Rosmarinic acid (RA) is a phenolic antioxidant naturally occurring in the plants of the Lamiaceae family, including basil (Ocimum basilicum L.). Existing analytical methods for determining the RA content in leaves are time-consuming and destructive, posing limitations on quality assessment and control during cultivation. In this study, we aimed to develop non-destructive prediction models for the RA content in basil plants using a portable hyperspectral imaging (HSI) system and machine learning algorithms. The basil plants were grown in a vertical farm module with controlled environments, and the HSI of the whole plant was captured using a portable HSI camera in the range of 400–850 nm. The average spectra were extracted from the segmented regions of the plants. We employed several spectral data pre-processing methods and ensemble learning algorithms, such as Random Forest, AdaBoost, XGBoost, and LightGBM, to develop the RA prediction model and feature selection based on feature importance. The best RA prediction model was the LightGBM model with feature selection by the AdaBoost algorithm and spectral pre-processing through logarithmic transformation and second derivative. This model performed satisfactorily for practical screening with R2P = 0.81 and RMSEP = 3.92. From in-field HSI data, the developed model successfully estimated and visualized the RA distribution in basil plants growing in the greenhouse. Our findings demonstrate the potential use of a portable HSI system for monitoring and controlling pharmaceutical quality in medicinal plants during cultivation. This non-destructive and rapid method can provide a valuable tool for assessing the quality of RA in basil plants, thereby enhancing the efficiency and accuracy of quality control during the cultivation stage.

The growing interest in healthy diets has driven the demand for food ingredients with enhanced health benefits. In this study, we aimed to explore a method to enhance the bioactivity of kale using a home vertical farming appliance. Specifically, we investigated the effects of treating kale with a green tea water extract (GTE; 0.1–0.5 g/L in nutrient solution) for two weeks before harvest during five weeks of kale cultivation. GTE treatment did not negatively affect the key quality attributes, such as yield, semblance, or sensory properties. However, it led to the accumulation of bioactive compounds, epicatechin (EC) and epigallocatechin gallate (EGCG), which are typically absent in kale. In the control group, no catechins were detected, whereas in the GTE-treated group, the concentration of EC and EGCG were as high as 252.11 and 173.26 μg/g, respectively. These findings indicate the successful incorporation of catechins, known for their unique health-promoting properties, into kale. Additionally, GTE treatment enhanced the biosynthesis of glucosinolates, which are key secondary metabolites of kale. The total glucosinolate content increased from 9.56 μmol/g in the control group to 16.81 μmol/g in the GTE-treated group (treated with 0.5 g/L GTE). These findings showed that GTE treatment not only enriched kale with catechins, the primary bioactive compounds in green tea but also increased the levels of glucosinolates. This study, conducted using a home vertical farming appliance, suggests that bioactivity-enhanced kale can be grown domestically, providing consumers with a nutrient-fortified food source.

Artemisia annua L. is a well-known therapeutic herb that is widely used in folk medicine in Asian and African countries. A. annua can alleviate fever, wounds, and inflammation and is also popular as an anti-malarial agent. Cu and Zn are essential nutrients for human wellness and are vital to plants; they sometimes act as elicitors and induce stress mechanisms in plants to stimulate the production of secondary metabolites, which have bioactivities. Therefore, we added Cu or Zn to a nutrient solution and cultivated A. annua to enhance the Cu or Zn content. The Cu or Zn treatment during A. annua cultivation elevated their accumulation, and Zn showed a dramatic accumulation level in harvests. The aerial part of Zn16X contained 35 times higher Zn content than that of the control. Although the Cu or Zn contents were elevated, the plant height and yield were not affected, indicating the absence of toxic effects. The Cu or Zn treatment decreased the artemisinin content; however, these treatments increased the amounts of phenolic acids and flavonoids in A. annua. In particular, Zn4X showed a notable increase in the phenolic acids and flavonoids amounts. Moreover, the contents of certain types of caffeoylquinic acids were also highly elevated in Zn4X. Overall, Cu or Zn treatment in A. annua increased Cu or Zn accumulation and stimulated phenolic acid and flavonoid synthesis, which may have enhanced the therapeutic efficacy of A. annua.

Many studies have examined how various cultivation methods and elicitors elevate target crop values. Post-harvest treatments, such as the drying method, may alter the final product’s characteristics. We investigated the effect of nutrient solution concentration during the hydroponic cultivation and drying method (cold air drying and freeze drying) after harvesting Agastache rugosa Kuntze, an herb used for folk medicine and as a deodorant, spice, and tea in East Asia. To explore the properties of A. rugosa, we determined its growth parameters, secondary metabolites, and photoprotective effects. We observed the highest growth and yields in A. rugosa grown under 4.0 dS·m−1 electrical conductivity (EC) conditions. However, the EC 2.0 group showed higher antioxidative properties than those grown in EC 1.5 and 4.0 conditions. Drying conditions varied the content and ratios of major active compounds (rosmarinic acid, tilianin, and acacetin) in A. rugosa. Cold air drying caused rosmarinic acid transmutation to tilianin and acacetin, and tilianin showed a stronger positive correlation with antioxidative and photoprotective activities than rosmarinic acid. The increased tilianin content in cold-air-dried A. rugosa accompanied the improved photoprotective effects in dermal cell lines. This study reveals the effects of cultivation and drying methods in A. rugosa production, and proposes alternate industrial production techniques.

The integration of hyperspectral imaging with machine learning algorithms has presented a promising strategy for the non-invasive and rapid detection of plant metabolites. For this study, we developed prediction models using partial least squares regression (PLSR) and boosting algo-rithms (such as AdaBoost, XGBoost, and LightGBM) for five metabolites in Brassica juncea leaves: total chlorophyll, phenolics, flavonoids, glucosinolates, and anthocyanins. To enhance the model performance, we employed several spectral data preprocessing methods and feature-selection al-gorithms. Our results showed that the boosting algorithms generally outperformed the PLSR models in terms of prediction accuracy. In particular, the LightGBM model for chlorophyll and the AdaBoost model for flavonoids improved the prediction performance, with R2p = 0.71–0.74, com-pared to the PLSR models (R2p = 0.53–0.58). The final models for the glucosinolates and anthocya-nins performed sufficiently for practical uses such as screening, with R2p = 0.82–0.85 and RPD = 2.4–2.6. Our findings indicate that the application of a single preprocessing method is more effective than utilizing multiple techniques. Additionally, the boosting algorithms with feature selection ex-hibited superior performance compared to the PLSR models in the majority of cases. These results highlight the potential of hyperspectral imaging and machine learning algorithms for the non-destructive and rapid detection of plant metabolites, which could have significant implications for the field of smart agriculture.

This study aimed to develop a research-use plant growth chamber from which plant researchers can easily acquire data and in which plants can be effectively grown by improving the sealing and control performance of the plant grower. The low-cost plant growth chamber presented in this paper enables control of internal temperature, LED lighting, and aeroponics and features easy remote operation using open-source technology. Furthermore, it can apply a prediction model for the area and fresh weight using canopy images. We also demonstrated that the small enclosed plant grower could provide the opportunity to improve the efficiency and reproducibility of plant growth for various research aims. When used in plant-growth tests, the manufactured prototype achieved over 600 µmol m−2 s−1 photosynthetic photon flux densities (PPFD) and internal temperatures satisfying day/night temperature of 21/17 °C, demonstrating its applicability to grow various plants. Moreover, we confirmed that the sensor and image data storage, download functionality, and image analysis operated normally. This prototype is advantageous for researchers who have difficulty investing in commercial phenotype equipment and facilitates access to phenotype data processing through a programming approach using canopy images. In the future, as hardware manufacturing costs continue to drop and performance improves, the proposed prototype provides the potential for plant science researchers to utilize creative application programs, systematic experimental design, and shared datasets and code.

Kale is a prominent leafy vegetable because of its high content of bioactive compounds and various health benefits. Microalgae have been suggested as a biostimulator that can replace chemical fertilizers by enhancing crop yield and supporting soil carbon sequestration. In this study, the effect of Chlorella vulgaris as a plant biostimulant on the growth and secondary metabolite contents of "Red Russian" kale (Brassica napus var. Pabularia) with green leaves and purple veins has been demonstrated. Three Chlorella treatments were used: CS, C. vulgaris suspension; CB, C. vulgaris biomass; and CFS, filtered C. vulgaris-free supernatant. The plant growth rates, phytochemical contents, and individual glucosinolate and anthocyanin contents were determined. There was no significant difference under the CS and CB treatments, while CFS negatively influenced on kale growth with 37% reduction of dried weight. In contrast, metabolite production differed according to Chlorella treatments. Total contents of chlorophyll and carotenoid were increased by 1.57 and 1.41 folds by CS treatment, whereas total contents of phenol and flavonoids were enhanced by 1.30 and 1.22 folds by CFS treatment. Totally, seven glucosinolates and four anthocyanins were characterized and quantified individually. Notably, CFS treatment increased gluconasturtiin and all anthocyanins the most, 10.28-fold and 5.90-fold, respectively.

Red beet (Beta vulgaris L.) is a root vegetable consumed and cultivated all around the world. It contains plenty of sugars, inorganic ions and a variety of secondary metabolites known to improve human health. The aim of this work was to investigate the effect of light spectra on red beets and their components in a vertical farm (VF) compared to open field (OF). RED (red:blue-white = 4:1)-treated shoots elevated total phenolic contents (TPC) among lights. Sugar content in VF red beets was 4.2 times higher than beets from OF. Betalains in VF red beets were 2.4–2.8 times higher than OF ones, and RED-treated roots had significantly higher betalain levels compared to CON (red:blue-white = 2:1)-treated ones. VF red beets contained a higher level of inorganic nitrates and lower chloride compared to OF beets. In conclusion, the light spectrum alters the concentration of beet components to be higher than that of OF red beets, and RED light elevated TPC, sugars and betalains.

Partial least squares regression (PLSR) prediction models were developed using hyperspectral imaging for noninvasive detection of the five most representative functional components in Brassica juncea leaves: chlorophyll, carotenoid, phenolic, glucosinolate, and anthocyanin contents. The region of interest for functional component analysis was chosen by polygon selection and the extracted average spectra were used for model development. For pre-processing, 10 combinations of Savitzky–Golay filter (S. G. filter), standard normal variate (SNV), multiplicative scatter correction (MSC), 1st-order derivative (1st-Der), 2nd-order derivative (2nd-Der), and normalization were applied. Root mean square errors of calibration (RMSEP) was used to assess the performance accuracy of the constructed prediction models. The prediction model for total anthocyanins exhibited the highest prediction level (RV2 = 0.8273; RMSEP = 2.4277). Pre-processing combination of SNV and 1st-Der with spectral data resulted in high-performance prediction models for total chlorophyll, carotenoid, and glucosinolate contents. Pre-processing combination of S. G. filter and SNV gave the highest prediction rate for total phenolics. SNV inclusion in the pre-processing conditions was essential for developing high-performance accurate prediction models for functional components. By enabling visualization of the distribution of functional components on the hyperspectral images, PLSR prediction models will prove valuable in determining the harvest time.

Lemon balm (Melissa officinalis L.) is a popular herb used as an aromatic and medicinal resource as well as a herbal tea. Due to a lack of information on the hydroponic growth of lemon balm, three hydroponic systems (artificial soil bed, perlite bed, and aeroponic) that could be applied to industrial production were tested in the present study. In this context, the growth parameters, mineral contents, color traits, anti-oxidative capacities, and phenolic compounds of lemon balm were analyzed. As a result, the three types of systems assessed showed similar yields and even compared to previous studies. However, the soilless cultivation system (perlite and aeroponic) showed increased nitrate content but decreased the chlorine mineral content. In addition, they showed lowered total phenolic acid content and radical scavenging capacity, which was associated with decreased rosmarinic acid and lithospermic acid A, the major phenolic compounds in lemon balm. Conversely, the caffeic acid and methyl rosmarinate content increased by 6?8 times in soilless cultivation system compared to soil-based conditions. In conclusion, the hydroponic cultivation methods used in this study could be applied to the industrial production of lemon balm with yields and qualities consistent with traditional growth conditions. In addition, soilless hydroponic systems could be used to produce specified lemon balm rich in caffeic acid and methyl rosmarinate.

The urban hydroponic production system is accelerating industrialization in step with the potentials for reducing environmental impact. In contrast, establishing sustainable fertilizer dosing techniques still lags behind the pace of expansion of the system. The reproducibility of root-zone nutrient dynamics in the system is poorly understood, and managing nutrients has so far primarily relied on periodic discharge or dumping of highly concentrated nutrient solutions. Here, we assayed root-zone nutrient concentration changes using three possible nutrient dosing types. Three Brassica species were hydroponically cultivated in a controlled environment to apply the nutrient absorption and transpiration parameters to the simulation analysis. We found that nutrient dosing based on total ion concentration could provide more reproducible root-zone nutrient dynamics. Our findings highlight the nutrient absorption parameter domain in management practice. This simplifies conventional nutrient management into an optimization problem. Collectively, our framework can be extended to fertilizer-emission-free urban hydroponic production.

The effect of salt treatment on Brassica carinata (BC) microgreens grown under different light wavelengths on glucosinolates (GLs) and phenolic compounds were evaluated. Quantifiable GLs were identified using ultra-high performance-quadrupole time of flight mass spectrometry. Extracts' ability to activate antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)) was evaluated on human colorectal carcinoma cells (HCT116). Furthermore, BC compounds' ability to activate expression of nuclear transcription factor-erythroid 2 related factor (Nrf2) and heme-oxygenase-1 (HO-1) proteins was examined using specific antibodies on HCT116 cells. Sinigrin (SIN) was the abundant GLs of the six compounds identified and its content together with total aliphatic GLs increased in saline conditions. Fluorescent (FL) and blue plus red (B1R1) lights were identified as stable cultivation conditions for microgreens, promoting biomass and glucobrassicin contents, whereas other identified individual and total indole GLs behaved differently in saline and non-saline environments. Blue light-emitting diodes and FL light in saline treatments mostly enhanced SIN, phenolics and antioxidant activities. The increased SOD and CAT activities render the BC microgreens suitable for lowering oxidative stress. Additionally, activation of Nrf2, and HO-1 protein expression by the GLs rich extracts, demonstrate their potential to treat and prevent oxidative stress and inflammatory disorders. Therefore, effective salt treatments and light exposure to BC microgreens present an opportunity for targeted regulation of growth and accumulation of bioactive metabolites.

The production of low potassium vegetables arose out of the dietary needs of patients with renal dysfunction. Attempts have been made to reduce potassium content in vegetables and fruits; however, induced potassium deficiency has often resulted in decreased yields. Here, we investigated a new method of producing low potassium kale and present the characteristics of the resulting produce. By substituting potassium nitrate with calcium nitrate in the nutrient solution 2 weeks before harvesting, the potassium content of kale was reduced by 70% without a deterioration in yield and semblance qualities. Despite no relationships being detected between potassium deficiency and anti-oxidative properties, the total glucosinolate content, an indicator of the anti-cancer effect of cruciferous vegetables, was significantly increased by potassium deficiency in kale. This study demonstrates a novel method of producing low potassium kale for patients with renal failure, without a reduction in yield but with beneficial increase in glucosinolates.

Glucosinolates (GLs), found in Brassicaceae family, are precursor metabolites with anti-cancer properties. Increased GLs have been studied under various environmental growth conditions. Pak choi (Brassica rapa subsp. chinensis) is a GL-rich vegetable. We hypothesize that long exposure to light and drought will increase the biomass of, and GL production in, pak choi. The experiment was conducted for 6 weeks. Long light exposure (20 h/day) increased, whilst drought exposure (12 h/week) decreased the plant growth. The plants exposed to a combination of drought and long light conditions showed similar growth pattern as control plants. GL production increased at week 6 in plants exposed to long light, while drought exposure had no impact on GL production, with the exception of glucoraphanin. Significant positive correlations were observed between plant growth and GL yield with accumulated light exposure time. Our findings suggest that long exposure to light can be used to increase both the biomass and GL production in pak choi.

Ginsenosides are a class of natural product steroid glycosides and triterpene saponins with great therapeutic value. Although ginseng berries contain 4-10 times more ginsenosides than ginseng roots, a sustainable method has been established for ginseng root production but not for ginseng berry production. We elucidated the best conditions for stable berry production by cultivating four-year-old ginsengs on a developed vertical farm (VF) platform in a 3-level stereoscopic facility. Ginseng was cultivated in soil in mesh containers in three levels of cultivation shelves (W 0.85 m x D 4.80 m x H 1.15 m) installed in a cultivation room (W 5.88 m x 10.00 m x H 6.00 m). Each plant produced approximately 15 berries (3 g) in the VF, which is as many as those produced by plants in open fields (OF). Ginsenoside Rg1 and syringaresinol levels were higher in the berries from the VF than in those from the OF. In contrast, levels of total ginsenosides Rc, Rb2, and Rd were lower in berries from the VF than in those from the OF. Further, the levels of ginsenoside Re (major ginsenoside in ginseng berries from VF) were similar in the VF and OF. This difference in chemical composition can be attributed to the less variable environmental conditions in the VF compared to the OF. Berry yield strongly correlated with stem diameter and root weight. We thus conclude that this VF platform could be used to produce as many ginseng berries as an OF would produce. Additionally, it could be used for year-round production, thus enabling constant supply of therapeutically useful ginseng berries.

Lactuca indica L. has been traditionally used as a wild vegetable and as a medicinal plant for centuries. The various compounds present in it and their biological activities have been extensively reported. Hairy-root culture combined with agrobacterium-meditated metabolic engineering is a useful technique to achieve stable production of biologically active plant compounds. Here, we evaluated the enhancement of secondary metabolites in L. indica L. and their bioactivities by testing culture media composition and the use of an elicitor. Hairy roots were induced and cultured in MS or SH liquid media for 2 weeks prior to treatment with various concentrations of MeJa, for different periods. The resulting phenolic contents and physiological activities were analyzed. Higher total phenolic, flavonoid, and hydroxycinnamic acids contents were attained by elicitation with MeJa. Metabolite accumulation, especially in SH media and in the presence of MeJa, was time dependent. Particularly, accumulation of chicoric acid increased markedly with time. Similarly, we observed time dependent positive and negative responses of antioxidant activity in DPPH and ABTS assays, respectively. As in previous studies, the highest correlation was found between total phenolic content and total flavonoid content. Further, 3,5-DCQA showed the highest correlation with total phenolic content, total flavonoid content, and antioxidant activities in hydroxycinnamic acids. Our data effectively identified optimal culture conditions to increase the accumulation of secondary metabolites and antioxidant activity in hairy roots cultures of L. indica L.

A plant factory is a closed cultivation system that provides a consistent and modified environment for plant growth. We speculated that treatment of kale (Brassica oleracea) grown in a plant factory with NaCl, Na2SeO3, or both would increase the bioactive phytochemical levels including glucosinolates (GLSs) and isothiocyanates (ITCs), the key molecules in cancer prevention. The kale was harvested and analysed after treatment with NaCl and Na2SeO3 alone or in combination for 1 or 2 weeks. Exposure to NaCl alone but not Na2SeO3 increased plant root growth. Levels of sinigrin were increased by a 2-week exposure to Na2SeO3 alone or in combination with NaCl, whereas no changes were observed in glucoraphanin and gluconasturtiin gluconasturtiin levels. Importantly, the ITC concentration was affected by 2-week treatment with both compounds. To evaluate the bioactivity of kale, HepG2 human hepatoma cells were treated with plant extract for 6 h. Only the extract of kale roots exposed to a combination NaCl and Na2SeO3 for 2 weeks showed an increased expression of nuclear factor erythroid 2-related factor (Nrf2), which regulates genes encoding antioxidant proteins. These data suggest that co-treatment with NaCl and Na2SeO3 increased the ITC content and chemopreventive effects of kale root.

Recently, plant factory related businesses are increasing because of abnormal climate and natural disasters. Various industries have entered the plant factory business with new cultivating techniques. Various attempts are being made to produce high value crops with research and development of various cultivating techniques. Additionally in the plant factory business, large-scale production, automation and labor-saving are also important for establishing a sustainable industry. Therefore, several techniques have been utilized to improve the use of space, application of automation, and productivity in the plant factory.

An ultrasonic pollination device was developed to achieve effective artificial pollination of strawberries in artificial light type plant factories. A phase array of hundreds of ultrasonic transducers was appropriately controlled and focused on one point in space, and it is possible to generate a force at any position in space. The force was modulated at 30 Hz which is the characteristic frequency of strawberry flower. The pollination experiment was conducted using the strawberry variety F1 Elan (Fragaria×ananassa). The total weight of the strawberries harvested over 22 days was 1.22 kg, and the average weights of individual strawberry fruits were 9.1 g.

This study focuses on generating and controlling air flow caused by temperature differences and increasing the greening rate in urban areas by means of biowalls. In this study, computational fluid dynamics (CFD) software and an artificial neural network (ANN) inverse model were used to study generating and controlling air flow. First, an ANN inverse model was trained and tested using the data obtained from the CFD simulation. Then, the trained ANN inverse model recommended greening patterns to generate the desired air flow. Finally, a model study was conducted under similar conditions on the greening patterns recommended by the ANN inverse model. The most highly recommended greening pattern was whole-greening, in which the average temperature of 35.5°C would generate ascending air flow at a rate of 0.3 m • s−1. Wind velocity in the model study of a whole-greening pattern in which average temperature was 33.8°C, was 0.29 m • s−1 which is close to the desired wind velocity in the ANN inverse model. This result shows that it is possible to generate and control air flow near bio-greening caused by temperature differences, and this method which used CFD simulation and ANN inverse model is applicable.