Controlling irrigation in a container nursery using IoT

1.   Introduction

Stevia rebaudiana Bertoni, is a herbaceous perennial plant species that belongs to family Asteraceae and is native to specific regions from South America, specifically to Brazil and Paraguay ^[1]. Currently stevia cultivation has been extended to other regions of the world including Argentina, China, Japan, Korea, Mexico, Paraguay, Indonesia, Russia, USA, Tanzania, Canada, Malaysia, and Thailand ^[2,3,4]. Steviol glycosides are specialized metabolites that are only produced by Stevia rebaudiana, which makes it different from other plants ^[5]. It has been reported that some steviol glycosides (SGs) produced by Stevia are 300-400 times sweeter than common table sugar ^[6,7], and these SGs are non- caloric. This does not have any effect on the body blood glucose level, making it a beneficial sweeter to be used by diabetic patients throughout the world ^[7,8]. Different plant organs have different concentration of SGs; however, plant leaves have been reported with the most abundant concentrations of steviosides as well as other types of SGs. Until now 30, SGs has been reported; however, steviosides have found to be the major SGs (4–13% w/w) with Rebaudioside A (2–4% w/w), Rebaudioside C (1–2% w/w) and, Dulcoside A (0.4–0.7% w/w) within concentrations in Stevia rebaudiana ^[3,9]

In addition to its sweetening capability, Stevia rebaudiana has been found to be anti-inflammatory, antihypertensive, anti-hyperglycemic, anti-diarrheal, anti-tumor, a diuretic, and immunomodulatory through its specialized metabolites ^[10,11,12]. Reactive oxygen species (ROS) generation has been linked to cause a several type of diseases including, cardiovascular disease, cancer, diabetes, arthritis, neurological disorders, and aging. ROS production can further lead to the damage of certain tissues and cause cell death. Many compounds from different plants have been identified to be ROS scavengers and have favorable pharmacological effects. Stevia leaf extracts are reported to be rich in high levels of compounds with an ROS scavenging activity (13). Numerous phenolic compounds have been identified in dry matter from stevia leaves among other constituents. That suggests that Stevia rebaudiana leaf extracts can be utilized as a natural source of antioxidants along with zero-caloric sweeteners, thus potentially benefiting the consumers' health ^[4,13].

The earth's climate has been drastically changed due to human activities since the pre-industrial revolution. The earth's temperature is consistently increasing thus causing global warming due to increasing concentrations of greenhouse gases such as CO₂, CH₄, N₂O, etc. in the atmosphere, which trap the sun rays ^[14,15,16]. The massive generation of greenhouse gases from the quickly expanding industrial and residential sectors, have caused environmental contamination ^[17,18]. Environmental pollution has caused the concentration of CO₂ in the atmosphere to rise to 408 (ppm), from 280 (ppm) at the beginning of the twentieth century before the industrial revolution ^[19]. The Intergovernmental Panel on Climate Change (IPCC) indicted that the CO₂ concentration will cross 1000 (ppm) before the end of this century (19). There will be both positive and negative effects on major agriculture crops with the elevation of CO₂ in the atmosphere. It has been suggested by a number of studies that elevated CO₂ level will positively enhance photosynthesis, which subsequently have positive effect on plants such greater growth, higher above and belowground biomasses and higher yield ^[20,21,22]. On the other hand, it has been reported by several authors that elevated CO₂ level can have some negative effect on plants, which may have some serious consequences on the quality of different crop species such as declines in certain nutrients along with the protein concentration, some macro-micro elements and vitamins ^[23,24,25]. Due to the adverse effects, it is important to understand the plant response to the elevated level of CO₂ in detail.

The specialized metabolites in plants dramatically changes with both the temperature and CO₂ ^[26,27,28]. Some biogenic volatile organic compounds are seen to show an increased production under a high temperature ^[28,29,30]. Generally, elevated CO₂ level enhances the biosynthesis of phenolic compounds in plants; however, the response is specific from species to species ^[31,32]. The rate of photosynthesis in the plants is mainly controlled by two biochemical process: carboxylation and oxygenation ^[33]. In addition to the increasing RuBisCO activity to enhance photosynthesis, elevated atmospheric CO₂ level also change partitioning of the photoactivities for the synthesis of plant specialized metabolites. Furthermore, higher CO₂ levels raise the non-structural carbohydrate concentrations, which may encourage the plants' secondary metabolism ^[34,35]. Abzar et al. (2024 ^[36]) reported that steviosides and rebaudiosides were increased under eCO₂ in comparison to aCO₂. However, the research was solely focused on short- and long-term CO₂; none of the research was performed on different plant densities under eCO₂.

In addition to environmental conditions, additional agronomic methods, such as plant density, are crucial for an increased productivity because they provide equal opportunities for plant survival and the most efficient use of other inputs. The plant density and spacing significantly affect the quality and quantity of the plant's production ^[37,38], as well as other important agronomic attributes of the crops. Plant spacing is a non-fiscal agronomical practice which plays a key role in determining the dimensional distribution of plants, which may affect the structure of the canopy, light interception, and efficiency in using radiation and, accordingly, crop biomass production. The ideal plant density for a crop greatly varies based on the soil's fertility and the growing region's climate ^[39]. Leaf photosynthesis increases with a narrow row spacing and puts down weed growth by the stifling effect as compared with broader row spacing ^[40]. During the growing stage of crops, when photosynthesis produces the carbohydrates for the economic product, crops should fully intercept the sun radiation to generate the largest output per unit area ^[41,42]. For most crops, an increased plant population generally results in a higher biological yield per unit of land area up to a specific upper limit or threshold. A Planting density beyond the limit either causes the yield to drop or to maintain its current level.

Different species perform differently to the planting density in terms of the production and the efficient utilization of the available resources ^[43,44]. Hence, it is critical to understand the relationship between the crops and the planting density for a better production while utilizing the resources equally. Several authors have reported that planting density/spacing significantly increases yield attributes and biomass production of dry leaves ^[45,46,47].

In Japan by utilizing different planting densities (40000-400000) it was found that the yield obtained from stevia leaves increased with a high-density planting (83000-111000 plants Ha⁻¹) ^[48]. Taleie et al. 2012 ^[47] reported that the transplanting date and planting density showed significant effects on the fresh and dry weights of the leaves, and plant height, and the concentrations of phenol and flavonoid. Annual stevia crops grown under mid-hill conditions of the north-western Himalayas showed better performances in terms of the leaf dry biomass at a narrow spacing compared with a wider spacing ^[49]. In contrast, Kumar et al. 2014 ^[48] reported that different planting densities did not affect the steviol glycosides. In addition to the above finding, several studies have reported that dry leaves weight obtained from Stevia grown under wider spacing was significantly higher than plants grown in a narrow spacing ^[50,51]. The ideal plant density for stevia greatly varies depending on the climate and soil fertility of the growing region. The impact of an increased CO₂ and plant spacing on stevia growth, steviol glycoside content (%), and biomass output has not been well studied. Stevia in Malaysia is not very popular, and its fundamental agronomy and growth requirements are not well known to most farmers and large-scale producers. Considering the potential of Stevia, the present study was planned with the objective of determining the effect of elevated CO₂ levels under different planting densities on stevia growth and development under Malaysian environmental conditions.

2.   Materials and methods

2.1.   Experimental site and planting materials

Glasshouse conditions were used to conduct the current experiment. The glasshouse is located Putra Agriculture Center (PAC), University Putra Malaysia (UPM), Serdang, Selangor and Tenaga National Berhad Research (GHTNBR), Kawasan Institusi Penyelidikan, Jalan Ayer Itam, Kajang, Selangor. A glasshouse with elevated CO₂ levels was constructed in such a way that plants could receive a 12h photoperiod and an average photosynthetic photon flux density of 330 μmol m⁻² s⁻¹. CO₂ cylinders were used to provide 99.8% pure CO₂ and was continuously applied from 8:00 to 10:00 a.m. through a pressure regulator- into the fully sealed 5 m × 3.67 m greenhouse. Air sense CO₂ sensors designated to each chamber were used to measure the CO₂ concentrations during the CO₂ exposition period. The CO₂ level increased once after two weeks from 400 ppm to a maximum of 1200 ppm by adding 400 ppm each time. The greenhouse was equipped with dripped fertigation for irrigation purposes. The seedlings were prepared from stem cuttings. The seedlings with height of 7–8 cm were transferred to a medium that contain coco-peat without soil in 16 cm × 16 cm size (16 × 16) of polyethylene bags. The day and night temperatures were maintained from 27–35 ℃ and 18–21 ℃, respectively. The relative humidity was maintained from 50% to 60%. To allow for plant growth under their natural environment, the stevia plants were grown under 50–60% shade (light intensity 225 ± 50 μmol m⁻² s⁻¹) using black netting.

2.2.   Experimental setup

The current experiment used a nested design with randomized complete block design (RCBD) in four blocks. A factorial (2 × 3) arrangement, representing two CO₂ levels (elevated CO₂ (1200 ppm) and ambient CO₂ (400 ppm) with three planting densities- High Density Vertical (HDV) 78 plants/meter square, High density horizontal (HDH) 25 plants/meter square and Low density horizontal (LDH) 12 plants/meter square- was established for the experiment. Factor A (CO₂) was applied across the block, while the densities were nested in Factor A (CO₂) under ambient and elevated CO₂ (Figure 1).

Figure 1.  Plant material and cultivation method. [Notes. (A) Represents Plant material, (B) HDV, (C) LDH, (D) HDH.].

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2.3.   Biomass analysis

The biomass was evaluated at the 2^nd, 3^rd, and 4^th month after planting. Plants from each block were manually cut for the biomass analysis. The plants were carefully separated from the soil to measure the plant biomass. To measure dry weight for the canopy and roots (biomass), the plants were dried in an oven at 70 ℃ for 48 hours, and the canopy and root biomasses were measured in kilograms (kg). The total shoot and root dry weight were converted into ton/ha using the undermentioned formula suggested by Garibaldi, 2012 ^[52]. The plant base weight was calculated and multiplied by the number of plants per meter to obtain the weight of the total plant per square meter area.

In the above formula, the biomass obtained in kg/m was divided by 1000 and multiplied by 10000 to convert into tons per hectare (t/ha).

2.4.   Extraction and analysis of steviol glycosides

Healthy and fresh leaves were collected from the plants and washed under running tap water to extract the steviol glycosides. After washing, the leaves were dried in a hot air oven at 40 ℃ until they reached a consistent weight. Afterwards, a filtrate from the leaves was made, and the SGs were measured using a Waters high-performance liquid chromatography system (996 Photodiode Array Detector). For the extraction process, 10 mL of methanol was used to soak 100 mg of ground leaf sample in a hot water bath at 70 ℃ overnight to extract the steviosides and rebaudioside A then, the mixture was filtered through filter paper. N-hexane was used to help in the extraction of the fats from the sample after the filtrate dried under a low pressure. After the fat extraction process, the extract was dissolved in 10 mL of a HPLC-graded acetonitrile and water (8:2) mobile phase, and was subsequently filtered through a micro filter with a pore diameter of 0.45 m. Steviosides and Reb-A were quantified using standard samples to create standard curves. The HPLC was calibrated with steviosides and rebaudioside A standard (200,400,600,800, 1000, and 1200 μg/mL). The standards for steviosides and rebaudioside A were obtained from Wako Pure Chemical, Japan Pty. Ltd. To maintain the rest of the working conditions of the instrument, the methods from Pal et al. 2015b ^[53] were followed.

2.5.   Determination of total phenolic content (TPC)

The total phenolic content of the plant extract was determined according to the method reported by Alothman et al. 2009 ^[54] using the Folin–Ciocalteu reagent with some modifications. Five grams of fresh stevia leaves were harvested from all the treatments. To remove any debris and dust, the leaves samples were washed and cleaned under running tap water. The leaves samples were ground using a mortar and pestle to make a fine powder for the samples. After making a fine powder, the samples were mixed with 20 mL of 80% methanol and covered with aluminum foil. The mixture was placed in an orbital shaker for one hour. An aqueous extract was obtained by filtering the mixture using cotton wool and was used for further analyses. A 200 μL extract was added to a 10% Folin Ciocalteu phenol regent, and the mixture was thoroughly mixed. The mixture was incubated for five minutes. After five minutes, 800 μL of a 7.5% Sodium Carbonate (Na₂CO₃) solution was added. The mixture was incubated for 30 minutes at room temperature under dark conditions. The absorbance of the mixture was measured at 765 nm using a spectrophotometer (Fisher Thermo Scientific, Multikan Go, UK). The measurement of total the phenolic content was repeated in triplicate. The total phenolic content was expressed as mg Gallic acid equivalents (GAE) mg/g of fresh sample by using an equation obtained from the Gallic acid calibration curve.

2.6.   Determination of total flavonoid content (TFC)

The total Flavonoid content of the plant extract was measured according to colorimetric assay reported by Alothman et al. 2009 ^[55] with slight modifications. The extract from the leaf sample was prepared in a similar manner for TPC experiment. One mL of the extract was transferred into the test tube, and the following solutions were added to it: 0.3 mL of the sodium nitrate solution instantly, 0.3 mL of a 10% Aluminum chloride (AlCl₃) at five minutes, and 2 mL of Hydroxide at 6 minutes. The final volume was made up to 10 mL by adding distilled water. Finally, the mixture was mixed thoroughly, and the absorbance was measured using a spectrophotometer (Fisher Thermo Scientific, Multikan Go, UK) at 510 nm. The results were expressed as mg quercetin equivalents (QUE) mg/g of fresh sample. All samples were analyzed in triplicate, and the results were averaged.

2.7.   DPPH free radical-scavenging assay

Stevia's antioxidant capacity was studied by evaluating the free radical-scavenging effect on the 1, 1-diphenyl-2- picrylhydrazyl (DPPH) radical. The determination was assessed using the procedure reported by Sultana et al. 2008 ^[56] with slight modifications. Three grams of fresh samples were extracted with 25 mL of 80% ethanol using a homogenizer in an ice bath. The homogenate was centrifuged at 15,000 rpm and 4 ℃ for 20 minutes. 2850 μL of DPPH fresh working solution was added with 150 μL of the supernatant and incubated for 30 minutes in dark conditions. The absorbance of the solution was determined at 515 nm using a UV visible spectrophotometer (Fisher Thermo Scientific, Multikan Go, UK). The results were expressed as percentages of inhibition of the DPPH radical, which were calculated using the following equation:

where Abs control is the absorbance of the DPPH solution without extracts ^[57].

2.8.   Statistical analysis

The data was expressed as the mean values based on four replicates for each treatment. An analysis of variance (ANOVA) of the SAS (9.4) was used to identify significant differences in the plant biomass, glycosides and phytochemicals among different treatments at p = 0.05. The least significant difference (LSD) test was performed to determine the differences in means among the treatments.

2.9.   Ethics approval of research

Ethics approval was not required for this study, as the research only involved plant materials and did not involve any experimentation on humans or animals.

3.   Results

3.1.   Biomass

As, summarized in Figure 2, the results showed that CO₂ enrichment increased our stevia plant's below and above-ground biomasses throughout the growth period. The biomass-related parameters namely, shoot dry weight (SDW) and root dry weight (RDW), had assisted at the 2^nd, 3^rd, and 4^th month after planting (MAP). In terms of the SDW, the plants under eCO₂ had significantly higher values than the aCO₂ treated plants. At the 2^nd month the eCO₂ treated plants were found with (20%) higher SDWs, than the aCO₂ plants. At month three, no significant were differences seen among the aCO₂ and eCO_2, treated plants however the eCO₂ treated plants had slightly higher values. At the 4^th month, the plants under CO₂ enrichment showed significantly higher value (8.53 ton/ha) than the plant under ambient CO₂, (7.53 ton/ha) regardless of the different densities (Figure 2A). Under aCO₂ treatment, significant differences were observed for plants under different planting densities. At second month, the highest DSW was obtained from the HDV, (6.84 ton/ha) followed by the HDH (1.65 ton/ha). The LDH produced just 0.85 ton/ha of the SDW, which was significantly lower than all of densities. Similar to the second month, the plants under different densities showed the same pattern at the 3^rd, and 4^th, MAP (Figure 2B). Additionally, the plants grown in the glasshouse with increased eCO₂ level were found with significant differences between the different densities. The data is summarized in Figure 2B, which shows a similar trend to plants grown under the aCO₂ treatment in the normal greenhouses.

Figure 2.  Mean comparison in SDW between the aCO₂ and eCO₂ treatments with different planting densities. [Notes: Bars represent means and error bars show standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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Despite the different densities, RDW was seen to be significantly higher under the eCO₂ as compared plants grown under aCO₂ treatment. Figure 3A shows that significantly higher RDW weight values were recorded for the eCO₂ treated plants compared to those plants which were grown under aCO₂. For the plants with different densities under the aCO₂, treatment the results were the same as RDW, which was discussed in the previous section (Figure 3B). Under the eCO₂, treatment the HDV plants produced significantly higher RDWs (1.82 ton/ha) in the second month than the HDH (0.42 ton/ha) and the LDH (0.21 ton/ha). A similar trend in results was observed for the 3rd and 4^th MAP (Figure 3B).

Figure 3.  Mean comparison in RDW between the aCO₂ and eCO₂ treatments with different planting densities. [Notes: Bars represent means and error bars show standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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3.2.   Total flavonoid and phenolic content

From the current study, it was found that the TFC in our plants significantly increased with CO₂ elevation at early growth and at the maturity stage (Figure 4A). The plants under the eCO₂ treatment were observed with a 17% increment in the TFC at 2^nd month, a 24% increment at the 3^rd MAP and a 15% at the 4^th, MAP in comparison with the aCO₂ treatment. However, the plants produced a higher amount in the 3^rd month than in the 2^nd and 4^th months of growth. Under the aCO₂ treatment significant differences were found with the planting densities. The data obtained at the 2^nd month of growth showed that the LDH plants produced significantly higher amounts of TFC than the HDV; however, the HDH was found to be non-significant to the LDH as well as the HDV. In the 3^rd month of growth, the LDH and the HDH plants produced significantly higher amounts of TFC (524 μg/g) and (500 μg/g) than the HDV (383 μg/g) however; the HDH, and LDH did not show any significant differences (Figure 4B). A similar trend was seen at the 4^th MAP. The trend for the TFC under eCO₂ treatment was similar to the aCO₂ treatment for plants grown with different densities. However, at the 2^nd month, the HDV plants were seen with the highest amount of TFC (474 μg/g), followed by the HDH (437 μg/g); no significant differences were observed with the LDH with TFC values significantly lower (394 μg/g) than the HDV and HDH. The results are summarized in Figure 4b, which shows a similar pattern to the aCO₂ treatment at the 3^rd and 4^th MAP.

Figure 4.  Mean Comparison of TFC at the different planting densities under the aCO₂ and eCO₂ conditions. [Notes: Bars represent means and error bars show standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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The results from the current experiment indicate that eCO₂ concentrations positively enhance the TPC in the stevia plants. The results summarized in Figure 5A show that the TPC content was significantly enhanced under the eCO₂ treatment, compared with aCO₂ treatment on the 2^nd month of growth by 31%, at the 3^rd MAP by 14%, and 29% at the 4^th MAP in comparison to plants grown under aCO₂. However, the results also showed that the maximum TPC was produced by plants at the 3^rd MAP and the minimum amount was recorded at month four, regardless of the different planting densities. The TPC was highly significant for different planting densities under the aCO₂ treatment at the first month, of growth where the LDH plant was found to produce the highest TPC (112 μg/g), followed by the HDV (78 μg/g) and the HDH plants (50 μg/g). At the 3^rd and 4^th, MAP the HDH and LDH plants were found with slightly higher amounts (Figure 6b) but were not significantly different according to the LSD at the probability level of (≤ 0.05). Under the eCO₂ treatment the LDH plants produced 137 μg/g, followed by the HDH 120 μg/g, which were significantly higher than the HDV 90 μg/g, at the 2^nd month of growth. Similarly, at the 3^rd MAP, the LDH plant produced higher TPC (170 μg/g), which was non-significant to the HDH (163 μg/g) but was significantly higher than the HDV (151 μg/g). After harvest in month four, no significant differences were observed for any treatment (Figure 5B).

Figure 5.  Impact of CO₂ levels and planting density on mean TPC. [Notes: Bars represent means and error bars show the standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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Figure 6.  Variation in means of scavenging activity across planting densities under ambient and elevated CO₂ Conditions. [Notes: Bars represent means and error bars show standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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3.3.   DPPH

The results from the current study demonstrate a significant enhancement in scavenging activity against DPPH radicals in Stevia rebaudiana plants under the eCO₂ condition at early growth stages. The results from Figure 8A illustrate that plants under the eCO₂ condition had significantly stronger scavenging activity (56%) in comparison with plants under the aCO₂ (49%) at the 2^nd month; and similarly, at the 3^rd month, the highest scavenging percentage was shown by the plant extract from the eCO₂ treatment (70%), while the extract from plants under the aCO₂, showed a 59% activity against DPPH radicals. No significant differences in scavenging activities were seen among the aCO₂ and eCO₂ treated plants at the 4^th MAP against DPPH radicals irrespective of planting density. Under the aCO₂ conditions, no significant differences were observed between plants with different densities in the 2^nd month. On the 3^rd and 4^th month, the LDH plants were found with strongest scavenging activities against DPPH however; the HDV and HDH were found to be non-significant (Figure 6B). Additionally, the results demonstrate that after exposing the plants to eCO₂ with different planting densities, the LDH plants were found with strongest antioxidants activities as compared to the HDH and HDV. However, the HDH plants had significantly higher values than the HDV at the 3^rd month, of growth; at the 1^st and 4^th MAP, no significant differences were observed for the HVD and HDH (Figure 6B).

3.4.   Glycosides

Elevated CO₂ level positively enhanced the glycosides content in stevia. As shown in Figure 7A, indicate that the stevia plants have produced (8%) significantly higher steviosides at the 2^nd month harvest under the eCO₂ treatment in comparison to the aCO₂ treatment. No significant differences were seen at the 3^rd month harvest, although the amount of steviosides were slightly higher under the eCO₂ treatment than the aCO₂ treatment. At the 4^th month harvest the eCO₂ treated plants produced (32.6 mg/g) steviosides significantly higher than the plant under the aCO₂ treatment (28.6 mg/g), despite differences in the planting densities. Under the aCO₂ treatment no significant differences were seen for different planting densities at 2^nd month; alternately at 3^rd month, the LDH and HDH plants produced significantly higher amount of steviosides than the HDV; though the results for steviosides were non-significant at the final harvest on the 4^th MAP, among the different planting densities (Figure 7B). Under elevated CO₂ levels the highest values for the steviosides were recorded for the LDH (30.41 mg/g) which were non-significant when compared to the HDH (30 mg/g) but significantly higher than the HDV (27 mg/g) at the first month harvest. At the 3^rd month, there were no significant differences between all three planting densities; however, at the final harvest after four months (Figure 7B), the LDH plants were able to produce 36.45 mg/g, of steviosides which were significantly higher than the HDH (31 mg/g) and the HDV (30mg/g).

Figure 7.  Mean difference in steviosides content under aCO₂ and eCO₂ concentrations and different planting densities. [Notes: Bars represent means and error bars show standard errors. Means with the same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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The analysis reveals a significant increase in rebaudiosides A under the eCO₂ treatment compared to the aCO₂ treatment. Specifically, rebaudiosides A showed a notable increase in the second month harvest under the eCO₂ treatment which was recorded (20%) higher than the aCO₂ treatment. At the 3rd month, harvest no significant difference was observed between the aCO₂ and eCO₂ treated plants. At the final harvest on the 4^th MAP, the plants exposed to eCO₂ produced (16 mg/g), of rebaudiosides A which was significantly higher than the plants under aCO₂ treatment (Figure 8A). Under aCO₂ treatment no significant differences were seen among the different planting densities (Figure 8B). However, the plants exposed to eCO₂ with different planting densities showed significant differences at the 2^nd month, while the trend was same as aCO₂ treatment at the 3^rd and 4^th month harvest. The results summarized in Figure 8B show that the LDH and HDH plants had higher values for rebaudiosides A, which were non-significant according to LSD test at the probability level of p ≤ 0.05.

Figure 8.  Mean difference in rebaudiosides A content under aCO₂ and eCO₂ concentrations and different planting densities. [Notes: Bars represent means and error bars show standard errors. Means the with same letter in a group do not show a significant difference according to the LSD at p ≤ 0.05. aCO₂ = ambient carbon dioxide; eCO₂ = elevated carbon dioxide; HDV = high density vertical farming; HDH = high density horizontal farming; LDH = Low density horizontal farming.].

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4.   Discussion

It is well known that the concentration of carbon dioxide has increased over the past 50 years; within this timeframe, much research has been conducted on plant performance under eCO₂; most of those findings showed that eCO₂ stimulated plant growth through the CO₂ fertilization effect. At the current CO₂ level, the Rubisco enzyme involved in leaf photosynthesis is suboptimal ^[58,59]. Therefore, the CO₂ enrichment in the atmosphere will benefit the plants in terms of growth and yield, specially for C₃ crops ^[60,61], by positively enhancing the physiological and biochemical process ^[62,63,64]. The results from our study revealed that the eCO₂ significantly increased overall plant biomass regardless of the different planting densities. The results from the current study illustrate that the shoot fresh and dry weights were significantly higher under the eCO₂ treatment as compared to aCO₂ treatment. Similarly, the root fresh and dry weight were also seen with significant increments under the eCO₂ concentration.

However, under different planting, densities the HDV showed a higher biomass than the HDH. while the LDH was seen with lowest values. The high difference in biomass (i.e. SDW, and RDW) among the different planting densities was due to the number of plants per unit area. Ball et al. 2000 ^[65] showed that plants under the high density ensured an increased light interception, crop biomass, and high growth rate of crop. However, it has been confirmed that low planting densities with low yields can be caused by a small number of plants per unit of area. Thus, a decrease in the yield under low planting densities is related with the high plant numbers per unit area ^[66,67]. These findings may explain that why the fresh and dry biomasses were lower under the LDH than the HDV and the HDH. The results from the current study are similar to Degraaff et al. 2006 ^[68], where they reported that the availability of an additional photosynthate enabled most plants to grow faster under elevated CO₂, with the dry matter production being increased on average by 17% for the above-ground biomass. Additionally, our results are also in line with Ainsworth et al. 2008 ^[62], who found 12–14% increments in the total yield for C₃ crops such as wheat, rice and soybean under elevated CO₂ level. Elevated CO₂ levels result in the partial closure of the stomata, which increases the water use efficiency in plants; thus, can contribute to the high biomass production in plants ^[69]. Lamichaney et al. 2021 ^[70] reported that under eCO₂ conditions, the total dry weight of chickpeas (C₃ crop) was 28-29% higher which supports of our results from the current study.

The results showed that eCO₂ has significantly affected the level of the TFC, the TPC and antioxidant activities despite differences in the planting densities. Those plants, which were exposed to elevated CO₂, were seen with the highest flavonoid content throughout the growth period; similarly, the TPC was also increased with the CO₂ elevation. The DPPH antioxidant activities were recorded significantly higher under the elevated CO₂ in the 2^nd, and 3^rd, month while no significant differences were seen at the 4^th month. Ibrahim et al. 2012 ^[71] reported an increment in plant specialized metabolites due to an enrichment in the total non-structural carbohydrate (TNC) and the total soluble sugar under eCO₂ conditions. Elevated CO₂ levels in the atmosphere can cause a plant to reallocate resources, which can impact many physiological processes such as alterations in the primary and secondary metabolisms. Under eCO₂ conditions plants can produce more carbohydrates, which will not affect the nutrient balance in plants but also serve as a source of specialized metabolites, many of which are health-promoting phytochemicals. The reallocation of plant resources, especially to specialized metabolites, is based on the hypothesis of carbon–nutrient balance (CNB) ^[72]. Several reports have shown that eCO₂ in the atmosphere can lead to the accretion of certain carbon-based specialized metabolites such as flavonoids and phenolic compounds in many plant species ^[73,74,75]. However, eCO₂ is also anticipated to stimulate the production of NADPH, which means that it can improve the plants' ability to reroute NADPH to maintain a higher concentration of antioxidants, such as ascorbate and glutathione ^[76]. Similarly, Backer and Klaring 2016 ^[77], reported the accumulation of several flavonoid and other phenolic compounds in lettuce (C₃ plant) under the eCO₂ treatments which supports our results. On the other hand, Sallas et al. 2003 ^[78] reported a decline in the TPC in Norway spruce under eCO₂ conditions; however, the effect of CO₂ can be species specific and favor C₃ plants which produce high specialized metabolites under high atmospheric carbon dioxide. Our results are also in line with the finding from Dong et al. 2018 ^[79], where they reported that eCO₂ (1200 ppm) increased the of total antioxidant capacity, the TPC, and the TFC by 59%, 8.9%, and 45.5% respectively.

The photosynthetic rate and intake of the carbon capacity of various plants leaf sections are affected by the plant density because the plant density impacts the nutritional status and light distribution characteristics of plants. The primary active ingredients in medicinal plants are specialized metabolites. The population structure of plants is primarily impacted by the planting density, which enhances competition between individuals for nutrients, light, and water. The plant yield and quality are impacted by these internal environmental factors, which are dependent on the planting density ^[66,80]. Wu et al. 2020 ^[80] reported that the 1450 plant m⁻² of perilla sprouts produced the highest TFC compared with 1887 and 2325 plants m^-2, which are similar to our results for the highest flavonoids under the LDH. In term of the highest phenol content and antioxidant activity under the LDH are in agreement with Yuan et al. 2018 ^[81], who reported that tobacco plants (Nicotiana tabacum) grown at lower densities had increased levels of alkaloids such as nicotine, which are specialized metabolites involved in plant defense. According to Cheynier et al. 2013 ^[82], plants develop a vast amount of phenolic specialized metabolites, which are essential to their interactions with the environment. In contrast to our results Kaluzewicz et al. 2017 ^[83], reported that higher plant densities led to increased concentrations of phenolic compounds. However, a study by Riad et al. 2009 ^[84] suggested that no significant effect was seen among the planting density on the TPC, in cabbage. Reilly et al. 2014 ^[85] reported similar results for broccoli. In our current study, the LDH were found with the highest phenolic content. On the other hand, the HDV farming showed lower phenolic content than the HDH, which may explain why there was no effect of the planting density on TPC.

Steviol glycosides are the key components that make stevia different from other crops. Steviosides and rebaudiosides are reported to be the most abundant glycosides by percentage, especially in leaves as compared to other parts of the plant. From our current investigation, we found that both steviosides and rebaudiosides A were significantly increased with increased CO₂ concentrations, despite differences in the planting densities. At the final harvest, the CO₂ treated plants had 12% increment in steviosides as compared to the non-treated plants. However, the plants under the eCO₂ treatment, showed a maximum amount of the steviosides at the 4^th month, while plants under the aCO₂ treatment were seen with maximum values at the 3^rd MAP. Dong et al. 2018 ^[79] reported that eCO₂ promoted soluble sugar in vegetables due increased CO₂ fixation under eCO₂ promoting triose phosphate in the leaves, which can be further transformed to other sugar such as glucose, sucrose, and fructose. As we mentioned in the earlier section and is supported by Booker, 2000 ^[86], that eCO₂ increases the concentration of the total non-structural carbohydrates which further stimulates the production of specialized metabolites. The meta-analysis from Dong et al. 2018 ^[79] showed that the concentrations of glucose, fructose, sucrose, and total the soluble sugar were increased 13.2%, 14.2%, 3.7%, and by 17.5%, respectively in terms of all vegetables which supports our results for stevia being a C₃ plant; C₃ crops, show similar trends, even though there is lack of studies on steviosides and rebaudiosides under eCO₂. Moreover, our results are in line with Wang and Bunce, 2004 ^[87], where they reported that eCO₂ (950 ppm) increased total soluble sugar in the strawberry fruits by 20% as compared to 350 (ppm). Our results are also similar to El-Azem 2013 ^[88], who found a 13% increment in radishes and a 20% increment in turnips under the eCO₂ treatment (1000 ppm) in comparison to the aCO₂ (400 ppm).

The planting density does not significantly affect steviosides under the aCO₂ treatment. However, under the eCO₂ treatment vertical farming showed the lowest values compared to horizontal farming. The difference in steviosides under the eCO₂ treatment was because of the farming techniques rather than the density, as no significant differences were seen in the HDH and the LDH. Overall, no significant differences were observed for rebaudiosides A under the different planting densities under the aCO₂ as well as eCO₂ treatment. Kumar et al. 2014 ^[48], reported no significant differences for different planting densities for steviosides and rebaudiosides. Our results also show similarities to Benhmimou et al. 2017 ^[89], who reported that no significant differences were seen in the total steviol glycoside content of dry leaves under different planting densities. Gomes et al. 2018 ^[90] reported that a low plant density (3, 3333 plants ha⁻¹), promoted the highest content of rebaudioside A and steviosides at the beginning of flowering over high-density planting (1, 66 667 plants ha⁻¹) which show similarities to the increment of steviosides under low density planting than high density vertical planting.

Controlling the CO₂ procedures can show a positive effect in optimizing the plant growth and yield in commercial crop production. By specifically regulating the CO₂ concentrations in controlled environments, such as greenhouses or vertical farms, there is a possibility to enhance the CO₂ fertilization effect observed in C₃ crops like Stevia. The efficiency of photosynthesis can be greatly promoted by this approach, which leads to a higher biomass accumulation and an improved plant metabolism, as demonstrated in the current study. In larger-scale crop production, utilizing CO₂ enrichment could potentially increase the overall crop productivity, thus, allowing farmers to achieve higher yields while maintaining the resource efficiency. Moreover, other environmental factors, such as light and temperature, can be integrated with CO_2, to create optimal conditions for plant growth, thus, enhancing both the quantity and quality of harvests. If broadly adopted, this technique could extensively contribute to the future of sustainable agriculture by increasing production and reducing the environmental footprint of crop farming.

5.   Conclusions

Form our findings we conclude that eCO₂ significantly increased the biomass and secondary metabolism in stevia plants regardless of different densities throughout the growth period. However, the HDH farming (25 plants m²), performed better than the HDV (78 plants m²) and showed no significant differences to the LDH (12 plants m²) based on individual plant performances, which is suggested for stevia planting under Malaysian weather conditions. Additionally, the application of CO₂ elevation control procedures could be considered in commercial crop production on a large scale to further boost the plant growth and yield. The regulation CO₂ level may possibly enhance the photosynthesis process and biomass accumulation, which is favorable to increase the crop productivity, specifically in environments with controlled conditions.

Use of AI tools declaration

The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.

Acknowledgment

The work was partially supported and funded by TNB Research Sdn. Bhd. The authors are also thankful to all the staff members of Ladang 15, Faculty of Agriculture, University Putra Malaysia staff members for their support throughout the project.

Conflict of interest

The authors declare no conflict of interest.

Author contributions

A Abzar, made a significant contribution to the work reported, including conception, study design, execution, acquisition of data, analysis and interpretation like all areas. Siti Zaharah Sakimin, made a significant contribution to work reported, including conception, study design, execution, acquisition of data, analysis and interpretation like all areas and supervised the project. Hawa ZE Jaafar and Nor Elliza Tajidin made a significant contribution to the work analysis and study design and co-supervised the project. Arsalan Ishaque Made a significant contribution to the writing, reviewing and editing.