Abstract
This study aimed to investigated metabolism and browning-related enzyme
differences of Fuji apples in fresh (FC), browning pulp (BR), and
browning inhibition pulp (CM) at 0, 4, 6, and 8 months of storage.
Apples stored for 4-months exhibited the highest browning rate and
color differences, with browning inhibition effectiveness decreasing
over time. PPO and POD activity increased, while CAT and SOD decreased.
Untargeted metabolomics revealed differential metabolites (445, 468,
265) in FC, BR, and CM among four-storage, mainly related to
carbohydrate, lipid, and amino acid metabolism. In BR vs. FC,
differential metabolites were primarily enriched in secondary
metabolite biosynthesis (within 6-months) and energy metabolism (after
8-months). In CM vs. FC, differential metabolites were significantly
enriched in nitrogen metabolism. Nitrogen metabolite accumulation
induces browning, which can be mitigated by CaCl[2] through alleviating
nitrosative stress and oxidative damage. These findings provide
metabolic insights into quality control during apple storage and
processing.
Keywords: Apple processing browning, Enzyme activity, Metabolites
composition
Graphical abstract
Unlabelled Image
[31]Open in a new tab
Highlights
* •
Apples stored for 4 months showed the highest browning rate and
color differences.
* •
PPO, POD, PAL increased, while SOD, CAT decreased in apple storage
period.
* •
Carbohydrate metabolism regulates browning by maintaining high
energy levels.
* •
Activation of the glycerophospholipid pathway mitigates senescence
during storage.
* •
Nitrogen metabolite induces browning, Ca^2+ mitigates it by
alleviating nitrosative stress.
1. Introduction
Apples (Malus domestica), valued for their rich nutritional profile and
bioactive metabolites, are cultivated and consumed worldwide, with an
annual production of exceeding 95 million tons. The majority of apples
are cultivated in China (around 47.57 million tons), Turkey (4.82
million tons), and the United States (4.43 million tons) ([32]FAOSTAT,
2023). As a seasonal fruit, apples have limited immediate consumption,
so the bulk of the harvest is stored to ensure long-term availability.
After harvesting, fully ripe apples can be refrigerated for up to
6 months or stored in a controlled atmosphere for up to 8 months,
depending on the variety ([33]Han et al., 2023). The ‘Fuji’ apple
variety is preferred in the cold storage supply chain due to its
excellent storability. Given the nature of climacteric fruit, apples
exhibit post-harvest ripening. Studies have shown continuous changes in
the physiological metabolism and physicochemical properties of apples
during storage ([34]Butkeviciute et al., 2022). [35]Wang et al. (2024)
linked the progressive reduction in energy metabolism-related enzyme
activities and energy levels in apples storage. Substantial research
supports the significant role of organic acid ([36]Han et al., 2023),
lipid ([37]Liu et al., 2022), and amino acid ([38]Bekele et al., 2016)
metabolism in influencing apple quality during storage. Extended cold
storage has been identified the absence of secondary metabolites such
as terpenoids, aldehydes, and phenolics as compared to pre-storage
apples ([39]Chai et al., 2020). Additionally, studies have highlighted
distinct expression patterns of hexose and cell-wall carbohydrate
metabolism genes in stored apples ([40]Dambros et al., 2023). While
many studies have explored the impact of storage on apple fruit,
limited research has delved into the effect of postharvest storage on
processing quality of apple. Similarly, studies on other foods have
also demonstrated that the raw materials composition and storage
conditions can influence the overall quality of processed products
([41]Li et al., 2025; [42]Ma et al., 2024; [43]Mazur et al., 2014).
Pulping is the most fundamental and crucial method in apple processing.
It remains unclear how metabolic changes in apples during storage
affect apple pulp quality.
Apples can be processed into juice, cider, sauce, canned goods,
fresh-cut segments, and dried products, where enzymatic browning
commonly occurs, leading to unfavorable quality deterioration.
Therefore, browning can be used as an indicator to assess the quality
of apples during processing. Enzymatic browning is generally triggered
by the oxidation of polyphenols catalyzed by polyphenol oxidase (PPO)
and phenol peroxidase (POD) ([44]Zuo et al., 2021). Numerous ongoing
investigations are elucidating the intricate relationship between
enzymatic browning and the overall physiological metabolism of fruit
and vegetables ([45]Li, Huang, et al., 2024; [46]Shi et al., 2022). For
instance, the degradation of the cell membrane was related to lipid
metabolism, which resulting in fresh-cut eggplant browning ([47]Liu et
al., 2022). The biosynthesis of secondary metabolites, flavonoids, and
phenylpropanoids, as well as sugar metabolism, are associated with the
browning of ‘Meihong’ apples ([48]Zuo et al., 2021). And the browning
of fresh-cut potato was caused by respiratory metabolism, and multiple
amino acid metabolic pathways ([49]Qiao et al., 2022). Furthermore,
various strategies are being developed to counteract fruit browning.
Among these, calcium chloride (CaCl[2]) has emerged as an effective
anti-browning agent by regulating enzymatic activity and physiological
metabolism ([50]Ahmad et al., 2024). Calcium ions (Ca^2+) stabilize
membrane integrity and cell wall structure, while mitigating fruit
softening and senescence. In this study, CaCl[2] was used to pretreat
apples for browning intervention in processing, with metabolomic
profiling to illustrate stress response of apple at different storage
periods.
Metabolite levels can be considered the ultimate response of biological
systems to external conditions. Metabolomics is commonly utilized to
reflect the metabolite status of fresh agricultural products during
storage. To clarify the processing quality indicated by browning in
apple at different storage periods, this study investigated the
metabolomics variation of Fuji apples stored for 0, 4, 6, and 8 months,
and compared their metabolomics differences with browning pulp and
browning inhibition pulp. It is of great significance to understand the
influence of storage on apple processing in order to optimize the
storage period and improve the processing quality of apples.
2. Material and methods
2.1. Material and sample treatments
Mature ‘Fuji’ apples (Malus domestica Borkh.) were harvested at
commercial maturity from an orchard in Wangjiayuan, Changping District,
Beijing, China (116°07′ E, 40°19′ N) on October 9, 2022. Immediately
after harvest, the fruits underwent a precooling treatment at 16 °C for
24 h, designed to rapidly remove field heat and suppress respiration.
Apples with uniform size, color, and free of mechanical injury or
disease were selected and subsequently stored at standard refrigeration
conditions (4 ± 2 °C, 90 ± 5 % relative humidity, normal atmosphere)
following USDA guidelines for long-term apple storage ([51]Gross et
al., 2014). Samples were collected after 0, 4, 6, and 8 months of cold
storage, based on reported browning timelines for ‘Fuji’ apples under
extended storage conditions ([52]Tanaka et al., 2018). For each storage
period, 80 apples were collected to ensure sufficient material for
processing and to account for potential sample loss. The apples were
then randomly divided into three groups for sample preparation: fresh
control (FC), browning pulp (BR), and browning-inhibited pulp (CM). FC
samples were prepared by peeling and cutting apples into 5 × 5 × 1 mm^3
slices, which were immediately frozen in liquid nitrogen and labeled as
F0, F4, F6, and F8, corresponding to the respective storage durations.
BR samples were obtained by pulping apple slices at room temperature
using a high-speed blender, the pulp was held for 10 min until
achieving marked and stable enzymatic browning, then frozen in liquid
nitrogen and labeled as B0, B4, B6, and B8. For CM samples, apple
slices were immersed in 2 % (w/v) calcium chloride (CaCl[2]) solution
for 30 s prior to pulping, followed by standing at room temperature for
10 min before being frozen in liquid nitrogen and labeled as C0, C4,
C6, and C8 ([53]Lara et al., 2024; [54]Zhang et al., 2019). Three
independent biological replicates were performed for each treatment at
each storage interval, with 8 apples per replicate (n = 24
apples/treatment/storage time). All prepared samples were stored at
−80 °C until further analysis.
2.2. Determination of browning degree
The chroma characters of browning pulp and browning inhibition pulp
were measured using a CM-5 spectrophotometer (Konica Minolta, Tokyo,
Japan). L*, a* and b* values were measured within 10 min of pulping.
The colorimeter was calibrated with a black and white calibration plate
prior to measurement. The results were based on the CIELAB (L*, a*, b*)
color space. ‘L*’, ‘a*’, and ‘b*’ represent lightness, redness, and
yellowness, respectively. The color differences (ΔE) and browning index
(BI) of the samples were calculated using the following formulas
([55]Hu et al., 2023):
[MATH: ΔE=a1∗−a0∗
2+b1∗−b0∗
2+L1∗−L0∗
2 :MATH]
[MATH: BI=100x−0.310.1
72 :MATH]
where
[MATH: x=a∗+1.75L∗5.645L∗+a∗−3.012b∗ :MATH]
The SpectraMagic NX program was utilized for the analysis of
chromaticity values. The horseshoe diagram was employed to illustrate
the trajectory of color shift in color space and to map it onto a
two-dimensional plane. Furthermore, the rate of ΔE change in three
minutes was used to quantify the browning rates. Meanwhile, ΔE and BI
values of all samples at 10 min were calculated.
2.3. Measurement of PPO, POD, SOD, CAT, PAL and H[2]O[2]
The activities of polyphenol oxidase (PPO), peroxidase (POD), catalase
(CAT), superoxide dismutase (SOD), phenylalanine ammonia-lyase (PAL)
and the content of H[2]O[2] were detected using G0113W, G0107W, G0105W,
G0101W, G0114W, and G0112W kits respectively (Suzhou Grace
Biotechnology Co., Ltd., Suzhou, China). The measuring steps were
performed following the manufacturer's instructions. PPO, POD, CAT,
SOD, and PAL activities were measured at 420, 470, 510, 450, and
290 nm, respectively, using a microplate reader. The H[2]O[2] content
was measured at 415 nm by a microplate reader and expressed as mmol
kg^−1. One unit of SOD activity (U g^−1) was defined as the amount of
enzyme required to induce 50 % inhibition of the xanthine oxidase
coupling reaction system. The CAT activity was determined as the
decomposition of 1 μmol of H[2]O[2] per minute per gram of tissue at
25 °C, which equates to one unit (U) of activity. Meanwhile, one unit
(U) of PPO, POD, and PAL activity was defined as the change in
absorbance values at 420 nm, 470 nm, and 290 nm, respectively, by 0.01,
1, and 0.05 per minute per gram of tissue in the reaction system, the
units were expressed as U kg^−1.
2.4. Untargeted metabolomics analysis by LC–MS/MS (HILIC/MS)
2.4.1. Sample preparation
The prepared apple samples were first ground into a fine powder using
liquid nitrogen. The apple powder was then mixed with 50 % methanol
solution at a ratio of 1:5 (w/v), vortexed, and stored at −20 °C
overnight. Subsequently, the solution underwent centrifugation at
15682 ×g for 20 min at 4 °C. The supernatant was carefully collected
and filtered through a 0.22 μm PVDF filter membrane in preparation for
UPLC-MS analysis. A quality control (QC) sample, comprising a mixture
of all samples, was also prepared. It is noteworthy that all extraction
reagents were pre-cooled to −20 °C before use.
2.4.2. Chromatography-mass spectrometry analysis
Untargeted metabolomics analysis was performed using an
ultra-high-performance liquid chromatography (UHPLC) system (ExionLC
2.0, DH Tech. Dev. Pte. Ltd., USA) coupled to a high-resolution mass
spectrometry (AB Sciex Triple TOF 5600, DH Tech. Dev. Pte. Ltd., USA).
Chromatographic separation was achieved using an ACQUITY UPLC HSS T3
column (1.8 μm, Waters, USA) maintained at 40 °C, with the sample
temperature held at 10 °C. The mobile phases consisted of 0.1 % formic
acid in water (A) and 0.1 % formic acid in acetonitrile (B), delivered
at a flow rate of 0.30 mL min^−1 under gradient elution.
The spectral signals were gathered using both positive and negative ion
scanning modes, with spectra obtained through information dependent
acquisition (IDA) in high-sensitivity mode. The Electrospray ionization
(ESI) source parameters were configured as follows: sheath gas flow
rate at 30 PSI, Gas1 flow rate at 50 PSI, Gas2 flow rate at 50 PSI,
temperature set to 500 °C, and spray voltage at 5500 V for the positive
ion mode and − 4500 V for the negative ion mode. The scanning duration
was set to 15 min, with the primary scan range spanned from 60 to
1250 m/z, and each primary scan followed by 12 secondary scans. The
secondary scan range was 50–1250 m/z, with a secondary accumulation
time of 30 ms. Additionally, the collision energy was set at ±35 for
the positive and negative ion mode, with a collision energy range of
theoretical frequency ± 15 EV. A QC sample was inserted every 10
samples to verify the stability of the instrument during the injection
process.
2.4.3. Metabolomics data processing
The raw data acquired from mass spectrometry were imported into
Progenesis QI (Waters) software for peak identification and data
preprocessing. The internal standard normalization method was utilized
in this data analysis. A multivariate analysis was then conducted on
the resulting data, which included details on the number of peaks,
sample names, and normalized peak areas. Principal component analysis
(PCA) and supervised orthogonal projections to latent structures
discriminate analysis (OPLS-DA) were used to visually observe group
separation and identify significantly altered metabolites.
Additionally, the variable importance in the projection (VIP) value of
the first principal component in the OPLS-DA analysis was determined.
Metabolites with VIP > 1, p < 0.05, and CV (coefficient of
variation) < 30 % in QC were considered significantly differential
metabolites. All experiments were performed in triplicate. To determine
the metabolic pathways related to differential metabolites, pathway
enrichment analysis was carried out by MetaboAnalyst 5.0
([56]https://www.metaboanalyst.ca/) and mbrole 2.0
([57]https://csbg.cnb.csic.es/mbrole2/). The metabolic pathways linked
to the compounds were elucidated through analysis of the pathway
database of the Kyoto Encyclopedia of Genes and Genomes (KEGG,
[58]https://www.genome.jp/kegg) ([59]Dadwal et al., 2023).
2.5. Statistical analyses
The experiments were carried out in triplicate (n = 3) to determine and
quantify the content. The data were presented as mean standard
deviation (SD). Statistical tools like Origin software (version 9.0)
and Microsoft Excel were employed for bar graphs. Heat maps and
enrichment analysis plots were created using the OmicStudio tools at
[60]https://www.omicstudio.cn/tool. Metabo-Analyst (version 5.0) was
utilized to produce PCA, OPLS-DA, cluster heat map, and co-relation
diagrams ([61]Dadwal et al., 2023).
3. Results
3.1. Browning characteristics of apples during different storage periods
Browning in apple pulp processing reflects both the external appearance
and internal quality of the fruit. The browning rate and degree are
influenced by the processing techniques and formulations, which is
worth clarifying ([62]Jiang et al., 2016). The rate and extent of
browning in apple pulp from four storage stages were analyzed in BR
(B0, B4, B6, B8) and CM (C0, C4, C6, C8), depicted by the Browning
Index (BI), total color change (ΔE), and chroma value locus (Table S1,
[63]Fig. 1). The BI value of BR gradually increased with extended
storage, except for B6, which had the lowest BI value of 749.56. The ΔE
value significantly increased and then gradually decreased with
extended storage, with B4 showing the highest ΔE value (34.13) and
browning rate (0.109). The trajectory of chromaticity changes was
consistent with the above results.
Fig. 1.
[64]Fig. 1
[65]Open in a new tab
Chroma value locus of the four storage apples with browning processing:
(A) L*, a*, b* locus of browning pulp of the four storage apples; (B):
Horseshoe diagram of browning pulp of the four storage apples; (C): L*,
a*, b* locus of browning inhibition pulp of the four storage apples;
(D): Horseshoe diagram of browning inhibition pulp of the four storage
apples. (B0: browning pulp of 0 month storage apple; B4: browning pulp
of 4 months storage apple; B6: browning pulp of 6 months storage apple;
B8: browning pulp of 8 months storage apple;
C0: browning inhibition pulp of 0 month storage apple; C4: browning
inhibition pulp of 4 months storage apple; C6: browning inhibition pulp
of 6 months storage apple; C8: browning inhibition pulp of 8 months
storage apple.)
In pulp with browning inhibition pretreatment, the chromaticity value
trace was significantly shorter compared to browning pulp, with minimal
changes observed on the horseshoe diagram. The BI value increased with
storage length, peaking at 664.13 for C6. The ΔE and browning rate also
showed noticeable increases, indicating that the browning inhibition
effect gradually diminished with extended storage. The browning rate
and degree of apples varied across storage periods during pulp
processing, and the browning inhibition pretreatment significantly
impacted browning accumulation. Thus, the analysis of browning data
revealed that the Fuji apples showed a tendency to susceptibility of
browning during processing increases with the prolongation of storage
duration. Concurrently, the effectiveness of browning inhibition
decreased as the storage period extended.
3.2. Browning related enzyme activity of apples during different storage
periods
It has been reported that processing induced membrane damage initiates
the loss of subcellular compartmentalization, leading to the
interaction between enzymes and the phenolic substrates associated with
browning. Therefore, investigating browning-related enzymes is crucial
to understanding the differences in browning during apple pulping
across four storage periods. The activities of PPO
(169.30–581.74 U g^−1), POD (1.43–4.40 U g^−1), PAL (0.01–0.24 U g^−1),
and the content of H[2]O[2] (0.14–0.25 mmol kg^−1) showed an increasing
trend in the FC across different storage periods. PPO plays a dual role
in stimulating plant disease resistance and catalyzing tissue browning.
Additionally, the three pivotal enzymes (PPO, POD, and PAL) are
involved in the biosynthesis and oxidation of secondary metabolites,
which function as defense-related enzymes typically used to assess
disease resistance ([66]Li, Wang, et al., 2020). Consequently, the
activities of these enzymes increase with apple senescence to resist
disease occurrence during storage. However, the activities of CAT
(8.59–13.36 U g^−1) and SOD (145.96–251.50 U g^−1) exhibited the
opposite trend, gradually decreasing by 36 % and 42 % during apple
storage, respectively ([67]Fig. 2). This decrease may be linked to
apple senescence, which is accompanied by lipid peroxidation and
increased susceptibility to browning during storage. SOD and CAT are
pivotal antioxidant enzymes responsible for scavenging reactive oxygen
species (ROS). ROS generation is triggered in plant cells under stress
conditions during fruit storage. SOD plays a crucial role in protecting
cells from oxidative stress, while CAT serves as the primary enzyme for
breaking down hydrogen peroxide (H[2]O[2]). Studies have indicated that
elevated activities of antioxidant enzymes, along with their
synergistic action, play a significant role in neutralizing ROS and
preserving cellular redox homeostasis, thereby influencing the
regulation of senescence processes in plants ([68]Jimenez et al.,
2002). Furthermore, recent studies have shown that enzyme assembly and
compartmentalization, mediated by phase separation, can significantly
influence metabolic efficiency and stress responses in plant systems
([69]Chen, Shi, Li, et al., 2025). Such mechanisms may also contribute
to the observed variations in PPO, POD, and antioxidant enzyme
activities during apple storage and browning.
Fig. 2.
[70]Fig. 2
[71]Open in a new tab
Comparison of activities of (A) polyphenol oxidase (PPO), (B)
peroxidase (POD), (C) catalase (CAT), (D) superoxide dismutase (SOD),
(E) phenylalanine ammonia-lyase (PAL), and (F) the content of H[2]O[2]
of the four-storage apples with browning pulp and browning inhibition
pulp. (Notes: The different letters above the bars indicate
statistically significant difference at p < 0.05.)
Regarding BR, PPO activity gradually increased with extended storage
periods. Compared to the FC of the corresponding storage period, PPO
activity in B0 and B4 increased, while B6 showed no significant change
and B8 markedly decreased. POD activity in BR increased with storage
period, with B6 reaching the highest enzyme activity at 7.19 U g^−1,
which was higher than that of FC. Browning pulp did not cause
significant changes in PAL enzyme, except for an increase in B0. The
H[2]O[2] content of BR increased significantly with the storage period,
particularly in B0, which increased by 4.7 times compared to F0. CAT
and SOD activities in BR decreased compared to FC. CAT activity in BR
decreased in B4, with no further changes in the subsequent storage
periods. SOD activity in BR gradually increased during the first
6 months of storage, then decreased thereafter.
In CM, there was a significant decrease in PPO and POD enzyme activity
compared to FC and BR counterparts. Among them, the PPO activity
increased by 2.3 times over the storage period, while POD activity
increased after storage, peaking at C4 by 1.7 times. This indicated
that pretreatment with calcium chloride (CaCl[2]) aids in suppressing
enzyme activities, thereby modulating the browning process, while the
four storage periods fruit possessed different responses to CaCl[2]
pretreatment. H[2]O[2] content in CM was lower than that in FC but
higher than that in BR, indicating the role of H[2]O[2] as a signaling
molecule in browning inhibition pretreatment. While higher SOD and CAT
activities in CM than those of BR were induced by external browning
inhibition pretreatment. Notably, CAT activity increased by 2.5 times
specifically in C8, and SOD activity increased by 1.4–3.7 times
compared to BR counterparts. [72]Kou et al. (2015) also observed a
significant increase in CAT and SOD enzyme activities in pear fruit
treated with exogenous calcium. Enhanced enzymatic activities in fresh
fruits and vegetables can effectively suppress ROS accumulation,
fortify cell membrane stability, and mitigate ROS-induced phenolic
oxidation ([73]Li, Zhou, et al., 2020). Consequently, reduced ROS
levels contribute to delayed browning, consistent with the lower levels
of H[2]O[2] detected in calcium-treated fruit compared to untreated
fruit during storage. Furthermore, the elevated activities of CAT and
SOD in calcium-treated fruit suggest that calcium supplementation may
enhance the ROS scavenging mechanism, thereby protecting cells from
oxidative injury ([74]Ban et al., 2021). PAL activity in CM increased
5.9 times with extended storage compared to BR, likely due to CaCl[2]
pretreatment, which led to increased phenolic synthesis and
corresponding antioxidant properties that help preserve the structural
integrity of fruit cell walls ([75]Du et al., 2020). These results
suggest that apples from different storage periods respond differently
to pulping processing, exhibiting varied browning-related enzyme
activities. The same was observed in apples with CaCl[2] pretreatment
for browning inhibition.
3.3. Metabolomics analysis
To comprehensively understand the dynamics of the metabolome and the
regulatory networks during apple storage, untargeted metabolomic
profiling was conducted. The total ion chromatograms (TIC) of the
samples in both positive and negative ion modes, as well as the base
peak chromatograms (BPC) of the quality control (QC) samples, are
presented in Fig. S1 and Fig. S2, respectively. The correlation heatmap
of the analyzed samples ([76]Fig. 3A) and the Pearson coefficient of
the QC samples ([77]Fig. 3B) demonstrate good repeatability in the
detection process and the stability of the instrument, ensuring the
accuracy of the experimental data. PLS-DA revealed distinct
differentiation patterns in metabolome profiles among the groups,
indicating significant differences among apple fruit of fresh, browning
pulp, and browning inhibition pulp in different storage periods
([78]Fig. 3C).
Fig. 3.
[79]Fig. 3
[80]Open in a new tab
Quality control analysis (QC) and sample reproducibility analysis. (A)
The correlation coefficient's proximity to 1 implies greater
reproducibility between two samples. In the correlation heat map, all
within-group samples demonstrated commendable repeated correlations,
indicating satisfactory instrument functionality and dependable data
acquisition during sample testing. (B) Quality control samples (QC),
which were created by combining all the sample extracts, to evaluate
the repeatability of the samples when subjected to identical treatment
methods. The results of the analysis showed that the Pearson
correlation coefficient of the intensity values of co-quantified
metabolites between any two groups of repeated experiments was greater
than 0.80, indicating a high degree of consistency. (C) The samples
were subjected to PLS-DA score plots of dimensionality reduction
analysis to identify discrepancies between the sample groups and to
evaluate the consistency within each group. The PLS-DA plot utilized
the first two principal components, PC1 and PC2, to represent the
samples, with a smaller difference in spatial distribution indicating a
closer correlation between the data of the two samples.
3.3.1. Differential metabolites composition
In the apple samples, 8440 and 7960 metabolites were detected in
positive ion and negative ion modes, respectively. Among them, 445,
468, and 265 differential metabolites were identified in the FC, BR,
and CM groups, respectively. These significant metabolites were
classified into eight groups, including lipids, organic heterocyclic
compounds, organic oxygen compounds, organic acids, phenylpropanoids,
benzenoids, nucleosides, and others ([81]Fig. 4A). Lipid metabolites
accounted for the highest proportion, with 22 % of total metabolites in
FC, and 21 % and 26 % in BR and CM, respectively. Subsequently, organic
heterocycles accounted for 16 %, 15 %, and 13 % in FC, BR, and CM,
respectively, while organic acids accounted for 15 %, 14 %, and 12 %,
respectively. The higher proportion of lipid metabolites in CM suggests
a possible role in maintaining membrane integrity and inhibiting
enzymatic browning during storage. Organic heterocycles and organic
acids were the next most abundant classes, indicating substantial
changes in secondary and primary metabolism during storage and
processing. Principal component analysis (PCA) revealed discernible
disparities in the metabolomic profiles of FC, BR, and CM across
different storage periods ([82]Fig. 5A). The PCA score plot delineated
the two principal components, PC1 and PC2, accounting for 49.1–69.6 %
and 9.0–16.8 % of the variance within FC, BR, and CM, respectively.
Notably, the PCA illustrated a close association between apples stored
for 6 and 8 months in FC, BR, and CM, indicating a convergence of
metabolic patterns at later stages of storage. This trend suggests that
the apple tissue reaches a relatively stable metabolic state after
extended cold storage, regardless of processing treatment. Furthermore,
the cluster heatmap revealed the clustering of metabolites exhibiting
analogous expression patterns. As depicted in [83]Fig. 5B, distinct
clusters emerged during the storage of FC, BR and CM, underscoring
significant alterations in metabolic profiles over time. The screened
metabolites were annotated using the KEGG database and subsequently
subjected to pathway enrichment analysis. [84]Fig. 4B illustrated that
the differential metabolites within the FC were enriched in 30 KEGG
pathways, primarily involving lipid, amino acid, and carbohydrate
metabolism, indicating baseline metabolic fluctuations during cold
storage. Conversely, the differential metabolites within BR and CM were
enriched in 55 and 31 KEGG metabolic pathways, respectively.
Specifically, the metabolites enriched pathways in BR included
carbohydrate metabolism, metabolism of cofactors and vitamins, and
amino acid metabolism, while those in CM encompassed lipid metabolism,
amino acid metabolism, and carbohydrate metabolism.
Fig. 4.
[85]Fig. 4
[86]Open in a new tab
The significant differential pathways and metabolites of the four
storage apples fresh control (FC), their browning pulp (BR), and
browning inhibition pulp (CM). (A) Metabolites composition changes in
FC, BR, and CM; (B) Enrichment analysis of differential metabolite
pathways; (C) KEGG analysis of the significant differential metabolites
in FC, BR, and CM of the four storage apples. (The color change from
red to blue means that the p-value increases successively.) (For
interpretation of the references to color in this figure legend, the