Effects of spatial setting of LED light source on yield, quality, and water-use efficiency in greenhouse tomato

Abstract

In most parts of northern China, the light environment in facilities deteriorates owing to shortened sunshine time and weaker light intensity in winter. Artificial light supplementation is an effective method for alleviating the problems of vegetable growth, quality, and yield reduction caused by limited light. In this study, LEDs were used to examine different spatial settings (CK: no supplemental lighting; T1: upward supplemental lighting between plants; T2: downward supplemental lighting at the top of the plant; T3: downward supplemental lighting between plants; and T4: upward supplemental lighting at the bottom of the plant) on the biomass, yield, quality, water-use efficiency, and electric energy efficiency of ‘Jingfan 502’ tomato plants. LED supplemental light treatment significantly increased the dry and fresh weights of tomato overground and whole plants, decreased the dry matter distribution rate of stems, increased the dry matter distribution rate of leaves, increased the water-use efficiency of tomato plants, and increased the soluble sugar content, organic acid content, and sugar–acid ratio of tomato fruits. Among them, whole plant fresh weight, whole plant dry weight, fruit allocation ratio, yield, water-use efficiency, total sugar content, and sugar–acid ratio of tomatoes were the highest under the T4 treatment, with increases of 22.63%, 17.54%, 8.83%, 48.33%, 39.72%, 27.38%, and 6.5%, respectively, compared with CK. The electrical energy efficiency of plants under the T4 treatment was the highest at 32.84 g/kw. After principal component analysis of the 14 indicators, the composite scores were T4 > T2 > T3 > T1 > CK. The LED light source with bottom-upward supplemental light was the most suitable for tomatoes. The findings provide a theoretical basis for water-saving and high-quality production of overwintering tomatoes in a solar greenhouse in northern China.

Introduction

The tomato(Solanum lycopersicum L.)is an annual plant in the Solanaceae family. It is favored by consumers because of its distinctive flavor and high nutrient content [1, 2]. However, in most areas of northern China, cold winter weather makes it impossible to cultivate vegetables in open fields and vegetable cultivation can only be conducted in greenhouses [3]. However, the long-term overcast and snowy weather in most northern regions in winter means that there can only be 6–7 h of light inside greenhouses, coupled with factors such as aging of transparent greenhouse covering materials and excessive dust. This leads to insufficient lighting in the greenhouse, which is not conducive to plant growth [4]. Insufficient light duration can lead to a reduced yield and quality of strawberries [5] and cucumbers [6], causing substantial losses for local farmers. As a light-loving plant, tomatoes experience weak light stress because of light deficiency, which leads to a slowdown in crop growth and lower quality [7, 8]. To address insufficient lighting during facility cultivation in China, in-depth analyses have been conducted, and some effective countermeasures have been proposed for supplementary light.

Artificial supplementary light has been used in horticultural facilities to achieve large-scale, efficient horticultural crop production. Selecting appropriate supplementary light for vegetable crops can alleviate the harm from insufficient light and promote crop growth [10]. Artificial light sources used for facility cultivation include fluorescent lamps, high-pressure sodium lamps, and metal halide lamps. However, because of their high operating temperature, high energy consumption, low luminous efficiency, and light quality, which are not suitable for optimal growth, they have gradually been replaced [9]. Light-emitting diodes (LEDs) can contribute to environmental protection owing to their low energy consumption, high energy conversion efficiency, long life, low radiant heat release, and the ability to easily modulate the emission spectrum. This makes them a viable supplementary lighting source in agricultural lighting systems [10, 11]. LED light can promote the growth of tomato seedlings [12] and increase cucumber yields [13]. Different LED light qualities have varying biological effects [14–17]. Combined blue and red LED light is more effective than other bands for the normal growth, physiological activities, and photosynthesis of various crops and has become a key research topic with an international focus. Supplementation with red and blue LED at night in the winter has substantially improved tomato and zucchini growth, fruit quality, and yield [18]. Red and blue LED supplemental lights can increase the soluble sugar content and reduce the organic acid content in tomato fruits, thus improving the flavor quality of tomato fruits [19]. The use of red/blue lamps instead of fluorescent lamps also helps improve the grafted tomato transplant quality and power savings [20]. The duration of LED supplemental lighting also has a considerable impact on plant growth and quality. Research by Wang et al. [18] on cucumbers showed that treatment with red and blue LED light for 3 h significantly promoted cucumber growth, development, and dry matter accumulation. Supplemental lighting of tomato plants increased the growth and yield of tomato plants exposed to night-time supplementary lighting for 3, 4, and 5 h to varying degrees compared to untreated tomatoes [21]. The intensity of supplementary light influences the growth and quality of crops [22]. Leaf development and seed oil content of Brassica napus increased with increasing light intensity [23]. Recently, the potential of LED lighting for crop growth during greenhouse cultivation has been explored. According to the different hanging positions and irradiation directions of the supplemental lights, supplemental lighting can be divided into top hanging lighting, canopy top lighting, internal lighting of the plant, bottom lighting, and three-dimensional multi-layer lighting [24]. Intra-canopy LED lighting was found to be superior to top LED lighting in terms of increasing tomato yield [25]. Hovi-Pekkanen et al. [26] showed that using an LED internal fill light could increase crop yields by 50%. Supplementary lighting with multicolor light applied from either the inner canopy or underneath the canopy effectively enhanced tomato photosynthetic efficiency and improved plant development [27].

There are substantial imbalances in the spatial and temporal distribution of water resources in China, especially in the northwestern region where water shortages are particularly prominent. As a crop with a high water demand, water is the most critical element in tomato production, except under light conditions. However, under the current agricultural irrigation model, there is a high level of water, consumption, but these water resources are not used efficiently [28, 29]. With limited water resources, maximizing tomato yield while improving water use efficiency has become a key issue in agricultural production. Supplementation with LED lighting is an effective strategy for overcoming water shortages. The effects of spectral composition and intensity on the water use efficiency of greenhouse crops has been a key research focus. Combined red and blue LEDs is the main spectrum for indoor plants [30]. However, the responses of different plants to water-use efficiency differed under different red and blue spectral ratios. A red: blue ratio of 3 provides optimal growing conditions for the indoor cultivation of basil and lettuce, promoting growth and water use efficiency [31, 32]. A red: blue ratio of 8: 2 promoted water use in peppers [33]. Tomato plants grown under LED supplementation (95% red, 5% blue) showed better water status [34]. Li et al. confirmed that the use of LED light maximizes the water-use efficiency of tomato plants [35]. Light intensity affects water use in pepper [33]. However, the effects of different spatial settings of LED light sources on tomato water use have received relatively little attention.

To date, research on LED supplemental lighting has predominantly focused on light intensity, light quality ratio, and photoperiodic regulation. Meanwhile, there has been relatively limited research on the effects of different LED positions with red and blue light on tomato quality and water-use efficiency. Therefore, this experiment used the ‘Jingfan 502’ tomato variety as the test material. LED with red and blue light (7R2B) was used as the artificial supplemental light source under greenhouse conditions to evaluate the effects of supplemental light at different spatial positions, such as upward supplemental lighting between plants, downward supplemental lighting at the top of the plant, downward supplemental lighting between plants, and upward supplemental lighting at the bottom of the plant, on tomato yield, dry matter accumulation, quality, water-use efficiency, and electrical energy efficiency. Upward supplemental lighting at the bottom of the plant may be the most effective way to promote the growth and development of tomatoes and achieve the synergistic effect of water-use efficiency while increasing yield and improving quality. We aimed to verify this hypothesis, clarify the relationship between spatial regulation of the light environment and the physiological response of tomato growth, provide precise and efficient supplemental light strategies for tomato cultivation in overwintering facilities in northern China, and provide technical support for the synergistic efficiency of energy and water conservation in facility agriculture.

Materials and methods

Materials

Our experiment was conducted in a glass greenhouse from October 2023 to March 2024 at Gansu Agricultural University, No.1 Yingmen Village, Anning District, Lanzhou City, Gansu Province (N 36.1051°, E 103.7123°). The test tomato variety was ‘Jingfan 502’ from Jingyan Yinong Seed Sci-Tech Co., Ltd. (Beijing, China) The substrate was Green Energy Ruiqi Cultivation Substrate (Gansu Luneng Agricultural Science and Technology Co, Ltd., Lanzhou, China), which had a maximum water holding capacity of 219% in the field, and a capacity of 266 kg/m³. The light source was a red and blue (7R2B) LED plant growth light (Shenzhen Houyi Energy Saving Technology Co., Ltd., Shenzhen, China) with a maximum light intensity of 400µmol·m^− 2·s^− 1.

Material culture and growth conditions

Full tomato seeds were selected, sterilized with a 0.03% potassium permanganate solution for 15 min, and soaked in warm water for 10 h. The soaked seeds were sprinkled on a plate covered with gauze for 30 h to promote germination. Tomato seeds were planted in a cavity tray and put into an artificial climate chamber (light 20000 Lx, temperature 25 ℃/18 ℃, relative humidity 30%) for seedling cultivation. When the seedlings had grown five true leaves, they were transplanted into pots and cultivated in a glass greenhouse with a light intensity of 7000–15,000 Lx, daytime temperatures of 24–28 ℃, night temperatures of 12–18 ℃, and relative humidity of 10–85%. The planting density was 2200 plants·667 m^− 2. The cultivation method was potted (pot height, 20 cm × diameter, 26 cm), and the weight of the substrate in each pot was 5.1 kg. We applied an equal amount of Hoagland’s Nutrient Solution to each treatment during the tomato growth process, and the specific fertilization method was 1 L of a one-concentration Hoagland nutrient solution every 15 d.

Experimental design

The same upper and lower irrigation limits (90% and 70% field capacity) were set at the beginning of the treatment. The water content of the substrate was monitored using TDR 350 (Spectrum, FieldScout TDR 350, ± 3.0% VWC, USA) at 18:00 daily. When the lower irrigation limit was reached, the irrigation water in each pot was 989 mL. The supplemental lighting treatment was carried out in the sixth week after tomato planting, and the filling light times were 6:00–9:00 am and 17:00–20:00 pm. The experiment had a completely randomized design in which seedlings with similar growth were divided into five groups (Fig. 1), that is, no supplemental lighting (CK), upward supplemental lighting between plants (T1), downward supplemental lighting at the top of the plant (T2), downward supplemental lighting between plants (T3), and upward supplemental lighting at the bottom of the plant (T4). The LEDs were 10 cm from the plants, and the canopy light intensity was 51 µmol·m^− 2·s^− 1 and was adjusted according to plant growth. Each treatment was repeated three times. Each time, 12 plants were grown, and shade cloth was placed over plants to the left and right of each treatment.

Fig. 1.

Schematic diagram of LED supplementary lighting spatial location setup

Growth indicators

At the fruit ripening stage, five uniformly growing tomato plants were selected for each treatment to record the fruit weight and the number of fruits per plant. The yield of each tomato plant was calculated according to the fruit number and weight, and the yield per 667 m² was calculated according to the yield of each tomato plant and the planting density. The roots and shoots (leaves and stems) of tomato plants were separated and weighed. After 30 min of green removal at 105 ℃, the dry weight was obtained by drying to a constant weight at 80 ℃. The dry matter distribution rate of each organ was calculated based on the dry and fresh weights of the roots, stems, leaves, and whole plants.

Water-use efficiency

The irrigation amount of each tomato was recorded, the yield per plant was counted during the picking period, and the yield per plant was measured using an electronic scale. After the entire growth period of tomatoes, the water-use efficiency was calculated according to the tomato yield and total irrigation amount.

Electric energy efficiency

The electricity consumption for each supplemental light treatment was recorded from the start of light supplementation to the end of the experiment. At harvest, yields were weighed and recorded for each treatment. The yield increase by supplemental light treatments was subtracted from the yield of the supplemental light treatments minus the yield of the non-supplemental light treatments. Electrical efficiency was calculated as the increase in yield from the supplementary mental treatment divided by the electricity consumption of each supplemental treatment.

Soluble sugar content

The contents of sucrose, glucose, and fructose in tomato fruits were determined according to the method described by Wang et al. [19]. After tomato fruit ripening, 15 tomato plants were randomly selected for each treatment. Tomato fruits of the same ear were picked and a quarter of each fruit was chopped. After mixing well, 5 g were weighed and added to a 25 mL volumetric bottle with a fixed volume of ultra-pure water. It was then inserted into an ultrasonic bath at 30 ℃ for 1 h before being filtered into a 50 mL centrifuge tube. It was then centrifuged at 4 ℃ at 10,000 r·min^− 1 for 10 min until 2 mL of the supernatant had been absorbed before being filtered with a 0.22 μm water filter into brown sample bottles for liquid chromatography. This was performed using high-performance liquid chromatography (HPLC). The detector was an Agilent differential light-blocking detector (Agilent series 1100, USA). The mobile phase was V (acetonitrile): V (water) = 75: 25, the flow rate was 1.0 mL·min^− 1, and the column temperature was 30 ℃. The chromatography was performed on an LC-NH2 amino column (460 mm× 250 mm) with an injection volume of 20 µL.

Organic acid content

The contents of oxalic acid, ascorbic acid, malic acid, and citric acid in tomato fruits were determined according to the methods of Jin et al. [36]. 5 g homogenized tomato fruits were processed according to the methods detailed in Sect. 2.4.5. They were then added to a 25 mL volumetric bottle and the volume was set with ultra-pure water. They were well mixed, added to a 50 mL centrifuge tube, centrifuged at 10,000 r·min^− 1 for 10 min at 4 ℃, and then 2 mL supernatant was absorbed. The filter was filtered using a 0.22 μm water filter into the sample bottle to determine the HPLC. The measurements were conducted using a high-performance liquid chromatometer (Agilent 1260 Infinity II, Agilent Technologies, USA) with a UV (Ultra Violet) detector. The mobile phase was 0.2 mmol /L sodium dihydrogen phosphate, the flow rate was 1.2 mL·min^− 1, and the column temperature was 30 ℃. This was performed using an X-Peony AQ-C18 column (250 × 4.6 mm) with the detection wavelength at 210 nm and the sample volume at 5 µL.

Statistical analysis

The experimental results are presented as mean ± standard error (SE) of three replicates. All the data were analyzed using one-way ANOVA with SPSS software (version 22.0; SPSS Institute Inc., US). Significant differences were compared using Duncan’s multiple range test (P < 0.05). Origin 2022 and GraphPad Prism 9.5.0 were used for mapping, and Excel 2016 software was used for data processing. Origin 2022 and Microsoft Cloud tools were used for Pearson’s correlation, principal component analysis (PCA), and hierarchical cluster analyses (HCA).

Results

Effects of different Spatial settings of LED light sources on tomato biomass

Biomass reflects the synthetic organic matter content of the plants. As shown in Table 1, compared with the CK treatment, treatments T1, T2, T3, and T4 significantly increased the fresh weight and dry weight of the shoot and whole tomato plant. Compared with CK treatment, the shoot and whole plant fresh weight in T4 treatment increased by 23.82% and 22.63%. The dry weight of the shoot and whole plant increased by 17.83% and 17.54%, respectively. The shoot fresh weight of tomato significantly increased by 8.4%, 4.78%, and 16.67% and the whole plant fresh weight increased by 7.52%, 4.16%, and 15.1% under the T2, T3, and T4 treatments, respectively, compared to the T1 treatment. The T4 treatment significantly increased the shoot fresh weight by 7.76% and 10.01% and the whole plant fresh weight by 7.04% and 10.5%, respectively, over the T2 and T3 treatments. Compared with T1, T2, and T3 treatments, the T4 treatment increased the shoot dry weight by 5.87%, 4.18%, and 4.54% and the whole plant dry weight significantly increased by 5.59%, 3.65%, and 4.86%, respectively. Compared with the CK treatment, treatments T1, T2, T3, and T4 significantly increased the tomato root dry and fresh weights by 10.63%, 9.76%, 8.73%, and 10.83%, and dry weights by 19.55%, 20.84%, 14.29%, and 23.20%, respectively. Compared with the T3 treatment, the dry weight of the T4 treatment increased by 7.80%.

Table 1.

Effects of Spatial settings of LED light sources on tomato biomass

Treatments	Fresh Weight (g)			Dry Weight (g)
	Root	Shoot	Whole plant	Root	Shoot	Whole plant
CK	20.50 ± 0.52b	203.02 ± 2.46d	223.52 ± 1.95e	9.31 ± 0.20c	88.45 ± 0.96c	98.43 ± 0.89c
T1	22.68 ± 0.42a	215.47 ± 1.24c	238.15 ± 1.08d	11.13 ± 0.29ab	98.44 ± 0.74b	109.57 ± 0.93b
T2	22.50 ± 0.58a	233.58 ± 2.58b	256.07 ± 2.88b	11.25 ± 0.18ab	100.04 ± 0.34b	111.62 ± 0.49b
T3	22.29 ± 0.62a	225.77 ± 1.30b	248.06 ± 0.93c	10.64 ± 0.04b	99.69 ± 0.20b	110.33 ± 0.16b
T4	22.72 ± 0.25a	251.38 ± 3.86a	274.10 ± 4.10a	11.47 ± 0.12a	104.22 ± 0.43a	115.69 ± 0.42a

Note: Different lowercase letters indicate significant differences between processing (P < 0.05). CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant

Effects of different Spatial settings of LED light sources on dry matter distribution rate in tomato

As shown in Fig. 2A, compared with the CK treatment, the T1, T2, T3, and T4 treatments significantly reduced dry matter allocation in tomato stems by 7.98%, 10.82%, 11.24%, and 12.77%, respectively. As shown in Fig. 2B, in tomato leaves, compared to the CK treatment, the T1, T2, T3, and T4 treatments significantly increased dry matter allocation by 7.98%, 10.82%, 11.24%, and 12.77%, respectively. As shown in Fig. 2C, compared with the CK treatment, T2, T3, and T4 supplemented light treatments increased the distribution of dry matter in tomato fruits by 6.23%, 3.92%, and 8.83%, respectively. Meanwhile, the T1 treatment showed no significant difference compared with the CK treatment.

Fig. 2.

Effects of LED light source spatial setting on dry matter accumulation and allocation of tomato stem (A), leaf (B), and fruit (C). CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant. Data are expressed as average values (n = 3). Different lowercase letters indicate significant differences between treatments determined using Duncan’s multiple range test (P < 0.05). Standard errors are indicated by bars

Effects of different Spatial settings of LED light sources on tomato yield

As shown in Table 2, compared with the CK treatment, the spatial setting of the LED light source treatment significantly increased the fruit weight per plant, fruit number per plant, yield per plant, and 667 m² yield of tomatoes. Among these, the T4 treatment had the most significant difference, increasing by 15.85%, 28.09%, 48.33%, and 48.33%, respectively. Compared to the CK treatment, the single fruit weight, fruit number per plant, and yield per plant of the T2 treatment tomato increased by 15.5%, 20.05%, 38.63%, and 38.63%, respectively. Compared with the CK treatment, the single fruit weight, fruit number per plant, and yield per plant of the T3 treatment tomato increased by 6.99%, 16.09%, 24.08%, and 24.08%, respectively. The single fruit weight, fruit number per plant, and yield per plant of the T1 treatment tomato increased by 2.24%, 20.05%, 22.73%, and 22.73% compared with the CK treatment, respectively. Compared with the T3 treatment, the fruit number per plant, yield per plant, and 667 m² yield of the T1 treatment tomatoes increased by 8.29%, 10.34%, 19.53%, and 19.54%, respectively. Compared with the T2 treatment, T4 the tomato fruit number per plant, yield per plant, and 667 m² yield increased by 0.3%, 6.7%, 6.99%, and 6.98%, respectively. Compared with the T1 treatment, T4 the tomato fruit number per plant, yield per plant, and 667 m² yield increased by 13.31%, 6.7%, 20.86%, and 20.85%, respectively.

Table 2.

Effects of Spatial settings of LED light sources on tomato yield

Treatments	Single fruit weight (g)	Number of fruits per plant	Yield per plant (g)	Yield per ha (kg)
CK	74.00 ± 0.29d	8.33 ± 0.33c	616.50 ± 22.53d	19720.80 ± 124.76d
T1	75.66 ± 0.35c	10.00 ± 0.00ab	756.63 ± 3.49c	26188.80 ± 766.37b
T2	85.47 ± 0.18a	10.00 ± 0.00ab	854.67 ± 1.76b	27159.00 ± 581.34b
T3	79.17 ± 0.64b	9.67 ± 0.33b	764.93 ± 21.89c	21734.24 ± 748.68c
T4	85.73 ± 0.12a	10.67 ± 0.33a	914.43 ± 27.73a	30883.88 ± 279.87a

Note: Different lowercase letters indicate significant differences between processing (P < 0.05). CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant

Effects of different Spatial settings of LED light sources on water-use efficiency of tomato

Figure 3 shows the effect of the spatial setting of the LED light source on the water irrigation and water-use efficiency of a single tomato plant. As shown in Fig. 3A, compared to the CK treatment, the T1, T2, T3, and T4 treatments significantly increased the amount of water irrigated per tomato plant by 6.55%, 1.75%, 2.18%, and 6.11%, respectively. The T1 and T4 treatments had the highest irrigation amount for tomato plants, which was 4.76% and 4.89% higher than that of the T2 treatment, and 4.54% and 4.66% higher than that of the T3 treatment, respectively. As shown in Fig. 3B, the water-use efficiency of tomatoes in the T1 and T3 treatments increased by 13.33% and 23.20%, respectively, compared to the CK treatment. The water-use efficiency of tomatoes in the T2 treatment significantly increased by 42.88%, 18.31%, and 11.91% compared with the CK, T1, and T3 treatments, respectively. The water-use efficiency of tomatoes in the T4 treatment increased by 39.72%, 20.73%, and 14.2% compared with the CK, T1, and T3 treatments, respectively. No significant differences were observed among the other treatments.

Fig. 3.

Effects of spatial setting of LED light source on irrigation (A) and water-use efficiency (B) per tomato plant. CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant. Data are expressed as average values (n = 3). Different lowercase letters indicate significant differences between treatments determined using Duncan’s multiple range test (P < 0.05). Standard errors are indicated by bars

Effects of different Spatial settings of LED light sources on electrical energy efficiency of tomato plants

Table 3 shows that the T1, T2, T3, and T4 treatments increased the yield relative to the CK treatment, and each LED light source spatial setting consumed the same amount of electricity. Compared with the T1 treatment with the lowest electric energy efficiency, the T2 and T4 treatments significantly improved the electric energy efficiency, with an increase of 69.9% and 112.56%, respectively. There was no significant difference between the T1 and T3 treatments. The electrical energy efficiency of each LED light source spatial setting treatment was: T4 > T2 > T3 > T1. The T4 treatment promoted an increase in yield, and the electrical energy efficiency was the highest for each supplemental lighting treatment.

Table 3.

Effects of Spatial setting of LED light source on electrical energy efficiency of tomato

Treatment	Increased yield (g)	Power consumption (kW·h)	Electric energy efficiency (g/kW)
CK	--	--	--
T1	140.13 ± 3.49c	9.072	15.45 ± 0.38c
T2	238.17 ± 1.76b	9.072	26.25 ± 0.19b
T3	148.43 ± 21.89c	9.072	16.36 ± 2.41c
T4	297.93 ± 27.73a	9.072	32.84 ± 3.06a

Note: Different lowercase letters indicate significant differences between processing (P < 0.05). CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant

Pearson’s correlation analysis, PCA, and HCA of tomato biomass, yield, Water-use efficiency, and electrical energy efficiency

As shown in Fig. 4A, the Pearson correlation analysis showed multiple sets of significant or highly significant correlations among the tomato metrics. Among these, root dry weight and root fresh weight (r = 0.98) showed a significant positive correlation. Shoot dry weight was significantly positively correlated with root fresh weight (r = 0.94), shoot fresh weight (r = 0.91), and root dry weight (r = 0.95). Single fruit and shoot fresh weights were significantly positively correlated (r = 0.93). Yield per plant and shoot fresh weight (r = 0.96), root dry weight (r = 0.92), shoot dry weight (r = 0.95), and single fruit weight (r = 0.92) showed significant positive correlations. Water-use efficiency was significantly and positively correlated with shoot fresh weight (r = 0.95), shoot dry weight (r = 0.91), single fruit weight (r = 0.97), and yield per plant (r = 0.98). Electrical energy efficiency and shoot fresh weight (r = 0.96), root dry weight (r = 0.92), shoot dry weight (r = 0.95), single fruit weight (r = 0.92), yield per plant (r = 1), water-use efficiency (r = 0.98) showed significant positive correlations. The PCA models for different treatments are shown in Fig. 4B. PCA captured most of the changes, and the sum of the first two principal components reached 96.2%, of which Principal Component 1 (PC1) and Principal Component 2 (PC2) accounting for 89.3% and 6.9% of the total variance, respectively. The load diagram showed that tomato root fresh and dry weights had a strong second principal component load, and other indicators had a strong first principal component load. The CK, T1, T2, T3, and T4 groups were significantly separated according to PC1 and PC2. As shown in Fig. 4C, the classification model based on cluster analysis divided the five treatments into two categories, namely, T1, T2, T3, T4, and CK.

Fig. 4.

Pearson’s correlation analysis (A), PCA (B), and HCA (C) of biomass, yield, water-use efficiency, and electrical efficiency in tomatoes under different LED spatial settings

Effects of different Spatial settings of LED light sources on efficiency of tomato plant soluble sugar content in tomato fruits

Sugar is an important component of the flavor quality of tomatoes and is the most direct consumer perception of fruit flavor. As shown in Fig. 5, compared to the CK treatment, the LED light source space-setting treatment significantly increased the soluble sugar content of tomato fruits. Figure 5A shows that the content of glucose in tomato fruits of T1, T2, T3, and T4 treatments increased by 6.99%, 17.56%, 17.56%, and 17.36%, respectively, compared with the CK treatment. The T2, T3, and T4 treatments increased by 9.88%, 9.88%, and 9.82% compared with the T1 treatment, respectively. The fructose contents in the tomato fruits of the T1, T2, T3, and T4 treatments increased by 44.31%, 43.13%, 38.82%, and 47.02%, respectively, compared with the CK treatment. The fructose content in tomato fruits treated with T4 increased by 5.93% compared with the T3 treatment (Fig. 5B). The sucrose content in tomato fruits of the T1, T2, T3, and T4 treatments increased by 59.26%, 58.8%, 55.09%, and 68.18%, respectively, compared with the CK treatments. Compared to the T1, T2, and T3 treatments, the sucrose content in tomato fruits treated with the T4 treatment increased by 8.43%, 8.75%, and 11.34%, respectively (Fig. 5C).

Fig. 5.

Effects of spatial setting of LED light source on glucose (A), fructose (B), and sucrose (C) content in tomato fruits. CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant. Data are expressed as average values (n = 3). Different lowercase letters indicate significant differences between treatments determined using Duncan’s multiple range test (P < 0.05) Standard errors are indicated by bars

Effects of different Spatial settings of LED light sources on organic acid content in tomato fruits

Four important organic acids, oxalic acid, ascorbic acid, citric acid, and malic acid, were detected in tomato fruits using HPLC to assess the effects of the spatial settings of the LED light source on organic acid content. Citric acid was the most abundant among the four organic acid fractions tested, followed by ascorbic acid. As shown in Fig. 6A, compared with the CK treatment, the T1, T2, T3, and T4 treatments significantly increased the oxalic acid content in tomato fruits by 45.45%, 36.36%, 27.27%, and 33.33%, respectively, compared with the T3 treatment. The T1, T2, and T4 treatments increased the oxalic acid content by 14.29%, 7.14%, and 4.76%, respectively. The T1 treatment increased by 6.67% and 9.1% compared with the T2 and T4 treatments, respectively. As shown in Fig. 6B, compared with the CK treatment, ascorbic acid content in tomato fruit significantly increased under T1, T2, T3, and T4 treatments by 28.7%, 28.7%, 33.91%, and 22.61%, respectively, and the T3 treatment increased ascorbic acid content by 9.22% compared with the T4 treatment. As shown in Fig. 6C, compared with the CK treatment, the citric acid content in tomato fruits significantly increased by T1 and T3 treatments, by 29.71% and 34.86%, respectively. Compared with T2 and T4 treatments, T1 treatment significantly increased by 24.73% and 24.04%, respectively. The T3 treatment increased by 29.67% and 28.96% compared with the T2 and T4 treatments, respectively. As shown in Fig. 6D, compared with the CK treatment, the T1, T2, T3, and T4 treatments significantly increased the malic acid content in tomato fruits by 69.57%, 169.57%, 73.91%, and 113.04%, respectively. The T2 treatment significantly increased the malic acid content by 58.97%, 55%, and 26.53% relative to the T1, T3, and T4 treatments, respectively. The T4 treatment showed a significant increase of 25.64% relative to the T1 treatment.

Fig. 6.

Effects of spatial setting of LED light source on organic acid content (A–D) in tomato fruit. CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant. Data are expressed as average values (n = 3). Different lowercase letters indicate significant differences between treatments determined using Duncan’s multiple range test (P < 0.05). Standard errors are indicated by bars

Effects of different Spatial settings of LED light sources on total sugar, total acid, and sugar–acid ratio in tomato fruits

As shown in Fig. 7A, the T1, T2, T3, and T4 treatments significantly increased the total sugar content in tomato fruits by 20.57%, 28.41%, 25.58%, and 27.38%, respectively, relative to the CK treatment. The T2, T3, and T4 treatments significantly increased the total sugar content in tomato fruits by 6.5%, 4.16%, and 5.65%, respectively, relative to the T1 treatment. As shown in Fig. 7B, the T1, T2, T3, and T4 treatments increased the total acid content in tomato fruits by 32.59%, 25.32%, 37.66%, and 19.62%, respectively, relative to the CK treatment. The T1 treatment significantly increased the total acid content in tomato fruits by 5.81% and 10.85%, respectively, relative to the T2 and T4 treatments. The T3 treatment showed a significant increase of 9.85% and 15.08% relative to the T2 and T4 treatments, respectively. As shown in Fig. 7C, compared with the CK treatment, the T4 treatment significantly increased the sugar–acid ratio in tomato fruits by 6.5%. Compared with T1 and T3, T4 significantly increased the sugar–acid ratio in tomato fruits by 16.96% and 16.44%, respectively. Compared with T1 and T3, T2 significantly increased the sugar–acid ratio in tomato fruits by 12.5% and 12%, respectively. T1 and T3 treatments significantly reduced the sugar–acid ratio in tomato fruits by 8.94% and 8.54%, respectively, compared with the CK treatment.

Fig. 7.

Effects of LED light source spatial setting on total sugars (A), total acid (B), and sugar–acid ratio (C) in tomato fruit. CK: no supplemental lighting, T1: upward supplemental lighting between plants, T2: downward supplemental lighting at the top of the plant, T3: downward supplemental lighting between plants, T4: upward supplemental lighting at the bottom of the plant. Data are expressed as average values (n = 3). Different lowercase letters indicate significant differences between treatments determined using Duncan’s multiple range test (P < 0.05). Standard errors are indicated by bars

Correlation analysis, PCA, and HCA of total sugar, total acid, and sugar–acid ratio

The strength of the relationship between tomato indicators under each treatment was determined using Pearson’s correlation analysis (Fig. 8A). Sucrose content was significantly and positively correlated with fructose content (r = 0.99) (Fig. 8A). Malic acid and glucose levels (r = − 0.97) showed a significant negative correlation. The total sugar content was significantly and positively correlated with glucose (r = 0.93), fructose (r = 0.96), and sucrose (r = 0.96). The sugar–acid ratio and ascorbic acid (r = − 0.91), and malic acid (r = − 0.89) showed a significant negative correlation. Figure 8B shows a visual representation of the PCA-based classification model for the sugar and acid fractions of tomato fruits under different treatments. The first and second principal components explained 90.7% of the total variance, with PC1 and PC2 explaining 66.2% and 24.5%, respectively. The loading plot shows that fructose, sucrose, total sugar, sugar–acid ratio, and ascorbic acid were the main contributors to the first principal component. Oxalic acid exhibited strong second principal component loading. From PC1 and PC2, the CK group was significantly separated from the T1, T2, T3, and T4 groups by PC1. Both T2 and T3 are in the first quadrant, whereas CK is in the third quadrant, T1 is in the second quadrant, and T4 is in the fourth quadrant. The results of hierarchical clustering were consistent with those of PCA as shown in Fig. 8C. The clustered heat map is a widely used statistical method that represents the results of the assay with progressive colors and the blue bar indicates higher content. The five different treatments could be categorized into two groups according to their contents. The first group is the CK treatment, and the second group is the T1, T2, T3, and T4 treatments.

Fig. 8.

Pearson’s correlation analysis (A), PCA (B), and cluster analysis (C) of soluble sugars and organic acids in tomatoes under different LED spatial settings

PCA ranking of biomass, yield, soluble sugar, organic acid, water-use efficiency, and electrical energy efficiency of tomato

Two principal components were obtained using principal component analysis of 14 tomato metrics, including root dry fresh weight, stem dry fresh weight, leaf dry fresh weight, total sugar, total acid, sugar–acid ratio, number of fruits per plant, yield per plant, water-use efficiency, and electrical energy efficiency under different LED light source spatial settings. As shown in Table 4, the cumulative variance contribution of the two principal components reached 96.75%. The variance contribution of PC1 was 79.69% and the variance contribution of PC2 was 17.06%. This represents the main information from the test processing which can replace the original observation value for evaluation of different fill light processes. After extracting the principal components, we determined the score for each principal component by calculating the eigenvalues, eigenvectors, and standardized data, considering the variance of each component’s contribution. The total score for each treatment was then calculated. The scores for the different treatments are presented in Table 5. Analysis of 14 indices showed that there were significant differences in each index of tomatoes subjected to different treatments. The LED light source spatial setting treatment in the tomato 14 indicators of the comprehensive ranking order from high to low were T4 > T2 > T3 > T1 > CK. The T4 treatment had the highest comprehensive score of 2.85, indicating that upward supplemental lighting at the bottom of the plant is the most effective.

Table 4.

PCA eigenvalues and variance contribution rate

Principal component (PC)	Initial eigenvalue
	Eigenvalue	Variance contribution value	Cumulative variance contribution value
PC1	11.16	79.69	79.69
PC2	2.39	17.06	96.75

Table 5.

Ranking of different treatments

Treatments	Y1	Y2	Composite score	Ranking
CK	−4.26	−6.61	−4.52	5
T1	0.17	−2.30	−0.26	4
T2	1.14	3.33	1.48	2
T3	0.55	−0.70	0.32	3
T4	2.23	6.28	2.85	1

Discussion

Light is an energy source for photosynthesis and material metabolism, and is an important environmental factor affecting the growth and yield of greenhouse plants. Therefore, it is important to select the correct type of supplemental lighting to address the problem of light deficiency in greenhouses during winter and improve the production efficiency of agricultural facilities [37]. Supplemental LED lighting significantly promotes plant biomass accumulation and yield formation [38–41]. All the treatments with LED supplemental lighting significantly increased root, shoot, and fruit fresh weights, promoted plant dry matter accumulation, and increased fruit yield compared to the control. Our experiment also showed that appropriate LED supplementary light increased the dry matter allocation of tomato plants to the fruits and reduced it to the stems. This is similar to the results of Hao et al. [42], who found that supplemental lighting could increase plant dry mass production, with dry mass allocation increasing to fruits and decreasing to stems. There were also differences in crop growth and dry matter partitioning between organs by different supplemental light positions [24, 43] Shao et al. found that bottom supplemental light significantly increased tomato single fruit weight and yield, reduced stem dry matter allocation, and increased fruit dry matter allocation compared to top and side supplemental light [24]. Zhang et al. [44] found that providing upward supplemental light increased the fresh weight of the outer leaves of lettuce. Supplemental light under the canopy promotes the accumulation of tomato seedling biomass [12]. Upward supplemental lighting at the bottom of the plant significantly increased the fresh weight, dry weight, single fruit weight, fruit dry matter allocation, number of fruits per plant, and yield per plant compared with the other treatments. PCA and HCA showed that supplemental lighting treatments could promote tomato fruit yield, especially under the T4 treatment. This may be because the supplemental light from the underlying canopy made the light environment in the lower canopy of tomato plants more uniform and promoted the amount of carbon assimilation by plants by improving the photosynthetic capacity of leaves while transporting more organic matter to the fruit, thereby promoting fruit development [24, 27, 45]. Similar results were obtained in a study on the effect of supplemental lighting provided from underneath the canopy or within the inner canopy on the growth and fruit development of single-trussed tomato plants. Supplemental lighting under the canopy increased the fruit yield of tomato plants compared to supplemental lighting within the inner canopy [46]. Improving water use efficiency remains the primary goal of sustainable agricultural development [47–49]. LED application significantly improved water use efficiency in tomatoes [35], lettuce [31], cannabis [50], and sweet peppers [33]. LED application significantly improved the irrigation amount and water use efficiency of a single tomato plant. This may be because supplementary light increases the photosynthetic efficiency of tomato plants, thus increasing water consumption. However, productivity and carbon assimilation also increase, which leads to an increase in the plant’s water use efficiency [46]. The results of this study were confirmed using the biomass and yield indicators of the tomatoes. The water-use efficiency of tomatoes under the T4 treatment was the highest, potentially because the light received by tomato leaves under the bottom-up light treatment was more uniform than that under other light treatments [35]. LED lights also exhibit considerable energy-saving abilities [51, 52]. For the same power consumption, the electrical energy efficiency of the LED light source spatial settings was ranked as T4 > T2 > T3 > T1. This is consistent with the results observed for the base supplemental lighting [24].

Sugar and organic acids in tomatoes are the key components that affect the flavor quality of tomatoes, and they are also the most intuitive for consumers. The sweetness of tomato fruit is mainly from glucose and fructose [53]. The glucose and fructose contents of tomato fruits accounted for a substantial proportion of the sugar. Citric acid accounted for the highest proportion of organic acids in tomato fruits, which is in line with the results of Bastías et al. [54]. Wang et al. [19] found that supplementary LED lighting in the morning promoted the accumulation of organic acids and sugars in tomatoes. Supplemental light also significantly increases soluble sugar content in tomatoes [21], strawberries [55], and grapes [56]. In this experiment, supplemental LED lighting promoted the accumulation of sugars (glucose, fructose, and sucrose) and acids (oxalic acid, ascorbic acid, citric acid, and malic acid) in tomato fruits compared to the CK treatment. This was consistent with the results of previous studies on tomato fruits. This may be because of the synergistic accumulation of sugars and acids in the fruit, which improves the photosynthetic capacity of tomatoes [46], promotes the assimilation efficiency of the fruit [46], increases the gene expression levels of sucrose phosphosynthase and invertase [57], and regulates the metabolic activity of organic acids [58]. The spatial setting of the LED light source had different effects on the sugar–acid ratio in tomato fruits. This may be attributed to the different synthesis and catabolic metabolic rates of fruit acid fractions owing to different supplemental light positions. Pearson’s correlation analysis showed multiple significant or highly significant correlations between components and is commonly used to estimate statistical correlations between multiple variables [59]. Pearson correlation analysis showed that the sugar–acid ratio was significantly negatively correlated with citric acid, suggesting that citric acid has an important effect on the flavor quality of tomato fruits. PCA showed a significant separation of the CK treatment from treatments T1, T2, T3, and T4, which was supported by the HCA results. Compared with other supplemental lighting treatments, upward supplemental lighting at the bottom of the plant significantly promoted the accumulation of total sugars and the decomposition of total acids in fruits. This increased the sugar–acid ratio, which improved the flavor quality of tomato fruits. Similar results were found in a study by Tian et al., where bottom supplemental light reduced the titratable acid content compared with top supplemental light [60].

Vegetable growth, quality, yield, and water-use efficiency are reflective indices of the effect of the LED light source spatial setting. Therefore, it is important to select the optimal LED light source spatial location. To date, many prior studies have only used simple comparative methods to evaluate the effects of treatments on tests, which may lead to substantial deviations in the test results from the actual results [61, 62]. There are already many methods to assess crop growth and fruit quality [63, 64]. Among them, PCA is the existence of a certain degree of correlation between a number of indicators through factor dimensionality reduction, transformed into a representative of the indicators of the principal components of the indicators. The contributions of the value and factor scores are used to build a function for comprehensive evaluation, which can be used to generate a more holistic reference value [65]. Cao et al. [66] used PCA to evaluate the cold tolerance of tomato strains. Wang et al. [64] applied PCA to evaluate the response of greenhouse tomato yield and fruit quality to deficient irrigation and nitrogen application strategies. PCA was applied to the effects of seven production areas on the nutritional composition and quality traits of dried jujube [67]. PCA of the 14 indicators showed that the ranking was T4 > T2 > T3 > T1 > CK. This suggests that upward supplemental lighting at the bottom of the plant (T4) was the most suitable supplemental light treatment for improving tomato quality and yield.

Conclusion

Upward supplemental lighting at the bottom of the plant was the optimal spatial setting for LED lighting. Upward supplemental lighting at the bottom of the plant increased shoot and whole plant dry and fresh weights and fruit dry matter partitioning ratios in the tomato plant. This resulted in higher tomato yields. Compared with other treatments, upward supplemental lighting at the bottom of the plant also significantly improved water-use efficiency and electrical energy efficiency, which resulted in improved energy and water conservation to a certain extent. Upward supplemental lighting at the bottom of the plant promoted soluble sugar content, organic acid content, and sugar–acid ratio in fruits, resulting in better flavor quality. Therefore, a suitable LED spatial setting can provide a theoretical reference for water-saving and high-quality production of overwintering tomatoes in solar greenhouses in China.

Abbreviations

LEDs

Light-emitting diodes

HPLC

High performance liquid chromatography

PCA

Principal Component Analysis

HCA

Hierachical Cluster Analysis

PC

Principal component

UV

Ultra Violet

ANOVA

Analysis Of Variance

Author contributions

J.L., J.Y., and W.Z. conceived and designed the research. W.Z., and W.L. conducted the experiments. W.Z., and X.M., analyzed the data and prepared the figures and illustrations. S.W., L.J., and N.J. contributed the materials. W.Z. wrote the manuscript. Z.X., W.Z., Q.Z., and Q.S. read the manuscript and made valuable inputs. All authors read and approved the submission of the manuscript.

Funding

This work was supported by the Key Research and Development Program of Gansu (24YFNA018), Longyuan Youth Talent Project in Gansu Province (LYYC-2023-02), Fuxi Young Talents Fund of Gansu Agricultural University (GAUfx-04Y03), Major Science and Technology Special Projects in Gansu Province (22ZD6NA009, 23ZDNA008), the Special Project of Central Government Guiding Local Science and Technology Development (23ZYQA0322).

Data availability

The authors declare that all relevant data generated or analyzed during this study are included in this published article.

Declarations

Ethics approval and consent to participate

There are no ethical issues involved in this paper.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.