Next Article in Journal
Integration of Green and Far-Red Light with Red-Blue Light Enhances Shoot Multiplication in Micropropagated Strawberry
Previous Article in Journal
Fruit Astringency: Mechanisms, Technologies, and Future Directions
Previous Article in Special Issue
A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Horticulturae
Volume 11
Issue 6
10.3390/horticulturae11060700
horticulturae-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Intermittent Blue Light Supplementation Affected Carbohydrate Accumulation and Sugar Metabolism in Red-Light-Grown Tomato Seedlings

by
Xiangyu Gao
1,2,
Lingzhi Li
3,
Wenzhong Guo
1,
Yifan Zhai
1,3,
Xiaoming Wei
1,* and
Xiaoli Chen
1,*
1
Intelligent Equipment Technology Research Center, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China
2
College of Horticulture and Landscape Architecture, Tianjin Agricultural University, Tianjin 300384, China
3
College of Horticulture, Shanxi Agricultural University, Jinzhong 030801, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(6), 700; https://doi.org/10.3390/horticulturae11060700
Submission received: 27 April 2025 / Revised: 31 May 2025 / Accepted: 15 June 2025 / Published: 17 June 2025
(This article belongs to the Special Issue LED Lighting Effects on the Growth and Development of Fruits and Vegetables)
Browse Figures
Versions Notes

Abstract

:
According to previous studies, dynamic light regimes might enhance seedling development, survival rates, or economic efficiency in factory-based seedling production systems compared to continuous red and blue light irradiation. However, there have been few studies revealing the effects of discontinuous red and blue light on the carbohydrate accumulation and metabolism of tomato seedlings. Therefore, we planted tomato seedlings in an artificial light plant factory under a red background light with intermittent blue light intervention, namely R (as the control), R/RB32, R/RB40, R/RB64, and R/RB80 at an equal daily light integral. The growth, carbohydrate accumulation, and sugar metabolism were analyzed to investigate the effects of dynamic lighting modes on tomato seedlings. The results demonstrated the following: (1) Pure red light induced spindling of tomato seedlings, while intermittent blue light treatments enhanced stem thickness, leaf number, and leaf area, resulting in greater biomass accumulation. Among these treatments, the highest antioxidant enzyme activity and the lowest reactive oxygen species (ROS) content, accompanied by the highest biomass, were all observed in tomato seedlings subjected to R/RB80 (intermittent supplementation of 80 μmol·m−2·s−1 blue light under red light background). (2) The carbohydrate accumulation in tomato seedlings was increased under all treatments relative to the control. The sucrose content, enzyme activity, and gene expression level of sucrose phosphate synthase (SPS) were all up-regulated in tomato leaves treated with blue light irradiation compared with pure R. In addition, the highest soluble sugar content, along with the peak SPS activity and gene expression, was observed under the R/RB80 treatment. Meanwhile, the lowest fructose content accompanied by the lowest activity and gene expression of sucrose synthase (SS) were observed in tomato leaves treated with R/RB32. This implies that blue light supplementation may regulate sugar accumulation by modulating the activity or expression of enzymes involved in sucrose metabolism. (3) Moreover, shoot biomass, enzyme activity, and expression level of SPS were all found to increase with the increase in supplementary blue light intensity, indicating that short-duration high-intensity blue light was more effective in promoting carbohydrate accumulation in tomato seedlings than long-term low-intensity blue light based on the equal DLI.

1. Introduction

Tomato (Solanum lycopersicum), a dual-purpose crop for both fruit and vegetable production, is rich in nutrients such as lycopene, vitamins, and carotenoids [1]. As a light-demanding species, tomato seedlings require intensive illumination due to their early bud differentiation and short vegetative growth period [2]. Light served as the primary energy source for photosynthesis as well as a key modulator of crop productivity and metabolic profiles [3]. To optimize biomass accumulation and physiological preparedness for subsequent growth stages, LED light sources were widely adopted in factory-based tomato seedling cultivation [4,5,6]. Precise light regulation not only accelerates breeding cycles and improves seedling quality but also enables standardized industrial-scale production. Given the critical role of seedling quality in determining survival rates and ultimate yield, mechanistic studies investigating how LED light regulates tomato seedling development are essential for optimizing production strategies.
Light acts as a signal to regulate plant growth and development. Plants sense light signals of different wavelengths (e.g., red, far-red, blue, or ultraviolet light) through a series of photoreceptors, which regulate downstream signaling pathways to control plant growth and development [7]. Phytochromes (PHYA, PHYB, PHYC, PHYD, phyE) serve as red and far-red light receptors, while cryptochromes (CRY1, CRY2, CRYy3) and phototropins (PHOT1, PHOT2) act as blue ultraviolet light receptors [8]. These photoreceptors play a crucial role in plant photomorphogenesis. Zhou et al. [9] found that under blue light, cryptochrome promoted interaction and ubiquitination between NPR1 (NONEXPRESSER OF PATHOGENESIS-RELATED GENES 1) and PIF4 (Phytochrome Interacting Factor 4), thereby inhibiting the hypocotyl elongation of Arabidopsis seedlings. Yan et al. [10] demonstrated that phyB indirectly promoted the expression of cell elongation-related genes under red light irradiation in Arabidopsis. Light receptors can also synergistically regulate photomorphogenesis with hormones. For example, Xu et al. [11] discovered that blue light signaling mediated by cryptochrome 1 (CRY1) induced photomorphogenesis in Arabidopsis by inhibiting gibberellin signaling; additionally, Xu et al. [12] suggested that auxin signaling was affected by the interaction of light receptors (CRY1 or PHYB) with AUX/IAA proteins (Auxin/Indole-3-Acetic Acid proteins) in Arabidopsis under blue or far-red light, and the balanced light and auxin signals jointly regulated plant morphogenesis. These studies indicated the regulatory chain of “light signal—hormone—growth” in plants. This mechanism not only revealed the interaction between light receptors and hormone signaling networks but also explained the morphological adaptation of plants to the light environment, such as shade avoidance syndrome. Shade avoidance syndrome (SAS) is a typical adaptive response of plants to shaded conditions and is characterized by morphogenetic changes such as stem elongation and reduced leaf expansion [13]. In the shade avoidance response, the light signals that can be recognized by plant photoreceptors and trigger the shade avoidance response are referred to as shade signals [14]. These shade signals include a decrease in the red-to-far-red light ratio (R/FR) and a reduction in blue light and UV-A. However, studies have demonstrated that shade avoidance syndrome could be inhibited by cryptochrome (CRYs) [15,16]. Currently, the effect of blue intermittent light on SAS in tomatoes remains unclear, especially in applied research of supplementary lighting in protected agriculture.
Carbohydrates, the primary products of photosynthesis, were predominantly composed of sucrose, glucose, fructose, and starch. These compounds serve dual roles as carbon skeletons for morphogenesis and metabolic energy for cellular activities [17,18,19]. The dynamics of carbohydrate synthesis, translocation, and catabolism critically determine crop yield potential and quality attributes. In tomato seedlings, carbohydrate accumulation provides the substrate pool for cell division and expansion, while sugar metabolism dynamically governs source–sink allocation through the coordinated action of key enzymes, including sucrose phosphate synthase (SPS), sucrose synthase (SS), acid invertase (AI), and neutral invertase (NI) [20,21,22]. Emerging evidence highlighted spectral optimization as a potent strategy to enhance seedling vigor through efficient carbohydrate allocation. For instance, Wang et al. [23] demonstrated that the content of total sugar, sucrose, and starch were all increased in cucumber under blue light compared to white light or pure red light. Similarly, Kondo et al. [24] reported that the highest total sugar content was observed under blue light in grape berries compared with red light. Conversely, Choi et al. [25] found that pure red light was more conducive to the synthesis of sucrose in strawberry compared with pure blue light, suggesting species-specific responses to light quality.
With the advancement of LED and light formula control technologies, plant light formulas are no longer limited to adjusting light quality, intensity, or photoperiod but have extended to the modulation of light patterns [26,27]. The antagonistic effects of red and blue light on certain plant physiological activities might be mitigated by optimizing light supply modes [28]. In previous studies on light supply modes, the intensity and/or ratio of red and blue light in continuous mixed red and blue light were primarily explored [29,30,31]. However, recent studies have shown that the short-duration high-intensity blue light irradiation enhanced biomass and secondary metabolites in lettuce, whereas prolonged high-intensity exposure to blue light induced photo-oxidative damage [32]. Sivakumar et al. [33] found that the dry weight, leaf area, and carbohydrate content of sweet potato were increased under intermittent blue light and mixed red and blue light treatments compared to continuous white light irradiation. Furthermore, Elkins and van Iersel [34] demonstrated that, at the same DLI, the daily photochemical integral (DPI) in lettuce was improved under extending photoperiods with lower intensity. These findings collectively highlighted that strategic red–blue light supplementation could synergistically optimize seedling morphogenesis and metabolism by balancing light duration, light intensity, and light quality.
The above studies have shown that different wavelengths of light (such as red light, blue light, and far-red light) have specific regulatory effects on plant photomorphogenesis, flowering time, secondary metabolism, etc. Compared to continuous red and blue light irradiation, dynamic light regimes might enhance seedling development, survival rates, or economic efficiency in factory-based seedling production systems. DLI (daily light integral), defined as the total amount of photosynthetically active radiation (PAR) received per day, directly influences the photosynthetic output and growth rates. Therefore, this study investigated a dynamic lighting regime based on equal DLI. This approach ensured consistent total photon input across all treatment groups while isolating the effects of spectral modulation strategies. Under the same DLI, we compared the impacts of varying intensities of blue light on tomato seedlings to reveal how specific wavelengths and intervention intensities regulate photomorphogenesis and sugar metabolism. Further, we investigated the growth and carbohydrate allocation in tomato seedlings exposed to intermittent blue light supplementation based on red light background illumination. And the enzymatic activity and gene expression level of sucrose metabolism-related enzymes such as SPS, SS AI, and NI were analyzed to investigate the effects of intermittent red and blue light on the sugar metabolism of tomato seedlings.

2. Materials and Methods

2.1. Experimental Setup and Growth Conditions

The experiment was conducted in a plant factory with artificial lighting (PFAL) in BAAFS, Beijing, China. Tomatoes (Solanum lycopersicum cv. Micro Tom) were cultivated in Groden agricultural rock wool imported from the Netherlands. Environmental conditions in the plant factory were maintained at 24 ± 1 °C (day)/13 ± 1 °C (night), 65 ± 1% relative humidity, and 450 ± 2 μmol·mol−1 CO₂ concentration. The nutrient solution was formulated using the Japanese Yamazaki formula, with irrigation applied once daily. Throughout the entire experimental period (40 days), the electrical conductivity (EC) of the nutrient solution was regulated to the range of 1.2–1.8 mS·cm−1, and each plant received 720 mL of nutrient solution per irrigation.
An LED spectral modulation system, which could be set to any light recipe and irradiation mode, was used as the light source. LED panels providing red (peak at 660 nm) and blue (peak at 450 nm) light were suspended vertically from the top of the plants, positioned 60 cm above the cultivation surface. After sowing, the rock wool blocks were cultivated under different red and blue light supply modes, with a 16 h photoperiod (8:00–24:00) and 8 h dark phase. The photosynthetic photon flux density (PPFD) was measured using an LI-250A light meter (LI-COR Biosciences, Lincoln, NE, USA) at plant canopy. The experiment lasted for 40 days, starting from sowing.
Tomato seedlings were exposed to differential light patterns (Table 1), with all five light treatments maintaining an identical daily light integral (DLI) of 12.672 mol·m−2. Pure red light (220 μmol·m−2·s−1) with a 16 h photoperiod served as the control. Treatment groups received intermittent blue light supplementation (1.152 mol·m−2 DLI) under red light background (200 μmol·m−2·s−1, 16 h photoperiod). Blue light intensities were set at 32, 40, 64, and 80 μmol·m−2·s−1, with total durations of 10, 8, 5, and 4 h, respectively. The control was denoted as R, while treatments were, respectively, labeled as R/RB32, R/RB40, R/RB64, and R/RB80 (Figure 1).

2.2. Sampling and Index Determination

Nine tomato seedlings randomly selected from each treatment were considered as one replication, with three replications per treatment. The height and stem diameter of the seedlings, as well as the number and area of leaves, were measured at 20, 23, 26, 29, 32, and 35 days after sowing (DAS). Dry weight (DW), serving as the biomass indicator, was measured at harvest (40 days after sowing, 40 DAS). Plant material was oven-dried at 70 °C for 48 h until reaching constant weight, followed by DW determination. Seedling height and leaf area were measured using a ruler, while stem diameter was measured using a vernier caliper. Biomass was determined using an electronic balance.

2.3. Determination of Carbohydrates

For total carbohydrates, sugar, and starch analysis, leaves were sampled at 11:00 on the day of harvest (40 DAS). The contents of total carbohydrates, glucose, fructose, sucrose, and starch were determined according to Buysse and Merckx [35]. The freeze-dried plant samples (0.20 g) were extracted overnight in 25 mL of 80% ethanol (v/v), and the supernatant was analyzed for the contents of sucrose, fructose, glucose, and total carbohydrates. The precipitate was collected and boiled in 10 mL of 2% HCl (v/v) for 3 h, and the supernatant was used for starch content analysis.

2.4. Determination of Protein, Ash, Water, and Fat Contents

Fresh tomato leaf and stem samples (1 g) were separately mixed with 5 mL of 80% (v/v) ethanol, placed in an 80 °C water bath for 30 min, and centrifuged at 12,000× g for 10 min. The supernatant was collected to measure the contents of protein, fat, and ash using the biochemical analysis kits according to the instructions of the ELISA kit (Shanghai C-Reactive Biotechnology Co., Ltd., Shanghai, China).

2.5. Determination of Enzyme Activities and ROS Content

Fresh tomato leaf and stem samples (0.5 g) were separately mixed with 5 mL of pre-chilled extraction buffer (50 mM phosphate buffer, pH 7.0, containing 1% PVP and 1 mM EDTA) and thoroughly ground into a homogenate under ice-bath conditions. The homogenate was transferred to a centrifuge tube and centrifuged at 4 °C for 20 min at 12,000× g. The supernatant was collected for the measurement of activities of antioxidant enzymes (superoxide dismutase, SOD [E.C.1.15.1.1]; peroxidase, POD [E.C.1.11.1.7]; catalase, CAT [E.C.1.11.1.6]) and the content of reactive oxygen species (ROS). Among these, the activities of antioxidant enzymes (SOD, POD, CAT) were determined using enzyme-linked immunosorbent assay kits, and ROS content was quantified according to the biochemical analysis kit protocol. The above measurements were conducted according to the instructions of the ELISA kit (Shanghai C-Reactive Biotechnology Co., Ltd.).
Frozen samples (1.0 g) were mixed with 5 mL of 0.1 M Tris-HCl buffer, ground, and extracted in liquid nitrogen [26]. The extract was centrifuged at 10,000× g for 20 min at 2 °C, and the supernatant was dialyzed against fivefold-diluted Tris–HCl buffer. The dialyzed supernatant was used to determine the activities of sucrose metabolism-related enzymes. Sucrose phosphate synthase (SPS, EC 2.4.1.14) activity was quantified by sucrose production [36,37]. Similarly, sucrose synthase (SS, EC 2.4.1.13), acid invertase (AI, EC 3.2.1.26), and neutral invertase (NI, EC 3.2.1.26) activities were determined by quantifying reducing sugars from sucrose hydrolysis [38,39].

2.6. Sucrose Metabolism-Related Gene Expression Analysis by Quantitative Real-Time Reverse-Transcription Polymerase Chain Reaction (RT-PCR)

Gene expression levels were quantified using quantitative real-time RT-PCR, as described by Tamura et al. [40]. RNA-seq was employed to sequence the tomato samples. Primer pairs for real-time PCR were designed using Premier Primer 6.0 based on the original sequences. The GAPDH gene was used as an internal control in the assay. The primer sequences for the target gene and the internal reference gene were designed and are shown in Table 2.

2.7. Statistical Analysis

The data were confirmed by the Shapiro–Wilk test to follow a normal distribution (p > 0.05), and the Levene test confirmed the homogeneity of variance (p > 0.05). Statistical analyses were conducted using one-way analysis of variance (ANOVA) with SPSS statistical software (IBM SPSS Statistics 27.0). Differences among mean values were determined using Tukey’s multiple range test at a significance level of 0.05. Origin 2021 was used for graphing.

3. Results

3.1. The Effect of Different Intermittent Blue Light Supplementation on Growth Dynamics and Biomass of Tomato Seedlings

Dynamic changes in plant height, stem diameter, leaf area, and leaf number of tomato seedlings under intermittent irradiation treatments from 20 to 35 days after sowing (DAS) are shown in Figure 2. At 35 DAS, plant height was reduced by 9.94–19.62% under all blue light treatments compared to the control (pure red light), but there was no significant difference (Figure 2a), while stem diameter, leaf number, and leaf area were increased under all treatments (Figure 2b–d). The highest leaf number and leaf area were both detected under R/RB80, which were significantly enhanced by 59.15% and 32.85%, respectively, compared with the control. The number and the area of tomato leaves were increased with the increase in supplementary blue light intensity.
Pure red light induced expansive growth, whereas intermittent blue light treatments resulted in compact and vigorous morphology of tomato seedlings based on the same daily light integral (DLI).
As shown in Figure 3, at 40 DAS, the dry weight of tomato seedlings was increased under all treatments compared to the control (pure red light). Among the treatments, the highest dry weight was detected under the R/RB80 treatment, which was significantly enhanced by 115.45% relative to the control (p < 0.05). With the supplementary blue light intensity increased from 32 μmol·m−2·s−1 to 80 μmol·m−2·s−1, the dry weight of tomato seedlings gradually increased. These results indicated that intermittent blue light supplementation significantly enhanced biomass accumulation, and the effect became more pronounced at higher blue light intensities based on the same daily light integral (DLI).

3.2. The Effects of Different Intermittent Blue Light Supplementation on Protein, Fat, Water, and Ash in Tomato Seedlings

The mineral composition of tomatoes, represented by ash content, reflects the plant’s capacity to absorb minerals from the nutrient solution. In this study, ash content in tomato leaves was increased under all intermittent blue light-involved treatments compared to the control, while water content exhibited an opposite trend. Notably, the ash content in tomato leaves showed an approximately negative correlation with blue light intensities, increasing by 87.5%, 75%, 62.5%, and 37.5% under R/RB32, R/RB40, R/RB64, and R/RB80, respectively, relative to the control. This indicated that intermittent blue light supplementation enhanced mineral uptake, and long-term low-intensity lighting modes were more favorable for this process. Additionally, the contents of protein and fat were increased in tomato leaves subjected to all blue light treatments except R/RB32, suggesting that short-duration high-intensity intermittent blue light may enhance the synthesis of these compounds (Figure 4).

3.3. The Effect of Different Intermittent Blue Light Supplementation on Carbohydrate Accumulation in Tomato Seedlings

As shown in Figure 5, the contents of sucrose and glucose were increased in tomato seedling leaves treated with all blue light intermittent treatments relative to the control, indicating that the intermittent blue light supplementation may accelerate the accumulation of sucrose and glucose in leaves. Among the blue light treatments, R/RB32 treatment resulted in the highest sucrose content but the lowest fructose and glucose in leaves, while R/RB40 showed the lowest sucrose content and the highest glucose and fructose levels.
In addition, it was noticed that tomato seedlings exposed to R/RB40 treatment displayed the highest total soluble sugar content in leaves while the lowest content in stems, suggesting that the transport of soluble sugars from source to sink may be inhibited under this treatment. Although R/RB80 treatment did not increase the total soluble sugar in leaves as much as R/RB40, it had the greatest effect on increasing the total soluble sugars in stems. The concentrations of glucose, fructose, and sucrose were relatively balanced under R/RB80, indicating stable sugar homeostasis.
Both starch and carbohydrates were enhanced in tomato leaves subjected to all blue-light-involved treatments compared to the control. Compared to the control, starch content in leaves and stems under R/RB40 increased by 49.61% and 26.61%, respectively, reaching the highest levels among all treatments. Tomato seedlings treated with R/RB64 showed the highest total carbohydrate in leaves among all treatments, with an 86.08% increase compared to R.

3.4. The Effect of Different Intermittent Blue Light Supplementation on Antioxidant Enzyme Activities, Sugar Metabolizing Enzyme Activities, and Reactive Oxygen Species (ROS) Content in Tomato Seedlings

Cluster analysis was conducted on sucrose metabolism-associated enzymes, antioxidant enzymes, and ROS in tomato stems and leaves. As shown intuitively from the heatmap (Figure 6), the activities of antioxidant enzymes and sucrose metabolism-associated enzymes were enhanced greatly in tomato plants subjected to R/RB80 treatments, which might explain the higher biomass of tomato seedlings observed in R/RB80 treatment (Figure 2).
A large amount of ROS was produced under environmental stress, which could cause toxicity to plant tissues and physiological metabolism. ROS was removed timely and effectively by antioxidant enzymes to alleviate the abiotic stress in plants. Compared to the control, the activities of CAT in tomato seedlings were increased, while the ROS content in leaves was decreased (by 7.36–20.64%) under all blue-light-involved treatments. The highest enzyme activities of POD and SOD in leaves were detected under R/RB80 treatment, increasing by 14.21% and 2%, respectively, compared to the control.
The key enzymes that promote the synthesis of sucrose are sucrose phosphate synthase (SPS) and sucrose synthase (SS). Among them, SS catalyzed both the synthesis and cleavage of sucrose, while sucrose was irreversibly hydrolyzed into glucose and fructose by acid invertase (AI) and neutral invertase (NI). Compared to the control, SPS activity was increased in leaves and stems under all blue light treatments, with rises of 11.55–23.8% and 0.83–13.67%, respectively. In addition, the results showed that SPS activity in tomato seedlings was increased with the increase in supplementary blue light intensity, suggesting that short-duration high-intensity intermittent blue light was more conducive to SPS activity. In tomato seedings, compared to the control, SS (cleavage) activity in stems was increased under R/RB32, R/RB40, and R/RB80 treatments by 4.63%, 9.18%, and 6.88%, respectively. However, SS (cleavage) activity was decreased in tomato leaves subjected to all blue-light-involved treatments. Long-term low-intensity blue light irradiation such as R/RB32 appeared more effective in enhancing NI activity, which might be attributed to light-induced modulation of pH in seedlings.

3.5. The Effect of Different Intermittent Blue Light Supplementation on the Gene Expression Levels of Sucrose Phosphate Synthase (SPS), Sucrose Synthase (SS), and Invertase in Tomato Seedlings

Figure 7 shows that, compared to the control, the expression of the SS gene (sus3) was down-regulated in tomato seedlings exposed to all intermittent blue light treatments. This indicated that blue light might inhibit the expression level of SS. AI and NI were regulated by the Wiv-1 gene and the LOC101255835 gene, respectively, and the highest gene expression levels of AI and NI were observed under R/RB64 treatment. The highest expression level of the SPS gene (sps) was detected in tomato leaves under the R/RB80 treatment, showing a 42.72% increase compared to the control.

3.6. Correlation Analysis Between Sucrose, Fructose, Glucose, Sucrose Metabolism Enzyme Activities, and Related Gene Expression Levels of Tomato Seedlings

As shown in Figure 8, it was observed that sucrose content was positively related to the activity or gene expression level of SPS while negatively related to those of NI, AI, and SS (cleavage) in tomato seedlings. Moreover, sucrose content was found to be positively correlated with the contents of starch, carbohydrates, proteins, and fats in tomato leaves. It may be because sucrose, serving as the central hub of carbon metabolism in plants, provides essential prerequisites, carbon skeletons, and energy sources for the synthesis of fats and proteins in tomato seedlings. Glucose and fructose in tomato stems were positively correlated with NI activity and NI gene expression level, respectively. This implied that up-regulated activity or gene expression level of sucrose decomposing enzyme accelerated the hydrolysis of sucrose into hexoses in tomato seedlings.
Further analysis revealed that SPS activity was positively correlated with SPS gene expression level in tomato stems. However, the correlation analysis indicated that the activities of sucrose-metabolizing enzymes did not always align with their corresponding gene expression levels. For example, both NI and AI showed negative correlations between their enzymatic activities and gene expression levels in tomato seedlings. This might be because enzyme activity was related not only to gene expression levels but also to many other factors, such as pH, temperature, and product concentration.

4. Discussion

Plants possess a delicate light perception and light signal transduction system, and light environments affect the photoresponse through photoreceptor proteins [41,42]. Phytochromes are the photoreceptors for red light and far-red light, whereas cryptochromes and phototropins act as blue light photoreceptors; these photoreceptors regulate key processes in photomorphogenesis [8]. Different light environments generate different light signals. Shade avoidance syndrome (SAS) is a typical light morphogenetic response of plants to weak light environments [43]. The previous studies demonstrated the necessity of both red and blue light for the growth and development of plants. Blue light could inhibit stem elongation, promote leaf thickening, and increase leaf area, whereas red light modulated internode elongation and flowering time in plants [31]. However, some studies have shown that the growth and development of plants were significantly regulated by the synergistic and antagonistic effects of the light signaling pathway. Chen et al. [28] reported higher lettuce biomass under pure red light (R) compared to alternating red and blue light (R/B) or the mixed red and blue light (RB), and they pointed out that there might be signal crosstalk in the red and blue light signal transduction pathways, and the antagonism could be eliminated by appropriate alternating irradiation of red and blue light. Our study proved that the biomass of tomato seedlings exposed to blue-light-involved treatments (R/RB) was higher than that under R treatment. It seemed that the lighting mode of R/RB could maximize the positive effects of pure red light and the mixture of red and blue light while reducing the antagonistic effect between red and blue light.
In our study, plant height was decreased under all blue-light-involved treatments, while stem thickness, leaf number, leaf area, and the shoot biomass of tomato seedlings were increased relative to the control (pure red light). This result is consistent with the findings of Liang et al. [31], indicating that compared to treatments without blue light, polychromatic light containing blue light resulted in robust growth of tomatoes. This phenomenon might be closely linked with the positive effects of cryptochromes on the expression of genes related to stomatal development [44], the formation of chloroplast thylakoid membranes, and chlorophyll synthesis [45], as well as the positive effects of phototropins on leaf expansion [46]. Furthermore, it had been found that blue light antagonized the shade avoidance response through cryptochrome [16,31], balancing growth and stress resistance. In our study, the inhibition of stem elongation by these blue light-related treatments was consistent with the suppression of cryptochrome-mediated shade avoidance syndrome (SAS). Additionally, our results showed a progressive increase in leaf number, leaf area, and dry weight with elevated blue light intensities based on the same DLI. This trend might be associated with the enhanced antioxidant capacity of tomato seedlings under higher blue light intensities, as supported by Li et al. [47], who demonstrated that low blue light exposure triggered leaf senescence.
Sucrose, the primary product of photosynthesis in leaves (source tissues), was transported to sink tissues to serve as the principal source of carbon and energy [48]. Sugar metabolism was intrinsically linked to plant physiological status, influencing critical processes including growth regulation, developmental progression, final yield, and product quality [49,50,51]. Li et al. [52] reported that tomatoes exposed to mixed red and blue light exhibited higher contents of carbohydrates, starch, and sucrose, along with elevated SS activity compared to monochromatic red light. In our study, based on equal DLI, the contents of glucose, sucrose, total soluble sugar, starch, and total carbohydrate, as well as SPS activity, were all increased in tomato leaves exposed to red background light with supplementary blue light relative to pure red light, while the activities of SS (cleavage) and AI were decreased. Zhan et al. [53] confirmed that combined red and blue light (R:B = 1:1, RB) most effectively enhanced SPS activity in tomato leaves, whereas SS activity was significantly lower under RB treatment than under pure red light (R). In addition, our results revealed that the SS activity in the cleavage direction was much higher than that in the synthesis direction, which indicated that SS in tomato seedlings mainly performed the decomposition function. The observation was in concordance with previous studies, which suggested that SS mainly acted on the sucrose decomposition rather than synthesis in plants such as lettuce, Zizania latifolia, and Arabidopsis thaliana [28,54,55].
Our study showed that compared to the control, the contents of glucose, starch, and carbohydrates in tomato seedlings were increased under all blue-light-involved treatments. Moreover, R/RB80 treatment resulted in the highest leaf number, leaf area, shoot biomass, and total soluble sugar accumulation in tomato seedlings, as well as the highest activities of SPS, SS (synthesis), and AI in tomato seedlings. Ruan [56] reported that sucrose metabolism-related enzymes participated in both metabolic processes and developmental regulation, potentially explaining the synergistic changes between growth indicators and enzymatic activities under specific light conditions.
Qin et al. [57] found that the gene expression level of SPS in tomatoes was more sensitive to environmental factors than SS. In our study, the gene expression level of SPS was up-regulated in tomato leaves treated with blue light irradiation compared with pure R and was found to increase with the increase in intermittent blue light intensity. This indicated that blue light induced the gene expression of SPS in tomato seedlings. Furthermore, short-duration high-intensity blue light was more efficient in up-regulating SPS expression than long-term low-intensity blue light based on the equal DLI. In addition, the highest total soluble sugar accompanied by the highest activity and gene expression of SPS was detected in tomato seedlings treated with R/RB80, while the lowest fructose content accompanied by the lowest activity and gene expression of SS were observed in tomato leaves treated with R/RB32. It implied that blue light supplementation might affect sugar accumulation by regulating the activity or gene expression of sucrose metabolizing related enzymes. In this study, compared to pure R, the activities of AI and NI were decreased in tomato leaves subjected to all blue light supplementation treatments except R/RB32 treatment. The result was generally consistent with multiple studies demonstrating that invertase activity was reduced under a red–blue light combination compared with pure red light [52,58]. This demonstrated that blue light appeared to inhibit the activity of invertase. Furthermore, it was noteworthy that the NI activity was higher than AI activity in tomato seedlings exposed to all blue light supplementation modes in our study, which might be associated with intracellular pH fluctuations induced by light regime alterations.
Our study demonstrated that compared with pure red irradiation, intermittent blue light supplementation represented a promising strategy for the factory-scale cultivation of tomato seedlings. Under R/RB64 and R/RB80 treatments, tomato seedlings exhibited the highest biomass and most vigorous morphology. Specifically, the R/RB80 treatment resulted in the highest total soluble sugar content, with sucrose, fructose, glucose, starch, and carbohydrates consistently maintaining high levels across all treatments. Antioxidant enzymes and sucrose metabolism-related enzymes were obviously up-regulated under R/RB80 treatment, indicating synchronized enhancements in carbohydrate metabolism and stress tolerance. Notably, although the R/RB64 treatment showed higher gene expression levels of sucrose metabolizing enzymes, it simultaneously resulted in lower plant height and stem diameter. A comprehensive analysis of morphological traits, sugar metabolism, and carbohydrate accumulation identified R/RB80 as the optimal light regime. Importantly, based on the same DLI, short-duration high-intensity blue light supplementation improved key growth parameters more effectively than long-term low-intensity exposure despite shorter irradiation duration. This phenomenon may be attributed to the sensitivity of photoreceptors to photon flux density (PFD), whereby high-intensity blue light preferentially triggers photomorphogenic responses via cryptochrome-mediated signaling pathways. The research by Liscum et al. [46] also highlighted the adaptive regulation of plants to environmental light signals. They found that plants regulated phototropism through the allocation of photoreceptors under varying blue light intensities: phot1 dominated under low light intensity, while phot1 and phot2 acted synergistically under high light intensity. Furthermore, the weaker growth of tomato seedlings under low-intensity blue light might also be linked to leaf senescence triggered by low-intensity blue light [47]. Thus, intermittently replacing part of red light with blue light without increasing light quanta could promote the growth of tomato seedlings, and short-duration, high-intensity blue light was recommended. Additionally, blue light supplementation in dense planting could effectively alleviate shade avoidance syndrome (SAS).

5. Conclusions

This study proved that intermittently replacing part of red light with blue light without increasing light quantum could promote the growth of tomato seedlings, and short-duration high-intensity blue light seemed more effective than long-term low-intensity blue light. The R/RB80 treatment not only exhibited the greatest biomass but also led to high levels of sucrose, fructose, glucose, starch, and total carbohydrate accumulation in tomato seedlings among all treatments. Additionally, this treatment triggered the highest enzymatic activity and gene expression levels of SPS, underscoring its superior efficacy in promoting carbon assimilation and overall plant growth. Blue light supplementation might affect sugar accumulation by regulating the activity or gene expression levels of sucrose metabolizing related enzymes. As a whole, a comprehensive analysis of morphological traits, antioxidant enzyme activities, and carbohydrate accumulation identified R/RB80 as the optimal light regime in the present study. These findings not only provide practical guidance for optimizing tomato seedling cultivation in plant factories but also establish a theoretical foundation for selecting efficient lighting regimens in controlled-environment agriculture systems.

Author Contributions

X.G. wrote the main manuscript; L.L. and W.G. conducted the experiments; Y.Z. performed statistical data analyses; X.W. guided the experiment; X.C. designed the project and reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Beijing Intelligent Greenhouse Vegetable Innovation Consortium Project (BAIC12-2025) and the Beijing Rural Revitalization Agricultural Science and Technology Project (NY2501010225).

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Perveen, R.; Suleria, H.A.; Anjum, F.M.; Butt, M.S.; Pasha, I.; Ahmad, S. Tomato (Solanum lycopersicum) Carotenoids and Lycopenes Chemistry; Metabolism, Absorption, Nutrition, and Allied Health Claims—A Comprehensive Review. Crit. Rev. Food Sci. Nutr. 2015, 55, 919–929. [Google Scholar] [CrossRef] [PubMed]
  2. Huang, Q.; Yang, Z.; Liu, X.; Wang, X.; Xu, C.; Ding, Y.; Li, J.; Zheng, Q. Discussion on the mechanism of effects of high temperature and humidity on tomato flower bud differentiation in seedling stage. Chin. J. Agrometeorol. 2021, 42, 56. [Google Scholar]
  3. Darko, E.; Heydarizadeh, P.; Schoefs, B.; Sabzalian, M.R. Photosynthesis under artificial light: The shift in primary and secondary metabolism. Philos. Trans. R. Soc. B Biol. Sci. 2014, 369, 20130243. [Google Scholar] [CrossRef]
  4. Song, J.; Zhang, R.; Yang, F.; Wang, J.; Cai, W.; Zhang, Y. Nocturnal LED Supplemental Lighting Improves Quality of Tomato Seedlings by Increasing Biomass Accumulation in a Controlled Environment. Agronomy 2024, 14, 1888. [Google Scholar] [CrossRef]
  5. Bantis, F.; Chatzigeorgiou, I.; Sismanis, M.; Ntinas, G.K.; Koukounaras, A. Vegetable Production in PFALs: Control of Micro-Environmental Factors, Principal Components and Automated Systems. Agriculture 2024, 14, 642. [Google Scholar] [CrossRef]
  6. Paponov, I.A.; Paponov, M. Supplemental lighting in controlled environment agriculture: Enhancing photosynthesis, growth, and sink activity. CABI Rev. 2025, 20, 0008. [Google Scholar] [CrossRef]
  7. Trivellini, A.; Toscano, S.; Romano, D.; Ferrante, A. The role of blue and red light in the orchestration of secondary metabolites, nutrient transport and plant quality. Plants 2023, 12, 2026. [Google Scholar] [CrossRef]
  8. Shah, A.; Tyagi, S.; Saratale, G.D.; Guzik, U.; Hu, A.; Sreevathsa, R.; Reddy, V.D.; Rai, V.; Mulla, S.I. A comprehensive review on the influence of light on signaling cross-talk and molecular communication against phyto-microbiome interactions. Crit. Rev. Biotechnol. 2021, 41, 370–393. [Google Scholar] [CrossRef]
  9. Zhou, Y.; Liu, P.; Tang, Y.; Liu, J.; Tang, Y.; Zhuang, Y.; Li, X.; Xu, K.; Zhou, Z.; Li, J.; et al. NPR1 promotes blue light–induced plant photomorphogenesis by ubiquitinating and degrading PIF4. Proc. Natl. Acad. Sci. USA 2024, 121, e2412755121. [Google Scholar] [CrossRef]
  10. Yan, Y.; Zhu, J.; Qiu, Q.; Li, J.; Cao, X.; Deng, X. The Arabidopsis demethylase REF6 physically interacts with phyB to promote hypocotyl elongation under red light. Proc. Natl. Acad. Sci. USA 2025, 122, e2417253122. [Google Scholar] [CrossRef]
  11. Xu, P.; Chen, H.; Li, T.; Xu, F.; Mao, Z.; Cao, X.; Miao, L.; Du, S.; Hua, J.; Zhao, J.; et al. Blue light-dependent interactions of CRY1 with GID1 and DELLA proteins regulate gibberellin signaling and photomorphogenesis in Arabidopsis. Plant Cell 2021, 33, 2375–2394. [Google Scholar] [CrossRef] [PubMed]
  12. Xu, F.; He, S.; Zhang, J.; Mao, Z.; Wang, W.; Li, T.; Hua, J.; Du, S.; Xu, P.; Li, L.; et al. Photoactivated CRY1 and phyB Interact Directly with AUX/IAA Proteins to Inhibit Auxin Signaling in Arabidopsis. Mol. Plant 2018, 11, 523–541. [Google Scholar] [CrossRef]
  13. Colombo, M.; Montazeaud, G.; Viader, V.; Ecarnot, M.; Prosperi, J.M.; David, J.; Fort, F.; Violle, C.; Fréville, H. A genome-wide analysis suggests pleiotropic effects of Green Revolution genes on shade avoidance in wheat. Evol. Appl. 2022, 15, 1594–1604. [Google Scholar] [CrossRef]
  14. Lorrain, S.; Allen, T.; Duek, P.D.; Whitelam, G.C.; Fankhauser, C. Phytochrome-mediated inhibition of shade avoidance involves degradation of growth-promoting bHLH transcription factors. Plant J. 2008, 53, 312–323. [Google Scholar] [CrossRef] [PubMed]
  15. Lorrain, S.; Genoud, T.; Fankhauser, C. Let there be light in the nucleus! Curr. Opin. Plant Biol. 2006, 9, 509–514. [Google Scholar] [CrossRef] [PubMed]
  16. Fraser, D.P.; Hayes, S.; Franklin, K.A. Photoreceptor crosstalk in shade avoidance. Curr. Opin. Plant Biol. 2016, 33, 1–7. [Google Scholar] [CrossRef]
  17. Song, H.; Xin, J.; Yang, D.; Dong, G.; Deng, X.; Liu, J.; Zhang, M.; Chen, L.; Su, Y.; Yang, H.; et al. NnSUS1 encodes a sucrose synthase involved in sugar accumulation in lotus seed cotyledons. Plant Physiol. Biochem. 2024, 210, 108591. [Google Scholar] [CrossRef]
  18. Ludewig, F.; Flügge, U.-I. Role of metabolite transporters in source-sink carbon allocation. Front. Plant Sci. 2013, 4, 231. [Google Scholar] [CrossRef]
  19. Sakr, S.; Wang, M.; Dédaldéchamp, F.; Perez-Garcia, M.-D.; Ogé, L.; Hamama, L.; Atanassova, R. The sugar-signaling hub: Overview of regulators and interaction with the hormonal and metabolic network. Int. J. Mol. Sci. 2018, 19, 2506. [Google Scholar] [CrossRef]
  20. Osorio, S.; Ruan, Y.-L.; Fernie, A.R. An update on source-to-sink carbon partitioning in tomato. Front. Plant Sci. 2014, 5, 516. [Google Scholar] [CrossRef]
  21. Gupta, H.; Goyal, M.; Roy, A.K. Lodging susceptibility index is associated with impaired source-sink relationship and sucrose allocation in oat varieties. Cereal Res. Commun. 2024, prepublish. 1–22. [Google Scholar] [CrossRef]
  22. Khan, Q.; Qin, Y.; Guo, D.-J.; Yang, L.-T.; Song, X.-P.; Xing, Y.-X.; Li, Y.-R. A Review of the diverse genes and molecules involved in sucrose metabolism and innovative approaches to improve sucrose content in sugarcane. Agronomy 2023, 13, 2957. [Google Scholar] [CrossRef]
  23. Wang, H.; Gu, M.; Cui, J.; Shi, K.; Zhou, Y.; Yu, J. Effects of light quality on CO2 assimilation, chlorophyll-fluorescence quenching, expression of Calvin cycle genes and carbohydrate accumulation in Cucumis sativus. J. Photochem. Photobiol. B Biol. 2009, 96, 30–37. [Google Scholar] [CrossRef] [PubMed]
  24. Kondo, S.; Tomiyama, H.; Rodyoung, A.; Okawa, K.; Ohara, H.; Sugaya, S.; Terahara, N.; Hirai, N. Abscisic acid metabolism and anthocyanin synthesis in grape skin are affected by light emitting diode (LED) irradiation at night. J. Plant Physiol. 2014, 171, 823–829. [Google Scholar] [CrossRef]
  25. Choi, H.G.; Moon, B.Y.; Kang, N.J. Effects of LED light on the production of strawberry during cultivation in a plastic greenhouse and in a growth chamber. Sci. Hortic. 2015, 189, 22–31. [Google Scholar] [CrossRef]
  26. Chen, X.L.; Yang, Q.C. Effects of intermittent light exposure with red and blue light emitting diodes on growth and carbohydrate accumulation of lettuce. Sci. Hortic. 2018, 234, 220–226. [Google Scholar] [CrossRef]
  27. Chen, X.L.; Yang, Q.C.; Song, W.P.; Wang, L.C.; Guo, W.Z.; Xue, X.Z. Growth and nutritional properties of lettuce affected by different alternating intervals of red and blue LED irradiation. Sci. Hortic. 2017, 223, 44–52. [Google Scholar] [CrossRef]
  28. Chen, X.; Wang, L.; Li, Y.; Yang, Q.; Guo, W. Alternating red and blue irradiation affects carbohydrate accumulation and sucrose metabolism in butterhead lettuce. Sci. Hortic. 2022, 302, 111177. [Google Scholar] [CrossRef]
  29. Yao, X.Y.; Liu, X.Y.; Xu, Z.G.; Jiao, X.L. Effects of light intensity on leaf microstructure and growth of rape seedlings cultivated under a combination of red and blue LEDs. J. Integr. Agric. 2017, 16, 97–105. [Google Scholar] [CrossRef]
  30. Fan, X.-X.; Xu, Z.-G.; Liu, X.-Y.; Tang, C.-M.; Wang, L.-W.; Han, X.-L. Effects of light intensity on the growth and leaf development of young tomato plants grown under a combination of red and blue light. Sci. Hortic. 2013, 153, 50–55. [Google Scholar] [CrossRef]
  31. Liang, Y.; Kang, C.; Kaiser, E.; Kuang, Y.; Yang, Q.; Li, T. Red/blue light ratios induce morphology and physiology alterations differently in cucumber and tomato. Sci. Hortic. 2021, 281, 109995. [Google Scholar] [CrossRef]
  32. Shao, M.; Liu, W.; Zha, L.; Zhou, C.; Zhang, Y.; Li, B. Differential effects of high light duration on growth, nutritional quality, and oxidative stress of hydroponic lettuce under red and blue LED irradiation. Sci. Hortic. 2020, 268, 109366. [Google Scholar] [CrossRef]
  33. Sivakumar, G.; Heo, J.; Kozai, T.; Paek, K.-Y. Effect of continuous or intermittent radiation on sweet potato plantlets in vitro. J. Hortic. Sci. Biotechnol. 2006, 81, 546–548. [Google Scholar] [CrossRef]
  34. Elkins, C.; van Iersel, M. Longer photoperiods with the same daily light integral increase daily electron transport through photosystem II in lettuce. Plants 2020, 9, 1172. [Google Scholar] [CrossRef]
  35. Buysse, J.; Merckx, R. An improved colorimetric method to quantify sugar content of plant tissue. J. Exp. Bot. 1993, 44, 1627–1629. [Google Scholar] [CrossRef]
  36. Sun, Z.; Li, Y.; Zhou, J.; Zhu, S.H. Effects of exogenous nitric oxide on contents of soluble sugars and related enzyme activities in ‘Feicheng’ peach fruit. J. Sci. Food Agric. 2011, 91, 1795–1800. [Google Scholar] [CrossRef] [PubMed]
  37. Lowell, C.A.; Tomlinson, P.T.; Koch, K.E. Sucrose-metabolizing enzymes in transport tissues and adjacent sink structures in developing citrus fruit. Plant Physiol. 1989, 90, 1394–1402. [Google Scholar] [CrossRef]
  38. Cordon, A.J. Enzyme Distribution Between the Cortex and the Infected Region of Soybean Nodules. J. Exp. Bot. 1991, 42, 961–967. [Google Scholar]
  39. King, S.P.; Lunn, J.E.; Furbank, R.T. Carbohydrate Content and Enzyme Metabolism in Developing Canola Siliques. Plant Physiol. 1997, 114, 153–160. [Google Scholar] [CrossRef]
  40. Tamura, K.-i.; Kawakami, A.; Sanada, Y.; Tase, K.; Komatsu, T.; Yoshida, M. Cloning and functional analysis of a fructosyltransferase cDNA for synthesis of highly polymerized levans in timothy (Phleum pratense L.). J. Exp. Bot. 2009, 60, 893–905. [Google Scholar] [CrossRef]
  41. Ballaré, C.L. Light regulation of plant defense. Annu. Rev. Plant Biol. 2014, 65, 335–363. [Google Scholar] [CrossRef] [PubMed]
  42. Casal, J.J. Photoreceptor signaling networks in plant responses to shade. Annu. Rev. Plant Biol. 2013, 64, 403–427. [Google Scholar] [CrossRef] [PubMed]
  43. Li, Y.; Kong, D.; Fu, Y.; Sussman, M.R.; Wu, H. The effect of developmental and environmental factors on secondary metabolites in medicinal plants. Plant Physiol. Biochem. 2020, 148, 80–89. [Google Scholar] [CrossRef] [PubMed]
  44. Chen, L.; Cao, X.; Li, Y.; Liu, M.; Liu, Y.; Guan, Y.; Ruan, J.; Mao, Z.; Wang, W.; Yang, H.Q.; et al. Photoexcited Cryptochrome 1 Interacts With SPCHLESS to Regulate Stomatal Development in Arabidopsis. Plant Cell Environ. 2025, 48, 286–296. [Google Scholar] [CrossRef]
  45. Mao, Z.; Wei, X.; Li, L.; Xu, P.; Zhang, J.; Wang, W.; Guo, T.; Kou, S.; Wang, W.; Miao, L.; et al. Arabidopsis cryptochrome 1 controls photomorphogenesis through regulation of H2A. Z deposition. Plant Cell 2021, 33, 1961–1979. [Google Scholar] [CrossRef]
  46. Liscum, E.; Askinosie, S.K.; Leuchtman, D.L.; Morrow, J.; Willenburg, K.T.; Coats, D.R. Phototropism: Growing towards an understanding of plant movement. Plant Cell 2014, 26, 38–55. [Google Scholar] [CrossRef]
  47. Li, Z.; Lyu, X.; Li, H.; Tu, Q.; Zhao, T.; Liu, J.; Liu, B. The mechanism of low blue light-induced leaf senescence mediated by GmCRY1s in soybean. Nat. Commun. 2024, 15, 798. [Google Scholar] [CrossRef]
  48. Qazi, H.A.; Paranjpe, S.; Bhargava, S. Stem sugar accumulation in sweet sorghum—Activity and expression of sucrose metabolizing enzymes and sucrose transporters. J. Plant Physiol. 2012, 169, 605–613. [Google Scholar] [CrossRef]
  49. Farrar, J.; Pollock, C.; Gallagher, J. Sucrose and the integration of metabolism in vascular plants. Plant Sci. 2000, 154, 1–11. [Google Scholar] [CrossRef]
  50. Singh, A.K.; Santos-Merino, M.; Sakkos, J.K.; Walker, B.J.; Ducat, D.C. Rubisco Regulation in Response to Altered Carbon Status in the Cyanobacterium Synechococcus elongatus PCC 7942. Plant Physiol. 2022, 189, 874–888. [Google Scholar] [CrossRef]
  51. Jang, J.-C.; Sheen, J. Sugar sensing in higher plants. Plant Cell 1994, 6, 1665–1679. [Google Scholar] [PubMed]
  52. Li, Y.; Xin, G.; Wei, M.; Shi, Q.; Yang, F.; Wang, X. Carbohydrate accumulation and sucrose metabolism responses in tomato seedling leaves when subjected to different light qualities. Sci. Hortic. 2017, 225, 490–497. [Google Scholar] [CrossRef]
  53. Zhan, X.; Yang, Q.; Wang, S.; Wang, Y.; Fan, X.; Bian, Z. The Responses of Sucrose Metabolism and Carbon Translocation in Tomato Seedlings under Different Light Spectra. Int. J. Mol. Sci. 2023, 24, 15054. [Google Scholar] [CrossRef] [PubMed]
  54. Jiang, J.; Cao, B.; Huang, K.; Zhang, Q.; Han, X.; Zhu, Q. Changes of NSC, enzymes and endogenous hormones during Zizania gall’s swelling. Acta Hortic. Sin. 2005, 32, 134. [Google Scholar]
  55. Fallahi, H.; Scofield, G.N.; Badger, M.R.; Chow, W.S.; Furbank, R.T.; Ruan, Y.-L. Localization of sucrose synthase in developing seed and siliques of Arabidopsis thaliana reveals diverse roles for SUS during development. J. Exp. Bot. 2008, 59, 3283–3295. [Google Scholar] [CrossRef]
  56. Ruan, Y.L. Signaling role of sucrose metabolism in development. Mol. Plant 2012, 5, 763–765. [Google Scholar] [CrossRef]
  57. Qin, G.; Zhu, Z.; Wang, W.; Cai, J.; Chen, Y.; Li, L.; Tian, S. A tomato vacuolar invertase inhibitor mediates sucrose metabolism and influences fruit ripening. Plant Physiol. 2016, 172, 1596–1611. [Google Scholar] [CrossRef]
  58. Chen, X.L.; Wang, L.C.; Li, T.; Yang, Q.C.; Guo, W.Z. Sugar accumulation and growth of lettuce exposed to different lighting modes of red and blue LED light. Sci. Rep. 2019, 9, 6926. [Google Scholar] [CrossRef]
Horticulturae 11 00700 g001
Figure 1. The light spectrum of R and R/RB treatments. The red section indicates the wavelength range of red light in the spectrum, while the blue section indicates the wavelength range of blue light.
Figure 1. The light spectrum of R and R/RB treatments. The red section indicates the wavelength range of red light in the spectrum, while the blue section indicates the wavelength range of blue light.
Horticulturae 11 00700 g001
Horticulturae 11 00700 g002
Figure 2. The plant height (a), stem thickness (b), leaf number (d), and leaf area (c) of tomato seedlings exposed to different intermittent blue light supplementation. Note: (a) The plant height of tomato seedlings. (b) The stem thickness of tomato seedlings. (c) The number of tomato seedling leaves. (d) The area of tomato seedling leaves. Note: All data passed normality and homoscedasticity tests, satisfying the requirements for ANOVA (Shapiro–Wilk test, Levene test, p > 0.05). Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation. This is the same as below.
Figure 2. The plant height (a), stem thickness (b), leaf number (d), and leaf area (c) of tomato seedlings exposed to different intermittent blue light supplementation. Note: (a) The plant height of tomato seedlings. (b) The stem thickness of tomato seedlings. (c) The number of tomato seedling leaves. (d) The area of tomato seedling leaves. Note: All data passed normality and homoscedasticity tests, satisfying the requirements for ANOVA (Shapiro–Wilk test, Levene test, p > 0.05). Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation. This is the same as below.
Horticulturae 11 00700 g002
Horticulturae 11 00700 g003
Figure 3. The aboveground dry weight of tomato seedlings exposed to different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Figure 3. The aboveground dry weight of tomato seedlings exposed to different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Horticulturae 11 00700 g003
Horticulturae 11 00700 g004
Figure 4. Content of protein, fat, water, and ash in tomato seedlings exposed to different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Figure 4. Content of protein, fat, water, and ash in tomato seedlings exposed to different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Horticulturae 11 00700 g004
Horticulturae 11 00700 g005
Figure 5. The content of sucrose, glucose, fructose, soluble total sugar, starch, and total carbohydrate in tomato seedlings under different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Figure 5. The content of sucrose, glucose, fructose, soluble total sugar, starch, and total carbohydrate in tomato seedlings under different intermittent blue light supplementation. Note: Lowercase indicates the difference in significance among treatments at 0.05 level. The bar represents the standard deviation.
Horticulturae 11 00700 g005
Horticulturae 11 00700 g006
Figure 6. Cluster analysis of antioxidant enzyme activities, sugar metabolizing enzyme activities, and reactive oxygen species (ROS) content in tomato seedlings under different intermittent blue light supplementation. Note: superoxide dismutase (SOD); peroxidase (POD); catalase (CAT); reactive oxygen species (ROS); sucrose phosphate synthase (SPS); sucrose synthase (SS); acid invertase (AI); neutral invertase (NI).
Figure 6. Cluster analysis of antioxidant enzyme activities, sugar metabolizing enzyme activities, and reactive oxygen species (ROS) content in tomato seedlings under different intermittent blue light supplementation. Note: superoxide dismutase (SOD); peroxidase (POD); catalase (CAT); reactive oxygen species (ROS); sucrose phosphate synthase (SPS); sucrose synthase (SS); acid invertase (AI); neutral invertase (NI).
Horticulturae 11 00700 g006
Horticulturae 11 00700 g007
Figure 7. The gene expression levels of SPS, SS, AI, and NI in tomato seedlings exposed to different intermittent blue light supplementation.
Figure 7. The gene expression levels of SPS, SS, AI, and NI in tomato seedlings exposed to different intermittent blue light supplementation.
Horticulturae 11 00700 g007
Horticulturae 11 00700 g008
Figure 8. Correlation analysis between sucrose, fructose, glucose, enzyme activities, and related gene expression levels of sucrose metabolism in tomato seedlings exposed to different intermittent blue light supplementation. Note: ** indicates significant positive correlation or significant negative correlation among indexes at the 0.01 level; * indicates significant positive correlation or significant negative correlation among indexes at the 0.05 level.
Figure 8. Correlation analysis between sucrose, fructose, glucose, enzyme activities, and related gene expression levels of sucrose metabolism in tomato seedlings exposed to different intermittent blue light supplementation. Note: ** indicates significant positive correlation or significant negative correlation among indexes at the 0.01 level; * indicates significant positive correlation or significant negative correlation among indexes at the 0.05 level.
Horticulturae 11 00700 g008
Table 1. Experimental treatment setup with different intermittent blue light supplementation.
Table 1. Experimental treatment setup with different intermittent blue light supplementation.
TreatmentSupplementary Lighting Modelight Intensity (μmol·m−2·s−1)Daily Light Integral (DLI) (mol·m−2)Total Hours of Blue Light Supplementation (h)
Light PeriodDark PeriodRed LightBlue Light
RRed light irradiation for 16 h.Dark period 8 h220012.672 (R: 12.672; B: 0)0
R/RB32Red light irradiation for 0.6 h and then switch to mixed red and blue light irradiation for 1 h, cycling 10 times during the light period.2003212.672 (R: 11.52; B: 1.152)10
R/RB40Red light irradiation for 1 h and then switch to mixed red and blue light irradiation for 1 h, cycling 8 times during the light period.2004012.672 (R: 11.52; B: 1.152)8
R/RB64Red light irradiation for 2.2 h and then switch to mixed red and blue light irradiation for 1 h, cycling 5 times during the light period.2006412.672 (R: 11.52; B: 1.152)5
R/RB80Red light irradiation for 3 h and then switch to mixed red and blue light irradiation for 1 h, cycling 4 times during the light period.2008012.672 (R: 11.52; B: 1.152)4
Table 2. The primer sequences for the target gene and the reference gene.
Table 2. The primer sequences for the target gene and the reference gene.
GenePrimer Sequence
spsF: CTGTACTGGCATCTCGGTCC
R: ATGACAGCCTTGCGTAGACC
sus3F: TGTTGAGGAGCTGACTGTGC
R: AGAGAGGTGCCTGTTGAGGA
Wiv-1F: AACCCGCTATCTACCCGTCT
R: TCGGGCTTGATCCACTTACG
LOC101255835F: TGTTACAGTCCAGGGCAAGG
R: AGGTGCTACACGGCCAATAG
GAPDHF: AGCCACTCAGAAGACCGTTG
R: AGGTCAACCACGGACACATC
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Gao, X.; Li, L.; Guo, W.; Zhai, Y.; Wei, X.; Chen, X. Intermittent Blue Light Supplementation Affected Carbohydrate Accumulation and Sugar Metabolism in Red-Light-Grown Tomato Seedlings. Horticulturae 2025, 11, 700. https://doi.org/10.3390/horticulturae11060700

AMA Style

Gao X, Li L, Guo W, Zhai Y, Wei X, Chen X. Intermittent Blue Light Supplementation Affected Carbohydrate Accumulation and Sugar Metabolism in Red-Light-Grown Tomato Seedlings. Horticulturae. 2025; 11(6):700. https://doi.org/10.3390/horticulturae11060700

Chicago/Turabian Style

Gao, Xiangyu, Lingzhi Li, Wenzhong Guo, Yifan Zhai, Xiaoming Wei, and Xiaoli Chen. 2025. "Intermittent Blue Light Supplementation Affected Carbohydrate Accumulation and Sugar Metabolism in Red-Light-Grown Tomato Seedlings" Horticulturae 11, no. 6: 700. https://doi.org/10.3390/horticulturae11060700

APA Style

Gao, X., Li, L., Guo, W., Zhai, Y., Wei, X., & Chen, X. (2025). Intermittent Blue Light Supplementation Affected Carbohydrate Accumulation and Sugar Metabolism in Red-Light-Grown Tomato Seedlings. Horticulturae, 11(6), 700. https://doi.org/10.3390/horticulturae11060700

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop