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ISSN : 1225-8504(Print)
ISSN : 2287-8165(Online)
Journal of the Korean Society of International Agriculture Vol.34 No.1 pp.49-56
DOI : https://doi.org/10.12719/KSIA.2022.34.1.49

Effect of Different Red and Blue Light Compositions on the Root and Shoot Growth of Pakchoi (Brassica Rapa subsp. Chinensis) Using Food Jukebox

Rupesh Tayade, Yoonha Kim†
Department of Applied Bioscience, Kyungpook National University, Daegu 41566
† Corresponding author (Phone) +82-53-950-5710 (E-mail) kyh229@knu.ac.kr
January 18, 2022 February 18, 2022 February 18, 2022

Abstract


Chinese cabbage or pakchoi (Brassica Rapa subsp. Chinensis) is one of the most popular vegetables in Korea. It is grown and consumed throughout the year because it has many benefits. This study reports on the growth performance of pakchoi grown in the hydroponic system using a Food Juke Box (FJB) under different light compositions. The chlorophyll content (CC), root fresh weight (RFW), and shoot fresh weight (SFW) were measured. Further, various vegetation indices (VIs), such as modified chlorophyll absorption in reflectance index (MCARI1), normalized difference vegetation index (NDVI), optimized soil-adjusted vegetation index (OSAVI), and structure insensitive pigment index (SIPI), were employed to predict SFW. The study results indicated a significant increase in the CC of pakchoi with different light treatments compared with the control. The CC was highest under treatment with 70% white light, 20% blue light, and 10% red light (T1) than under treatment with 50% white light, 30% blue light, and 20% red light (T2). All used VIs showed significant differences with different light combination treatments. There was no significant change in RFW and SFW between the control and T1. However, a significant reduction in RFW and SFW was observed in T2 compared with the control. A comparison between T1 and T2 demonstrated that RFW and SFW were increased by 23% and 25%, respectively, compared with those in T2. The correlation result showed that SFW had a significant positive correlation with RFW (0.76***). Further, a significant negative correlation was observed with OSAVI (−0.25*), MCARI1 (−0.54***), and CC (−0.19*). In conclusion, our findings implied that different light combinations in pakchoi affected the photosynthetic pigments although they did not improve SFW. This research will pave the way for pakchoi production in hydroponics using smart farming FJB. This will further promote plant development, especially for domestic consumption, and help fulfill the growing demand for leafy vegetables.


Chlorophyll , Food Jukebox , Light combination , Pakchoi , Vegetative indices

초록

    INTRODUCTION

    Pakchoi (Brassica Rapa subsp. Chinensis) is commonly known as a nonheaded Chinese cabbage. It is an essential leafy vegetable crop cultivated and consumed by most Asian countries all year round due to its beneficial phytochemical composition. Studies have shown that it contains phytochemicals, such as provitamin A, vitamin C, minerals, and fiber (Son et al., 2018;Keefe et al., 2019). Thus, consumer demand for pakchoi is increasing due to its benefits (Rahman, 2003;Block et al., 2004;Son et al., 2018).

    Among various environmental factors, light quality is crucial for its yield because of its significant role in photosynthesis efficiency (Song et al., 2020). Under sunlight, visible light mainly participates in photosynthesis (Ahmed et al., 2020). However, red light (RL) and blue light (BL) also play significant roles in the photosynthetic reaction (Song et al., 2020). They contribute to plant growth and development (Song et al., 2020). Both RL and BL are absorbed in plants by photosynthetic pigments such as chlorophylls and carotenoids (Ahmed et al., 2020). Thus, they are significantly involved in the regulation of phyto-chrome and cryptochrome. Both lights impact photomorphogenesis and regulation of the stomata (Ahmed et al., 2020).

    As the human population increases, the need for agricultural land will continue to increase. Currently, the human population has exceeded 7.8 billion worldwide (Cohen, 1995). This increasing population will cause agricultural land to be used as residential land, thereby reducing the availability of land (Mansour et al., 2020). Hence, there is an increasing demand for smart farming although the available techniques are limited. Hydroponics is a popular crop production method for overcoming the limitations of agricultural land (Saiz-Rubio and Rovira-Más, 2020;Kumar et al., 2021). It does not require soil for growth; instead, it uses specially formulated fertilizers and artificial lighting (Kumar et al., 2021).

    In South Korea, the Korea Institute of Science and Technology (KIST) developed an open platform for collecting, sharing, analyzing, and using plant phenome data to develop growth models.They produced a small growth chamber known as the Food Jukebox (FJB). Environmental factors, such as temperature, humidity, carbon dioxide, nutrient concentration, light intensity, and light quality, can be regulated in an FJB via a web-based open platform (http://fjbox.jinong.co.kr/). Although KIST developed FJB, they lacked sufficient information on the required environmental conditions for optimal plant growth and development. Therefore, further studies are needed to determine the optimal environmental condition for vegetable growth in FJBs. Hence, this study aimed to investigate the effect of different light treatments, such as white light (WL), red light (RL), and blue light (BL), on the growth of pakchoi. We used varied RL and BL ratios to evaluate optimal light quality to improve the productivity of pakchoi in this study. Furthermore, we employed vegetation indices (VIs) in the leaf area to predict fresh weight or growth conditions during pakchoi cultivation.

    MATERIALS AND METHODS

    Growth condition of FJB

    FJBs can regulate environmental conditions, such as temperature, humidity, carbon dioxide (CO2), and electrical conductivity of the nutrient solution. Hence, the aforementioned environmental conditions were relatively controlled during the experimental period (Fig. 1). The FJB uses Peltier elements to provide indoor cooling and heating functions. The system temperature can be adjusted. When there is an increase in CO2 concentration inside a chamber, the ventilation fan is activated.

    In the experiment, total 325 surface mounted diode (SMD) LED module was connected with printed circuit board then it was used as light source. Among them, we used 64 of blue LED, 112 of red LED and 176 of white LED. The information three LED light sources shows in Table 1. The peak wavelength of each LED light was 454 nm (blue), 658 nm (red), and 450 nm (white). However, the maximum light intensity of each LED light was 3,400 μmol m-2 s-1 (blue), 870 μmol m-2 s-1 (red), and 285 μmol m-2 s-1 (white) (Fig. 2). The brightness of the LED was adjustable (0%–100%)(Table 1).

    During the experiment, the researchers supplied the essential elements for pakchoi growth using hydroponical means. Table 2 contains detailed information on the formulated nutrient solution, which was directly sprayed on the roots using a pump. The nutrient spray exposure times were set at 120 seconds per hour (daytime) and 120 seconds per 2 hours (nighttime). A LAN port on the website controls FJB conditions (http://fjbox.jinong.co.kr/). The ventilation fan reduces the temperature and supplies CO2 into a chamber.

    Plant material and growth condition

    The F1 hybrid seeds of pakchoi “SingSingHaGye” (Asia Seed Korea, South Korea) were used for this experiment. A seed was laid on a sponge hole to induce seed germination and the growth of pakchoi seedlings. The sponge-containing seeds were placed in plastic containers filled up to 60% with water. Then, the seeds were grown in the FJB for 2 weeks under 100% white light (WL) at 26°C, under 60% relative humidity and 400 ppm CO2 (Fig. 3A). The seedlings were transplanted into a chamber of FJB after 2 weeks (Fig. 3B). Afterward, we performed three different light treatments to compare growth characteristics. The light treatments included i) 100% WL (control), ii) 70% WL, 20% BL, and 10% RL (T1), and iii) 50% WL, 30% BL, and 20% RL (T2). Each light source was applied for 10 hours daily.

    Determination of shoot and root phenotype

    The chlorophyll content (CC) was measured using a chlorophyll Meter (MC-100, Apogee Instruments Inc., USA), and VIs were measured using a vegetative index detector (RP410, Photon System Instruments, Czech Republic). Data were collected 2 weeks after transplantation. Within this period, every third leaf was selected in each plant. Further, the measurement of CC and VIs was taken for 6 days. The plants were harvested 6 weeks after their seeds were sown. Then, the plant was separated from the sponge, and the leaves were cut off from the roots. The fresh weights of the root and shoot were measured using a scale. The experiment was replicated six times (n = 5).

    Statistical analysis

    The SAS software (SAS release 9.4; SAS, Gary, NC, USA) was used to perform analysis of variance (ANOVA) on the quantitative data at p < 0.05, p < 0.01, and p < 0.0001 levels to determine statistical significance. Duncan's multiple range test was also used to compare the means between the treatments (p < 0.05). Data regression and graphical analysis were performed using Microsoft Excel 2016 and SigmaPlot 10.0 (Systat Software Inc., USA). The correlation among the VI, shoot, and root parameters was measured using the Pearson correlation test.

    RESULTS AND DISCUSSION

    Variance of phenotypes

    ANOVA test was performed to identify the effects of different compositions of control, T1, and T2 on pakchoi CC, root, and shoot growth. It was also used to measure the effect of the various compositions on VIs. The results of ANOVA are shown in Table 2. There was a significant difference between the different light treatments regarding CC and all other VIs. Further, there was a significant difference in the period of MCARI1 and OSAVI data collection. MCARI value only showed a significant difference for period x treatment. However, no significant difference was observed in RFW and SFW for different light treatments (Table 2). The replicate effects showed no significant differences for most VIs and RFW, except CC and SFW. This indicates that the experiment was conducted uniformly, and the treatment was controlled properly across parameters. It also implies that FJB could be the ideal platform to grow the vegetables under stable and uniform conditions, provided all parameters are accurately maintained.

    Effect of different light treatment on the CC, MCARI1, NDVI, OSAVI, SIPI, RFW, and SFW of pakchoi

    Until now, little attention has been given to studying the root, shoot growth, and plant physiology under different light combinations. Chlorophyll pigments absorb sunlight for energy to make carbohydrates using CO2 and H2O; hence, their quantities are strongly related to the primary production of food and energy (Gitelson et al., 2006). Moreover, chlorophyll helps measure leaf nitrogen due to the strong relationship between the quantity of leaf chlorophyll present and leaf nitrogen, which is an essential plant nutrient (Clevers and Kooistra, 2011). Furthermore, changes in leaf chlorophyll levels are associated with the impacts of disease, nutritional deficiencies, and environmental stresses (Sonobe and Wang, 2017). The CC is thus one of the most important indicators of photosynthetic activity among all biochemical variables. Therefore, CC levels were examined in our study.

    Our findings demonstrated that the different combinations of WL, RL, and BL affected the CC. According to Fig. 4A, CC increased from day 1 to day 6 in T1 and T2 compared with the control. Notably, T1 showed a highly significant increment in CC during the entire period compared with the control and T2 conditions. On average, CC significantly increased by 4% in T1 compared with the control. Previous studies have reported that different light sources enhance the accumulation of photosynthetic pigments like chlorophyll, carotenoid, and anthocyanins in baby leaf lettuce and green alga (Im et al., 2006;Lee et al., 2010). Similar results were recently reported by (Zheng et al., 2018;Huang et al., 2021) following their investigation of the red-leaf pakchoi under different BL intensities. Our results were consistent with the findings of Gu et al. (2019) and Huang et al. (2021). They demonstrated that RL promotes chlorophyll synthesis, whereas BL depletes the accumulation of chlorophyll. However, studies have shown that both RL and BL combinations were beneficial for the growth and morphology of pakchoi (Chen et al., 2017). These reports complement our findings, thus establishing the significance of our study.

    Visible and infrared light sources are employed to create the vegetation indices of simple ratio (SR), normalized difference vegetation index (NDVI), and green normalized vegetation index (GNDVI) (Gizaw et al., 2016). This would effectively distinguish minute changes in vegetative greenness and rate of senescence. VIs can determine the concentration of photosynthetic pigments, such as carotenoid and anthocyanin in the leaf. The concentration of these pigments indirectly determines the availability of photosynthesis. Thus, we examined the different VIs under different light compositions in pakchoi. Our findings indicated a significant increment in MCARI1 value of T1 and T2 over time compared with the control, except on day 2 of the study (Fig. 4B-E). The remaining VIs, NDVI, OSAVI, and SIPI also showed a similar trend of increment over the period (days 1–6) compared with the control (Fig. 4B-E). Recently, a relevant study reported hyperspectral imagings of variations in anthocyanin accumulations in leaf tissues of four different cultivars in pakchoi grown under different environmental conditions (Kim et al., 2021). However, there is a paucity of information on the use of VIs under different light compositions in pakchoi. Thus, we were unable to correlate our findings with those of previous studies. These results suggested that compared to WL alone, a combination of WL, RL and BL significantly enhanced the CC and influenced other tested VIs.

    RFW and SFW were measured at the end of the experiment (Fig. 5A, B). A slight increase in the RFW and SFW in T1 was observed, compared with control. However, a 25% and 23% increase in RFW and SFW, respectively, was observed in T1, compared with the T2 condition (Fig. 5A, B). Previous research demonstrated that different light intensity or sources influenced plant biomass, growth, and yield in various species (Smeets and Garretsen, 1986;Zhou et al., 2009;Lu et al., 2017;Viršilė et al., 2019;Spaninks et al., 2020). However, illuminance and intensity that affect one plant's growth and development may not have the same effect on another. Moreover, our results suggest that lower BL has a biological effect that is better than a higher intensity BL composition. This indicated that each plant has different optimal light environment. Additionally, there might be an influence of FJB and hydroponic conditions. Hence, it is advised that the future studies can explore other variables. Our research might be the first step toward advanced studies on pakchoi to examine how different light sources affect the plant under regular soil conditions, hydroponics, and FJB settings.

    Correlation between CC, RFW, SFW and VIs

    A correlation analysis was performed on CC, RFW, SFW, and VIs (Fig. 6). In the comparison between CC and VIs, CC showed a significantly positive correlation with MCARI1 (0.33**), NDVI (0.48***), OSAVI (0.51***), and SIPI (0.27*). In contrast, CC showed a negative correlation with RFW and SFW. NDVI showed a significantly positive correlation with OSAVI (0.74***), and SIPI (0.92***). OSAVI showed a positive correlation with SIPI (0.69***) and a negative correlation with RFW (–0.23*) and SFW (–0.25*). A positive correlation (0.76***) was observed between RFW and SFW. A similar correlation was reported for morpho-physiological traits of grafted tomato seedlings under different light treatments (Yousef et al., 2021). Except for SIPI, all other VIs showed a negative correlation with both RFW and SFW (Fig. 6). These findings suggested that NDVI and OSAVI can be used to predict CC; however, other VIs were unsuitable for predicting CC in pakchoi. In pakchoi, SFW is similar to the yield. Therefore, the prediction of SFW is associated with yield forecast. From this perspective, MCARI1 showed the most strong correlation with SFW. Hence, we believe that it is a promising index.

    CONCLUSION

    Artificial light sources are used in the glasshouses, greenhouses, and indoor farming. Considering that light is important for plant growth and development, it is essential to ascertain the best light source for optimum yield. Our findings revealed that BL and RL treatments influence pakchoi plant growth and morphology. Meanwhile, CC was increased at lower BL treatment than at higher BL. Although no significant change in plant SFW was observed in T1 during the tested periods. A significant reduction in RFW and SFW was observed in T2 compared with the control and T1. Thus, our findings are a reference point for further research, which will require an extended experimental period of growing pakchoi under various light combinations to obtain optimal growth results. According to correlation test, NDVI and OSAVI showed higher correlation with CC, thus this two Vis can be used to predict CC. In pakchoi, SFW means the yield. Therefore, the prediction of SFW is associated with yield forecast. From this perspective, MCARI1 showed the most strong correlation with SFW, thus we believe that it can be use to predict yield of pakchoi. In conclusion, we anticipate that growing pakchoi in hydroponics using smart farming FJB will promote plant growth, particularly for domestic consumption, and aid in meeting the increased demand for vegetables.

    ACKNOWLEDGMENTS

    We owe a debt of gratitude to Dr. Je Hyeong Jung. He made a very generous donation to FJB, which was highly appreciated. We also want to express our gratitude to Ms. Ndosiri Josepha Ngwangum for her assistance in data collection during the experiment.

    Figure

    KSIA-34-1-49_F1.gif

    A blueprint of the FJB growth chamber used for pakchoi growth. The red dotted line and arrow show environmental sensors, such as the fan, heatsink, camera, and sensors. The blue dotted line and arrow indicate parts of the hydroponic system, such as the nozzle, pump, and EC detector.

    KSIA-34-1-49_F2.gif

    Maximum light intensity and the peak wavelength of each LED light source.

    KSIA-34-1-49_F3.gif

    Seedlings and mature pakchoi in FJB. (A) The sponge and plastic container were used as the nursery. Seeds were directly propagated into the middle of the sponge block. Then, the seedlings were grown in the sponge into mature seedings. The nursery was kept in the FJB throughout the growing period. (B) Mature seedlings were transplanted into the plate cultivation hole in the FJB chamber. Each sponge block was directly put into the plate cultivation hole. Then, seedlings were allowed to grow throughout the experimental period.

    KSIA-34-1-49_F4.gif

    Comparison of different light composition effects on the chlorophyll content (CC) and vegetation indices. Abbreviations presented in the figure are CC, modified chlorophyll absorption in reflectance index (MCARI1), normalized difference vegetation index (NDVI), optimized soil-adjusted vegetation index (OSAVI), and structure insensitive pigment index (SIPI). Data presented are mean values with SD (n = 5 for panels A–E). Different letters on bars indicate a significant difference (p < 0.05) between different light treatments (Duncan’s multiple range tests).

    KSIA-34-1-49_F5.gif

    Comparison of different light composition effects on root and shoot growth of pakchoi. (A) Root fresh weight (RFW). (B) Shoot fresh weight (SFW). Data presented are mean values with SD (n = 5 for panels A and B). Different letters on bars indicate a significant difference (p < 0.05) between the different light treatments (Duncan’s multiple range tests).

    KSIA-34-1-49_F6.gif

    Correlation analysis for all pairs of variables to read from the diagonal. The upper part of the figure represents the corresponding Pearson correlation coefficient, with the absolute text value along with the significance level. The lower side of the figure represents scatter plots and smoothing splines for each possible pairing. Abbreviations presented in the figure: chlorophyll content (CC), modified chlorophyll absorption in reflectance index (MCARI1), normalized difference vegetation index (NDVI), optimized soiladjusted vegetation index (OSAVI), structure insensitive pigment index (SIPI), root fresh weight (RFW), and shoot fresh weight (SFW). The correlation analysis was tested against the null hypothesis and asterisks indicate a significant difference using the resulting p-value (*:0.01 < p < 0.05; **: 0.001 < p < 0.01; ***: p < 0.0001).

    Table

    Light intensity at 30 cm distance from LED light source.

    Composition of the hydroponic system.

    Analysis of variance of CC, various VIs, root, and shoot parameters of pakchoi for the three treatments.

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