegetable oils and to the changes in glycerides. All statistical analyses were performed using IBM SPSS 27.0 software (IBM, Armonk, NY, USA), with p < 0.05 considered statistically significant. Principal component analysis (PCA) and correlation analysis were performed using Origin 2025 software. The total number of observations included in the PCA was n = 5 oils × 5 time points × 3 replicates = 75. Prior to PCA, all variables were Z-score standardized (mean-centered using Equation (4) and scaled to unit variance using Equation (5)) to eliminate scale effects and ensure equal weighting of each feature [39].
X i j c e n t e r e d = X i j − X ¯ j
X i j s c a l e d = X i j − X ¯ j S D j
where X i j represents the original value of variable j for sample i, X ¯ j denotes the mean of variable j, and S D j is the standard deviation of variable j.

3. Results and Discussion

3.1. Fatty Acid Composition of the Oils

Table 1 presents the fatty acid compositions of five fresh vegetable oils. The proportions of saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs) vary markedly among the oils, which may influence their oxidative stability during high-temperature frying [40]. SFO and SBO are rich in PUFA (61.49% and 55.33%, mainly linoleic acid, C18:2), which are beneficial to health but more prone to oxidative degradation due to the reactivity of bis-allylic hydrogen atoms, thereby promoting the formation of hydroperoxides, aldehydes, and polymeric compounds [10]. In contrast to these PUFA-rich oils, PO contains a high SFA content (45.47%, mainly palmitic acid, C16:0), which is generally associated with relatively high thermal stability [16]. However, excessive SFA intake is linked to cardiovascular risks [41]. CNO exhibits the highest MUFA level (57.79%), dominated by oleic acid (C18:1). CSO shows a more balanced profile, with PUFA (46.63%) and MUFA (29.94%) contents. In summary, SFO and SBO are rich in PUFA and thus more prone to oxidative degradation, while PO is SFA-dominant and is generally considered to possess relatively high thermal stability. CNO and CSO possess a more balanced fatty acid profile.

3.2. Changes in Physical and Chemical Properties

3.2.1. Changes in TPC

Figure 1A illustrates changes in TPC values among five different oils during deep-frying. The TPC levels of all five oils increased over time with frying times (p < 0.05). These results are consistent with previous studies [11,42], indicating a progressive accumulation of degradation products, including TGP, TGD, oxidized triglyceride monomer (oxTGM), diacylglycerol (DAG), monoacylglycerol (MAG), and FFAs. Among all the oils, SFO consistently exhibited the highest TPC levels, reaching 42.2% after 32 h of deep-frying, followed by SBO (40.3%) and CSO (37.6%). In contrast, PO and CNO maintained significantly lower TPC levels throughout the frying process, with PO displaying the lowest final TPC level (29.8%) at the end of frying, reflecting a more favorable oxidative stability profile. The greater accumulation of TPC observed in SFO and SBO may be attributed to their fatty acid compositions, particularly their high linoleic acid (C18:2) content, which has been positively associated with TPC formation [43]. In addition, the resting intervals during intermittent frying may enhance oxygen dissolution, thereby promoting the accumulation of TPC [44]. Conversely, PO and CNO contain comparatively higher proportions of SFA and MUFA, which are generally associated with improved thermal stability and lower levels of polar compound formation during extended frying. Collectively, these findings suggest that SFO, SBO, and CSO exhibit less favorable thermal stability characteristics under the applied frying conditions, whereas PO and CNO demonstrate greater resistance to TPC accumulation and therefore appear more suitable for sustained high-temperature frying.

3.2.2. Changes in AV

Figure 1B illustrates the changes in AV for the five oils during 32 h of intermittent frying. All oils exhibited a significant increase in AV (p < 0.05), reflecting the progressive accumulation of FFAs. Initially, SFO exhibited the lowest initial AV (0.083 mg/g), while CNO had the highest (0.347 mg/g). After 6 h of deep-frying, PO showed a significantly higher AV than all other oils (p < 0.05) and maintained the highest level throughout the frying process. The AV of CNO also showed a significant upward trend (p < 0.05), second only to that of PO. In contrast, SFO maintained the lowest AV across the frying period, with a final value below 0.60 mg/g. This suggests that oil hydrolysis may be relatively limited, or that the hydrolyzed FFAs may have participated in subsequent reactions during frying. These results align with those reported by Abd et al. [15], who observed higher FFA levels in PO after 160 frying cycles, followed by CNO, SBO, and SFO. This may be attributed to the higher SFA and MUFA content in PO and CNO, which are more resistant to oxidation than PUFA. Consequently, this relatively higher oxidative stability may allow FFAs to persist and accumulate by limiting their further transformation into more complex degradation products [12]. In contrast, FFAs generated from the hydrolysis of highly unsaturated oils may be more susceptible to volatilization or secondary reactions, making them less likely to accumulate in the oil and resulting in lower observed AV levels over frying time. Overall, a lower AV does not necessarily indicate better oil quality; instead, it may reflect a different degradation pathway and potentially faster deterioration.

3.2.3. Changes in Color

Figure 2 shows the color evolution of five vegetable oils before and after frying. Initially, all oils appeared light, ranging from pale yellow to light brown, whereas after frying, they darkened to varying extents, shifting toward orange-brown or dark brown. The darkening of frying oils can be attributed to the accumulation of oxidative polymerization products formed during lipid oxidation, the presence of natural pigments (such as carotenoids, chlorophylls, and gossypol), and high-temperature-carbonized food residues remaining in the oils [45,46]. Additionally, melanin and other pigmented compounds from the Maillard reactions of food proteins can migrate into the oils, further intensifying their colors [47].
To quantify color changes in oils during the frying process, this study measured the color parameters of the oils, including L* (lightness), a* (red/green), b* (yellow/blue), and ΔE [48]. Among these, changes in ΔE reflect the overall color variation in the oils during frying and can capture color alterations induced by chemical processes such as oxidation, polymerization, or Maillard reactions [19,49]. As shown in Table S2 and Figure 1C, with increasing frying time, L* and b* values decreased significantly (p < 0.05), indicating a reduction in brightness and a trend toward darker tones, whereas a* and ΔE values increased significantly (p < 0.05), reflecting enhanced redness and overall darkening. Previous studies have confirmed the strong association between color deterioration and physicochemical changes during thermal processing by establishing kinetic models of ΔE as a function of temperature and time in fried carrots [50]. However, according to the Deutsche Gesellschaft für Fettwissenschaft e.V. (DGF), the color of oil does not directly correspond to fat deterioration. Therefore, although color parameters cannot replace core physicochemical indices such as TPC, their pronounced changes over time render them a valuable and intuitive auxiliary indicator for monitoring thermal load and the accumulation of reaction products during frying. SFO exhibited the most pronounced increase in ΔE, reaching 9.39 within 12 h and subsequently approaching a plateau. SBO followed a similar trend, stabilizing at 8.57–9.00 after 20 h. These changes are likely associated with thermal oxidation and the subsequent formation of aldehydes, ketones, and polymeric compounds that contribute to oil darkening. These polymers, whether cyclic or acyclic, increase viscosity and form brown residues during frying [10]. In contrast, PO showed a more moderate increase in ΔE, reaching 6.51 after 32 h, while CNO and CSO exhibited comparatively minor color changes, with final ΔE values around 3.00. Overall, all oils darkened significantly during frying, with SFO and SBO exhibiting the most pronounced color changes over time, consistent with their high PUFA content.

3.2.4. Changes in Oxidative Stability

The oxidative stability of oils can be effectively determined by evaluating conventional quality parameters such as POV, p-AV, and TOTOX [51]. Changes in POV, p-AV, and TOTOX values for different oils during frying are shown in Table S3.
The highest POV observed in SFO indicated extensive oxidative degradation. In contrast, PO exhibited consistently lower POV levels during most of the frying period, reflecting a more favorable thermal and oxidative stability profile. CNO, CSO, and SBO exhibited moderate POV levels throughout the frying process. In this study, the POV of different oils did not exhibit a simple linear increase but instead showed pronounced fluctuations. POV primarily reflects the accumulation level of primary lipid oxidation products, namely hydroperoxides [52,53]. During frying, the continuous progression of free-radical chain reactions generally promotes the formation of hydroperoxides, thereby leading to an increase in POV [10]. However, with prolonged frying time, the actual trend of POV is governed by the dynamic balance between the “formation rate” and the “decomposition rate” of hydroperoxides. Because hydroperoxides are highly thermally unstable, their O–O bonds readily undergo cleavage under sustained high temperatures, further triggering chain-branching reactions and generating aldehydes, ketones, and acids as secondary oxidation products [10,51,54]. Consequently, when the temperature-induced decomposition rate exceeds the formation rate, POV decreases; conversely, when the formation rate predominates, POV increases. The alternating dominance of these formation and decomposition processes ultimately results in the nonlinear fluctuations observed for POV. Notably, a decrease in POV at the later stage of frying does not indicate an improvement in oil quality; rather, it signifies that lipid oxidation has shifted from the primary stage to an advanced degradation stage, during which large amounts of secondary and even tertiary oxidation products continuously accumulate in the system, thereby intensifying the overall deterioration of the oil. This phenomenon is consistent with previous reports [38,44]. Meanwhile, the p-AV increased significantly (p < 0.05), although the extent of change differed among oils. Higher p-AV values were observed in SBO, SFO, and CSO compared to PO and CNO, which may be related to the decomposition of unstable primary oxidation products into secondary compounds. Aladedunye and Przybylski [55] suggested that elevated p-AV may be linked to initial dissolved oxygen levels in frying oil and the thermo-oxidative degradation it promotes. Similarly, TOTOX values increased significantly with frying time (p < 0.05), with more pronounced increases observed in SFO and SBO, likely due to their higher PUFA contents, which make them more prone to free radical attack and chain oxidation. By the end of frying, the values reached 580.24 and 389.26, respectively. TOTOX values followed a similar trend to p-AV, suggesting that secondary oxidation dominated throughout frying [46]. In summary, oxidative degradation became increasingly evident with frying time, with PO and CNO exhibiting comparatively greater oxidative stability under the conditions examined.

3.2.5. Changes in IV

As shown in Figure 3A, all oils exhibited a significant decrease in IV during frying (p < 0.05), reflecting the loss of double bonds and a decrease in unsaturation caused by oxidative degradation [56]. SBO had the highest initial IV (131.1 g/100 g), which remained relatively stable for the first 8 h before declining markedly to 114.1 g/100 g. Similarly, SFO, which started with a comparable initial IV, followed a similar downward trend, reaching 112.6 g/100 g by the end of frying. In contrast, PO exhibited the smallest overall decrease, losing only about 7.50 g/100 g over the frying period. These results indicate that PUFA-rich oils (SFO, SBO) are more susceptible to oxidation and unsaturated bond degradation under thermal stress, whereas SFA-rich oils (POs) show greater oxidative stability [57]. Overall, a pronounced decrease in IV reliably indicates oxidative degradation, particularly in oils that are unstable and highly unsaturated.

3.2.6. Changes in CV

As shown in Figure 3B, the CV of all oils increased significantly with frying time (p < 0.05), indicating advanced oxidative degradation and the formation of carbonyl compounds, which are key contributors to off-flavors and reduced nutritional quality in fried foods [28,58]. CSO exhibited the highest initial CV (15.8 meq/kg), significantly higher than the other oils (p < 0.05), likely due to residual impurities from incomplete refining. SFO and SBO exhibited the greatest increases in CV, reaching 122.9 and 119.6 meq/kg, respectively, by the end of the 32 h frying period. In contrast, PO displayed a more moderate increase, culminating at 102.9 meq/kg at the conclusion of the experiment. These trends correspond with fatty acid composition: PUFA-rich oils are more susceptible to oxidation, resulting in more pronounced increases in CV, whereas SFA-rich oils such as PO are more stable [59]. Taken together, the combined analysis of POV, p-AV, CV, and other oxidation indicators demonstrates that oils with higher saturation levels (e.g., PO and CNO) possess greater oxidative stability.

3.3. Changes in TAG Degradation and Polymerization Products

Vegetable oils are primarily composed of TAG, especially in the refined oils, which accounts for over 95.0% of the total lipid content. In certain types of olive oil, the TAG content can exceed 99.0% [60,61]. In frying operations, alterations in TAG are directly related to the physicochemical indicators, such as TPC, AV, and related indices. However, the specific reaction pathways of TAG themselves remain unclear in prior studies, necessitating further investigation to explore the in-depth mechanism underlying these changes. As shown in Figure 4, significant differences were observed in the initial TAG contents among the oils, with SBO exhibiting the highest level (98.1%) and PO the lowest (92.1%). As the frying process progressed, significant reductions in TAG content were observed in all oils, with net losses in the order of SFO (30.4%) > SBO (25.8%) > CSO (24.9%) > CNO (21.2%) > PO (19.3%). Oils rich in PUFA, such as SFO and SBO, exhibited greater extents of TAG loss, while PO and CNO—rich in SFA or MUFA—were relatively more thermally stable. Chen et al. [62] similarly observed that highly unsaturated soybean oil displayed the largest degree of TAG breakdown during frying.
TAG undergoes degradation through oxidation and hydrolysis, leading to the formation of DAG and MAG [63]. PO had the highest initial DAG content (7.15%), while SFO, CNO, and CSO ranged from 1.64% to 2.09%, and SBO was the lowest at 0.94%. Despite these initial differences, DAG levels remained relatively stable during frying, suggesting that hydrolysis is not the dominant degradation pathway under prolonged high temperatures. This simultaneously reflects the inherent thermal stability of DAG, which may even exceed that of TAG under these specific conditions [64]. The MAG contents remained minimal across all oil samples and demonstrated a progressive decline with prolonged thermal exposure during frying. This result indicates that MAG, acting as a transient intermediate, is prone to further transformation into FFAs and secondary oxidation products under elevated thermal conditions.
Besides the degradation pathways, TAG undergoes polymerization during thermal treatment, resulting in the formation of polymeric species such as TGD and TGP [65]. TGD and TGP concentrations significantly increased (p < 0.05) over time in all oils during frying. This trend is consistent with previous studies by Ahmad et al. [16] and Xu et al. [66], suggesting that TAG polymerization under thermal stress is likely driven by radical-mediated crosslinking and Diels–Alder-type cycloaddition. After 32 h of frying, SFO showed the highest total polar polymer content (31.6%), followed by CSO (26.5%), SBO (25.8%), CNO (20.7%), and PO (20.2%). These differences reflect the influence of fatty acid composition, as PUFA-rich oils (e.g., SFO) are more susceptible to oxidative degradation and polymer formation, while oils with higher SFA or MUFA content (e.g., CNO, PO) exhibit comparatively greater thermal stability. Overall, the extent of TAG degradation and polymerization during frying is closely linked to the fatty acid composition. The accumulation of polar polymers further indicates that polymerization predominates over hydrolysis under prolonged heating, suggesting their potential as reliable indicators for monitoring oil quality during frying.

3.4. Changes in 3-MCPDE, 2-MCPDE, and GE Contents

The changes in 3-MCPDE, 2-MCPDE, and GE contents during the course of the frying cycle are displayed in Figure 5. In accordance with Regulation (EU) 2020/1322 issued by the European Commission, the maximum permissible levels of 3-MCPDE and GE in refined edible oils are defined as 1250 μg/kg and 1000 μg/kg, respectively. Although current regulatory frameworks do not specify a threshold to limit the content of 2-MCPDE in oil-based products, this study incorporated the quantification of 2-MCPDE. This analytical inclusion was necessitated by their documented potential for interconversion to 3-MCPDE via isomerization processes under thermal treatment, as evidenced in prior mechanistic studies [11].
Figure 5A,B show the changes in 2-MCPDE and 3-MCPDE levels during frying across different oils. Initially, PO exhibited markedly higher levels of 2-MCPDE (2010 μg/kg) and 3-MCPDE (3630 μg/kg), significantly exceeding those of the other oils (p < 0.05). However, both compounds declined rapidly in PO, with 2-MCPDE decreasing to 1020 μg/kg and 3-MCPDE to 607 μg/kg after 8 h, and becoming nearly undetectable at 32 h. This phenomenon is consistent with previous reports [15,67]. In contrast, MCPDE levels in CNO exhibited an increasing trend during the early stage of frying, with 2-MCPDE reaching a maximum at 16 h (341 μg/kg) and 3-MCPDE peaking at 24 h (759 μg/kg). This behavior may be attributed to the higher degree of unsaturation of FFAs in CNO, which are more prone to dissociation than those in PO, thereby promoting the release of hydrogen ions and an acidic environment in the reaction system [10]. Under such conditions, acylglycerols undergo protonation to form key cyclic acyloxonium ion intermediates, which subsequently undergo nucleophilic substitution with reactive chlorine donors to generate MCPDEs [12]. The formation of MCPDEs is highly dependent on the synergistic effects of acylglycerols, chlorine sources (inorganic or organic), and FFAs [68]. Moreover, it depends not only on the content of chlorides present but also on their chemical reactivity [69]. For example, NaCl exhibits relatively high thermal stability and under anhydrous conditions appears unable to directly provide chlorine-free radicals or chloride ions for MCPDE formation [70]. Because crispy meat continuously supplies water and inorganic chlorides (e.g., NaCl) to the system, reactive chlorine donors derived from chlorine free radicals or chloride ions can be continuously generated and participate in the reaction under acidic and high-temperature conditions [69]. This effect is particularly pronounced in CNO with a relatively high initial acidity. As reported by Li et al. [71], an increase in acidity can promote MCPDE formation. SFO, CSO, and SBO maintained consistently low levels of MCPDEs (<500 μg/kg), which is potentially due to enhanced transformation under oxidative conditions or the absence of precursors necessary for MCPDE formation during early frying stages. The results indicate that 2-MCPDE and 3-MCPDE at a high initial content, such as PO, may undergo further breakdown or participate in polymerization reactions more extensively, but oils like CNO may favor continued formation despite lower initial oxidative breakdown. It seems there exists a balance of competitive reactions between polymerization and the production of 2-MCPDE and 3-MCPDE.
The changing trends of GE during frying vary widely depending on the kind of oil, as seen in Figure 5C. Initially, PO and CSO had high GE contents—988 µg/kg and 884 µg/kg, respectively. Both showed gradual decreases over time, with PO decreasing to 462 µg/kg and CSO to 538 µg/kg after 32 h. This reduction is likely due to the high reactivity of the GE epoxy ring, which undergoes nucleophilic attack by water and free fatty acids [66,72]. In contrast, SBO maintained relatively stable GE levels with minor fluctuations, while the levels in SFO and CNO remained undetectable throughout frying, indicating minimal initial contamination and no significant in situ formation under the tested conditions. In conclusion, the data imply that fatty acid saturation and glyceride degradation behavior together impact the risk of GE and MCPDE generation during frying. Under the present frying conditions, prolonged thermal exposure appeared to favor the decomposition or transformation of these contaminants rather than their accumulation, particularly in the later stages of frying. Meanwhile, SFO, CSO, and SBO exhibit lower contaminant levels, implying that fewer opportunities exist to support reaction pathways for contaminant formation during extended frying of these oils. Overall, producing frying oils with low initial contaminant levels, particularly 3-MCPDE, such as PO, is critical for ensuring food safety.

3.5. PCA of Oil Samples

The quality changes in various oils during deep-frying were systematically evaluated using PCA. As shown in Figure 6, the PCA results indicated that the first two principal components exhibited eigenvalues of 7.35 (PC1) and 2.59 (PC2) and together explained 71.8% of the total variance (PC1: 52.5% and PC2: 18.5%), effectively distinguishing the quality variations among different oils throughout the frying process. The loading plot revealed that PC1 was primarily associated with the accumulation of products such as TPC, CV, p-AV, TGD, and TGP, reflecting the overall deterioration trend of oil quality. The increase in these degradation markers led to higher PC1 scores, indicating a decline in oil quality. PC2 integrated changes in oil color parameters (L*, a*), IV, and glycerides (DAG and MAG), highlighting differences in degradation characteristics among the oils. Therefore, monitoring critical indicators such as TPC and TGP can effectively assess the quality changes in frying oils, while additional evaluation based on color attributes and IV can provide a more comprehensive comparison of frying suitability across different oils in practical applications. The score plot clearly demonstrated that different oil samples exhibited distinct distribution. SFO and SBO exhibited broad dispersion along both PC1 and PC2, indicating substantial thermo-oxidative degradation during prolonged frying. This degradation is evidenced by elevated levels of polar compounds and polymers. Conversely, CNO and PO demonstrated markedly constrained clustering, with sample coordinates concentrated in the negative PC1 quadrant, a region associated with reduced polar compound generation and comparatively lower progression of oxidative changes. Overall, these results underscore the significant degradation in physicochemical properties and relatively lower oxidative resistance of SFO, SBO, and CSO. In contrast, CNO and PO maintained higher stability, likely due to their unique fatty acid compositions and higher concentrations of endogenous antioxidant bioactive compounds.

3.6. Correlation Analysis of Indicators

To further elucidate the relationships among physicochemical parameters, glycerides, and contaminants in refined edible oils during frying operations, Pearson’s correlation analysis was conducted. The results are shown in Figure 7.
TPC exhibited strong positive correlations with TGP (r = 0.99, p < 0.01) and TGD (r = 0.96, p < 0.01), indicating that the accumulation of polar polymers is a major contributor to the increase in TPC. Oxidation indices such as p-AV, TOTOX, and CV also showed strong positive correlations with TPC (r = 0.90–0.97, p < 0.01), highlighting the important role of oxidative degradation in the formation of polar compounds. Overall, polymerization and oxidation products exhibited stronger correlations with TPC than hydrolysis products. Despite the moisture released from the crispy meat during frying, the intense thermal conditions favor radical-mediated polymerization reactions, leading to the formation of high-molecular-weight aggregates (TGD and TGP) that constitute the majority of the polar fraction.
Significant inverse correlations were observed between refining-derived contaminants (2-MCPDE, 3-MCPDE, and GE) and deterioration markers (TPC, TOTOX, TGD, TGP, and CV) during thermal frying (p < 0.05). In contrast, these contaminants were positively correlated with DAG and MAG levels (r > 0.5, p < 0.05), suggesting a potential association between DAG/MAG and the formation of these contaminants. Mechanistically, partial hydrolysis of TAG during the initial stage of frying produces DAG and MAG, which may participate in heat-induced chlorination or epoxide-related rearrangement reactions, thereby influencing the formation of MCPDEs and GE [73]. Furthermore, L* and b* values exhibited moderate to strong correlations with polar polymers and contaminants (p < 0.05), suggesting that these color parameters may serve as rapid, non-invasive auxiliary indicators for monitoring oil quality changes and contaminant formation during deep-fat frying. However, for accurate evaluation, they should be interpreted in conjunction with other physicochemical indices. In addition, the potential influence of food-derived pigments and surface residues should be considered when applying color-based models in complex frying systems.

4. Conclusions

This study reports on the quality changes in various vegetable oils during a four-day intermittent frying of crispy meat. In terms of oxidative stability, PO and CNO demonstrated superior resistance, characterized by lower time-dependent increases in TPC, TOTOX, CV, and polar polymers. In contrast, PUFA-rich oils (SFO, CSO, and SBO) underwent pronounced degradation; after 32 h of frying, their TPC and polar polymer concentrations surpassed 37.0% and 25.0%, respectively. PCA also revealed pronounced segregation among oil matrices, with CNO and PO demonstrating tightly clustered patterns—a pattern indicative of relatively greater oxidative stability—compared to the broader dispersion observed in SFO and SBO. Prolonged thermal frying led primarily to the decomposition or transformation of 2-MCPDE, 3-MCPDE, and GE rather than their accumulation, particularly during the later stages of frying. Pearson’s correlation analysis indicated that DAG and MAG were positively correlated with oil refining process contaminants such as 2-MCPDE, 3-MCPDE, and GE (r > 0.5, p < 0.05). However, the significant negative correlations (p < 0.05) observed between these contaminants and the markers of TPC, TOTOX, TGD, TGP, and CV suggest a potential competitive relationship between their formation and lipid degradation reactions during thermal frying.
This paper provides a comprehensive insight into the oil-specific deterioration and contaminant formation patterns of five vegetable oils during intermittent deep-fat frying of crispy meat, thereby offering scientific guidance for oil selection and food safety management in the catering industry. Future research may focus on the standardization of color parameters such as L* and b* as rapid, non-invasive auxiliary indicators for monitoring oil degradation and contaminant generation (e.g., MCPDEs, GE, and polar polymers) during deep-frying. Nevertheless, these color metrics should be applied in conjunction with other physicochemical indices, and the establishment of robust predictive models and well-defined threshold values would facilitate real-time quality control in industrial frying operations. This study primarily adopted an ANOVA-based analytical strategy, which, although capable of identifying significant differences among time points, does not explicitly model within-system temporal correlation and therefore has limitations in inferring degradation kinetics or precisely comparing degradation rates among different oils. Future studies may apply linear mixed-effects models (LMMs) to further elucidate the dynamic evolution of oil degradation.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/foods15040771/s1; Figure S1: Chromatogram of the 37-component fatty acid methyl ester (FAME) standard mixture; Table S1: Calibration curves for 2-MCPDE, 3-MCPDE, and GE; Table S2: Changes in L*, a* and b* during frying; Table S3: Changes in POV, p-AV and TOTOX during frying.

Author Contributions

Z.W.: Writing—original draft, Visualization, Investigation, Data curation. Y.L.: Methodology, Investigation. Q.L.: Methodology, Formal analysis, Data curation. R.L.: Investigation, Formal analysis. M.C.: Methodology, Investigation. S.Z.: Supervision, Writing—review and editing, Funding acquisition, Conceptualization. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by Beijing High-level Talent Team Construction Project, China (19008025035).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data supporting this study are provided within the article and Supplementary Materials. Additional information is available from the corresponding authors upon request.

Acknowledgments

Authors gratefully acknowledge the panelists of Laboratory of Natural Products Bio-Synthesis and Application, Beijing Technology and Business University.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Changes in TPC (A), AV (B), and ΔE (C) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types.
Figure 1. Changes in TPC (A), AV (B), and ΔE (C) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types.
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Figure 2. Comparison of colors pre-frying and post-frying.
Figure 2. Comparison of colors pre-frying and post-frying.
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Figure 3. Changes in IV (A) and CV (B) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types.
Figure 3. Changes in IV (A) and CV (B) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types.
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Figure 4. Changes in TAG degradation and polymerization products in SFO (A), CNO (B), PO (C), CSO (D) and SBO (E) during frying. Notes: The content of the TAG utilizes the right Y-axis while the remainder uses the left Y-axis. Means with different lowercase letters are significantly different at p < 0.05 for 32 h frying time.
Figure 4. Changes in TAG degradation and polymerization products in SFO (A), CNO (B), PO (C), CSO (D) and SBO (E) during frying. Notes: The content of the TAG utilizes the right Y-axis while the remainder uses the left Y-axis. Means with different lowercase letters are significantly different at p < 0.05 for 32 h frying time.
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Figure 5. Changes in 2-MCPDE (A), 3-MCPDE (B), and GE (C) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types. ND indicates <LOD.
Figure 5. Changes in 2-MCPDE (A), 3-MCPDE (B), and GE (C) during frying. Notes: Means with different lowercase letters are significantly different at p < 0.05 within the same oil type across the 32 h frying period. Means with different uppercase letters at the same frying time are significantly different at p < 0.05 among different oil types. ND indicates <LOD.
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Figure 6. PCA analyses results. (A) Loading Plot, PC1 versus PC2 of all samples; (B) Score Plot, PC1 versus PC2 of data from determinations used as variables.
Figure 6. PCA analyses results. (A) Loading Plot, PC1 versus PC2 of all samples; (B) Score Plot, PC1 versus PC2 of data from determinations used as variables.
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Figure 7. Correlation analysis between indicators.
Figure 7. Correlation analysis between indicators.
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Table 1. Fatty acid composition (%) of fresh oils.
Table 1. Fatty acid composition (%) of fresh oils.
ParametersSFOCNOPOCSOSBO
C14:00.07 ± 0.00 e0.13 ± 0.00 b0.94 ± 0.00 d1.09 ± 0.00 a0.16 ± 0.01 c
C15:00.01 ± 0.00 c0.05 ± 0.00 a0.04 ± 0.00 b0.02 ± 0.00 c-
C16:06.27 ± 0.01 e8.33 ± 0.04 d39.35 ± 0.07 a18.37 ± 0.12 b12.75 ± 0.04 c
C17:00.03 ± 0.00 c-0.09 ± 0.00 b0.28 ± 0.01 a0.24 ± 0.03 a
C18:03.27 ± 0.00 b1.19 ± 0.07 e4.53 ± 0.01 a2.09 ± 0.11 d3.14 ± 0.04 c
C18:127.30 ± 0.00 d53.34 ± 0.13 a43.45 ± 0.07 b29.94 ± 0.01 c26.54 ± 0.02 e
C18:261.40 ± 0.00 a21.65 ± 0.33 d10.45 ± 0.07 e43.15 ± 0.15 b42.42 ± 0.02 c
C18:30.09 ± 0.00 d10.6 ± 0.15 b0.13 ± 0.00 d3.48 ± 0.01 c12.91 ± 0.07 a
C20:00.24 ± 0.00 e0.87 ± 0.01 b0.38 ± 0.00 d1.07 ± 0.01 a0.72 ± 0.01 c
C20:10.16 ± 0.00 c2.99 ± 0.07 a0.20 ± 0.00 bc-0.31 ± 0.02 b
C22:00.73 ± 0.00 b0.86 ± 0.10 a0.07 ± 0.00 d0.45 ± 0.02 c0.68 ± 0.03 b
C24:00.25 ± 0.00 b0.28 ± 0.01 a0.07 ± 0.00 e0.11 ± 0.00 d0.13 ± 0.00 c
SFA10.87 ± 0.01 e11.72 ± 0.07 d45.47 ± 0.09 a23.47 ± 0.22 b17.82 ± 0.00 c
MUFA27.46 ± 0.00 d57.97 ± 0.31 a43.65 ± 0.07 b29.94 ± 0.01 c26.85 ± 0.00 e
PUFA61.49 ± 0.00 a32.25 ± 0.18 d10.58 ± 0.07 e46.63 ± 0.15 c55.33 ± 0.09 b
Notes: a–e Values within the same row with different lowercase letters are significantly different (p < 0.05) for each parameter.
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MDPI and ACS Style

Wang, Z.; Liu, Y.; Li, Q.; Liu, R.; Cai, M.; Zhao, S. Comparative Assessment of Quality Deterioration in Various Vegetable Oils During Deep-Fat Frying of Crispy Meat. Foods 2026, 15, 771. https://doi.org/10.3390/foods15040771

AMA Style

Wang Z, Liu Y, Li Q, Liu R, Cai M, Zhao S. Comparative Assessment of Quality Deterioration in Various Vegetable Oils During Deep-Fat Frying of Crispy Meat. Foods. 2026; 15(4):771. https://doi.org/10.3390/foods15040771

Chicago/Turabian Style

Wang, Zelong, Yinuo Liu, Qiuxiao Li, Ruijia Liu, Ming Cai, and Shuna Zhao. 2026. "Comparative Assessment of Quality Deterioration in Various Vegetable Oils During Deep-Fat Frying of Crispy Meat" Foods 15, no. 4: 771. https://doi.org/10.3390/foods15040771

APA Style

Wang, Z., Liu, Y., Li, Q., Liu, R., Cai, M., & Zhao, S. (2026). Comparative Assessment of Quality Deterioration in Various Vegetable Oils During Deep-Fat Frying of Crispy Meat. Foods, 15(4), 771. https://doi.org/10.3390/foods15040771

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