Postharvest Shading Modulates Saccharide Metabolic Flux and Enhances Soluble Sugar Accumulation in Tobacco Leaves During Curing: A Targeted Glycomics Perspective

Abstract

Saccharides critically influence tobacco quality. To elucidate the effects of postharvest shading (PS) pre-curing on saccharide metabolic flux, a targeted glycomics analysis was conducted. Compared to light exposure (CK), PS delayed chlorophyll degradation during pre-curing but accelerated yellowing, ultimately resulting in similar pigment levels. Additionally, PS inhibited photosynthesis, leading to reduced starch content and increased soluble sugar content before curing. Furthermore, PS altered the starch-to-sugar conversion, ultimately resulting in significantly higher soluble sugar content and lower starch content. Targeted glycomics analysis identified 21 saccharides, with glucose, D-fructose, and sucrose being dominant. Notably, PS ultimately increased glucose, D-fructose, and sucrose levels by 74.09%, 66.49%, and 17.36%, respectively. Pairwise comparisons revealed 6, 12, 5, 13, 10, and 11 differentially expressed metabolites before curing and at 38, 40, 42, 54, and 68 °C during curing, respectively, between PS and CK. Conjoint analysis identified methylgalactoside and three oligosaccharides (sucrose, raffinose, and maltose) as the central metabolites of saccharide metabolism during curing. D-mannose, D-sorbitol, and D-glucuronic acid were identified as biomarkers for assessing storage-induced metabolic perturbations using random forest algorithms. Collectively, these findings suggest that PS might enhance tobacco quality via carbohydrate metabolism modulation, providing a scientific basis for pre-curing protocol optimization and industrial application.

1. Introduction

Tobacco (Nicotiana tabacum L.) is one of the most economically valuable non–food cash crops in global agriculture due to its significant economic value [1]. The combustion characteristics of tobacco are directly influenced by its carbohydrate composition [2,3]. Tobacco carbohydrate exhibits diverse structural configurations, primarily categorized into polysaccharides, oligosaccharides, and monosaccharides, which critically determine the organoleptic properties through three principal thermal degradation pathways, including Maillard reactions, pyrolysis, and caramelization [4]. Notably, polysaccharides such as starch produce undesirable combustion byproducts, necessitating enzymatic hydrolysis during curing [2,5]. Conversely, monosaccharides contribute beneficially to smoke characteristics [2].

Fructose, glucose, myo–inositol, and sucrose have been identified as key sweetening components in flue–cured tobacco leaf extracts. Optimizing their optimal ratio has been demonstrated to significantly improve the sweetness perception and overall flavor profile of cigarette smoke [6]. Additionally, 18 volatile organic compounds have been identified to be associated with sweetness, particularly furan/pyran derivatives and cycloketones, which significantly enhance the sweetness of tobacco smoke, while alkaloids and hydrocarbons are negatively correlated with sweet perception. Among saccharides, fructose and sucrose have the highest sweetness–enhancing effect [7]. Meanwhile, the organoleptic properties of tobacco are significantly influenced by key chemical ratios, particularly the total sugar–to–nicotine and sugar–to–protein ratios, which determine smoke mildness and aromatic quality [8]. Deviation from these optimal ratios results in either increased irritation or flavor attenuation [9]. An increased sugar content enhances leaf plasticity, compression resistance, and visual appeal [10]. However, while the contents of nicotine, nitrogen, potassium, and chlorine remain stable across different curing parameters, saccharide profiles exhibit significant technology–dependent variations [11].

The postharvest curing process plays a crucial role in determining the final quality of tobacco leaves, profoundly influencing both organoleptic properties and market value [12,13]. The intricate biochemical transformation occurs in three precisely controlled thermoperiods: the chlorophyll degradation phase (yellowing stage, 35~42 °C), color fixing and aroma stabilization phase (color fixing stage, 45~54 °C), and the structural dehydration phase (dry tendon stage, 55~68 °C) [14,15]. During curing, coordinated metabolic reprogramming regulates the formation of essential quality characteristics in the leaf tissue [4,16]. Contemporary curing protocols utilize intelligent control systems to accurately regulate microenvironmental parameters (such as thermal gradients, humidity ratios, and convective airflow patterns) during curing, promoting optimal biochemical conversions [15,17,18]. Meanwhile, the application of additives, such as starch-degrading bacteria [19], pectinase, mesophilic α-amylase, and lipase [20], pectinase preparation derived from Bacillus amyloliquefaciens W6-2 [5], and multi-enzyme preparations [21], haves been employed to enhance polysaccharides breakdown and sugars accumulation. However, industrial applications of these are still limited by factors like high enzyme preparation costs, poor environmental adaptability of enzymes, and potential ecological safety concerns.

The tight synchronization of flue–cured tobacco maturity necessitates rapid post–harvest transportation to automated curing facilities, followed by manual or mechanized leaf distribution onto drying racks before formal curing begins. Until now, standardized operating procedures for pre–curing tobacco handling and temporary storage have been absent. It is well–known that appropriate pre-flue-curing can reduce the yellowing duration in curing barns, reduce energy consumption during curing, and improve the appearance quality, economic traits, chemical composition, and smoking quality of cured tobacco leaves [22,23]. It is suggested that light exposure during the pre–flue–curing period can regulate the accumulation of photosynthetic products, subsequently influencing saccharides transformation during curing. However, the underlying regulatory mechanisms, particularly the impact of PS on saccharide metabolic flux and sugar accumulation, have not been clearly elucidated. Therefore, the present study implemented PS treatment, using light exposure as the control (CK) during the pre–curing period and employed targeted glycometabolomics to investigate the compositional dynamics of saccharides in tobacco leaves and the transformation patterns of carbohydrates during flue–curing, which will provide a scientific reference for optimizing light conditions for pre–curing in tobacco production.

2. Materials and Methods

2.1. Plant Materials and Sampling

Field trials were conducted at the Experimental Station of Guizhou Tobacco Research Institute in Fuquan (26°24′ N, 106°47′ E; 1200 m altitude), China, under a humid subtropical monsoon climate regime. The initial soil physicochemical properties were as follows: 25.32 g/kg organic carbon, 138.73 mg/kg available nitrogen (N), 36.32 mg/kg phosphorus (P), and 218.69 mg/kg potassium (K), with a slightly acidic pH of 6.2.

A completely randomized design with three replicates was used. Individual plots (11 m × 11 m, 121 m²) followed a staggered planting pattern with 1.1 m row spacing and 0.55 m plant spacing. Seeds (cv. Yunyan87) were sown on 20 January 2023 and transplanted to the field on 25 April 2023. Microclimatic monitoring throughout the growing season recorded the following mean monthly temperatures: May (16.13~23.17 °C), June (19.23~24.93 °C), July (22.87~29.83 °C), and August (21.30~30.37 °C).

Basal fertilization included 525 kg/ha of NPK compound fertilizer (10–10–25), 450 kg/ha of fermented rapeseed meal, and 375 kg/ha of calcium-magnesium phosphate (CaMgP). At transplantation, root-zone drenching was applied using 150–200 mL per plant of an aqueous solution containing 1% (w/v) NPK fertilizer and 0.28% (v/v) lambda-cyhalothrin emulsifiable concentrate. Fertigation events were repeated at 10 and 30 days post-transplantation, each applying 100~150 mL of solution with a 4% (w/v) NPK concentration. All agronomic practices adhered to standardized protocols to ensure uniform crop management.

Prior to sampling, middle canopy tobacco leaves with uniform developmental characteristics were carefully selected based on standardized morphological criteria, including consistent growth stage, homogeneous chlorophyll distribution, and dimensional uniformity. At peak physiological maturity, a total of 400 pre-marked leaves per experimental replicate were systematically harvested between 7:30 and 8:00 a.m. on a clear day, leaves were vertically suspended on rods using clips and arranged outdoors in a single-layer configuration to eliminate inter-leaf shading. Then, a 10-h shading treatment was applied using a black woven polyethylene shade net (90% light reduction), with full light exposure as the control (CK). During the treatment period, the ambient temperatures ranged from 26.3 °C to 32.8 °C, with a mean temperature of 30.6 °C. Under CK conditions, photosynthetic photon flux density fluctuated between 820 μmol·m⁻²·s⁻¹ (at 8:00 a.m.) and 1950 μmol·m⁻²·s⁻¹ (at 13:00 p.m.), while relative humidity ranged from 70% to 85% based on local meteorological records. For the tobacco leaf curing process, a 180-h curing duration was rigorously established. The parameters (temperature, duration time, and head rate of dry bulb and wet bulb) for tobacco curing were set as illustrated in Figure 1. Leaves were collected before curing (BC) and during curing at thermal transition points, corresponding to the following dry bulb temperature stages: 22 h at 38 °C, 14 h at 40 °C, 14 h at 42 °C, 6 h at 45 °C, 8 h at 48 °C, 6 h at 51 °C, 14 h at 54 °C, 8 h at 60 °C, and 28 h at 68 °C. Each sample set (n = 30) was immediately flash-frozen in liquid nitrogen and stored at −80 °C in an ultra-low temperature freezer to maintain biomolecular integrity for subsequent analyses.

2.2. Measurement of Pigments

For pigment analysis, 100 mg freeze-dried ultrafine powder samples were extracted with pre-chilled (4 °C) 1.5 mL of 80% (v/v) acetone. Incubation proceeded at 4 °C for 16 h with gentle rotation (15 rpm) under dark conditions. The extraction was repeated 3 times with fresh pre-chilled solvent, followed by immediate centrifugation (10,000× g, 10 min, 4 °C) after each extraction. The absorbance of the combined supernatants was measured spectrophotometrically at three characteristic wavelengths: 470, 645, and 663 nm. Pigment contents were quantified according to the modified methods of Chen [24]. The concentrations of chlorophyll a, chlorophyll b, total chlorophyll, and carotenoid were calculated using the following equations:

Chlorophyll a = 12.71 A₆₆₃ − 2.59 A₆₄₅

Chlorophyll b = 22.88 A₆₄₅ − 4.67 A₆₆₃

Total chlorophyll = Chlorophyll a + Chlorophyll b

Carotenoid = (1000 A₄₇₀ − 1.82 chlorophyll a − 85.02 chlorophyll b)/198

2.3. Measurement of Non-Structural Carbohydrates

For non-structural carbohydrates analysis, 100 mg freeze-dried ultrafine powder samples were extracted by adding 1.5 mL fresh pre-chilled 80% ethanol and the extraction was repeated 3 times, followed by centrifugation (10,000× g, 10 min, 4 °C), and the supernatant was collected to determine soluble sugar content according to the method of ‘Tobacco Determination of Water Soluble Sugars’. The residual pellet was digested with 1.5 mL boiling water for 15 min. After cooling, 1.5 mL of 9.2 mol/L perchloric acid was added and incubated at 0 °C for 15 min, followed by centrifugation (4 °C, 5000× g, 2 min) to collect supernatant. The extraction procedure was repeated using 1.5 mL of 4.6 mol/L perchloric acid under identical incubation and centrifugation conditions, with supernatant recovery maintained. A final washing step was performed by resuspending pellets in 1.5 mL deionized water (0 °C, 15 min incubation) prior to centrifugation. The combined supernatants were centrifuged (4 °C, 15,000× g, 2 min) and subsequently used for starch content quantification using the modified anthrone-sulfuric acid method, as described by Chen [24].

2.4. Gas Chromatography-Mass Spectrometer (GC-MS) Analysis

Freeze-dried samples were pulverized using a mixer mill (MM 400, Retsch GmbH, Haan, Germany) with a zirconia bead (1.5 min, 30 Hz). A 20-mg aliquot of the powder was extracted with 500 μL of methanol:isopropanol:water (3:3:2, v/v/v) by vortexing (3 min) and ultrasonic treatment (30 min). The extract was centrifuged (12,000× g, 4 °C, 3 min), and 50 μL of the supernatant was mixed with 20 μL of an internal standard solution (1000 μg/mL) and dried under nitrogen. The residue was freeze-dried and mixed with 100 μL of methoxyamine hydrochloride in pyridine (15 mg/mL) and incubated at 37 °C for 2 h. Subsequently, 100 μL of N,O-bis(trimethylsilyl)trifluoroacetamide was added, vortexed, and incubated at 37 °C for 30 min. The derivatized sample was diluted to an appropriate concentration and analyzed by GC-MS using an Agilent 8890 gas chromatograph (Agilent Technologies, Santa Clara, CA, USA) coupled to a 5977B mass spectrometer (Agilent Technologies, Santa Clara, CA, USA) with a DB-5MS column (30 m × 0.25 mm i.d. × 0.25 μm film thickness; J&W Scientific, Folsom, CA, USA) [25,26]. Helium was used as the carrier gas (1 mL/min). Injections (1 μL) were performed in split mode (5:1). The oven temperature program was as follows: 160 °C (1 min), ramp to 200 °C at 6 °C/min, to 270 °C at 10 °C/min, to 300 °C at 5 °C/min, to 320 °C at 20 °C/min, and hold for 5.5 min. The ion source and transfer line temperatures were set at 230 °C and 280 °C, respectively. Samples were analyzed in selective ion monitoring mode [27].

Data visualization and statistical analysis, including principal component analysis (PCA), partial least squares_discriminant analysis (PLS_DA), heatmap analysis, Pearson correlation analysis, debiased sparse partial correlation analysis, and random forest analysis, were performed using the online platform MetaboAnalyst 6.0 https://www.metaboanalyst.ca/ (accessed on 1 May 2025) [28]. Differentially expressed metabolites (DEMs) were screened by a fold change threshold of ≥1.2 or ≤0.8, variable importance in projection (VIP) scores ≥1, and p-value ≤ 0.05.

2.5. Data Analysis

Data were compiled using WPS (version 2019) and subsequently analyzed with SPSS (version 19.0). Significant differences were assessed by Student’s t-test or one-way ANOVA (p ≤ 0.05). Data are expressed as mean ± standard deviation.

3. Results

3.1. Leaf Pigments

The contents of chlorophyll a, chlorophyll b, and total chlorophyll b decreased dramatically at the end of 38 °C, slowly decreased to a very low value at the end of 48 °C, and maintained until the end of curing (Figure 2a–c). PS slightly delayed the degradation of chlorophyll during pre-curing, with the contents of chlorophyll a, chlorophyll b, and total chlorophyll being slightly higher than CK. During curing, the chlorophyll contents detected at most temperature points were similar between PS and CK. Only at 45 °C, the content of chlorophyll a and total chlorophyll under PS were significantly higher than that under CK; at 68 °C, the content of chlorophyll b under PS was significantly lower than that under CK. During curing, the carotenoid content initially decreased, then increased, reaching a peak at the end of the 45 °C, followed by a fluctuating downward trend (Figure 2d). Similarly, the carotenoid contents detected at most temperature points were similar between PS and CK. Only at 38 and 60 °C, the content of carotenoid under PS was significantly lower than that under CK; at 45 °C, the content of carotenoid under PS was significantly higher than that under CK.

3.2. Leaf Non-Structureal Carbohydrate

The content of starch dropped dramatically at the end of 42 °C, then slowly decreased until the end of curing (Figure 3a). Compared to CK, PS showed significantly lower starch content before curing. However, the starch content dropped faster under CK than that of PS, with significantly lower starch content detected before the end of 45 °C during curing. By contrast, PS caused faster degradation of starch from 48 °C, with significantly lower starch content detected at 51 °C, 54 °C, 60 °C, and 68 °C. The content of soluble sugar increased dramatically at the end of 40 °C, then fluctuated and remained at a high level until the end of curing (Figure 3b). PS significantly increased the soluble sugar content before curing, while in the early stage of curing, the sugar content did not increase as fast as CK, and the sugar content was significantly lower than CK at 38 °C and 40 °C. However, after reaching the peak, the soluble sugar content under PS decreased slightly, and the content was significantly higher than that of CK until the end of curing.

3.3. Leaf Carbohydrate Transformation

To gain insights into the effects of PS on saccharides metabolome dynamics in tobacco leaves, targeted glycomics analysis was performed using a GC–MS platform. A total of 21 saccharides were identified and predominantly classified into three distinct groups, comprising 17 monosaccharides, 3 disaccharides, and 1 terpenoid (Figure 4a, Table S1). PCA revealed distinct metabolome profiles between PS and CK before curing, as well as at 38 °C, 40 °C, 42 °C, 54 °C, and 68 °C. PC1 and PC2 explained 65.1% and 34.2% of the variance, respectively (Figure 4b). Subsequently, PLS_DA analysis was employed to enhance the differentiation between PS and CK, confirming the suitability of the model for identifying differentially expressed metabolites (DEMs). Component 1 and Component 2 accounted for 60.6% and 38.9% of the variance, respectively (Figure 4c).

The heatmap analysis highlighted substantial fluctuations in metabolite levels throughout the curing process (Figure 5a). Samples collected before curing, as well as those subjected to curing temperatures of 38 °C and 40 °C, formed a cohesive cluster. In contrast, samples exposed to 42 °C, 54 °C, and 68 °C were grouped separately. The 21 identified metabolites were categorized into two distinct groups: one comprising 8 metabolites that exhibited relatively low levels before the curing phase concluded at 40 °C, followed by varying degrees of increase after the curing temperature reached 42 °C; the other consisting of 13 metabolites whose levels oscillated more frequently throughout the curing process.

Pairwise comparison analyses identified 5 up-regulated and 1 down-regulated differentially expressed metabolites (DEMs) (fold change ≥1.20 or ≤0.80, p value ≤ 0.05, and VIP value ≥ 1.00) in the comparison of PS_BC versus CK_BC, with 2 up-regulated and 10 down-regulated DEMs in PS_38 °C versus CK_38 °C, 5 down-regulated DEMs in PS_40 °C versus CK_40 °C, 4 up-regulated and 7 down-regulated DEMs in PS_42 °C versus CK_42 °C, 5 up-regulated and 3 down-regulated DEMs in PS_54 °C versus CK_54 °C, and 6 up-regulated and 5 down-regulated DEMs in PS_68 °C versus CK_68 °C (Figure 5b).

Before curing, the total saccharide content under PS increased by 38.17% compared to CK (

Table 1. The contents of saccharide in tobacco leaf before and after curing.

Saccharide	CK_BC (mg/g)	PS_BC (mg/g)	CK_68 °C (mg/g)	PS_68 °C (mg/g)
Sucrose	28.807 ± 0.736 c	37.982 ± 3.678 c	103.239 ± 16.819 b	121.16 ± 2.013 a
Glucose	8.797 ± 0.164 d	15.089 ± 2.613 c	26.196 ± 0.336 b	45.605 ± 0.672 a
D-Fructose	7.783 ± 0.131 d	11.892 ± 1.573 c	18.621 ± 0.33 b	31.002 ± 0.391 a
Inositol	6.572 ± 0.183 bc	7.260 ± 0.401 b	8.879 ± 0.739 a	6.394 ± 0.464 c
D-Mannose	0.033 ± 0.001 d	0.060 ± 0.004 c	0.341 ± 0.002 b	0.551 ± 0.003 a
Methylgalactoside	0.504 ± 0.010 b	0.467 ± 0.008 c	0.543 ± 0.008 a	0.332 ± 0.014 d
Maltose	0.148 ± 0.005 b	0.144 ± 0.02 b	0.237 ± 0.044 a	0.228 ± 0.016 a
D-Ribose	0.176 ± 0.002 b	0.199 ± 0.005 a	0.084 ± 0.002 c	0.072 ± 0.005 d
D-Galactose	0.176 ± 0.003 b	0.198 ± 0.011 a	0.112 ± 0.008 d	0.128 ± 0.008 c
D-Sorbitol	0.016 ± 0.001 c	0.013 ± 0.001 d	0.042 ± 0.002 b	0.066 ±0.000 a
Raffinose	0.005 ± 0.000 b	0.005 ± 0.002 b	0.062 ± 0.010 a	0.064 ± 0.001 a
L-Fucose	0.060 ± 0.002 b	0.059 ± 0.001 b	0.065 ± 0.004 a	0.047 ± 0.001 c
D-Xylulose	0.012 ±0.000 c	0.012 ±0.000 c	0.032 ± 0.001 b	0.034 ±0.000 a
D-Xylose	0.020 ±0.000 bc	0.028 ±0.000 a	0.023 ± 0.003 bc	0.024 ± 0.001 c
D-Arabinose	0.013 ± 0.000 d	0.015 ± 0.001 c	0.017 ± 0.001 b	0.019 ± 0.000 a
D-Glucuronic acid	0.013 ±0.000 c	0.013 ± 0.003 c	0.028 ± 0.001 a	0.018 ±0.000 b
L-Rhamnose	0.031 ± 0.001 a	0.033 ± 0.001 a	0.020 ± 0.001 b	0.017 ± 0.001 c
D-Galacturonic acid	0.003 ± 0.000 b	0.004 ± 0.000 b	0.005 ± 0.001 b	0.013 ± 0.001 a
2-Deoxy-D-ribose	0.009 ± 0.000 b	0.009 ± 0.001 b	0.011 ± 0.001 a	0.009 ± 0.000 b
Xylitol	nd	nd	0.003 ± 0.000 a	0.002 ± 0.000 b
Phenylglucoside	nd	nd	0.006 ± 0.000 b	0.016 ± 0.000 a
Total	53.18 ± 1.184 d	73.48 ± 8.233 c	158.563 ± 17.278 b	205.800 ± 3.430 a

BC, before curing; CK, control; PS, postharvest shading; nd, not detected. Different letters indicate significant differences by one-way ANOVA (p ≤ 0.05).

). Notably, PS led to significant increases in D-mannose (78.67%), glucose (71.53%), D-fructose (52.79%), D-xylose (34.57%), and sucrose (31.85%) before curing, while D-sorbitol content decreased by 18.04%. Upon completion of flue-curing, the total saccharide contents increased significantly, by 198.16% under PS and 180.08% under CK. Among the saccharides, raffinose showed the most substantial increase, with contents rising by 1238.52% under PS and 1061.41% under CK. D-mannose also increased substantially, by 823.47% under PS and 920.85% under CK, followed by D-sorbitol, which increased by 395.02% under PS and 158.64% under CK. Meanwhile, sucrose (219.00% and 258.38%), glucose (202.25% and 197.79%), and D-fructose (139.25% and 160.70%) increased substantially under both PS and CK. Conversely, D-ribose, L-rhamnose, and D-galactose showed the most pronounced decreases, with reductions ranging from 35.51% to 64.01%. Compared to CK, phenylglucoside content exhibited the greatest increase (190.97%) after curing under PS, followed by D-galacturonic acid (165.55%). Conversely, methylgalactoside content decreased the most (38.85%) under PS, followed by D-glucuronic acid (33.33%). Notably, glucose, D-fructose, and sucrose, the dominant saccharides, increased by 74.09%, 66.49%, and 17.36%, respectively, under PS.

Pearson correlation analysis revealed that 21 metabolites were clustered into two groups (Figure 6a). Overall, most metabolites exhibited negative correlations among groups and showed positive correlations within each group, indicating extensive interconversion between these two types of metabolites during the curing process. Specifically, within group I, the contents of the three metabolites highlighted in the green box showed a significant positive correlation, while the contents of the nine metabolites highlighted in the yellow box were mostly significantly positively correlated. Similarly, within group II, the contents of the nine metabolites were mostly significantly positively correlated.

The top 10 metabolites correlating with the contents of total saccharide, sucrose, glucose, and D-fructose were presented (Figure 6b). Notably, glucose, D-fructose, and sucrose were identified as the top 3 saccharides that were significantly positively correlated with total saccharide content, whereas methylgalactoside and L-fucose exhibited significant negative correlations with total saccharide content. The content of sucrose was significantly positively correlated with D-xylulose, D-sorbitol, and raffinose, while being significantly negatively correlated with D-ribose, methylgalactoside, and L-fucose. The content of glucose was significantly positively correlated with D-fructose, total sugars, and D-xylose, while being significantly negatively correlated with methylgalactoside. The content of D-fructose was significantly positively correlated with glucose, D-xylose, and total saccharide, while being significantly negatively correlated with methylgalactoside.

Debiased sparse partial correlation analysis facilitates the identification of novel metabolic pathways or network modules within the saccharide and alcohol metabolite network of tobacco leaves during curing. The results indicated that four metabolites with high edge degrees were identified as network nodes in the metabolite network during tobacco leaf curing (Figure 7a). These metabolites included one trisaccharide (raffinose), two disaccharides (maltose and sucrose), and one monosaccharide (methylgalactoside), suggesting their significant roles within the metabolic network.

Random forest analysis revealed that D-mannose, D-sorbitol, and D-glucuronic acid could serve as potential molecular biomarkers for the tobacco leaf curing process under different temporary storage conditions (Figure 7b), suggesting their potential utility in monitoring metabolic shifts and assessing the impact of storage conditions on curing efficiency and end-product quality.

4. Discussion

4.1. Postharvest Shading Slightly Impacted Leaf Pigments Degradation During Curing

The flue-curing method has become the dominant approach in tobacco processing due to its superior efficiency and product quality compared to traditional sun/air-curing methods. A critical stage in the flue-curing process is the yellowing phase, during which significant changes occur in the pigment composition of tobacco leaves, particularly the accelerated breakdown of chlorophyll catalyzed by enzymatic activity [16,17]. Previous studies have indicated that optimized pre-curing protocols can accelerate the kinetics of chlorophyll degradation during the yellowing phase, thereby reducing energy consumption and enhancing overall leaf quality parameters [22,23]. During leaf senescence, the degradation of tobacco chloroplast ultrastructure in mesophyll cells correlates with changes in chlorophyll content, concurrent declines in bioactive cytokinin levels, reduced IAA/ABA ratios, and distinct gene expression patterns, including up-regulation of senescence-associated genes such as CP1/CP23 and GDH/GS1, alongside the continuous down-regulation of GS2 genes [29]. Typically, intense light exposure exhibits a significant capacity to accelerate chlorophyll degradation of tobacco leaves [30]. Consistent with these findings, PS temporarily retarded chlorophyll degradation during pre-curing storage compared to CK. However, PS accelerated chlorophyll degradation during the initial yellowing phase. This acceleration is likely due to the higher chlorophyll content retained under PS conditions, which acted as an expanded enzymatic substrate pool under elevated curing temperatures, suggesting that pre-curing conditions may modulate intermediate steps of leaf pigment metabolism. However, no visible differences in leaf color were observed between PS and CK after curing. Furthermore, the total contents of chlorophyll and carotenoid were comparable between PS and CK, indicating that PS had a negligible impact on the final pigment profiles of tobacco leaves.

4.2. Postharvest Shading Altered Starch-Sugar Transformation

Starch, a critical determinant of both sensory quality and smoking safety in flue-cured tobacco, is associated with excessive burnt odors, harsh smoke, and increased irritation when present in excessive amounts [31,32]. Soluble sugars, primarily consisting of sucrose, glucose, and fructose, are the key sweetening components in flue-cured tobacco leaves [2,6]. Compared to darkness, light exposure maintains postharvest photosynthetic capacity in spinach leaves, thereby promoting the accumulation of soluble carbohydrates, particularly glucose [33]. In this study, tobacco leaves were collected in the early morning, immediately following shading treatment that simulated an extended night period. It was reasonable that PS caused significantly lower starch levels in tobacco leaves before curing compared to CK, likely due to limited photosynthesis. Plants synthesize carbohydrates via daytime photosynthesis, accumulating them as transient starch reserves, which are subsequently hydrolyzed into sugars during the night to sustain growth and developmental processes [34,35]. However, shaded leaves exhibited significantly higher soluble sugar levels than CK, including elevated sucrose, glucose, and D-fructose before curing. This suggests that, unlike CK, PS might redirect metabolic fluxes toward soluble sugar production, possibly via enhanced starch degradation or altered carbon partitioning. Despite this, PS resulted in slower starch degradation rates during yellowing compared to CK, particularly at critical temperatures of 38 °C, 40 °C, and 42 °C. Interestingly, while CK leaves displayed a specific starch transform pattern after yellowing (initial slow increase followed by a gradual decrease), shaded leaves exhibited a consistent downward trend. As a result, shaded leaves exhibited significantly lower starch content after 48 °C and higher soluble sugar content after 40 °C. This suggests that PS might sustain more persistent starch degradation by avoiding light-triggered metabolic oscillations of carbohydrates, thereby enhancing carbohydrate stability under thermal conditions.

In the tobacco processing industry, various strategies have been investigated to degrade starch and increase sugar content, including modified curing protocols [4], starch-degrading bacterial inoculants [5], and exogenous sucrose applications [36]. In this study, PS resulted in a significantly lower starch content (a decrease of 14.17%) and a higher soluble sugar content (an increase of 8.03%) at the end of the curing process. Considering that shading is a highly cost-effective, easily operable, and widely adaptable method, these findings suggest that PS pre-curing could potentially serve as an effective tool for promoting starch degradation and sugar accumulation during postharvest processing.

4.3. Postharvest Shading Altered Saccharides Transformation During Curing

As a powerful analytical tool, targeted glycomics has revolutionized the detection and quantification of complex saccharide profiles [37]. In plant science, targeted glycomics plays a crucial role in deciphering the dynamic interplay of carbohydrate metabolism, especially during PS like the curing of Rehmanniae Radix [38]. In this study, a total of 21 saccharides in tobacco leaves were detected and quantified via targeted glycomics, with sucrose, glucose, D-fructose, and inositol being the most abundant. Clustering analysis of saccharides at different curing temperatures revealed significant saccharide transformations when the curing temperatures exceeded 42 °C. Pairwise comparison analyses revealed varying numbers of DEMs across different temperature comparisons between PS and CK. Generally, PS resulted in fewer up-regulated DEMs during the yellowing stage (38 °C, 40 °C, and 42 °C), but a significant increase in the number of up-regulated DEMs was observed at the color-fixing (54 °C) and dry-tendon (68 °C) stages. Fructose, glucose, myo-inositol, and sucrose are not only key determinants of sweetness perception but also contribute to the overall flavor profile of cigarette smoke by acting as precursors for volatile compounds and participating in Maillard reactions [11]. In this study, inositol content remained relatively stable throughout the curing process, while glucose, D-fructose, and sucrose exhibited marked changes. Compared to CK, the contents of glucose (1.74-fold), D-fructose (1.66-fold), and sucrose (1.17-fold) increased under PS, suggesting that PS could be a valuable tool for modulating tobacco quality attributes. Pearson correlation analysis revealed a distinct clustering of the 21 identified saccharides into two groups, with the majority of saccharides exhibiting positive correlations within each group and negative correlations between the groups. Notably, glucose, D-fructose, and sucrose were the top 3 saccharides in correlation with the total saccharides content, suggesting that they might serve as auxiliary reference indicators for evaluating the total sugar content in tobacco leaves. As the primary carbohydrate in saccharide metabolism, sucrose is transported over long distances and functions as the main sweetener, significantly impacting tobacco quality [2,25,33,34,39,40]. Interestingly, despite its prominence in saccharide metabolism, sucrose did not cluster with glucose or D-fructose and was not among the top 10 related metabolites. This observation, coupled with the findings from debiased sparse partial correlation analysis, which highlighted sucrose as a key network node with extensive interconnections to other metabolites, suggests a unique and multifaceted role for sucrose in tobacco leaf curing. These interconnections likely facilitate the interconversion between sucrose and other saccharides in tobacco leaves during curing.

Oligosaccharides are widely present in various tobacco products, including flue-cured tobacco, sun/air-cured tobacco, and the cut filler of commercially available tobacco [41]. Raffinose is a widespread trisaccharide belonging to soluble carbohydrates, ranked next to sucrose in their distribution in higher plants [42]. During curing, raffinose was the most increased saccharide, with contents rising by 1238.52% under PS and 1061.41% under CK. Maltose, a major disaccharide derived from starch hydrolysis, is subsequently converted into glucose [43]. Contrary to previous reports of undetectable maltose levels [44], GC-MS analysis in this study revealed quantifiable maltose concentrations (0.23~0.24 mg/g) in cured tobacco leaves. The identification of maltose and raffinose as prominent network nodes with high edge degrees by debiased sparse partial correlation analysis further emphasized the importance of oligosaccharides, which might serve as metabolic intermediates, contributing to the overall metabolic flux and equilibrium among different saccharides.

Although there is a relative paucity of research literature regarding plant-derived methylgalactoside, it has been proposed that methylgalactoside may potentially serve as a biomarker for elucidating the pathophysiology of anorexia nervosa [45]. It is plausible that methylgalactoside might play a role in modulating the flux through specific metabolic pathways, thereby influencing the accumulation and interconversion of other saccharides. In this study, the negative correlations of methylgalactoside with total saccharides, glucose, D-fructose, and sucrose, coupled with its identification as a prominent network node by debiased sparse partial correlation analysis, suggested that methylgalactoside might function as a metabolic regulator or biomarker in tobacco leaf curing.

D-galacturonic acid and D-glucuronic acid have been screened as the potential molecular biomarkers for appraising fruit softening progression during postharvest storage of apples [46]. Sorbitol, recognized as a distinct photosynthetic product, is transported over long distances within the plant body, particularly in the leaves of numerous fruit tree species [47]. It has been reported that sorbitol is crucial in the developmental stage-specific modulation of growth strategies through gibberellin-mediated signaling pathways [48]. Mannitol and sorbitol have been assessed as slow-growth storage supplements in MS medium based on their impacts on seedling survival rates, morphogenic responses, and post-storage recovery capabilities [49]. In this study, D-mannose (823.47% and 920.85%) and D-sorbitol (395.02% and 158.64%) were dramatically increased under both PS and CK during curing. Meanwhile, the identification of D-mannose, D-sorbitol, and D-glucuronic acid as potential molecular biomarkers for the tobacco leaf curing process through random forest analysis represented a significant advancement in understanding the biochemical dynamics associated with temporary storage conditions.

5. Conclusions

In conclusions, PS delayed chlorophyll degradation during pre-curing, yet no substantial differences in final pigment profiles were observed between PS and CK. Notably, PS induced profound alterations in starch-sugar interconversion dynamics, as indicated by suppressed starch biosynthesis and elevated soluble sugar levels during pre-curing, followed by a reduced rate of starch degradation during curing. These changes resulted in significantly lower starch content and higher soluble sugar content in PS leaves after curing compared to CK, suggesting potential benefits for tobacco sensory quality and smoking safety. Targeted glycomics identified 21 saccharide metabolites in tobacco leaves, with glucose, D-fructose, and sucrose being dominant. PS cured leaves exhibited increased contents of sucrose, glucose, and fructose, ranging from 17.36% to 74.09% relative to CK. These saccharides displayed a strong positive correlation with total saccharide content, highlighting their potential as surrogate markers for total sugar content assessment. Network analysis identified sucrose, maltose, raffinose, and methylgalactoside as pivotal metabolic nodes, implying their involvement in orchestrating saccharide metabolic fluxes. Additionally, D-mannose, D-sorbitol, and D-glucuronic acid emerged as biomarkers for tracking metabolic perturbations during the curing process. Collectively, these findings suggest PS as a valuable strategy for improving tobacco quality by modulating saccharide metabolism in tobacco curing, offering a scientific foundation for pre-curing protocol optimization and industrial application.