Table of Contents Author Guidelines Submit a Manuscript
Journal of Food Quality
Volume 2018, Article ID 4270279, 9 pages
https://doi.org/10.1155/2018/4270279
Research Article

Flavonoid Productivity Optimized for Green and Red Forms of Perilla frutescens via Environmental Control Technologies in Plant Factory

1Center for Environment, Health and Field Sciences, Chiba University, Kashiwa-no-ha 6-2-1, Kashiwa, Chiba 277-0882, Japan
2Department of Biological Sciences, Graduate School of Science, University of Tokyo, Tokyo 113-0033, Japan

Correspondence should be addressed to Natsuko Kagawa; pj.u-abihc.ytlucaf@okustank

Received 21 June 2018; Revised 9 November 2018; Accepted 27 November 2018; Published 20 December 2018

Academic Editor: Encarna Aguayo

Copyright © 2018 Na Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Perilla frutescens (Lamiaceae) is a dietary staple in Asia. It is an abundant source of flavonoids that are bioactively beneficial to human health and fitness. The current popularity of plant-based consumption is being driven by the healthful benefits of bioactive nutrition, and the concentration of bioactive agents found in raw plant materials is an important factor in the assessment of food quality. To test the feasibility of promoting flavonoid productivity in perilla plants via environmental treatment, plant factory technology was applied to perilla plant cultivation. Apigenin (AG) and luteolin (LT) are two of the most potent anticarcinogenic flavonoids in perilla, and these are also found in many vegetables and fruits. Quantitative analysis of AG and LT was conducted on plants cultivated under nine environmental forms of treatment imposed by three levels of light intensity (100, 200, and 300 µmol·m−2·s−1) combined with three levels of nutrient-solution concentration (1.0, 2.0, and 3.0 dS·m−1) for hydroculture. The contents of AG in green and red perilla plant were increased by high nutrient-solution levels under the same light intensity. In green perilla, the highest concentration of AG (8.50 µg·g−1) was obtained under treatment of the highest level of nutrient-solution (3.0 dS·m−1) and 200 µmol·m−2·s−1 of light intensity, whereas in red perilla, the highest concentration of AG (6.38 µg·g−1) was achieved from the highest levels of both of these forms of treatment (300 µmol·m−2·s−1 and 3.0 dS·m−1). The increase in AG content per plant between the lowest and the highest levels was recorded by 6.4-fold and 8.6-fold in green and red perilla, respectively. The behavior of LT concentration differed between green and red forms of perilla. LT concentration in red perilla was enhanced under nutrient deficiency (1.0 dS·m−1) and affected by light intensity. Different responses were observed in the accumulations of AG and LT in red and green perilla during treatments, and this phenomenon was discussed in terms of biosynthetic pathways that involve the expressions of phenylpropanoids and anthocyanins. The total yield of flavonoids (AG and LT) was improved with the optimization of those forms of treatment, with the best total yields: 33.9 mg·plant−1 in green Perilla; 10.0 mg·plant−1 in red perilla, and a 4.9-fold and a 5.4-fold increase was recorded in green and red perilla, respectively. This study revealed that flavone biosynthesis and accumulation in perilla plants could be optimized via environmental control technologies, and this approach could be applicable to leafy vegetables with bioactive nutrition to produce a stable industrial supply of high flavonoid content.

1. Introduction

Secondary metabolites (SMs) in plants are an important part of food nutrition, and their content could be used to determine food quality. SMs include terpenoids, phenylpropanoids, flavonoids, and alkaloids that are essential food ingredients that determine flavor, color, and taste in grains, vegetables, and fruits [1]. In addition, since the beneficial bioactivities to human health from compounds such as antioxidants have become well known, many SMs are being recognized as having medicinal effects on both the human body and mind [2, 3].

Recently, the intake of foods rich in bioactive SMs has gained in popularity worldwide. However, maintaining stable supplies of raw plant materials that can be used to produce foods high in nutritional value remains problematic due to the lack of an effective method to control the SM content in plant cultivation. Both the production and accumulation of SMs are sensitive to environmental conditions [4, 5]. Generally, plants grow rapidly in less stressful environments and produce better yields in biomass. On the other hand, both biotic and abiotic factors of stress induce the formation of SMs, such as phenolic compounds [6]. Meanwhile, a few attempts have been made to evaluate the quality of plants grown under different environments by detailing the stable expressions of the secondary metabolisms and concentrations of bioactive SMs that are expected to be included in plant-based foods as an additional health promoting component [7].

A plant factory is a food production system that can supply stable plant materials year-round with no influence from climate change [8], which has proven to be effective for medicinal plant production since the environmental conditions can be fully controlled. Owing to high levels of bacterial and insect control, no pesticides are needed for the plants produced in these systems. Therefore, plant factories can produce safe food with a desired level of quality when the optimal environmental condition can be determined for a particular crop. Regulating environmental factors such as light, temperature, and water has a significant impact on plant metabolic and synthetic pathways and enhances the SM content. It is well known that concentrations of SMs in plant are varying with its growth conditions. Providing high stressful environment to plants may promote accumulation of SMs; however, higher stress levels usually meanwhile result in lower yields. In the practical production in plant factories, it is greatly important to keep a balance between biomass yield and SMs concentration to maximize economic benefits. Therefore, quantifying the optimal stress level from a single environmental factor or from an interaction of multiple environmental factors becomes crucial for actual production of medicinal plants in a commercial plant factory. Unlike plant production in outdoor condition, a plant factory can precisely tune its environmental factors such as light intensity, light spectrum, nutrient solution level, temperature, air flow rate, etc. without limitation of locations. If the treatments and their effects on SMs synthesis are quantified, this technique can be directly applied into commercial plant factories all over the world not only theoretically but also practically.

Perilla frutescens (Lamiaceae) is widely used as a culinary herb in Asia, particularly in Japan. The color and flavor of perilla are familiar parts of traditional Japanese cuisine. In Japan, the extract of perilla is used to add color and flavor to pickled vegetables and Japanese plums. In Japan, Korea, and India, people commonly use perilla leaves in the preparation of raw fish and shell-fish to reduce the odor, and it is added to grilled red meat to add flavor [9]. As a medicinal herb for crude drugs, the extract of perilla is used for clinical applications, being listed in the pharmacopoeia in Japan [10], Republic of Korea [11], and in People’s Republic of China [12].

Apigenin (AG) and luteolin (LT) are the main flavonoids present in perilla and are also contained in many vegetables and fruits: celery, parsley, and onions for AG; red peppers, lettuce, berries, and onions for LT. AG, and LT are known as antioxidant, anti-inflammatory, and anticarcinogenic agents and, as such, they have attracted researchers’ attention due to their potential as chemopreventive agents [1, 1315]. Because of that, AG and LT have been candidate compounds for many pharmaceuticals or nutraceuticals from plant-derived dietary agents for the development of new therapies [1, 1315]. For medical use, however, it must be stated that many flavonoids including AG and LT have hermetic effects that have the potential to make them toxic, so that dose adjustment is necessary to achieve safety and efficacy [15]. Thus, the concentrations of AG and LT in plant-based foods are important and must be controlled by meeting the challenges of technology that can supply these raw materials in good quality.

In a previous study, we found that rosmarinic acid (RA), a major phenylpropanoid compound in herbs of Lamiaceae family, is highly increased in P. frutescens grown under uptake stress created by a nutrient-limited condition combined with high light intensity (LI) in plant factories, while maintaining a constant concentration of perillaldehyde (PA), a main terpenoid found in perilla essential oils [16]. Given the differences that exist between terpenoids and phenylpropanoids with respect to biosynthetic pathways and accumulation, there likely are no synchronous increases in PA and RA. However, since the biosyntheses of flavonoids share the biosynthetic pathway with phenylpropanoids, it remains unclear how flavonoids might react to an environment that affects the production of phenylpropanoids. This should be clarified in order to establish quality control for raw plant materials according to the concentrations of compounds that are a rich source of food nutrition. Therefore, in the present study, we investigated the quantitative production of flavonoids in a perilla plant via the gradual introduction of stresses commonly encountered in cultivation and compared the quantitative expressions of AG and LT. In a plant factory with artificial lighting, perilla plants were cultivated under nine different levels of environmental treatment created by a combination of light intensity and nutrient concentration in hydroponics. Quantitative chemical analysis via liquid chromatography-mass spectrometry (LC-MS) was conducted to measure the concentrations of AG and LT as two major flavonoids in perilla plants grown under different growth conditions.

2. Materials and Methods

2.1. Perilla Materials and Growth Conditions

Green perilla (P. frutescens var. crispa f. viridis Makino, Takii Seed Co., Ltd., Kyoto, Japan) and red perilla (P. frutescens (L.) Britton. var. acuta Kudo f. crispa Makino, 0657–79TS, National Institute of Biomedical Innovation, Osaka, Japan) seeds were sown in rockwool cubes (125 cm3) in a cultivation room. The LI was set to 150 µmol·m−2·s−1 (the unit of µmol·m−2·s−1 represents photosynthetic photon flux density on the surface of cultivation containers) with a photoperiod of 16 h per day provided by cool white fluorescent lamps (FHF32 EX-N-H, Panasonic, Co., Ltd., Japan), and the plants were irrigated with a nutrient solution (Otsuka hydroponic composition, OAT Agrio Co., Ltd., Tokyo, Japan) (Otsuka formula as described by Lu et al. [16]). The electrical conductivity (EC) and pH of the nutrient solution were adjusted to 1.2 dS·m−1 and 6.0, respectively. Air temperature, relative humidity, and CO2 concentration were set to 25/20°C (light/dark periods), 60–80%, and 400 µmol·mol−1, respectively.

2.2. Treatments

Three weeks after sowing, red perilla and green perilla seedlings were transplanted into a walk-in type plant factory (2.9 m × 2.0 m × 2.3 m in LWH) and subjected to three LI levels (100, 200, and 300 µmol·m−2·s−1) with a photoperiod of 16 h per day supplied by cool white fluorescent lamps and three EC levels (1.0, 2.0, and 3.0 dS·m−1) for five weeks. The LI was measured at the surface of the rockwool cubes using a light meter (LI-250A; Li-Cor Inc., Lincoln,NE, USA) before placing the plants. The experiment was set up in a 3 × 3 full factorial in split plot design with LI as the main plot and EC levels as subplot, and each treatment contained 18 plants. Three nutrient solution tanks (EC of 1.0, 2.0, and 3.0 dS·m−1 for each) were prepared beside the cultivation system. The plants were irrigated every 2 days from the bottom using fresh nutrient solution from each tank. The overflowed nutrient solution was discarded after each rockwool cube was saturated. Air temperature, relative humidity, and CO2 concentration were set at 23/20°C (light/dark periods), 60–80%, and 1000 µmol·mol−1, respectively.

2.3. Extraction

Extraction from perilla leaves was conducted according to Japanese Pharmacopoeia [10] and methods described in a previous article [16]. The leaves were sampled and dried at 30°C for 2 weeks. The dried perilla leaves were ground to powder and filtered through a sieve. A 10.00–10.50 mg sample was weighed accurately and transferred to a 1.5 mL tube. Methanol (1 mL) was added, mixed for 10 min at 2,000 rpm and 15°C using an Eppendorf ThermoMixer (Hamburg, Germany), and centrifuged for 5 min. To the residue, methanol (1 mL × 2) was added, and the same extract manner was performed twice. The extracts (about 3 mL) were combined and transferred to a 5 mL volumetric flask and diluted with methanol to a 5 mL total volume. The solution was filtered through Agilent 0.2 µm nylon syringe filters (Agilent Technologies Inc., Palo Alto, CA, USA) to prepare the samples for LC-MS.

2.4. Contents of AG and LT

LC-MS analysis of AG and LT was conducted according to a method described by Nishimura et al. [17] with some modifications. A Shimadzu LC-20A prominence system (HPLC) with a SIL-20AC autosampler and a LCMS-2020 mass spectrometer (MS) equipped with an electrospray ionization (ESI) source operating in negative mode were used for identification and quantification of AG and LT by chromatographic data processed using LabSolutions software (Shimadzu, Kyoto, Japan). The HPLC conditions for AG and LT were XBridge BEH C18 column (3.5 µm, 2.1 × 150 mm, Waters, MA, USA); temperature, 40°C; flow rate, 0.2 mL/min; run time, 15 min; mobile phase, 30% acetonitrile/0.1% formic acid; and injection volume, 1 µL. The eluent was passed to the electrospray source. A capillary voltage of 3.5 kV was used in the negative ion mode. Nitrogen was used as drying gas with a flow rate of 15 L·min−1 and as nebulizing gas with a flow rate of 1.5 L·min−1. The desolvation line temperature was set at 250°C. The ion trap was operated in full-scan mode from m/z 50 to 1000 and selected-ion monitoring (SIM) mode with m/z 269 for a molecular ion [M–H] of AG and m/z 285 for a molecular ion [M–H] of LT. The standards of AG and LT were dissolved in a little of THF and then diluted with methanol to prepare the standard solutions before use for identification and quantification. AG and LT contents per leaf dry weight (hereafter, AG and LT concentration) were estimated by dividing the AG and LT contents in samples by sample weight.

2.5. Chemicals

Methanol (LC-MS grade) and water (LC-MS grade) were purchased from FUJIFILM Wako Pure Chemical Corporation (Osaka, Japan). The AG and LT standards were obtained from Tokyo Chemical Industry Co., Ltd. (Tokyo, Japan). Acetonitrile (HPLC grade) was obtained from Sigma-Aldrich Japan (Tokyo, Japan). Formic acid was purchased from Kanto Chemical Co., Inc. (Tokyo, Japan).

2.6. Statistical Analysis

All measurements were repeated three times for each sample. Five to six plants were sampled from each treatment to determine concentrations. The means of the treatment data were subjected to analysis of variance for comparison via Tukey’s test using SPSS statistical software (IBM SPSS Statistics, Version 25.0. Armonk, NY: IBM Corp.). A value <0.05 was considered significant.

3. Results and Discussion

3.1. Concentrations of AG and LT in Green and Red Perilla

Concentrations of AG and LT in green perilla are shown in Figures 1(a) and 1(b), respectively, as the content per unit of leaf dry weight. The concentration of AG was decreased under an EC of 1.0 dS·m−1 using the same LI, and it tended to increase with increases in the EC under LIs of 100 and 200 µmol·m−2·s−1 (Figure 1(a)). The concentration of AG was the lowest (2.95 µg·g−1) under an EC of 1.0 dS·m−1 and a LI of 200 µmol·m−2·s−1, but it was increased to the highest level (8.50 µg·g−1) of concentration (2.9-fold increase) under an EC of 3.0 dS·m−1 and LI of 200 µmol·m−2·s−1. LI had little effect on the AG concentration under the same EC, with the exception of a comparison between LIs of 200 and 300 µmol·m−2·s−1 under an EC of 3.0 dS·m−1. The resultant LT concentration showed no significant differences as a result of treatment and was affected neither by LI nor by EC (Figure 1(b)).

Figure 1: Content per unit of leaf dry weight (µg·g−1) in perilla plants after 5 weeks of cultivation under different LI and EC treatments. (a) AG content per leaf dry weight (µg·g−1) in green; (b) LT content per leaf dry weight (µg·g−1) in green; (c) AG content per leaf dry weight (µg·g−1) in red; (d) LT content per leaf dry weight (µg·g−1) in red. Values are mean ± standard error (). Different letters indicate significant differences between at , as determined by Tukey’s test.

Concentrations of AG and LT in red perilla are shown in Figures 1(c) and 1(d), respectively, as the content per unit of leaf dry weight. The concentrations of AG tended to decrease with decreases in EC under the same LI, but LI showed little effect when EC treatment was unchanged. The lowest values (3.43 µg·g−1) were obtained under the lowest levels of EC and LI, and the highest values (6.38 µg·g−1) were obtained under the highest levels of EC and LI (1.9-fold increase). LT concentrations showed small differences after treatments, with the noted exception of treatments between 100 and 200 µmol·m−2·s−1 under an EC of 1.0 dS·m−1. LT concentrations tended to increase with decreases in EC and were significantly increased by the lowest level of EC (1.0 dS·m−1) with a LI of 200 µmol·m−2·s−1. The concentration of LT was the lowest (5.92 µg·g−1) under an EC of 3.0 dS·m−1 and LI of 200 µmol·m−2·s−1, but it was increased to the highest level (11.9 µg·g−1) of concentration (2.0-fold increase) under an EC of 1.0 dS·m−1 and LI of 200 µmol·m−2·s−1.

3.2. AG and LT Content per Plant in Green and Red Perilla

The contents of AG and LT per plant in green perilla are shown in Figures 2(a) and 2(b), respectively. The highest EC (3.0 dS·m−1) yielded the higher AG and LT content per plant under the same LI. The lowest levels of AG and LT content per plant were recorded under an EC of 1.0 dS·m−1 and LI of 200 µmol·m−2·s−1, but those levels were increased to the highest levels (6.4-fold and 3.7-fold increases in AG and LT, respectively) under an EC of 1.0 dS·m−1 and LI of 200 µmol·m−2·s−1. The AG and LT content per plant depended on growth conditions that were determined by the level of either low EC or low LI.

Figure 2: Content per plant in perilla plants after 5 weeks of cultivation under different LI and EC treatments. (a) AG content per plant (µg·plant−1) in green; (b) LT content per plant (µg·plant−1) in green; (c) AG content per plant (µg·plant−1) in red; (d) LT content per plant (µg·plant−1) in red. Values are mean ± standard error (). Different letters indicate significant differences between at , as determined by Tukey’s test.

The contents of AG and LT per plant in red perilla are shown in Figures 2(c) and 2(d), respectively. Unlike green perilla plants, the highest LI (300 µmol·m−2·s−1) yielded the higher AG content per plant under the same EC in red perilla. The higher level of AG content per plant was obtained under an EC level of 2.0 or 3.0 dS·m−1 combined with the highest LI (300 µmol·m−2·s−1). All other treatments obtained significantly lower levels of AG content per plant compared with the above treatments. The lowest AG content per plant (0.57 µg·plant−1) obtained under an EC level of 1.0 dS·m−1 and LI of 300 µmol·m−2·s−1 was increased to the highest (4.90 µg·plant−1) AG content per plant (8.6-fold increase) under an EC of 3.0 dS·m−1 and LI of 300 µmol·m−2·s−1. LT content per plant tended to increase with increases in LI under EC levels of 2.0 and 3.0 dS·m−1. LT content per plant was the lowest (1.30 µg·plant−1) under an EC of 1.0 dS·m−1 and LI of 100 µmol·m−2·s−1, and the highest value (5.19 µg·plant−1) was obtained (4.0-fold increase) under an EC of 3.0 dS·m−1 with LI of 300 µmol·m−2·s−1.

3.3. Flavonoid Production in Green and Red Perilla

Flavonoid biosynthesis has been studied extensively in different plant species [18]. Both AG and LT have a flavone in their chemical structure, and enzymes that work as key biocatalysts to synthesize the core structure of flavonoids such as flavone, flavonol, flavanone, and anthocyanidin. RA is an ester of two C6-C3 molecules called phenylpropanoid, and enzymes involved in the biosynthesis of RA have also been identified in Coleus blumei L. [19]. Recently, gene expression in P. frutescens associated with the biosynthetic pathways of flavonoids and phenylpropanoids has been revealed in studies using transcriptome analysis [20]. Thus, based on the knowledge above, we have proposed the biosynthetic pathways relevant to RA, AG, and LT, which are present in perilla, as shown in Figure 3. The pathway to flavones, AG and LT, includes the general biosynthesis of phenylpropanoids derived from L-phenylalanine to produce 4-coumaroyl-CoA, which is a crucial precursor for the biosynthesis of flavones and RA [19]. The substrate 4-coumaroyl-CoA is one of two used for esterification, during which it reacts with 4-hydroxyphenyllactic acid in a step that is important in the biosynthesis of RA. That fact suggests that producing molecules of AG, LT, and RA requires the use of an equivalent of 4-coumaroyl-CoA molecules as a biosynthetic precursor and also suggests the need to activate the enzymes involved in the phenylpropanoid pathway.

Figure 3: Proposed biosynthetic pathways for apigenin, luteolin, rosmarinic acid, and anthocyanins in perilla plants. Core enzymes involved in the biosynthesis of phenylpropanoid, flavone, and anthocyanin skeletons are shown. F3′H, flavonoid 3′-hydroxylase; FNS, flavone synthase; F3H, flavanone 3-hydroxylase; FLS, flavonol synthase; CHI, chalcone isomerase; CHS, chalcone synthase; PAL, phenylalanine ammonia-lyase; C4H, cinnamic acid 4-hydroxylase; 4CL, 4-coumaric acid: CoA ligase; TAT, tyrosine aminotransferase; HPPR, hydroxyphenylpyruvate reductase; RAS, hydroxycinnamoyl-CoA: hydroxyphenyllactate hydroxycinnamoyl transferase; 3H and 3′H, hydroxycinnamoyl-hydroxyphenyllactate 3-and 3′-hydroxylases.

Our results showed that the effect of EC levels on the accumulation of AG and LT was quite different. The concentration of AG was highest for an EC of 3.0 dS·m−1, whereas that of the LT was highest for an EC of 1.0 dS·m−1. In addition, the AG concentration was lowest under an EC of 1.0 dS·m−1, whereas that of the LT was lowest under an EC of 3.0 dS·m−1. These opposition responses between AG and LT could reflect their competitive relationship in the sharing of naringenin, which resides in the connection between the pathways to AG and anthocyanins (Figure 3). In our previous report, the concentration of RA was the highest under nutrient-limited conditions (EC of 1.0 dS·m−1) and decreased with the highest EC level (EC of 3.0 dS·m−1) in green and red perilla [16]. Interestingly, the similar responses between LT and RA were observed in red perilla, so that the LT concentration was enhanced in red perilla grown under nutrient-limited stress.

The effect of EC on LT accumulation differed between green and red perilla. In green perilla, the results of LT concentration showed neither a change nor a trend, but the LT content per plant had a wide range of figures depending on the environment. The yield of LT was promoted under high levels of both EC and LI in accordance with the biomass yield (Figures 1(b) and 2(b)). In red perilla, however, the concentration of LT was enhanced under an EC of 1.0 dS·m−1, which stood in opposition to the biomass trend (Figures 1(d) and 2(d)). This suggests that the LT metabolism in red perilla overcame the negative effect of EC during growth when LI reached at least 200 µmol·m−2·s−1, which caused an increase in the LT yield against a decrease in the biomass yield but only at this level of LI. With LI values of 100 and 300 µmol·m−2·s−1, the yield of LT showed a clear dependence on the biomass yield.

We compared AG and LT accumulation in green and red perilla (Figures 4 and 5). In red perilla, LT accumulation was always higher than that of AG, whereas in green perilla AG was higher than LT except for three treatments (Figure 4). LT molecules have a hydroxyl group at the 3′ position on the flavone skeleton, and a crucial enzyme that introduces the 3′-hydroxyl group on the corresponding precursor has been identified as flavone 3′-hydroxylase (F3′H) (Figure 3). Because red perilla plants manifest higher expression levels of genes encoding F3′H compared with levels expressed in green plants and because F3′H is one of the most important catalysts in anthocyanin synthesis in Arabidopsis [20], the accumulation of LT that was higher than that of AG in red perilla, presumably caused by the higher transformation activity of F3′H in anthocyanin biosynthesis in red plants compared with that in green plants. To clarify this interaction, we tried to trace biosynthetic precursors: naringenin chalcone, naringenin, kaempferol, quercetin, and eriodictyol by quantitative analysis using LC-MS, but none of them detected from extract of perilla dry leaves. It means that those molecules were not accumulated enough in a detective level on their relative pathway. Then, we though that those precursors are transformed quickly and used for biosynthesis of AG, LT, and anthocyanins.

Figure 4: Comparative content of apigenin and luteolin in perilla plants after 5 weeks of cultivation under different LI and EC treatments. (a) AG vs LT content per leaf dry weight (µg·g−1) in green; (b) AG vs LT content per plant (mg·plant−1) in green; (c) AG vs LT content per leaf dry weight (µg·g−1) in red; (d) AG vs LT content per plant (mg·plant−1) in red.
Figure 5: Total content of apigenin and luteolin (apigenin + luteolin) in perilla plants after 5 weeks of cultivation under different LI and EC treatments. (a) AG and LT content per leaf dry weight (µg·g−1) in green; (b) AG and LT content per plant (mg·plant−1) in green; (c) AG and LT content per leaf dry weight (µg·g−1) in red; (d) AG and LT content per plant (mg·plant−1) in red.

The total concentrations of AG and LT in green perilla were the lowest under a LI of 200 µmol·m−2·s−1 and an EC of 1.0 dS·m−1, but these were increased to the highest levels (2.2-fold increase) of concentration under LI of 200 µmol·m−2·s−1 and an EC of 3.0 dS·m−1 (Figure 5(a)). In red perilla, however, concentrations were the lowest under LI of 200 µmol·m−2·s−1 and an EC of 3.0 dS·m−1 and increased to the highest levels (1.4-fold increase) under LI of 300 µmol·m−2·s−1 and an EC of 1.0 dS·m−1 (Figure 5(c)). In other words, the range of total concentration was narrower in red plants compared with green plants, which indicated that red plants could withstand a greater environmental impact on flavone accumulation, which could result in greater uniformity of food quality. The total yield of AG and LT in green perilla was the lowest under LI of 200 µmol·m−2·s−1 and an EC of 1.0 dS·m−1 and increased to the highest yield (a 4.9-fold increase) under LI of 200 µmol·m−2·s−1 and an EC of 3.0 dS·m−1 (Figure 5(b)). For red perilla, the total yield of AG and LT was the lowest under LI of 100 µmol·m−2·s−1 and an EC of 1.0 dS·m−1 and increased to the highest yield (a 5.4-fold increase) under LI of 300 µmol·m−2·s−1 and an EC of 3.0 dS·m−1 (Figure 5(d)). Because green plants obtained larger biomass yields than red plants, they had the best total yield of AG and LT (33.9 mg·plant−1; LI: 200 µmol·m−2·s−1; EC: 3.0·dS·m−1) that were triple more than that of red plants (10.0 mg·plant−1; LI: 300 µmol·m−2·s−1; EC: 3.0 dS·m−1) under application of the best treatments for both (Figures 5(b) and 5(d)), in which the total concentrations of AG and LT in green and red plants were almost the same, 14.6 µg·g−1 and 13.3 µg·g−1, respectively (Figures 5(a) and 5(c)).

4. Conclusions

We examined the bioactive flavonoids that appear in green and red forms of perilla plants. The results indicated that LI and EC were the factors that most affected flavonoid productivity in both concentration and yield of apigenin and luteolin. Therefore, environmental treatments that were regulated by those factors had a remarkable impact on flavone biosynthesis and accumulation, and their use is proposed as an effective method for the cultivation of green and red perilla plants. These findings could be applicable to an optimization of cultivation control in the production of foods composed of leafy vegetables containing bioactive compounds.

Data Availability

The data used to support the findings of this study are included within the article.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Acknowledgments

This work was supported by the Japan Food Chemical Research Foundation and Phytochemical Plant Molecular Sciences, Chiba University. We thank Ms. Chayanit Tippayadarapanich (Kasetsart University) for technical assistance in cultivation. We also thank Dr. Kazuki Saito and Dr. Mami Yamazaki (Chiba University) for encouraging us to examine flavones in perilla.

References

  1. S. C. Gupta, J. H. Kim, S. Prasad, and B. B. Aggarwal, “Regulation of survival, proliferation, invasion, angiogenesis, and metastasis of tumor cells through modulation of inflammatory pathways by nutraceuticals,” Cancer and Metastasis Reviews, vol. 29, no. 3, pp. 405–434, 2010. View at Publisher · View at Google Scholar · View at Scopus
  2. N. Sugihara, T. Arakawa, M. Ohnishi, and K. Furuno, “Anti- and pro-oxidative effects of flavonoids on metal-induced lipid hydroperoxide-dependent lipid peroxidation in cultured hepatocytes loaded with α-linolenic acid,” Free Radical Biology and Medicine, vol. 27, no. 11-12, pp. 1313–1323, 1999. View at Publisher · View at Google Scholar · View at Scopus
  3. J. B. Harborne and C. A. Williams, “Anthocyanins and other flavonoids (January 1998 to December 2000),” Natural Product Reports, vol. 18, no. 3, pp. 310–333, 2001. View at Publisher · View at Google Scholar · View at Scopus
  4. R. A. Dixon and N. L. Paiva, “Stress-induced phenylpropanoid metabolism,” Plant Cell Online, vol. 7, no. 7, pp. 1085–1097, 1995. View at Publisher · View at Google Scholar · View at Scopus
  5. G. Sudha and G. A. Ravishankar, “Involvement and interaction of various signaling compounds on the plant metabolic events during defense response, resistance to stress factors, formation of secondary metabolites and their molecular aspects,” Plant Cell, Tissue and Organ Culture, vol. 71, no. 3, pp. 181–212, 2002. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Tonelli, E. Pellegrini, F. D’Angiolillo et al., “Ozone-elicited secondary metabolites in shoot cultures of Melissa officinalis L,” Plant Cell, Tissue and Organ Culture (PCTOC), vol. 120, no. 2, pp. 617–629, 2014. View at Publisher · View at Google Scholar · View at Scopus
  7. E. Ogawa, S. Hikosaka, and E. Goto, “Effects of nutrient solution temperature on the concentration of major bioactive compounds in red perilla,” Journal of Agricultural Meteorology, vol. 74, no. 2, pp. 71–78, 2018. View at Publisher · View at Google Scholar · View at Scopus
  8. T. Kozai and G. Niu, “Role of the plant factory with artificial lighting (PFAL) in urban areas,” in Plant Factory: An Indoor Vertical Farming System for Efficient Quality Food Production, T. Kozai, G. Niu, and M. Takagaki, Eds., p. 22, Academic Press, London, UK, 2016. View at Google Scholar
  9. H.-C. Yu, “Introduction,” in Perilla, the Genus Perilla, H.-C. Yu, K. Kosuna, and M. Haga, Eds., Harwood Academic Publishers, Amsterdam, The Netherlands, 1997. View at Google Scholar
  10. The Ministry of Health, Labour and Welfare of Japan, The Japanese Pharmacopoeia, The Ministry of Health, Labour and Welfare of Japan, Tokyo, Japan, 17th edition, 2017, http://www.mhlw.go.jp/file/06-Seisakujouhou-11120000-Iyakushokuhinkyoku/JP17_REV_1.pdf.
  11. The Ministry of Food and Drug Safety of Republic of Korea, The Korean Pharmacopoeia, The Ministry of Food and Drug Safety of Republic of Korea, Cheongju, Republic of Korea, 10th edition, 2012, http://www.mfds.go.kr/eng/eng/index.do?nMenuCode=128&page=1&mode=view&boardSeq=70483.
  12. Zisugeng and Zisuzi, Perilia Caulis and Perilia Fructus, Chinese Pharmacopoeia, Beijing, China, 2015.
  13. D. Patel, S. Shukla, and S. Gupta, “Apigenin and cancer chemoprevention: progress, potential and promise (review),” International Journal of Oncology, vol. 30, no. 1, pp. 233–245, 2007. View at Publisher · View at Google Scholar
  14. F. Liu-Smith and F. L. Meyskens, “Molecular mechanisms of flavonoids in melanin synthesis and the potential for the prevention and treatment of melanoma,” Molecular Nutrition & Food Research, vol. 60, no. 6, pp. 1264–1274, 2016. View at Publisher · View at Google Scholar · View at Scopus
  15. V. C. George, G. Dellaire, and H. P. V. Rupasinghe, “Plant flavonoids in cancer chemoprevention: role in genome stability,” Journal of Nutritional Biochemistry, vol. 45, pp. 1–14, 2017. View at Publisher · View at Google Scholar · View at Scopus
  16. N. Lu, E. L. Bernardo, C. Tippayadarapanich, M. Takagaki, N. Kagawa, and W. Yamori, “Growth and accumulation of secondary metabolites in perilla as affected by photosynthetic photon flux density and electrical conductivity of the nutrient solution,” Frontiers in Plant Science, vol. 8, p. 708, 2017. View at Publisher · View at Google Scholar · View at Scopus
  17. T. Nishimura, K. Ohyama, E. Goto, and N. Inagaki, “Concentrations of perillaldehyde, limonene, and anthocyanin of Perilla plants as affected by light quality under controlled environments,” Scientia Horticulturae, vol. 122, no. 1, pp. 134–137, 2009. View at Publisher · View at Google Scholar · View at Scopus
  18. H. Bashandy, M. Pietiäinen, E. Carvalho et al., “Anthocyanin biosynthesis in gerbera cultivar “Estelle” and its acyanic sport “Ivory”,” Planta, vol. 242, no. 3, pp. 601–611, 2015. View at Publisher · View at Google Scholar · View at Scopus
  19. M. Petersen and M. S. J. Simmonds, “Rosmarinic acid,” Phytochemistry, vol. 62, no. 2, pp. 121–125, 2003. View at Publisher · View at Google Scholar · View at Scopus
  20. A. Fukushima, M. Nakamura, H. Suzuki, K. Saito, and M. Yamazaki, “High-throughput sequencing and de novo assembly of red and green forms of the Perilla frutescens var. crispa transcriptome,” PLoS One, vol. 10, no. 6, Article ID e0129154, 2015. View at Publisher · View at Google Scholar · View at Scopus