Enhancing Pereskia aculeata Mill. Cultivation with LED Technology: A Sustainable Approach

Abstract

Using light-emitting diode (LED) in plant production optimizes growth with higher energy efficiency, reduces carbon footprint and resource consumption, and promotes more sustainable agriculture. However, the plants’ growth characteristics and biochemical composition may vary depending on the light’s wavelength, spectrum, and intensity. Therefore, LEDs as a light source have become a promising choice for improving cultivation efficiency, as they can modulate the spectrum to meet the needs of plants. Pereskia aculeata is a plant species from the cactus family with high protein, vitamins, minerals, and fiber. The objective of this study was to evaluate the effect of LED lighting on the cultivation of P. aculeata and its influence on biometric color and physicochemical aspects. Two treatments were carried out without the addition of artificial light: one inside the greenhouse (C-ins) and the other outside the greenhouse (C-out), and four treatments with LEDs in different spectral bands: monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red). The biometric characteristics and the color of the leaves collected from the different treatments were evaluated. After this, the leaves were dried, ground, and evaluated. The physicochemical and thermal characteristics, bioactive compounds, and antioxidant activity of the leaves from each treatment were described. The biometric characteristics were intensified with red LED, and the color of the leaves tended toward green. The dried yield was around 50%, except for C-out treatment. Regarding nutritional characteristics, the highest protein (29.68 g/100 g), fiber (34.44 g/100 g), ash (20.28 g/100 g), and lipid (3.44 g/100 g) contents were obtained in the treatment with red light. The red treatment also intensified the content of chlorophyll a (28.27 µg/L) and total carotenoids (5.88 µg/g). The blue treatment intensified the concentration of minerals and provided greater thermal stability. Regarding bioactive properties, the cultivation of P. aculeata inside the greenhouse favored the concentration of phenolic compounds and a greater antioxidant capacity. Therefore, the quality of light for P. aculeata demonstrates that the length of red and blue light corroborates the development of the plant through the wavelength absorbed by the leaves, favoring its characteristics and planting in closed environments.

1. Introduction

Light is an essential energy source for plant growth, which regulates plant physiology. Plants use light as an energy source for carbon fixation during photosynthesis and as a signal to activate and regulate many other vital processes related to plant growth and development, such as flowering, elongation, and secondary metabolite production [1]. As the assimilative function of light is essential for their survival, plants have developed precise light detection mechanisms to maintain and/or maximize photosynthetic performance and the concentration of its components (secondary metabolites) [2,3].

Natural light is often insufficient for the ideal development of plants in nature due to environmental conditions, meaning artificial lighting is used, which can be an alternative for production in environments susceptible to climate change. Light-emitting diodes (LEDs) have stood out as a primary light source for plant cultivation chambers as they allow control of spectral composition (light quality) and adjustment of light intensity (light quantity). LEDs have numerous advantages over incandescent or fluorescent lamps, mainly due to their high light levels with low radiant heat production, the maintenance of useful light production for years, and low electrical energy consumption [4].

With the ability to simulate different light conditions, LEDs enable the cultivation of various vegetables in closed environments, regardless of external climate conditions. This approach increases the productivity and quality of vegetables and reduces dependence on pesticides and chemical fertilizers, promoting more sustainable agricultural practices. The positive effect of LEDs on lettuce [5,6], basil [7], potato [8], and other vegetable cultivations has already been proven.

Although light is provided, not all of it is utilized by plants in their growth. The efficiency with which plants use light depends on several factors, including the wavelength of light, the absorption properties of pigments, and the balance between the photosystems [1]. Different wavelengths have varying efficiencies in driving photosynthesis; for instance, red light promotes cell growth, while blue increases photosynthesis and controls stomatal opening, regulating gas exchange. Consequently, optimizing the light spectrum is essential to maximize plant growth and productivity [1,9,10]. This efficiency varies with the pigment composition and absorption properties in photosystem I and II that promote, in an associated manner, the energy storage reactions of photosynthesis, so an appropriate balance between them is crucial; imbalances can reduce photosynthetic quantum yield, where the plant does not optimally use the available light energy for its metabolic processes [1]. Therefore, the optimal selection of light spectrum can enhance plant yield and quality, improving nutrient uptake and minimizing the environmental impact as it reduces pollutant emissions into the external environment.

Despite the studies already conducted, it is necessary to evaluate the effects of LEDs on other vegetables that are provided as food and nutritional alternatives, including Pereskia aculeata. P. aculeata Mill., known as ora-pro-nobis or Barbados gooseberry, belonging to the Cactaceae family, is a plant whose leaves contain significant amounts of proteins (20.0 g/100 g), minerals (18.0 g/100 g)—the main ones are calcium (up to 3.6 g/100 g) and magnesium (up to 2.6 g/100 g)—, fiber (17.5 g/100 g), carbohydrates (40.5 g/100 g), and vitamins, with vitamin C being the most prominent (182.5 g/100 g) [11]. Furthermore, P. aculeata contains a variety of phytochemicals, including phenolic compounds (such as caffeic acid derivatives), flavonoids (quercetin, kaempferol, and isorhamnetin glycosides), phytosterols (sitosterol, campesterol, and stigmasterol), and carotenoids (α-carotene, β-carotene, lutein, α-cryptoxanthin/zeaxanthin, and β-cryptoxanthin) that can have antioxidant, anti-inflammatory, and antibacterial activities [12,13,14,15]. The nutritional and phytochemical composition of P. aculeata is influenced by environmental conditions (light, temperature, and humidity), cultivation practices, and the plant’s growth stage [16]. As it is a sustainable source of bioactive compounds and ingredients, producing and consuming P. aculeata leaves are extremely important [17]. Therefore, improving the efficiency of your cultivation becomes strategic from the point of view of food and nutritional security.

The production of leaves with high nutritional composition is critical to ensure food security for sustainable human development, which is associated with efficiency and crop yield and has the potential to customize light parameters to intensify plant performance. Thus, this study aims to evaluate P. aculeata leaves grown with LEDs and characterize the biometric, physicochemical, thermal, and bioactive properties, and the presence of photopigments.

2. Materials and Methods

2.1. Plant Material and Growing Conditions

This experiment was conducted at the Biocompounds and Nutrition Laboratory of the Goiano Federal Institute (Rio Verde, Brazil). Vegetative propagation produced P. aculeata seedlings (Supplementary Figure S1). The seedlings, at two months old, were transferred to the greenhouse on 23 October 2020 under metal structures (1.10 × 0.90 × 0.60 m—length, width, and height, respectively) with supplemental lighting provided by 20 W LED tubes (Lanao series tubes, Shanghai, China) with different spectral bands: monochromatic red (600–700 nm), monochromatic blue (400–490 nm), white (400–700 nm), and blue–red (1:1) (Blue–Red). The soil used for planting was a combination of red latosols/sand/Bioplant Plus, in a proportion of 2:1:1. The structure’s height was adjusted according to the plant’s growth to maintain the intensity of the light supplementation. A layer of opaque black fabric was placed between the metal compartments to prevent light contamination between adjacent treatments. Furthermore, two control treatments were carried out without LED lights: one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins). The treatments were arranged in two blocks with five replicates each, where each replicate consisted of a single plant in a pot, totaling 10 samples per treatment.

The photosynthetic photon flux density of 100 ± 5 μmol m⁻² s⁻¹ was used with a photoperiod of 16 h (from 7:00 a.m. to 11:00 p.m.), measured at the top of the plant. The spectral quality and light intensity measurements were taken and adjusted at night using a LI-180 spectrum radiometer (Li-Cor Biosciences, Lincoln, NE, USA). The photosynthetically active radiation in the external environment recorded at 11:30 a.m. on 21 December 2020, was on average 2050 ± 50 µmol m⁻² s⁻¹, while in the greenhouse without supplementation, there was an average attenuation of 35%. The seedlings were irrigated daily with 300 mL of water.

2.2. Sample Preparation

For evaluation, the leaves were collected at the harvest stage 60 days after planting (Supplementary Figure S2), and only fully expanded leaves were collected, leaving just two on each plant. The collected leaves were sanitized (200 ppm sodium hypochlorite for 10 min). After sanitization, the leaves were stored in polyethylene bags and conditioned under refrigeration (4 °C) until analysis. The fresh samples were used to evaluate the biometric and color characteristics.

Sanitized P. aculeata leaves were frozen in an ultra freezer (−80 °C) and then freeze-dried in a Liotop L101 freeze-dryer (Liotop, São Carlos, Brazil). The dried products were homogenized using a 30-mesh sieve, packaged in polyethylene bags, and stored (−10 °C) until analysis. The dried samples were used to evaluate the yield, physicochemical and thermal characteristics, photopigment composition, and antioxidant activity.

2.3. Biometric and Color Characteristics

For biometric characteristics of the leaves collected from the different treatments, the mass (g), length (mm), width (mm), thickness (mm), and leaf area (mm²) were evaluated. Length measurements were obtained with a caliper. The leaf area was obtained from the integration of images by the ImageJ^® software (version 1.41o, National Institutes of Health, Bethesda, MD, USA).

Color parameters of in natura leaves were evaluated using a Colorflex EZ spectrophotometer (Hunterlab, Reston, VA, USA) with the Commission Internationale de l’Eclairage system (CIElab). The equipment was calibrated to include reflectance, a 10° observation angle, and D65 illuminant. Luminosity (L*), chromas a* and b*, and saturation (C) were determined directly on the equipment, and hue angle (h*) was calculated based on parameters a* and b*.

2.4. Physicochemical Characterization

To determine the pH, 10 g of the sample was added to 100 mL of distilled water, stirring for 15 min at 25 °C. After resting for approximately 10 min for decantation, the pH of the supernatant was read using a calibrated digital pHmeter (model K39-1420A, Kasvi, Pinhais, Brazil) [18].

The soluble solids were determined through the refractive index, using a refractometer ATAGO™ PR-101α (Fisher Scientific, Göteborg, Sweden) and expressed in °Brix [18].

Titratable acidity was measured by homogenizing 10 g of the sample with 100 mL of distilled water. The determination was carried out using potentiometric volumetry, using a standard 0.1 mol/L of sodium hydroxide solution until the pH value of the mixture reached 8.2–8.4, and the titration was then interrupted [18].

The water activity was carried out using the LabTouch Novasina equipment (Novasina, Model LabTouch, Lachen, Switzerland) at 25 °C and FAST mode.

The yield was determined by relating the leaves’ wet mass (before freeze-drying) and the dry mass (after freeze-drying). The yield was expressed as a percentage (%) considering the mass of in natura P. aculeata and the dry flour obtained.

2.5. Proximal and Mineral Composition

Contents of the moisture (method 925.09), proteins (method 954.01), lipids (method 920.39), and crude fiber (method 962.09) were determined according to the official methods of the Association of Official Analytical Chemists (AOAC) [18]. Carbohydrates were calculated using the difference method, and energetic value was calculated based on the composition using Atwater conversion factors of 4, 9, and 4 kcal/g for protein, lipids, and carbohydrates, respectively [19].

The mineral content was evaluated using the following methodologies: nitrogen (N), by the colorimetric Nessler method in the presence of an alkaline solution of tetraiodomercurate (II); potassium (K) and phosphorus (P), by colorimetry and by flame photometry; calcium (Ca), magnesium (Mg), iron (Fe), zinc (Zn), and manganese (Mn), by atomic absorption spectrophotometry; sulfur (S), by barium chloride turbidimetry; chlorine (Cl), by titration with silver nitrate (AgNO₃), and boron (B) by the Azomethine-H spectrophotometry method [20,21].

2.6. Bioactive Compounds and Antioxidant Activity

Chlorophyll a was determined from the extraction of a 1 g sample with 5 mL of 90% acetone solution, filtration, and volume adjustment to 100 mL. The extract was read using a spectrophotometer at 645 and 663 nm. Chlorophyll a was calculated using Equation (1):

$$Chlorophyll a\left({\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{\mathrm{m}\mathrm{L}}}\right)=20.2\times \left(A_{645}\right)+8.02\times (A_{663})$$

(1)

where A₆₄₅ is the absorbance measured at 645 nm, A₆₆₃ is the absorbance measured at 663 nm, V is the final volume of chlorophyll content, and W is the weight of the extract [22].

Pheophytin a was corrected by acidifying the solution in the cuvettes after the first reading (645 and 663 nm) by adding 100 µL of 0.1 M hydrochloric acid. After 90 s, the optical densities were determined at 750 and 665 nm (665 nm—maximum absorption peak of pheophytin a) [23]. Equation (2) was used to calculate pheophytin a.

$$Pheophytin \left({\displaystyle \frac{\mathsf{\mu }\mathrm{g}}{\mathrm{m}\mathrm{L}}}\right)=20.2\times \left(A_{750}\right)+8.02\times (A_{665})$$

(2)

where A₇₅₀ is the absorbance measured at 750 nm, A₆₆₅ is the absorbance measured at 665 nm, V is the final volume of chlorophyll content, and W is the weight of the extract.

Total carotenoids were determined based on a method described by Talcott and Howard [24]. Two g pulp was homogenized in 25 mL of acetone:ethanol (1:1) and 200 mg/L of butylated hydroxytoluene (BHT) in the dark at room temperature. Afterward, the extract was washed four times until the residue became colorless. The extract was filtered through the Whatman No. 4 paper filter, and its volume was adjusted to 100 mL. Absorbance was measured at 470 nm. The total carotenoids were calculated in agreement with [25] (Equation (3)).

$$Total carotenoids \left({\displaystyle \frac{\mathrm{m}\mathrm{g}}{100 \mathrm{g}}}\right)={\displaystyle \frac{A_{470}\times \mathrm{V}\times {10}^6}{A^{1\%}\times 100\times \mathrm{g}}}$$

(3)

where $A_{470}$ is the absorbance at 470 nm; V is the total volume of the extract; $A^{1\%}$ is the extinction coefficient for a mixture of solvents arbitrarily set at 2500, and g is the sample weight in grams.

Two crude extracts were prepared, the aqueous one by adding 1 mg of dry sample in 1 mL of water and 0.5 mg of dry sample in 1 mL of 70% ethanol solution. The determination of total phenolic compounds was performed based on the Folin–Ciocalteu method [26]. An aliquot of 0.5 mL of previously prepared crude extract, 2.5 mL of 10% (v/v) Folin–Ciocalteu reagent aqueous solution, and 2 mL of a 7.5% (w/v) aqueous solution of sodium carbonate were homogenized. The mixture was maintained for 5 min at 50 °C, and the absorbance was measured at 760 nm. The same procedure was performed using 0.5 mL of methanol to obtain the blank. The concentration of total phenolics was expressed as mg gallic acid equivalent (GAE) per g of extract.

As the aqueous extract proved to be more interesting for analyzing phenolic compounds, it was used to evaluate the antioxidant activity. The antioxidant activity of the extracts was measured using three methods: sequestration of the radical DPPH (2,2-diphenyl-1-picrylhydrazyl) [27]; the capturing ability of the ABTS radical [2,2′-azinobis (3-ethylbenzothiazoline-6-sulphonic acid)] [28] with modifications of Rufino et al. [29]; and through iron reduction (FRAP—ferric reducing antioxidant power) [30].

In the DPPH method, the degree of decolorization of the radical was obtained by mixing a 0.1 mL aliquot of the extract with 3.9 mL of the DPPH radical and homogenizing it in a tube shaker. The reading was carried out in a dark environment using a spectrophotometer at 517 nm. The concentration of P. aculeata (mg sample/g of DPPH) that caused a 50% (EC₅₀) reduction in DPPH radical was calculated from a standard curve of DPPH (10–60 μM). To calculate the EC₅₀, the absorbance equivalent to 50% of the DPPH concentration was substituted, and the value corresponding to the necessary amount of P. aculeata needed to reduce the initial concentration of the DPPH radical (EC₅₀) by 50% was found from a non-linear regression plot of the obtained absorbances versus sample concentration.

In a dark environment, a 30 µL aliquot of the previously prepared extract was homogenized with 3.0 mL of the ABTS radical to determine its ability to scavenge the ABTS radical. After resting for 6 min, a spectrophotometer was read at 734 nm. Trollox, a synthetic antioxidant analogous to vitamin E, was used as a standard at 20 to 80 μM concentrations to determine the straight-line equation. The calculation was carried out by substituting the absorbance equivalent to 1000 μM of the Trolox standard into the straight-line equation, and the value obtained corresponds to the μM Trolox/g of a sample.

Antioxidant activity using the reducing power of ferric ion was determined by preparing the FRAP reagent by mixing 55 mL of acetate buffer solution (300 mM, pH 3.6), 5.5 mL of 2,4,6-Tris(2-Pyridyl)-S-Triazine—TPTZ solution (10 mM TPTZ in 40 mM HCl), and 5.5 mL of FeCl₃ (20 mM) in aqueous solution. A 0.9 mL aliquot of the previously prepared extract was diluted (1:100), and 2.7 mL of FRAP reagent was added. Afterward, the mixture was incubated at 37 °C in a water bath for 30 min. Absorbance was measured at 595 nm.

2.7. Thermal Evaluation

The thermal characteristics of the leaves subjected to different light beams were determined using a differential scanning calorimeter (DSC) model DSC-60 (Shimadzu, Kyoto, Japan). DSC analysis was performed with a heating rate of 10 °C/min, a 25 to 300 °C temperature range, and an atmospheric nitrogen flow of 50 mL/min.

2.8. Statistical Analysis

All determinations were performed at least in triplicate, and the final results were shown as mean with standard deviation. The data were analyzed using analysis of variance (ANOVA), and the average values obtained were compared using Tukey’s test, with statistical significance (α) set at p < 0.05. Pearson’s correlation coefficient was used to relate the chemical composition variables studied in the present work with statistical significance (α) set at p < 0.05.

3. Results and Discussion

3.1. Characteristics of in Natura Leaves

The leaf area is a crucial parameter for estimating plant growth, as it directly impacts the plant’s ability to capture light energy and produce organic matter through photosynthesis. A larger leaf area allows for greater light absorption, which enhances the plant’s overall energy capture and contributes to its growth and development. The leaf area is also linked to various physiological processes, including gas exchange and transpiration, which are vital for metabolic functions. Therefore, understanding leaf area production is essential for optimizing plant health and productivity, as it influences the growth rate and the plant’s resilience to environmental stressors [31].

Table 1. Biometric characteristics of in natura P. aculeata leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

Treatments	Mass (g)	Length (mm)	Width (mm)	Thickness (mm)	Leaf Area (mm2)
C-out	1.37 ± 0.39 c	95.66 ± 12.78 c	37.13 ± 14.78 d	0.31 ± 0.14 c	2648.97 c
C-ins	1.70 ± 0.50 a	99.28 ± 10.42 b	38.12 ± 1.05 d	0.39 ± 0.04 b	2822.52 c
Red	1.72 ± 0.32 a	105.46 ± 10.22 a	50.39 ± 12.38 a	0.34 ± 0.12 c	3963.28 a
Blue	1.21 ± 0.19 c	105.41 ± 6.61 a	41.66 ± 3.82 c	0.37 ± 0.11 b	3275.09 b
White	1.53 ± 0.32 b	99.34 ± 8.40 b	47.84 ± 10.39 b	0.50 ± 0.12 a	3544.36 a
Red–Blue	1.51 ± 0.30 b	107.39 ± 8.65 a	42.11 ± 4.13 c	0.36 ± 0.07 b	3372.65 b

Mean and standard deviation followed by different letters on the same column indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents the biometric characteristics of P. aculeata leaves (Supplementary Figure S2) produced under different light conditions.

The main biometric characteristics, such as mass, length, width, and thickness, showed significant differences between the treatments evaluated. Among all treatments, the red and blue treatments have been reported as the most important light qualities for plant biomass accumulation, affecting the photosynthesis and photomorphogenesis of plants [7]. However, in this study, the red and C-ins treatments increased the fresh mass of P. aculeata leaves.

The length of P. aculeata leaves was higher in red (105.46 mm), blue (105.41 mm), and red-blue (107.39 mm) treatments. The width was higher in the red treatment (50.39 mm), and the thickness was higher in the white treatment (0.50 mm). Cultivation outside the greenhouse provided lower biometric parameters, while the light spectrums used efficiently grew the plant and provided more robust leaves.

The evaluation of the leaf area favors understanding the light used by the leaves, which is associated with the ability to intercept the incident/emitted radiation. The higher value in the leaf area suggests that the production and distribution of photoassimilates favor plant development [32]. The red (3963.28 mm²) and the white treatments (3544.36 mm²) presented the highest leaf area value.

Treatment outside the greenhouse promoted less leaf development, and this may have happened because 50% of the radiation that reaches the Earth’s surface is photosynthetically active radiation. In treatments inside a greenhouse, the physical conditions of the structure compromise part of photosynthesis. Thus, a plant strategy is to increase leaf area to compensate for the drop in photosynthesis. The LED lights can control radiation and produce high illumination levels for hours with low radiant heat, benefiting leaf structures [33].

Kim et al. [34] obtained similar results for the growth of shoots and roots of Panax ginseng hydroponic cultivation according to white and red light spectrums. Soltani et al. [35] obtained biometric growth parameters of grafted tomato seedlings exposed to different light spectrums (quality treatments of white, blue, and red light, and a combination of red (68%) and blue lights) and verified that the combination of red and blue lights presents the best results for biometric characterization. Pattaro, Falcioni, Moriwaki, and Alves, and Antunes [5] found that pure blue and other lights provided better biometric responses to lettuce development.

Therefore, LED lights positively impact leaf growth compared to controls (inside and outside the greenhouse). It is observed that red light generally promoted higher values in biometric characteristics, except leaf thickness. The wavelength of light plays a critical role in photosynthesis, influencing the efficiency of energy conversion and the dynamic interplay between photosystem I (PSI) and photosystem II (PSII), which collectively determine the quantum yield and overall productivity. The interaction between photosystems I (PSI) and II (PSII) and the quantum yield of photosynthesis is highly influenced by the wavelength of light, as demonstrated by studies on light absorption and excitation balance between the photosystems. Shorter wavelengths, such as blue light (400–500 nm), primarily excite PSII, enhancing electron flow and driving photosynthesis, but with less efficiency compared to red light (600–700 nm), which optimally excites both photosystems in balance [1,10].

Far-red light (>700 nm) contributes by overexciting PSI, increasing plastoquinone reoxidation, and more efficient PSII reaction center reopening, improving the overall quantum yield. This synergistic effect between light wavelengths maximizes photon use and supports acclimation processes, like adjustments in the PSI ratio, to balance excitation under varying light conditions [1,9]. Based on this, it is necessary to test different plant species to understand their responses and optimize cultivation practices, thereby improving productivity and compositional quality.

Table 2. Color parameters of in natura P. aculeata leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

Treatments	L*	a*	b*	h	C
C-out	42.46 ± 3.14 a	−12.79 ± 1.39 a	23.79 ± 3.76 a	113.03 ± 2.22 c	27.08 ± 4.04 a
C-ins	36.54 ± 2.25 b	−12.08 ±1.52 a	18.99 ± 3.29 d	166.94 ±1.64 a	22.60 ± 3.58 c
Red	40.02 ± 3.15 a	−11.62 ± 1.56 b	22.59 ± 4.76 b	112.66 ± 4.62 d	25.52 ± 4.20 b
Blue	36.99 ± 2.66 b	−10.50 ± 1.82 c	19.24 ± 3.22 c	113.31 ±3.45 c	22.14 ± 3.19 b
White	39.98 ± 3.00 b	−10.91 ± 3.67 c	22.88 ± 3.42 b	113.28 ± 2.28 c	26.20 ± 4.02 b
Red–Blue	34.46 ± 3.76 c	−7.86 ± 5.07 d	18.15 ± 5.20 d	115.62 ± 5.00 b	18.15 ± 5.20 d

L*: brightness; a* and b*: chromas; h: hue angle; C: saturation. Mean and standard deviation followed by different letters on the same column indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents the color parameters for fresh P. aculeata leaves grown under different treatments.

The color parameters of P. aculeta leaves appear to have been affected by the incidence of LED lights. P. aculeata leaves were brightest when grown outside the greenhouse and with red light.

The a* parameter of all treatments tended to be green (negative a*), which was already expected due to the presence of chlorophylls in P. aculeata (this will be discussed later). Applying LEDs reduced the intensity of the green color on the leaves. The b* parameter was yellow in all treatments, indicative of pigments such as carotenoids, essential for photosynthesis and photoprotection [36]. The hue angle (h) presented values between 90° corresponding to +b (yellow) and 180° corresponding to −a (green). These results reveal the evolution of the color tone of the P. aculeata leaf from a greenish to a more yellow tone with LED treatments. Saturation (C) expresses the intensity of the color, that is, the saturation in terms of pigments of this color [37]. Saturation was higher in the C-out treatment (27.08), consistent with the other responses obtained for the other color parameters.

One of the limitations of the fresh consumption of vegetables is their susceptibility to degradation due to the high water content in their composition [38]. In this case, dry material is an interesting alternative for various food products. Treatments outside the greenhouse and those where the LED light was applied showed higher percentages of P. aculeata yield after freeze-drying, with values close to 50%. In contrast, intermediate values were obtained for the red-blue (19.4%) and C-ins (16.0%) treatments. The low yield obtained in the red-blue treatment was due to obtaining plants with longer stems and fewer and more spaced leaves.

The C-ins treatment presented lower yield values, possibly related to the luminosity reduction. The incidence of solar radiation can vary from around 5 to 35% depending on the material used on the roof and the angle of the sun, which can influence the luminosity inside the greenhouse, reducing photosynthesis and plant development. Light deficiency in plants is often the most limiting factor for obtaining high yields. However, excess can also be harmful, associated with poor light quality, salinization of light in cultivation, and water availability [39].

3.2. Physicochemical Characteristics of P. aculeata Dry Leaves

Table 3. Total soluble solids, hydrogen potential (pH), titratable acidity, and water activity of P. aculeata dry leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

Treatments	Total Soluble Solids (°Brix)	pH	Titratable Acidity (%)	Aw
C-out	0.77 ± 0.25 b	4.96 ± 0.01 b	2.10 ± 0.10 a	0.560 ± 0.002 b
C-ins	0.65 ± 0.05 b	4.95 ± 0.02 b	1.98 ± 0.07 b	0.490 ± 0.008 c
Red	0.60 ± 0.00 c	5.03 ± 0.02 a	1.80 ± 0.10 c	0.660 ± 0.001 a
Blue	0.60 ± 0.17 c	5.03 ± 0.04 a	1.80 ± 0.10 c	0.580 ± 0.002 b
White	0.70 ± 0.00 b	4.97 ± 0.03 b	1.27 ± 0.06 d	0.620 ± 0.001 a
Red–Blue	0.87 ± 0.15 a	5.09 ± 0.01 a	2.23 ± 0.06 a	0.590 ± 0.020 b

Aw: water activity. Mean and standard deviation followed by different letters on the same line indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents values for total soluble solids (°Brix), hydrogen potential (pH), total titratable acidity, and water activity (Aw) of P. aculeata dry leaves after grown under different treatments.

P. aculeata dry leaves presented soluble solids results ranging from 0.60 to 0.87 °Brix, which was higher than had been reported by Ciríaco et al. [40] (0.3 °Brix). The highest value of soluble solids was obtained in P. aculeata leaves cultivated with red-blue treatment (0.87 °Brix). The total soluble solids value represents the presence of acids, salts, vitamins, amino acids, pectins, and sugars in the plant material [40].

The pH values obtained showed an acidic character for all treatments analyzed. Although there was a significant difference between treatments, they ranged from 4.95 to 5.09, which was still acidic. Ciríaco et al. [40] demonstrated a pH of 5.66 for P. aculeata leaves.

The pH provides an instantaneous reading of the concentration of free H⁺ ions in a solution at a given time. In contrast, titratable acidity provides a more comprehensive measure of the total amount of acid that can react with a base. Titratable acidity is an important parameter to be determined as it verifies the product’s quality since decomposition reactions, such as hydrolysis, oxidation, and fermentation, generate acidic compounds that increase the medium’s acidity [41]. C-out (2.10%) and red-blue (2.23%) treatments resulted in higher titratable acidity values, while white treatment promoted lower titratable acidity value (1.27%). Although red and blue treatments provided higher pH values than the other treatments, titratable acidity values were low, as they depend on the total amount of organic acids present, such as citric acid.

Borges-Machado et al. [42] related that the P. aculeata leaves are a highly perishable food (Aw = 0.992) and are susceptible to deterioration if not treated properly. Red (0.660) and white (0.662) treatments demonstrated higher Aw than the other treatments. However, all treatments presented Aw to ensure microbiological safety (Aw ≤ 0.6) [42]. The water activity in P. aculeata is a critical characteristic for safety and shelf life because it can promote microbial growth and the occurrence of chemical and enzymatic reactions, compromising the safety and nutritional, sensory, and technological properties of dry leaves [43].

3.3. Proximal and Mineral Composition

Table 4. Proximal composition (g/100 g) and caloric value (kcal/100 g) of P. aculeata dry leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

	C-Out	C-Ins	Red	Blue	White	Red–Blue
Moisture *	4.20 ± 0.00 b	3.77 ±0.00 c	4.49 ± 0.00 b	5.00 ± 0.00 a	4.51 ± 0,00 b	4.48 ± 0,00 b
Ash	19.51 ± 0.03 b	18.68 ± 0.05 c	20.28 ± 0.03 a	19.42 ± 0.01 b	19.32 ± 0.01 b	20.05 ± 0.10 a
Lipids	2.85 ± 0.02 c	3.20 ± 0.10 b	3.44 ± 0.10 a	3.33 ± 0.01 a	3.31 ± 0.01 a	2.99 ± 0.08 c
Proteins	23.16 ± 0.02 d	26.96 ± 0.10 b	29.68 ± 0.03 a	24.18 ± 0.01 c	24.06 ± 0.01 c	22.53 ± 0.05 d
Crude fiber	31.90 ± 0.06 b	30.09 ± 0.10 c	34.44 ± 0.10 a	31.25 ± 0.05 c	31.09 ± 0.05 c	30.12 ± 0.04 c
Carbohydrates	22.58	21.07	12.16	21.82	22.22	24.31
Calorie value	208.61	220.92	198.32	213.97	214.91	214.27

* Wet matter. Mean and standard deviation followed by different letters on the same line indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents the proximal composition of P. aculeata dry leaves subjected to different light treatments.

P. aculeata dry leaves presented a low moisture value (3.77 and 5.00 g/100 g). The low moisture content obtained guarantees stable storage at room temperature. The moisture levels obtained were within the range permitted by Brazilian legislation, which establishes a maximum moisture content of 15.0 g/100 g for the value of flours, cereal starch, and bran, according to Resolution-RDC n° 263, of September 22 [44].

In general, the results obtained in the treatments were similar to those obtained by Borges-Machado et al. [42] (13.9 g/100 g of ash, 26.6 g/100 g of proteins, 2.5 g/100 g of lipids, and 15.1 g/100 g of carbohydrates) and Mendes et al. [45] (14.0 g/100 g of ash, 20.8 g/100 g of proteins, 3.1 g/100 g of lipids, and 41.0 g/100 g of carbohydrates) for P. aculeata leaves, except ash and carbohydrate contents. Torres et al. [46] related a lower protein content for P. aculeata leaves (13.7 g/100 g) compared to all treatments in the present study (Table 4). The variation obtained within the composition parameters can be justified by the physiological characteristics of the plant and cultivation conditions, in the case of this study, by LED lighting with different colors.

As with the ash content, the protein and the crude fiber contents were higher in the red treatment (20.28, 29.68, and 34.44 g/100 g, respectively). When comparing the red with C-out treatments, there was an increase of around 22% in protein content. The protein content of P. aculeata leaves subjected to different LED lights was higher than reported for beef (16–22% of protein). However, it is also necessary to consider that the animal protein content depends on the genetic group, age, sex, and nutritional level [47].

Minerals are essential for health and ensure metabolic balance. In addition to being present in organisms, they are necessary in small daily quantities and can be considered essential components.

Table 5. Mineral composition (mg/100 g) of P. aculeata dry leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

Treatments	N	P	K	Ca	Mg	S	Fe	Mn	Cu	Zn	B
C-out	2.19 c	0.32 c	5.20 c	13.95 b	4.12 c	0.32 c	0.03 b	0.01 d	0.012 c	0.018 c	0.015 b
C-ins	2.01 c	0.32 c	1.36 d	10.25 c	4.43 c	0.35 c	0.04 a	0.01 d	0.014 b	0.025 a	0.016 b
Red	2.48 a	0.42 b	7.94 b	14.33 b	4.67 c	0.53 a	0.02 c	0.06 a	0.013 c	0.027 a	0.012 c
Blue	1.15 d	0.65 a	10.13 a	27.25 a	9.79 a	0.49 b	0.04 a	0.01 d	0.016 a	0.022 b	0.023 a
White	2.10 c	0.37 c	5.88 c	14.15 b	5.64 b	0.31 c	0.03 b	0.07 a	0.012 c	0.015 c	0.014 b
Red–Blue	2.39 b	0.41 b	5.50 c	10.93 c	4.21 c	0.38 b	0.02 c	0.05 b	0.011 d	0.023 b	0.010 d

N: nitrogen; P: phosphorus; K: potassium; Ca: calcium; Mg: magnesium; S: sulfur; Fe: iron; Mn: manganese; Cu: copper; Zn: zinc; B: boron. Means followed by different letters in the same column indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents the mineral composition in P. aculeata dry leaves in different light beams during cultivation.

The blue treatment had a greater impact on increasing the concentration of minerals in P. aculeata leaves than the other spectra and treatments, being, in decreasing order of quantity, the calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), iron (Fe), boron (B), and copper (Cu). The red treatment resulted in the highest content of nitrogen (N) > sulfur (S) > manganese (Mn) > and zinc (Z). The highest N content was expected since the treatment presented the highest protein content (Table 4).

In all treatments, Ca was the majority mineral, as reported by Hoff et al. [48]. Maciel et al. [49] obtained a higher concentration of potassium and magnesium, followed by sulfur, phosphorus, and calcium in P. aculeata extracts. These variations in vegetables, in addition to the LED treatments used, and external factors such as climate and local growing conditions, harvest time, and pre-processing methods, may be associated [50].

In general, for the proximal composition, the cultivation of P. aculeata carried out with LED in the red spectral range favored the ash, proteins, crude fibers, and lipid content. However, blue LED favored a higher content of most minerals.

3.4. Photosynthetic Pigments, Bioactive Compounds, and Antioxidant Activity Compositions

Photosynthetic pigments vary in quantity according to the plant’s growing conditions. These pigments absorb light energy, which is later transformed into chemical energy through photosynthesis. The natural green color of P. aculeata leaves is due to chlorophylls a and b. Chlorophyll a and pheophytin a are derivatives of chlorophyll [51,52].

Table 6. Chlorophyll a, pheophytin a, and carotenoids of P. aculeata dry leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

	Chlorophyll a (µg/L)	Pheophytin a (µg/L)	Carotenoids (µg/g)
C-out	27.49 ± 0.01 b	24.54 ± 0.01 c	0.18 ± 0.06 c
C-ins	28.74 ± 0.06 a	27.76 ± 0.03 b	3.95 ± 0.04 b
Red	28.27 ± 0.05 a	26.85 ± 0.02 b	5.88 ± 0.02 a
Blue	26.96 ± 0.01 c	32.81 ± 0.01 a	2.05 ± 0.01 d
White	29.75 ± 0.02 a	23.01 ± 0.03 c	3.88 ± 0.07 b
Red–Blue	27.64 ± 0.03 b	17.21 ± 0.03 d	3.78 ± 0.05 b

Mean and standard deviation followed by different letters on the same column indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

presents the quantification of the photopigments chlorophyll a, pheophytin a, and the total carotenoids in P. aculeata under different treatments.

Through Table 6, it is possible to verify that the different spectra received from an artificial light source (LED) strongly influenced the plant’s behavior, causing different concentrations of the photopigments. The C-ins, red, and white treatments provided the highest chlorophyll a content (28.74, 28.27, and 29.75 µg/mL, respectively). Pennisi et al. [6] studied five red/blue lights in different ratios (0.5, 1, 2, 3, and 4) in lettuce cultivation. They found chlorophyll concentration was higher in plants treated with LED than in fluorescent-light treatment.

The highest content of pheophytin a was found in the blue treatment (32.81 µg/mL), coinciding with the high chlorophyll content that this treatment presented (26.96 µg/mL). The high content of pheophytin is probably the result of the conversion of chlorophyll during the leaf drying process since the main route of chlorophyll degradation is by direct or indirect pheophytinization to pheophytin, and the degradation occurs through a variation in temperature [51]. Chlorophyll pheophytinization is the most common alteration of green leaves in food processing, with the consequent change in color from green to an opaque olive-brown [52].

Carotenoids are accessory photosynthetic pigments that capture and transfer light energy to chlorophylls [3]. Additionally, phytosterols such as sitosterol, 2,4-di-tert-butylphenol, campesterol, and stigmasterol, among others [53,54] are frequently reported, along with various carotenoids, including α-carotene, β-carotene, lutein, α-cryptoxanthin/zeaxanthin, and β-cryptoxanthin [13,53]. Furthermore, these compounds have been proposed in the food industry as active agents to mitigate lipid oxidation and control microbial growth. They also find applications in the pharmaceutical and cosmetic sectors, utilized in products such as mouthwashes, eye creams, and various herbal cosmetics [55].

The highest carotenoid content was found in the red treatment (5.88 µg/g), a value 3000 times higher than the treatment outside the greenhouse. Naznin et al. [56] cultivating lettuce, spinach, kale, basil, and sweet pepper in red and blue light demonstrated an increase in the concentration of carotenoids. From these results, it appears that the red treatment was the one that most positively affected the development of the photosynthetic system, indicating that phytochemical accumulations in P. aculeata plants were predominated by red light.

Phytochemicals are naturally occurring compounds in plants that contribute to their color, flavor, and resistance to pests and environmental stress. In P. aculeata, various phytochemicals have been reported in its composition as products of its metabolism, including phenolic compounds such as phenolic acids (caffeic acid derivatives) and flavonoids (quercetin, kaempferol, and isorhamnetin glycoside derivatives) [15]. Phenolic compounds represent a significant group of secondary metabolites produced by plants. They attract attention due to their diverse bioactive properties, including antioxidant, antihypertensive, and antimicrobial activities, and their ability to inhibit carcinogenesis.

The total phenolic compounds were evaluated using aqueous extract and hydroethanolic extract to determine which extract would extract the highest content of phenolic compounds. The total phenolic compounds in the treatments’ extracts ranged between 0.17 and 4.19 mg GAE/g (

Table 7. Total phenolic compounds and antioxidant activity of P. aculeata dry leaves grown under different treatments, with two control treatments (with no LED lights), one outside the greenhouse (C-out) and the other inside the greenhouse (C-ins), and the others inside the greenhouse with different light quality spectrums being monochromatic red (600–700 nm) (Red), monochromatic blue (400–490 nm) (Blue), white (400–700 nm) (White), and blue–red (1:1) (Blue–Red).

	Total Phenolic Compounds		Antioxidant Activity
	Hydroethanolic Extract (mg GAE/g)	Aqueous Extract (mg GAE/g)	DPPH (IC50 μg/mL)	ABTS (μM trolox/g)	FRAP (mmol Fe2+/g)
C-Out	4.15 ± 0.03 a	3.80 ± 0.01 b	181.31 ± 0.12 a	4.48 ± 0.21 b d	0.07 ± 0.02 a
C-Ins	4.19 ± 0.02 a	4.13 ± 0.08 a	36.60 ± 0.11 d	46.58 ± 0.17 a	0.04 ± 0.23 b
Red	1.01 ± 0.03 c	0.59 ± 0.02 d	34.76 ± 0.09 d	33.18 ± 0.19 a	0.06 ± 0.21 a
Blue	1.50 ± 0.01 b	0.89 ± 0.02 c	133.79 ± 0.14 c	10.48 ± 0.22 b	0.07 ± 0.03 a
White	0.98 ± 0.01 d	0.17 ± 0.09 d	157.18 ± 0.11 b	35.12 ± 0.15 c	0.06 ± 0.19 a
Red–Blue	4.19 ± 0.01 a	0.36 ± 0.13 b	122.10 ± 0.21 c	33.69 ± 0.16 c	0.01 ± 0.04 c

Mean and standard deviation followed by different letters on the same column indicate a significant difference between treatments, at a level of 5%, using the Tukey test.

). The total phenolic compounds of the hydroethanolic extract were more expressive than the aqueous extract, which created the realization that there is a greater extraction efficiency of compounds when there is a mixture of solvents due to the polarity of the chemical structures of the compounds with the extracting solvents. The C-ins treatment resulted in a higher concentration of total phenolic compounds in both solvents (4.19 and 4.13 mg GAE/g for the hydroethanolic and aqueous extracts, respectively). Torres et al. [46] found values similar to these, which studied the total phenolic compounds in different extracts of P. aculeata leaves and obtained 4.19 mg GAE/g for extracts obtained through supercritical fluid extraction at 50 °C.

The phenolic compounds in P. aculeata leaves are mainly derived from flavonoids and organic acids. The phenolic profile of the hydroethanolic extract of P. aculeata leaves shows the presence of quercetin derivatives, caffeic and cartharic acids, kaempferol 3-O-rutinoside, and isorhamnetin derivatives [57].

The antioxidant activity of extracts from treatments was determined by DPPH, ABTS, and FRAP methods (Table 7). Various methods are available for evaluating the antioxidant activity of plant compounds, as these components may exhibit unique characteristics, requiring assessment approaches that accommodate such variability. Antioxidant activity assays like FRAP, ABTS, and DPPH each possess distinct properties, enabling a more comprehensive and detailed analysis of the antioxidant potential of compounds found in P. aculeata [15]. The FRAP method evaluates the electron-donating capacity of a sample in an acidic environment, while the ABTS method identifies both lipophilic and hydrophilic antioxidants over a broad pH range. In contrast, the DPPH method measures the ability to neutralize the DPPH radical, thereby inhibiting chain oxidation reactions [58]. When expressed in IC₅₀, they represent the sample concentration that reduces 50% of the DPPH radical. Therefore, the lower IC₅₀ represents the better antioxidant capacity. Extracts from the C-ins and red treatments were the most efficient in eliminating the DPPH radical (IC₅₀ = 36.60 and 34.76 μg/mL, respectively). Except for C-ins and red treatments, all other treatments showed higher antioxidant capacity than those determined by Garcia et al. [15] (IC₅₀ = 72.9 µg/mL). Torres et al. [46] also obtained higher antioxidant capacity using the DPPH method (IC₅₀ = 310 to 7830 µg/mL) when evaluating extracts from P. aculeata leaves obtained by different extraction methods.

As in the DPPH evaluation, C-ins (46.58 μM trolox/g) and red (33.18 μM trolox/g) treatments showed a higher ability to scavenge the ABTS radical. Ciríaco et al. [40] determined the antioxidant activity of P. aculeata leaf flour and obtained a lower ABTS radical scavenging value (6.30 μM trolox/g) than that found in the present work.

Using the FRAP method, it was possible to observe the high efficiency of the extracts obtained by almost all treatments, except for C-ins and red-blue treatments. The high content of chlorophyll a and total phenolic compounds in the P. aculeata dry leaves grown inside the greenhouse is directly linked to its greater antioxidant power [51].

No bioactive compound studied in the present work demonstrated a significant Pearson correlation with the antioxidant activity methods. Interestingly, total phenolic compounds of hydroethanolic extract resulted in a significant inverse correlation with the FRAP antioxidant capacity method (−0.85). The in vitro determination of antioxidant activity is important for predicting this potential; however, once this result is positive, its relationship with in vivo antioxidant activity must be evaluated [59]. Furthermore, it is important to use more than one method to determine antioxidant activity in vitro, since each method may suffer different interferences and determine the antioxidant capacity of compounds of different natures [60].

Thermal Characterization

Differential scanning calorimetry (DSC) analysis was performed to observe exothermic or endothermic changes in P. aculeata dry leaves under different lights. Figure 1 presents the DSC of P. aculeata dry leaves grown under different light spectrums.

For a given endothermic event, higher temperatures than others for different samples may indicate that these samples have higher thermal stability. In terms of energy, the higher the energy required to be absorbed by a sample to carry out this process, the higher its stability and organization within the particles, as the fusion of a highly organized material requires more energy to break the forces within the particle that the fusion of a disordered material [61].

A broad endothermic peak occurred in all samples, with the curves centered at 87.69 (red-blue treatment) to 113.17 °C (blue light), depending on the matrix, and was characterized as the evaporation of residual water present in the P. aculeata dry samples. Dry samples melting temperatures were higher in C-out (125.51 °C), red (120.59 °C), and blue (136.04 °C) treatments. The enthalpy values of P. aculeata dry leaves subjected to C-ins (37.12 J/g) and red-blue (48.19 J/g) treatments were visibly lower when compared to the other samples.

In this study, the flour obtained from the cultivation of P. aculeata under blue light showed higher enthalpy (196.99 J/g) and melting temperature (136.04 °C) when compared to the other treatments, indicating better thermal stability and resistance of the compounds present in the sample.

The production of P. aculeata using different LEDs enabled the acquisition of plant material with high levels of protein (29.68 g/100 g), crude fiber (34.44 g/100 g), and a high content of bioactive compounds, making it suitable for various applications, especially as a food ingredient. Moreover, this approach has an appeal within the sustainability theme, as it allows producing a food component under controlled conditions, which is particularly important in areas where climatic events and significant climate changes can interfere with the production of specific foods.

4. Conclusions

This study can demonstrate that the red LED lighting was the treatment that provided the best results in the cultivation of P. aculeata. The red LED maximized production, presenting more intense biometric characteristics, with a 50% increase in leaf area when compared to cultivation outside the greenhouse. The red LED enhances leaf growth by optimizing photosystem I and II balance, thereby improving photosynthetic efficiency and quantum yield. This effect underscores the importance of wavelengths in maximizing plant productivity, suggesting that further studies on different plant species are needed to optimize cultivation practices and improve overall productivity and quality.

Regarding nutritional characteristics, it presented high protein content (29.68 g/100 g), crude fiber (34.44 g/100 g), ash (20.28 g/100 g), and lipids (3.44 g/100 g) in the red LED. As for pigments, it showed a higher content of chlorophyll a (28.27 µg/L) and total carotenoids (5.88 µg/g). The blue LED light intensified the concentration of minerals and provided greater thermal stability. Regarding bioactive properties, cultivating P. aculeata inside the greenhouse favored the concentration of phenolic compounds and a greater antioxidant capacity.

Therefore, it was evident that the use of LED lights changed the characteristics of P. aculeata, with red light having the most pronounced effect on cultivation. Therefore, this study confirms the efficiency and favorability of growing plants using LED lights.