Combined analysis of metabolomics and transcriptomics reveals the effects of sugar treatment on postharvest strawberry fruit quality

Abstract

The composition and accumulation of soluble sugars are key factors influencing the development of fruit flavor, and although the application of fertilizers can increase the postharvest fruit quality, long-term application will cause certain food hazards. Therefore, evaluating the effects of externally applied sugar sources on fruit quality is essential for improving postharvest strawberry quality. In this study, exogenous sugar application significantly enhanced the postharvest quality of ‘Yanli’. Specifically, strawberries treated with 0.2 mol∙L⁻¹ fructose increased the single fruit weight, soluble solids content and soluble sugar content. Based on these results, combined metabolomic and transcriptomic analyses were performed to assess the impact of 0.2 mol∙L⁻¹ fructose treatment. The results showed that broadly targeted metabolomics screened a total of 371 significantly different metabolites, 123 up-regulated and 248 down-regulated. Sugar-targeted metabolomics further revealed a marked increase in fructose content to 43.40 mg∙g⁻¹. Transcriptomic analysis identified 3,506 differentially expressed genes. Integration of transcriptomic and metabolomic data indicated that FaINV and FaSUS are key genes involved in the sugar metabolism pathway. These findings elucidate molecular responses to exogenous sugar treatment and offer a foundation for further investigation of gene functions in postharvest fruit quality regulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12870-025-06919-7.

Introduction

Strawberry (Fragaria × ananassa Duch.) is a perennial, herbaceous fruit plant belonging to the genus Fragaria of the Rosaceae family. It is characterized by its appealing red appearance, pleasant flavor, rich nutritional profile, and high commercial value [1]. Strawberries can be consumed fresh or processed into a variety of products. In China, strawberries rank second among berry crops in terms of cultivation area and production [2]. Sugar accumulation is a key determinant of postharvest fruit quality. Currently cultivated strawberry varieties are typically large-fruited and aromatic; however, some cultivars exhibit relatively low sugar content in ripe fruits [3]. This deficiency can compromise flavor and consumer acceptance, thereby limiting the market potential of strawberries. Therefore, understanding the mechanisms underlying sugar metabolism in strawberry is critical for improving postharvest fruit quality.

Soluble sugars—primarily glucose, fructose, and sucrose, along with small amounts of raffinose and mannose—play a central role in determining fruit sweetness. These sugars differ significantly in their perceived sweetness, with fructose being the sweetest: 1.73 and 2.33 times sweeter than sucrose and glucose, respectively [4]. The content and composition of these sugars contribute to the characteristic flavor and mouthfeel of strawberries. Fertilizers are commonly used to enhance fruit sugar content; however, excessive use of chemical fertilizers can lead to soil degradation, environmental pollution, and deterioration in fruit taste [5]. Alternatively, the application of exogenous sugars has emerged as a promising strategy for improving postharvest fruit quality [6]. Studies have shown that exogenous fructose application significantly increases the soluble sugar content in postharvest Balsam pear [7]. Similarly, glucose treatment (200 mmol·L⁻¹) has been shown to maintain cucumber firmness during storage, reduce respiration rate, enhance antioxidant enzyme activity- Superoxide dismutase (SOD), Peroxidase (POD), and Catalase (CAT), and extend fruit shelf life [8]. Sucrose has also been reported to promote fruit ripening in strawberries and tomatoes, thereby improving postharvest quality and commercial value [9, 10]. Notably, fructose typically accumulates at higher levels than glucose during strawberry ripening, while sucrose content remains relatively low [11]. However, the specific metabolic mechanisms governing the accumulation of these sugars in ripening strawberries remain largely unexplored.

Transcriptomics investigates gene expression at the mRNA level, while metabolomics is a powerful tool for profiling changes in fruit metabolites [12]. With advances in high-throughput genomic technologies, researchers have begun to link gene expression patterns with metabolic pathways. Integrating transcriptomic and metabolomic analyses offers a comprehensive approach to understanding the biological processes that regulate fruit development, ripening, quality traits, and stress responses. For example, Yang et al. used combined transcriptomic and metabolomic approaches to reveal differences in carbohydrate metabolism between two blueberry cultivars, identifying activation of the carbon metabolic network as a key driver of sugar accumulation [13]. While the chemical basis of sugar composition in strawberries has been extensively studied, the molecular mechanisms underlying sugar accumulation and metabolism remain unclear.

In this study, we used potted ‘Yanli’ strawberries as the experimental material to examine the effects of foliar application of various sugar types and concentrations on postharvest fruit quality and the activities of sugar metabolism-related enzymes. We also analyzed changes in sugar metabolic pathways using integrated metabolomic and transcriptomic data. Our findings aim to elucidate the mechanisms of sugar accumulation in postharvest strawberries, establish a foundation for enhancing fruit sugar content, and ultimately improve strawberry quality and marketability.

Materials and methods

Plant material and treatment

Octoploid strawberry ‘Yanli’ (Fragaria × ananassa Duch.) at uniform growth and developmental stages was used and cultivated in pots containing a substrate mixture of peat, vermiculite, and perlite in a 4:2:1 ratio. ‘Yanli’ was bred by Shenyang Agricultural University’s Fruit Tree Genomics and Molecular Breeding Team in March 2014 and planted in Shenyang Agricultural University’s greenhouse No. 14. At the large green fruit stage, various sugar solutions differing in type and concentration were applied by spraying. The types and concentrations of sugar treatments are listed in Table S1. The sugars used were glucose, fructose, sucrose, and a combination of all three. Each sugar type was applied at concentrations of 0.1 mol∙L⁻¹ and 0.2 mol∙L⁻¹. Nine treatment groups were established, with five plants per group and three biological replicates, totaling 135 plants. Spraying was performed using a spray can held 15 cm from the plant surface in all directions until runoff occurred. Treatments were administered once every 3 days, for a total of five applications. Fruits were harvested at the red-fruiting stage, snap-frozen in liquid nitrogen, and stored at − 80 °C for subsequent assessment of the effects of exogenous sugar application on postharvest fruit quality and sugar-metabolizing enzyme activities, followed by histological sequencing analysis.

Measurement of related indexes

Determination of postharvest fruit quality indexes

Referring to the method of Yu et al. [14], the maximum single fruit weight and soluble solids content of strawberries were measured; the firmness of fruits was measured by using an Italian TR firmness tester; the maximum longitudinal and transverse diameters of fruits, the fruit shape index, the soluble sugar content and the organic acid content was determined by using the method of Wang et al. [15]; the solids-acid ratio = soluble solids content/organic acid content.

Measurement of sugar metabolizing enzyme activities

Neutral invertase (NI) was extracted, and activity was assayed with slight modification about Zhang et al. [12]. Sucrose synthase synthetic (SUS-S) directional enzyme activity was measured using a sucrose synthase activity assay kit purchased from Solarbio. Fructose kinase (FK) and glucokinase (GK) extraction and activity assays were referred to the experimental method of Schaffer et al. [16].

UPLC-MS/MS analysis as well as sugar-targeted metabolism analysis

UPLC-MS/MS analysis and sugar-targeted metabolism analysis were performed with reference to the method of Zhang et al. [17].

Transcriptome analysis

Transcriptome analysis were performed with reference to the method of Mao et al. and Zhang et al. [18, 19].

RT-qPCR

The expression of 12 genes was detected according to the method of Luo et al. and Zang et al. [20, 21]. The primer sequences are shown in Table S2.

Statistical analysis

The statistical analysis was performed with reference to the method of Luo et al. [22].When the F-test showed significance, means were compared using Tukey’s post-hoc test.

Results

Effect of exogenous sugar treatments on postharvest strawberry fruit quality

Single-fruit weight, fruit shape index, and fruit firmness are key indicators of fruit appearance. ‘Yanli’ strawberry seedlings with uniform growth conditions were sprayed with sugar solutions of varying types and concentrations. The treatments had distinct effects on the appearance and quality parameters of postharvest fruits. As shown in Table 1, single-fruit weight increased under all exogenous sugar treatments compared with the control. Fructose and mixed sugar treatments produced a more pronounced increase in single-fruit weight than glucose and sucrose. Notably, fructose treatment at 0.2 mol∙L⁻¹ resulted in the highest single-fruit weight (21.15 g), which was 48.21% higher than the control. This treatment also produced a more favorable fruit shape index compared to the other treatments. Fruit firmness improved with all exogenous sugar treatments; the highest value (2.55 kg∙cm⁻²) was observed following fructose treatment at 0.2 mol∙L⁻¹, representing a 16.90% increase relative to the control.

Table 1.

Effect of exogenous sugar on postharvest fruit external quality of ‘Yanli’

Treatments	Single fruit weight (g)	Fruit shape index	Firmness (kg∙cm−2)
CK	14.27 ± 1.42b	1.12 ± 0.04a	2.18 ± 0.08bc
0.1 mol∙L−1 glucose	16.75 ± 1.35ab	1.04 ± 0.05a	2.38 ± 0.11ab
0.1 mol∙L−1 fructose	17.57 ± 0.96ab	1.10 ± 0.01a	1.95 ± 0.13c
0.1 mol∙L−1 sucrose	15.72 ± 2.64ab	0.98 ± 0.06a	2.55 ± 0.13ab
0.1 mol∙L−1 mixture sugar	18.63 ± 2.24ab	1.01 ± 0.03a	2.55 ± 0.12ab
0.2 mol∙L−1 glucose	16.17 ± 2.61ab	1.06 ± 0.05a	2.32 ± 0.20b
0.2 mol∙L−1 fructose	21.15 ± 2.02a	1.12 ± 0.05a	2.55 ± 0.06ab
0.2 mol∙L−1 sucrose	15.83 ± 0.91ab	1.12 ± 0.03a	2.75 ± 0.05a
0.2 mol∙L−1 mixture sugar	20.50 ± 2.68ab	1.06 ± 0.03a	2.51 ± 0.08ab

Different letters in the same column indicates statistical differences at P < 0.05

Examination of intrinsic quality parameters showed that exogenous sugar treatments significantly increased both soluble solid and soluble sugar contents in postharvest fruits (Table 2). Glucose and fructose treatments led to greater increases in soluble solid content than sucrose or mixed sugar treatments. Among all treatments, fructose at 0.2 mol∙L⁻¹ resulted in the highest soluble solid (15.38%) and soluble sugar (12.30%) contents, representing increases of 39.80% and 4.00%, respectively, over the control. Additionally, all sugar treatments reduced fruit organic acid content, leading to an increased solid–acid ratio, calculated as the ratio of soluble solids to titratable acid content.

Table 2.

Effect of exogenous sugar on postharvest fruit intrinsic quality of ‘Yanli’

Treatments	Soluble solid content (%)	Soluble sugar (%)	Organic acids (%)	Solid-acid ratio
CK	11.00 ± 0.52c	8.30 ± 0.10c	0.83 ± 0.02a	13.24 ± 0.90b
0.1 mol∙L−1 glucose	13.83 ± 0.48ab	8.59 ± 0.76c	0.77 ± 0.02ab	17.95 ± 0.60ab
0.1 mol∙L−1 fructose	13.42 ± 0.37b	9.67 ± 1.00bc	0.69 ± 0.04b	19.52 ± 1.79a
0.1 mol∙L−1 sucrose	12.67 ± 0.69b	8.44 ± 0.33c	0.76 ± 0.04ab	16.82 ± 2.08ab
0.1 mol∙L−1 mixture sugar	12.75 ± 0.56b	11.96 ± 0.79a	0.68 ± 0.01b	18.69 ± 1.01a
0.2 mol∙L−1 glucose	13.05 ± 0.66b	10.91 ± 0.25ab	0.67 ± 0.06b	19.92 ± 2.46a
0.2 mol∙L−1 fructose	15.38 ± 0.46a	12.30 ± 0.51a	0.78 ± 0.05ab	19.74 ± 1.25a
0.2 mol∙L−1 sucrose	12.87 ± 0.56b	10.58 ± 0.36ab	0.69 ± 0.04b	18.70 ± 1.42a
0.2 mol∙L−1 mixture sugar	12.83 ± 0.55b	11.91 ± 0.93a	0.78 ± 0.02ab	16.52 ± 1.27ab

Different letters in the same column indicates statistical differences at P < 0.05

Overall, exogenous sugar treatments enhanced single-fruit weight and fruit firmness, elevated soluble solid and sugar contents, reduced organic acid content, and increased the solid-acid ratio. Fructose at 0.2 mol∙L⁻¹ was the most effective treatment for improving postharvest fruit quality.

Effects of exogenous sugar treatments on the activities of enzymes related to sugar metabolism in postharvest strawberry fruit

NI activity was elevated in postharvest fruits treated with exogenous sugars. Fructose at both concentrations substantially increased NI activity, with the 0.2 mol∙L⁻¹ treatment producing the greatest effect—a two-fold increase relative to the control (Fig. 1A). Fructose at 0.2 mol∙L⁻¹ inhibited SUS-S activity (Fig. 1B). Measurements of hexose-metabolizing enzymes indicated that fructose at 0.2 mol∙L⁻¹ significantly increased FK and GK activities to 0.20 and 0.19 µmol∙g⁻¹∙min⁻¹ FW, respectively (Fig. 1C, D). In summary, fructose treatment at 0.2 mol∙L⁻¹ increased NI activity, suppressed SUS-S activity, and markedly enhanced FK and GK activities in postharvest strawberry fruits.

Fig. 1.

Effects of exogenous sugar treatments on soluble sugar fractions and sugar-related metabolizing enzyme activities in ‘Yanli’ strawberry postharvest fruits. A, NI content; B, SUS content; C, FK content; D, GK content. Error bars indicate the standard deviation of three biological replicates. Different letters indicate statistically significant differences (P < 0.05) in each group

Metabolomics sequencing and quality analysis

Given the prominent effects of the F2 treatment (fructose at 0.2 mol∙L⁻¹) on postharvest fruit quality, fruits at the red-fruiting stage were selected for broad-targeted metabolomic analysis. Total ion current chromatograms demonstrated stable signal detection across time points for each sample, with smooth baseline peaks (Fig. 2A).

Fig. 2.

Metabolome quality analysis. A, Mass spectrometry detection of total ion current overlap plot; B, Sample-to-sample correlation analysis; C, PCA analysis of metabolites in strawberry fruits. CK was the clean water control group, and F2 indicates the spraying of fructose at a concentration of 0.2 mol·L⁻¹, with three biological repeats for each

Pearson’s correlation coefficient (r) was used to assess the biological replicate relevance, and the r values were greater than or equal to 0.95 (Fig. 2B). The variability of intergroup and intragroup samples was analyzed using principal component analysis (PCA) values, respectively. We found that the PCA values of the intergroup and intragroup samples were 49.29 and 13.65%, respectively, indicating that the intragroup reproducibility was good (Fig. 2C); the metabolites of the intergroup samples tended to be separated, with obvious differences, which could be used for subsequent analysis.

Differential metabolite analysis

Using |Log₂FC|≥1 and VIP > 1 as criteria, a total of 371 significantly different metabolites were screened, including 123 upregulated and 248 downregulated metabolites. The metabolites were mainly concentrated as amino acids, organic acids, and sugars. Alkaloids and terpenoids are also present (Fig. 3A). Bar graphs were plotted using the data after the multiplicity of variance Log₂ treatment; we found that the top 20 metabolites with the highest multiplicity of variance were glutathione reduced form, 1,6-Di-O-caffeoyl-β-D-glucose*, Eucommin A, 7,3’,4’-trihydroxyquercetin, and others (Fig. 3B).

Fig. 3.

Analysis of differential metabolites in fructose-treated strawberry postharvest fruit. A, Donut plot of differential metabolite classification; B, Bar graph of DAMs; C, The scatter analysis of differentially metabolisms in KEGG pathway; D, Heat map of sugar differential metabolites; CK was the clean water control group, and F2 indicates the spraying of fructose at a concentration of 0.2 mol·L⁻¹

Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of the differential metabolites was conducted on 20 metabolic pathways (Fig. 3C). Additionally, we conducted sugar-targeted metabolomics to analyze the changes in sugar metabolism in strawberry after exogenous sugar treatment and found that the glucose and fructose contents increased and sucrose contents decreased after treatment with 0.2 mol∙L⁻¹ of fructose (Fig. 3D).

Transcriptome sequencing and quality analysis

To elucidate the molecular mechanism of fructose treatment at 0.2 mol·L⁻¹ to improve postharvest strawberry fruits quality, transcriptome sequencing analysis was also conducted on postharvest fruits treated with 0.2 mol·L⁻¹ of fructose, and clear water-treated postharvest fruits were used as the control. The results showed that Q30%>94.11%. Sequence comparison of clean reads with the reference genome (Fragaria × ananassa Yanli Genome v1.0) was conducted, and the mapped reads were in the range of 93.92–94.96% (Table 3).

Table 3.

Transcriptome sequencing quality analysis

Sample	Clean Reads	Clean Base (G)	Q30 (%)	Reads mappe (%)
CK-1	64,534,202	9.68	94.63	93.92
CK-2	67,455,788	10.12	94.69	94.73
CK-3	57,939,572	8.69	94.51	94.96
F2-1	74,065,228	11.11	94.66	94.56
F2-2	77,243,390	11.59	94.39	94.91
F2-3	80,861,114	12.13	94.11	94.95

Screening and identification of differentially expressed genes

The sequencing data of the F2 and control groups were correlated (Fig. 4A), and all r values between biological replicate samples within the groups of the sequencing result were greater than 0.9. A total of 3,506 differentially expressed genes were screened in the two groups of samples, among which 2,204 and 1,302 were upregulated and downregulated, respectively (Fig. 4B). The 20 most significant pathways were selected for KEGG enrichment scatter plots (Fig. 4C). The most enriched pathways were the biosynthesis of secondary metabolites, starch and sucrose metabolism, carbon metabolism, and biosynthesis of cofactors. Statistical analysis of all transcription factor classes of differential genes revealed that the NAC class of transcription factors accounted for the largest proportion, namely, 5.85%, followed by the MYB class of transcription factors, accounting for 5.76%. Similarly, ERF and bHLH classes of transcription factors accounted for a relatively large proportion, namely, 5.43 and 5.09% (Fig. 4D), respectively, and the more highly differentially expressed ones are listed in Table S3. The differentially expressed genes were also screened for sugar-related genes, totaling 23 (Table S4).

Fig. 4.

Analysis of differentially expressed genes in postharvest strawberry fruits treated with fructose. A, Correlation analysis between samples; CK was the clean water control group, F2 indicates the spraying of fructose at a concentration of 0.2 mol·L⁻¹. B, Statistics of differentially expressed genes. C, The scatter analysis of differentially expressed genes in KEGG pathway. D, Transcription factor differential gene statistics; E, GO functional analysis of differentially expressed genes of CK vs F2

The 3,506 differentially expressed genes were gene ontology (GO) annotated according to the molecular function, cellular components, and biological processes. cellular components, molecular functions, and biological processes contained 2, 15, and 14 secondary functional annotations, respectively. Among the cellular components, the cellular anatomical entity and protein-containing complex had the most functional annotations (Fig. 4E).

Combined transcriptome and sugar metabolism analysis

We focused on analyzing genes related to the sugar metabolism pathway (Fig. 5). Three metabolites, namely, fructose, glucose, and sucrose, were significantly altered in postharvest strawberry fruit after fructose treatment at 0.2 mol·L⁻¹. The most significant changes were in sucrose, fructose and glucose contents. Sucrose was broken down into glucose and fructose by NI, a process that resulted in a four-fold increase of beta-fructofuranosidase-like (FaINV, FxaYL_741g0913330) compounds, leading to an increase in the D-fructose and D-glucose contents. Notably, the FaSUS (FxaYL_131g0763550) content also decreased by four-fold, resulting in a reduction in the sucrose content, which comprises glucose and fructose. The FaFK (FxaYL_221g0466770, FxaYL_222g0417470) content increased by approximately three-fold. FaHK (FxaYL_141g0901850, FxaYL_122g0776200) increased by approximately 2.1-fold to accelerate the conversion of D-glucose to D-glucose 6 phosphate. The changes in the levels of these metabolic enzymes were consistent with previous physiological index measurements. Exogenous fructose treatment at 0.2 mol·L⁻¹ affected the accumulation of sugar content in postharvest strawberry fruits.

Fig. 5.

Co-expression analysis of structural genes and metabolites in the sugar metabolism pathway. The heatmap colored in green and red indicates metabolite accumulation and gene expression

RT-qPCR validation of some differential genes

We selected sugar metabolism pathway genes, sugar transporter proteins, and transcription factors for validation using reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR) and found that the expression trends were consistent with the transcriptome sequencing results, indicating that the transcriptome data were reliable. Meanwhile, we also found that the expression of the sugar metabolism-related gene FaINV was significantly upregulated, which was consistent with our combined analysis, whereas some sugar transporter proteins were also functioning; for example, exogenous fructose treatment significantly increased the expression of FaSWEET9-like. After exogenous sugar treatment, the expression of transcription factors, such as FaNAC86, FaERF3, and FaWRKY3, increased, which may affect the sugar content by influencing sugar transporter proteins and sugar metabolism-related genes (Fig. 6).

Fig. 6.

RT-qPCR analysis of candidate genes. Error bars represent the standard deviation of three biological replicates. *indicates that there is a statistically significant difference by t-test (*P < 0.05, **P < 0.01, ***P < 0.001). Orange indicates CK, and red indicates the spraying of fructose at a concentration of 0.2 mol·L⁻¹

Discussion

As the popularity of strawberries increases, the demand for improved postharvest strawberry fruit quality has also increased. The soluble sugar content of postharvest strawberries is an important index for evaluating the flavor and texture of fruits, and dynamic changes in its components and ratios affect the sensory quality of the fruits [23].

Sugar metabolism in fruits primarily involves sucrose, sorbitol, and hexose. Sucrose can be converted into other forms by the action of sugar-metabolizing enzymes. The main enzymes involved are: invertase (INV), SUS, and sucrose phosphate synthase (SPS) [24]. In this study, we found that the INV activity in strawberry postharvest fruits were significantly elevated under fructose and sucrose treatments. Spraying with exogenous fructose increased the contents of the three sugar fractions and consequently, an increase in the INV activity. Exogenous sucrose is catabolized within the fruit by converting enzymes and maintaining the balance of sugar fractions within the fruit. Further combined analysis of the transcriptome and metabolome revealed a maximum change of 43.40 mg·g⁻¹ in the fructose content regarding the metabolite changes after treatment with exogenous sugar. Previous studies have shown that the source of fructose in fruits is two-fold: first, the hydrolysis of sucrose to produce fructose and glucose under the action of INV; and second, the participation of SUS in both the synthesis of sucrose (optimum pH of 8.00–9.50) and catalyzation of the cleavage of sucrose (optimum pH of 5.50–6.50) under certain circumstances; it is one of the key enzymes in the metabolism of sucrose [25]. This was confirmed by combined transcriptomic and metabolomic analyses, which showed a four-fold increase in the FaINV (FxaYL_741g0913330) content, resulting in an increase in the metabolites D-fructose and D-glucose. Simultaneously, the FaSUS (FxaYL_131g0763550) content decreased four-fold. Therefore, we hypothesized that the high accumulation of fructose during sugar metabolism could not be attributed to the actions of these two genes (Fig. 7).

Fig. 7.

Illustrative model of sugar metabolism in postharvest strawberries treated with sugar

The process of carbon dioxide fixation by chloroplasts in the leaves of higher plants through photosynthesis is the main source of sugar accumulation in fruits. The assimilates are first transported over short distances to the phloem as sucrose or sorbitol, subsequently transported and unloaded over long distances through both the commensal and ectoplasmic pathways, and finally transported through the phloem into the fruits [26]. In most ripening fruits, the vacuole is the main organelle for the storage of soluble sugars, and the movement of sugars into and out of the vacuole requires the assistance of sugar transport proteins to penetrate the cell membrane [27]. Sugar transporter proteins are categorized into monosaccharide transporters (MSTs), sucrose transporters (SUTs), and bidirectional sugar transporters (sugars will eventually be exported transporters; SWEETs) [28, 29]. Notably, exogenous sugar treatments can alter the expression of sugar transporter-related genes; namely, CitSUT1 expression in mature leaves was suppressed by exogenous sucrose, glucose, mannose [30]. Moreover, the expressions of PlSUT2 and PlSUT4 were increased by sucrose treatment [31]. The results of this experiment were also consistent with the fact that 23 sugar-related differential genes were found in the combined analysis of the transcriptome and metabolome, including the sugar transporter protein gene SWEETs. This indicates that exogenous sugar treatments have a certain degree of influence on both the metabolism and transportation of sugars within postharvest strawberry fruits (Fig. 7).

Conclusion

Our study showed that exogenous sugar treatment was effective in improving postharvest strawberry fruit quality, wherein the most effective treatment was 0.2 mol·L⁻¹ of fructose. Combined transcriptomic and metabolomic analyses showed that the significant increase in the levels of fructose and glucose metabolites in the sugar metabolism pathway was caused by alterations in the levels of FaINV and FaSUS, which in turn affected the quality of postharvest strawberries. Our results provide a basis for the subsequent elucidation of the molecular mechanism of the effect of exogenous sugar treatment on postharvest strawberry fruit quality, and improvement of strawberry quality.

Abbreviations

SOD

Superoxide dismutase

POD

Peroxidase

CAT

Catalase

NI

Neutral invertase

SUS-S

Sucrose synthase synthetic

FK

Fructose kinase

GK

Glucokinase

UPLC-MS/MS

Ultra performance liquid chromatography-tandem mass spectrometry

RT-qPCR

Real-time quantitative polymerase chain reaction

PCA

Principal component analysis

VIP

Variable importance in projection

KEGG

Kyoto encyclopedia of genes and genomes

DAM

Differential metabolite

GO

Gene ontology

INV

Invertase

SWEETs

Sugars will eventually be exported transporters

SPS

Sucrose phosphate synthase

SUTs

Sucrose transporters

Authors' contributions

H.L., and R.R.T. planned the experiment; Z.H.Z., and J.Y.W. analysed of the transcriptome data; Z.H.Z., and Y.W. performed the metabolite analysis. Z.H.Z, and H.L. wrote the draft. All authors participated in reviewing and approving the final version of the paper.

Funding

This research was supported by the Basic Scientific Research Program of Colleges and Universities of Liaoning Province Education Department (JYTMS20231292).

Data availability

The RNA-seq data for this study can be accessed at the NCBI Sequence Read Archive (http://www.ncbi.nlm.nih.gov/sra) under accession number PRJNA1221617.

Declarations

Ethics approval and consent to participate

The plant material of this study protocol comply with relevant institutional, national, and international guidelines and legislation. All the strawberry materials required for the experiment and experimental protocols were approved by the Shenyang Agricultural University.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.