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Article

A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce

by
Tatiana P. L. Cunha-Chiamolera
1,
Tarik Chileh-Chelh
2,
Mohamed Ezzaitouni
2,
Miguel Urrestarazu
1,
Juan de Dios Carrillo Montalbán
1 and
José Luis Guil-Guerrero
2,*
1
Department of Agronomy, University of Almeria, La Cañada de San Urbano s/n, 04120 Almeria, Spain
2
Food Technology Division, ceiA3, CIAMBITAL, University of Almeria, La Cañada de San Urbano s/n, 04120 Almeria, Spain
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(5), 558; https://doi.org/10.3390/horticulturae11050558
Submission received: 10 April 2025 / Revised: 16 May 2025 / Accepted: 18 May 2025 / Published: 21 May 2025
(This article belongs to the Special Issue LED Lighting Effects on the Growth and Development of Fruits and Vegetables)
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Abstract

:
This study investigates the potential of a biostimulant derived from the invasive brown alga Rugulopteryx okamurae (RoB) to enhance lettuce growth and improve its phytochemical profile. The extraction of the biostimulant was optimized through the implementation of a Box–Behnken design, and the resulting extract was then compared with a commercial Ascophyllum nodosum-based product (AnB). This comparison was made under both optimal and suboptimal fertigation conditions in a controlled, soilless culture. Lettuce plants were monitored for water and nutrient uptake, growth parameters, and accumulation of key phytochemicals such as carotenoids, tocols, sterols, and squalene. RoB significantly increased fresh and dry biomass, with enhanced nitrate and potassium uptake, in comparison to standard nutrient solution controls (p < 0.05). Treatments incorporating RoB consistently resulted in higher concentrations of lutein, β-sitosterol, and squalene, particularly under suboptimal conditions (p < 0.05), thus suggesting a strong biostimulant effect that mitigates nutrient stress. Furthermore, principal component analysis demonstrated that biostimulant application induces distinct metabolic profiles, highlighting the coordinated regulation of antioxidant pigments and sterol compounds. The findings support the dual benefits of algae-derived biostimulants in promoting sustainable crop production by improving yield quality and increasing health-promoting phytochemicals, paving the way for innovative, eco-friendly fertilization practices in modern agriculture.

Graphical Abstract

1. Introduction

Seaweed extracts have been used in agriculture as soil conditioners or as plant growth biostimulators [1,2]. In agriculture, macroalgae have been used to compensate the deficiency of plant nutrients, for instance of N, P, and K. It has been reported that seaweed extracts stimulate seed germination, induce better root development, enhance frost resistance, and increase nutrient uptake, improve resistance to pests, and allow high yields [3,4,5]. Moreover, the better performance of seaweed manure in comparison to the conventional organic one has been reported [6]. Nearly 47 companies worldwide are manufacturing extracts from Ascophyllum nodosum for agricultural and horticultural applications [3,7,8,9,10].
Beach macroalgae have been suggested as a possible raw material for organic fertilizers [11], and currently, macroalgae are under investigation as biostimulants [4,12]. The nutrient-rich algal biomass with a high content of organic material and inorganic nutrients can be used directly as an organic fertilizer for the soil [5,13], or nutrients can be extracted from the biomass [14]. Macroalgal biostimulants have been shown to stimulate plant growth and yield with beneficial effects on root development and mineral absorption, enhancement of plant chlorophyll, crop yield, and resistance to environmental and biotic stresses [12]. Among macroalgae, brown ones are commonly used for biostimulant production, given that they are rich in polysaccharides such as alginates, fucoidans, and laminarin, which enhance the natural defense response of plants [7,15]. Until recently, every EU member state applied its policies to regulate the acceptance, marketing, and use of biostimulants in agriculture. Considering the fast-growing biostimulants market, the Regulation EU 2019/1009 [16] is timely, as it lays down a common definition and regulations for biostimulants. In the regulation, biostimulants are defined as “products that stimulate plant nutrition processes independently of the product’s nutrient content by improving plant’s nutrient use efficiency, tolerance to abiotic stress, quality traits, or availability of confined nutrients in soil or rhizosphere”. Maximum limits for heavy metals are defined in the regulation, and this content poses some restrictions to the use of macroalgae as biostimulants. Depending on the water quality, macroalgae may accumulate notable quantities of heavy metals, whose maximum levels (cadmium, hexavalent chromium, mercury, nickel, lead, and inorganic arsenic) have been defined in Regulation EU 2019/1009 [16]. Moreover, the newly established maximum level for cadmium in biostimulants in the EU is 1.5 mg kg−1 [16]. Thus, the harvesting site and species composition should be considered to avoid harmful concentrations of heavy metals.
The utilization of biofertilizers derived from macroalgae demonstrated favorable outcomes in promoting lettuce growth and yield while sustaining optimal electrical conductivity (EC) levels in the nutrient solution. For instance, Macrocystis pyrifera extracts have been evidenced to enhance seed germination, root growth, and seedling establishment, thereby augmenting nutrient and water uptake [17]. The combination of these biostimulants with the plant growth-promoting bacterium Azospirillum brasilense has been shown to further enhance lettuce growth under a wide range of irrigation treatments, suggesting a synergistic effect [17]. Additionally, macroalgal extracts help plants adapt to unfavorable conditions, such as water deficits, when the crop is being cultivated under optimal conditions. Consequently, numerous researchers examined the potential benefits of various factors, including cultural management, active material, and biostimulants, under both optimal and suboptimal conditions. These studies revealed substantial variations in the observed benefits [18,19].
The study’s primary hypothesis is that biofertilizer derived from the brown macroalga R. okamurae will enhance the productivity and quality of lettuce crops, with results comparable to those achieved with other biofertilizers derived from the brown macroalga A. nodosum, a common agricultural product. To this end, the study examined the effects of bioactive extracts in the nutrient solution on achieving optimal plant growth and determined the concentration of bioactive compounds in the harvested vegetable products.

2. Materials and Methods

2.1. Solvents and Reagents

Unless otherwise stated, all solvents and reagents used in the current work were purchased from Merck (Madrid, Spain).

2.2. Biostimulant Obtainment

Raw samples of R. okamurae were collected in December 2023 on the coast of Benalmádena (Málaga, Spain; geographic coordinates 36.580544, −4.539112) and delivered refrigerated to the laboratory. The taxonomic identification of R. okamurae was confirmed by optical microscopy images (Supplementary File S1). Samples were then washed with distilled water to remove salt, epiphytes, and sand, and stored at 4 °C until biostimulant obtainment.
The preparation of the biostimulant began by placing the biomass of R. okamurae in an oven at 60 °C for 72 h for drying. Then, the dried algal biomass was ground into a powder form and screened through 20–80 mesh sieves. The biostimulant consisted of algae extract, which was obtained using distilled water. The maximum yield variables were fine-tunned through a response surface experimental design of Box–Behnken, in which the algae:solvent ratio (1:10, 1:20, and 1:30, w/v), extraction time (1, 2, and 3 h), and extraction temperature (20, 40, and 60 °C), were considered. The extraction yield was determined by drying all the extracts at 100 °C. The maximum dry extract yield (4.2 g of extracts by 100 g dry algae) was obtained under the following conditions: 3 h, 60 °C, algae:solvent ratio of 1:30 (w/v), and using pure water as an extracting solvent. After extraction, the supernatant was filtered through a 0.22 μm filter paper using a vacuum filtration assembly.
The biostimulant extract obtained was stored at 4 °C until utilization, with a maximum duration of three days. Both the commercial biostimulant from A. nodosum, which yielded a dry residue of 11.5% on dry weight (dw), and the experimental biostimulant from R. okamurae obtained as described above, were diluted to the same dry matter concentration before use.

2.3. Biostimulants Analysis

Two biostimulants were checked in this work as indicated below. One of them was the biostimulant obtained from A. nodosum (Jospalga 25, AnB), which was supplied by Interjospal S.L. (Almería, Spain). Another assayed biostimulant was obtained from R. okamurae in the laboratory (RoB), and both were analyzed following the procedures described by Rincón-Cervera et al. [20]. The composition of both biostimulants is detailed in Table 1.
Alginate, mannitol, and phlorotannin’s were determined as previously reported [20], following the protocols described in Supplementary File S2. Trace elements were measured in each digested sample by inductively coupled plasma-mass spectrometry (ICP-MS) using a Hewlett Packard 4500 STS spectrometer (Hewlett Packard, Palo Alto, CA, USA), following the methodology of González et al. [21], as detailed in Supplementary File S2.

2.4. Lettuce Samples

Table 2 details the treatments developed in the experimental crops. The treatments are grouped into two conditions: (i) under optimal growing conditions; and (ii) suboptimal conditions. Then, the following culture conditions were set: T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimum of fertigation conditions; and tR = t0 + RoB; tA = t0 + AnB. The suboptimal conditions were assayed considering that the response to biostimulants can differ depending on the environmental conditions [18,19].

2.5. Fertigation Parameters and Crop Conditions

Both the commercial biostimulant from A. nodosum and the experimental biostimulant from R. okamurae obtained as described above were diluted to the same concentration of dry matter before use.
The experiment was carried out in controlled growth chambers located at the University of Almeria (Spain) from 13 November to 9 December 2023. The environmental variables in the chamber were a photoperiod of 16/8 h (day/night), at 18 to 22 °C, at a relative humidity of 65 to 75% and at a photosynthetic photon flux density of 250 μmol m−2 s−1 (400–700 nm) provided by L18 T8 AP67 LED lamps (Valoya, Helsinki, Finland), and the experiment’s duration was a 30-day cycle. Seedlings with four true leaves of lettuce cv “Maravilla de Verano” were transplanted into 250 mL plastic pots filled with coconut fiber. The two algal-based biostimulant types were dissolved in the nutrient solution and compared to standard fertigation de 2.0 dS m−1 y 5.8 de pH (Supplementary Table S1). The doses incorporated into the nutrient solution of the AnB were designed as indicated in the commercial product data sheet (JOSPALGA 25 ECO®, Interjospal, Almeria, Spain), while RoB was dosed so that the concentration of its dry matter was equivalent to the AnB one.
The fertigation management in the experiment was carried out following the criteria of Peçanha et al. [22]. The application of new fertigation was supplied when the plant transpired a ratio volume of water corresponding to 10% of the readily available water of substrate, and an extra volume was supplied to obtain a 15–25% drainage [22]. The pH, EC, nitrate, and potassium content of the nutritive solution and the drainage volume were measured using a Crison MM40+ pH meter (Hach® LPV2500.98.0002, Loveland, CO, USA), an EC-Meter Crison BASIC 30 conductivity meter (Hach® LPV2500.98.0002, Loveland, CO, USA), and a LAQUATwin B-742 and B-731 (Horiba®, Moulton, Northampton, UK), respectively. The ratio of drainage was measured using a test tube graduated to one-hundredth of a millimeter.

2.6. Growth Parameters and Sample for Chemical Analysis

The lettuce plants were harvested 30 days after transplantation at the tender leaf stage (16–17 leaves). Four plants of each treatment were divided by their different organs; the fresh weight (fw) of roots, stems, and leaves was measured, and then the dw was obtained by placing the material in an oven (Thermo Scientific Heratherm, Waltham, MA, USA) at 85 °C until reaching a constant weight. A precision analytical balance (model AX 124/E, OHAUS Corporation, Parsippany, NJ, USA) was used, expressing the result as g plant−1.
For chemical analysis, five plants per treatment from each replicate were harvested. After collecting, the plants were stored in thermal bags and frozen at −24 °C until processing. Once in the laboratory, they were labeled, weighed, measured, and placed into a glass desiccator until analysis.

2.7. Carotenoids Analysis

Carotenoids were extracted using acetone, as detailed in Supplementary File S2, following the procedure of Kimura and Rodríguez-Amaya [23]. High-performance liquid chromatography (HPLC) analyses of the carotenoid profiles were conducted using a Finnigan Surveyor chromatograph (Thermo-Finnigan, San Jose, CA, USA) equipped with a diode array detector (DAD) (Thermo-Finnigan, San Jose, CA, USA), and a reverse-phase C18 column. A 450 nm-HPLC-DAD chromatogram of a lettuce sample (Supplementary Figure S3) is included in Supplementary File S2. Quantification of the compounds was achieved using external calibration curves prepared with pure β-carotene.

2.8. Tocopherol and Tocotrienol Analysis

The extraction and quantification of tocopherols (Tp) and tocotrienols (T3) were carried out according to Fabrikov et al. [24] with some modifications. This methodology is fully described in Supplementary File S2. HPLC analyses of Tp and T3 were conducted using the previously described HPLC-DAD system at a constant temperature of 30 °C. The mobile phase consisted of methanol:acetonitrile (95:5, v/v, phase A) and 2-propanol:n-hexane (50:50, v/v, phase B), with a flow rate of 0.5 mL min−1. The total running time was 60 min. A 290 nm-HPLC-DAD chromatogram of a lettuce sample (Supplementary Figure S4) is shown in Supplementary File S2. The identification of peaks was based on Tp and T3 homologues (α, β, γ, and δ).

2.9. Phytosterols and Squalene Analysis

Phytosterols and squalene were quantified according to the Fabrikov et al. [24] procedure, as detailed in Supplementary File S2. Quantification was effected using calibration curves built with pure standards: stigmasterol, β-sitosterol, campesterol, and squalene. The results are expressed in mg 100 g−1 fw. HPLC analyses of phytosterols and squalene were conducted using the previously described HPLC system at a fixed temperature of 30 °C. An isocratic elution system was employed using a binary solvent mixture (methanol:acetonitrile, 70:30, and v/v), with a flow rate of 0.4 mL min−1 maintained for 45 min. The injection volume was 10 µL, and detection was performed at a wavelength of 210 nm. A 210 nm-HPLC-DAD chromatogram of lettuce (Supplementary Figure S5) is shown in Supplementary File S2. Quantification of the compounds was achieved using external calibration curves prepared with pure compounds.

2.10. Statistical Analysis

A randomized complete block design [25] was utilized to evaluate the effect of various treatments on lettuce growth. The experiment consisted of four replicates per treatment, with six plants allocated to each experimental unit. Chemical analyses were carried out in triplicate and results are reported as mean value ± standard deviation. Data were first assessed for normality using the Shapiro–Wilk test. A one-way ANOVA was then conducted, with mean separation carried out by Duncan’s multiple-range test and significance defined as p < 0.05 (Tukey’s criterion). Principal component analysis (PCA) and all other statistical procedures were performed in Statgraphics® Centurion XVI (StatPoint Technologies, Warrenton, VA, USA).

3. Results

3.1. Effect of Biostimulant Application via Fertigation on Monitoring Parameters

The fertigation drainage volume fraction ranged between 0.2 and 0.3, ensuring that the matric potential of the nutrient solution in the substrate remained within an optimal range [22]. EC values between 1 and 2 dS m−1 above the fertigation levels are considered acceptable for maintaining a suitable osmotic potential in the rhizosphere [5,22]. All treatments maintained EC values within this acceptable range, with an increase of approximately 1–2 dS m−1 above the supplied fertigation levels.
Throughout the cultivation period, drainage EC values remained stable but varied among treatments, reaching up to two units above the fertigation values by the end of the experiment (Supplementary Figure S1). As shown in Supplementary Figure S1B, the average EC of drainage values differed significantly among treatments, influenced by both the type of biostimulant applied and the fertigation system. The highest drainage EC values were observed in the treatment that combined standard optimal fertigation with R. okamurae biostimulant.
The pH values exhibited stability across all treatments, maintaining a consistent range between 6.9 and 7.4 during the cultivation process (see Supplementary Materials, Figure S1C). The lowest recorded pH value was observed in the standard optimum fertigation biostimulant treatment, measuring 1.2 units above the fertigation pH of 5.8 (Supplementary Figure S1D). The mean pH of drainage across treatments was 7.25, indicating optimal growth, as this value falls within the range of 1–2 units above the standard fertigation pH of 5.8 [5,22].

3.2. Effect of Biostimulants on Fertigation Uptake and Growth Parameters

From the first to the fourth week post-transplantation, water consumption increased by over 100% across all treatment groups (Figure 1A). It was demonstrated that treatments cultivated under optimal fertilization conditions exhibited elevated levels of water uptake from the second week onwards, compared to those grown under suboptimal conditions. Furthermore, throughout the entire crop cycle, plants receiving a full nutrient solution exhibited an average water absorption rate 25.8% higher than those subjected to nutrient-deficient conditions (Figure 1B).
Nitrate and potassium uptake followed a pattern similar to water absorption, with significant differences among treatments (Figure 1). Nitrate uptake increased linearly throughout cultivation, whereas potassium uptake remained relatively constant, except for a notable fluctuation in the TR treatment during the second week (Figure 1C,E). While nitrate uptake was generally higher under optimal fertigation, potassium absorption was higher in the TR and TA treatments (Figure 1D,F).
Fresh and dry biomass yields mirrored the trends observed for water and nutrient uptake (Figure 2). The different treatments had a significant impact on production, with a 50% reduction in mineral nutrition (representing suboptimal fertigation) leading to a 38% and 20% decline in fw and dw, respectively. The application of biostimulants in the nutrient solution had varying effects depending on fertigation conditions. Under optimal fertigation, both tested algal biostimulants demonstrated a clear benefit, with RoB increasing fw and dw by 13% and 5.6%, respectively. Notably, RoB also exhibited a positive effect under suboptimal conditions, reinforcing its potential as a growth enhancer.
The effects of the two seaweed extracts were found to be significantly divergent under optimal and suboptimal conditions (see Table 3). A comparison with the control revealed that the biostimulant effect of the two algal extracts was significantly more pronounced under optimal fertigation conditions (15%) than under suboptimal conditions (9%). In all conditions, the extract of R. osmophila exhibited a biostimulating effect on both fertigation (water, nitrate, and potassium uptake) and yield (dry and fresh weight), whereas the extract of A. nodosum demonstrated a clear positive effect only under optimal fertigation conditions.

3.3. Phytochemicals Content in Lettuce

Carotenoid profiles are detailed in Table 4. Total carotenoids were highest in lettuce grown with algae-based biostimulants, regardless of nutrient solution concentration. The highest carotenoid content was quantified in TA, tR, tA, and TR, with 15.8, 15.5, 15.3, and 15.1 mg 100 g−1 fw, respectively. The lowest carotenoid content was detected in the T0 samples (10.8 mg 100 g−1 fw), indicating that the standard nutrient solution alone resulted in significantly lower carotenoid accumulation. Lutein, the main carotenoid, increased in biofertilizer-treated samples, especially in TR and tR, suggesting that RoB stimulated lutein accumulation.
Tocols, sterols, and squalene are detailed in Table 5. The highest total tocol content was found in samples grown using RoB, in tR (0.57 mg 100 g−1 fw), which was significantly higher than the control, t0 (0.46 mg 100 g−1 fw).
The highest total sterol content was also found in tR (30.8 mg 100 g−1 fw), followed by TR (29.1 mg 100 g−1 fw). Lettuces treated with R. okamurae had a notable increase in sterol content, particularly β-sitosterol. The highest squalene content was found in tR (0.2 mg 100 g−1 fw), while it was undetected in t0. This suggests that biostimulation enhances squalene accumulation even under suboptimal conditions.

3.4. Principal Component Analysis

To investigate the potential relationship between the analyzed parameters and the sample characteristics, PCA was performed (Figure 3). The PCA was executed using the dataset encompassing all the variables presented in the plot. The analysis yielded 26 components. Collectively, these components account for 100.0% of the variability observed in the original data. The initial two components accounted for 38.14% and 20.63% of the total variance, respectively, representing 58.77% of the total variability. The biplot, a unique feature of PCA tools, facilitated a more nuanced interpretation of the data. The horizontal axis corresponds to PC1, while the vertical axis corresponds to PC2. Through geometrical representation, it is possible to observe that the samples can be grouped according to their values for the measured variables.

4. Discussion

4.1. Effect of Biostimulant Application via Fertigation on Monitoring Parameters

The fractions of drainage volume, electrical conductivity (EC), and pH are key parameters for monitoring and controlling nutrient solution management in fertigation systems [22]. As shown in Supplementary Table S2, under standard fertigation conditions with adequate drainage EC, the correlation between fertigation parameters, such as water and nutrient uptake, and yield was not significantly affected. Drainage pH showed a significant correlation with the assessed parameters of fertigation monitoring, consistently displaying a negative relationship with the amount of water uptake.
Classical research by Arnon and Johnson [26] established that an acidity level between 5.0 and 6.0 provides optimal conditions for lettuce cultivation. This finding suggests that, under standard fertigation conditions, pH values can serve as a reliable indicator for monitoring and optimizing crop fertigation [5,22].

4.2. Effect of Biostimulants on Fertigation Uptake and Growth Parameters

Among all evaluated parameters, water uptake exhibited the strongest correlation with crop production, consistent with findings under similar lettuce cultivation conditions [5]. Compared with control and Ascophyllum extract, R. okamurae extract showed a biostimulant effect on water uptake in both optimal and suboptimal fertigation. Atero-Calvo et al. [27] recently identified a significant biostimulant effect on the uptake of essential nutrients in lettuce plants by applying Macrocystis algae extract in conjunction with a mixture of amino acids, corn steep liquor extract, calcium, and the bioactive compound glycine betaine. In contrast, contrary to the findings of Shukla et al. [7], the extract from A. nodosum did not confer any significant benefits when plants were subjected to a suboptimal nutrient solution. Notably, the average biostimulant effect observed at harvest, measured through fresh and dry biomass, was 15 percentage points higher than uptake indicators such as water and nitrate absorption. Ergun et al. [28] and Julia et al. [17] also observed a significant positive effect on the growth of lettuce plants when using a different seaweed extract from Chlorella vulgaris and M. pyrifera, respectively.

4.3. Effect of Biostimulants on the Phytochemical Composition of Lettuce

It has previously been documented that algae have a beneficial effect on the growth and nutrient composition of lettuce. For instance, a low concentration of algae (15% C. vulgaris and 25% Ulva lactuca) in the extracts contributed to the production of plants with a satisfactory nutritional profile (gross composition and mineral elements), while a high concentration (75% U. lactuca) was conducive to lettuce production with some parameters not suitable for human diet and health [29]. Furthermore, the application of a combined biostimulant consisting of plant growth-promoting bacteria and freshwater algae (C. vulgaris) significantly affected the plant weight of both romaine and leaf lettuce in the spring and summer seasons [29]. Furthermore, an increase in total antioxidant capacity and total carotenoid content was observed in the summer crop of romaine lettuce [30]. Furthermore, the incorporation of C. vulgaris within the nutrient solution employed in hydroponic lettuce production has been shown to reduce the volume of solution by up to 60%, whilst concomitantly increasing the total soluble solids (°Brix) and vitamin C content of the plants [28]. The application of a biostimulant comprising Macrocystis algae extract and a mixture of biostimulant compounds to the green leaves of lettuce has been shown to enhance growth and quality parameters, including phenolic compounds, ascorbate, and antioxidant capacity [27]. In a separate study, lettuce cultivated in hydroponic experiments with a biostimulant derived from the microalgae Tetradesmus obliquus increased lipids, protein, some enzymatic activity, chlorophylls, and polysaccharides [31].
To date, a few experiments have been conducted using biostimulants derived from algae, in which the nutritional composition of lettuce was analyzed. However, the phytochemical modification of lettuce induced by using invasive algae, such as R. okamurae, remains unexplored. In the present study, the application of algae-derived biostimulants resulted in enhanced accumulation of key phytochemicals in lettuce cultivated under both standard (T0) and suboptimal (t0) nutrient conditions, as compared with controls that utilized the nutrient solution alone. The total carotenoid content in the biofertilized treatments (TA, TR, tA, and tR) ranged from approximately 15.1 to 15.8 mg 100 g fw−1, compared with 10.8 mg 100 g−1 fw in the T0 treatment. A similar trend was observed in the levels of tocols and sterols, with the tR treatment (a suboptimal nutrient solution augmented with RoB) exhibiting significantly elevated values.
Within the biostimulant treatments, the RoB one (TR, tR) demonstrated notable efficacy in enhancing lutein, sterols (particularly β-sitosterol), and squalene content. Conversely, the AnB (TA, tA) exhibited a predominant effect on total carotenoids and β-carotene, though its influence on sterols and squalene was less pronounced. On the other hand, in scenarios where nutrient input is suboptimal, biostimulants are effective in compensating for reduced nutrient input, as evidenced by the higher phytochemical levels observed in the tR treatment.
The enhanced phytochemicals under scrutiny in this study have been demonstrated to be of significance to health. Carotenoids such as lutein, β-carotene, and zeaxanthin have been shown to play crucial roles in protecting against oxidative stress, maintaining eye health, and potentially preventing chronic diseases. Their antioxidant properties and their ability to filter out harmful light have been demonstrated to support these benefits [32,33]. Tocols (vitamin E compounds) contribute to cellular protection by scavenging free radicals [34,35], while plant sterols have been associated with cholesterol-lowering effects [36,37]. The presence of squalene, with its potential cardio-protective and chemopreventive properties [38,39], further improves the nutritional profile of the lettuce.
From an agronomic perspective, the utilization of green biostimulants derived from algae supports sustainable cultivation practices (Rouphael and Colla [40]). These biostimulants enhance the nutritional quality of lettuce by increasing health-promoting phytochemicals, thus offering a viable strategy for reducing conventional chemical fertilizer inputs. This approach is consistent with current trends in sustainable agriculture, which aim to enhance crop quality while minimizing environmental impacts.

4.4. Principal Component Analysis

In the biplot analysis, it is evident that variables with longer vectors exert a greater influence on PCs. For instance, as illustrated in Figure 3, DW and several carotenoids exhibit prominent vectors along PC1, thereby underscoring their significance in differentiating the treatments. Vectors that are close in angle indicate a positive correlation. For instance, the close grouping of sterol-related compounds supports the idea that their biosynthesis is interlinked. The analysis suggests that PC1 (38.1% of variance) captures overall differences in plant growth and metabolic status. Treatments with optimal nutrient conditions (T0, TR, and TA) and those under suboptimal conditions (t0, tR, and tA) separate along this component. Variables that exhibit strong loading on this component (e.g., DW, certain carotenoids, and sterol compounds) are found to be influential in explaining differences in biomass accumulation and metabolic profiles. Concerning PC2 (which accounts for 20.6% of the variance), this axis appears to accentuate more subtle biochemical distinctions, potentially indicative of stress responses or alterations in pigment composition. It is further hypothesized that variables such as different xanthophylls (violaxanthin, zeaxanthin) and specific antioxidant-related compounds may be more pronounced along this axis.
Concerning the relationships among the measured variables, the antioxidant carotenoids (violaxanthin, zeaxanthin, anteraxanthin, luteoxanthin, cryptoxanthins, and total carotenoids) have been observed to tend to align in analogous directions. This observation suggests a potential for co-regulation of these pigments [41]. This co-variation may indicate that under both optimal and suboptimal conditions, the plant modulates these compounds as part of its photoprotection and oxidative stress management systems [42]. Regarding sterols (campesterol, sitosterol, stigmasterol, and total sterols) and squalene, there is a notable co-variation, suggesting a coordinated regulatory mechanism. The grouping of these compounds suggests that changes in membrane composition or signaling lipids are integral to how plants adjust to different nutrient regimes and biostimulant applications. These influence sterol composition and signaling pathways, potentially enhancing plant growth and stress tolerance. The specific mechanisms and outcomes depend on the types of biostimulants and the plant species involved [43]. As shown in Figure 3, total St, β-sitosterol, and campesterol exhibit negative loadings for both PC1 and PC2, indicating their orientation towards the suboptimal tR treatment. This observation suggests an increased concentration of these compounds in response to a limited nutrient supply, a finding that aligns with previous reports on how nutrient limitation can trigger metabolic adjustments in plants, i.e., microalgae increase sterol production under nutrient stress [44].
About biomass and nutrient-related traits: DW is a critical marker of overall growth and is influenced by nutrient availability [45]. It has positive scores for both PC1 and PC2, and its positioning relative to other variables (K, EC, water, nitrate, and FW) suggests that the plant’s biomass accumulation is closely linked to these culture variables and that both treatments (AnB and RoB) induced plant growth.
Concerning the impact of biostimulants, the biplot reveals that the application of biostimulants (RoB and AnB) under standard nutrient conditions results in a metabolic profile that differs from that of the control. The TR and TA clusters near one another imply that, despite employing different biostimulants, their overall impact on the measured metabolites is similar.
Finally, the ubication of optimal vs. suboptimal nutrient conditions (T0, TR, and TA vs. t0, tR, and tA), i.e., full (T0-related) vs. half nutrient solutions (t0-related), indicated that nutrient availability is a strong driver of metabolic change. In the context of suboptimal conditions, the supplementary application of biostimulants (tR and tA) appears to modify the metabolic responses of the plants, potentially mitigating stress or altering specific pathways (e.g., pigment synthesis or lipid metabolism).

5. Conclusions

This study suggests that biostimulants derived from algae, specifically those produced from the invasive brown alga R. okamurae (RoB), could offer significant agronomic and nutritional benefits for lettuce cultivation. The optimized extraction process, utilizing a Box–Behnken experimental design, yielded a biostimulant characterized by an efficient yield of bioactive compounds. When applied under both optimal and suboptimal fertigation conditions in a controlled, soilless system, RoB significantly enhanced water and nutrient uptake, resulting in higher fresh and dry biomass compared to plants receiving the standard nutrient solution. A key finding of this research is the pronounced biostimulant effect of RoB on the phytochemical composition of lettuce. Treatments involving RoB resulted in substantial increases in bioactive compounds, including carotenoids (particularly lutein), sterols (notably β-sitosterol), and squalene. These enhancements are of critical importance in meeting the growing consumer demand for health-promoting food products. In addition, PCA of the dataset revealed that biostimulant application gives rise to discrete metabolic profiles in lettuce. The clear separation between treatments under optimal and suboptimal conditions highlights the role of nutrient availability in shaping metabolic responses. From an agronomic perspective, the findings of this study offer evidence that biostimulants derived from algae could constitute a sustainable alternative to conventional chemical fertilizers. The dual benefits of enhanced yield and increased accumulation of health-promoting phytochemicals offer a promising strategy for the development of resilient, high-quality, and eco-friendly cropping systems. In conclusion, the successful application of RoB not only contributes to the advancement of sustainable agricultural practices, but also provides a viable route to improve the nutritional quality of crops. These findings lay the foundation for further research, including the optimization and broader application of macroalgal biostimulants. Studies aimed at expanding the range of crops and application modes are considered a priority, which will increase the potential to extend their benefits to a wider range of crops and agricultural systems.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11050558/s1, Supplementary File S1: Clues for the identification of Rugulopteryx okamurae and differentiation from Dictyota dichotoma; Supplementary File S2: Material and Methods; Supplementary Table S1: Nutrient solution used for the crop of lettuce; Supplementary Table S2: Pearson correlation matrix of the different parameters of fertigation and growth; Supplementary Table S3: Analysis of the standard reference material 2711; Supplementary Figure S1: Electrical conductivity (A,B) and pH (C,D) of lettuce plants grown in coconut soilless culture under different fertigation with RoB and AnB; Supplementary Figure S2: Differentiation of R. okamurae and D. dichotoma; Supplementary Figure S3: 450-nm HPLC-DAD chromatogram of a lettuce sample; Supplementary Figure S4: 290 nm HPLC-DAD chromatogram of tocols of a lettuce sample; Supplementary Figure S5: 280 nm HPLC-DAD chromatogram of sterols and squalene of a lettuce sample. References [46,47,48,49,50] are cited in the Supplementary Materials.

Author Contributions

Conceptualization, T.P.L.C.-C. and J.L.G.-G.; methodology, T.P.L.C.-C., T.C.-C., M.E., M.U. and J.L.G.-G.; software, T.P.L.C.-C., T.C.-C., M.E., M.U. and J.L.G.-G.; validation, T.P.L.C.-C., M.U. and J.L.G.-G.; formal analysis, T.P.L.C.-C., T.C.-C., M.E., M.U., J.d.D.C.M. and J.L.G.-G.; investigation, M.U. and J.L.G.-G.; resources, M.U. and J.L.G.-G.; data curation, T.P.L.C.-C., T.C.-C., M.E., M.U., J.d.D.C.M. and J.L.G.-G.; writing—original draft preparation, T.P.L.C.-C., T.C.-C., M.U. and J.L.G.-G.; writing—review and editing, J.L.G.-G.; visualization, T.P.L.C.-C., T.C.-C., M.E., M.U., J.d.D.C.M. and J.L.G.-G.; supervision, J.L.G.-G.; project administration, J.L.G.-G.; funding acquisition, M.U. and J.L.G.-G. All authors have read and agreed to the published version of the manuscript.

Funding

The authors acknowledge the financial support of the Vice-Rectorate of Scientific Policy of the University of Almeria (Project LANZADERA 2023/003 and P_FORT_GRUPOS_2023/88).

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary Materials.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Water, nitrate, and potassium uptake per week (A,C,E) and total (B,D,F), respectively, of lettuce plants grown in coconut soilless culture under different fertigations with biostimulants extracted from invasive (R. okamurae) and commercial (A. nodosum) algae. T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimum of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Different letters denote statistically significant differences at p < 0.05.
Figure 1. Water, nitrate, and potassium uptake per week (A,C,E) and total (B,D,F), respectively, of lettuce plants grown in coconut soilless culture under different fertigations with biostimulants extracted from invasive (R. okamurae) and commercial (A. nodosum) algae. T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimum of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Different letters denote statistically significant differences at p < 0.05.
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Figure 2. Fresh (FW—(A)) and dry weight (DW—(B)) of lettuce plants grown in coconut soilless culture under different fertigation with biostimulants extracted from invasive (Rugulopteryx okamurae) and commercial (Ascophyllum nodosum) algae. T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimum of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Different letters denote statistically significant differences at p < 0.05 by Tukey test.
Figure 2. Fresh (FW—(A)) and dry weight (DW—(B)) of lettuce plants grown in coconut soilless culture under different fertigation with biostimulants extracted from invasive (Rugulopteryx okamurae) and commercial (Ascophyllum nodosum) algae. T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimum of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Different letters denote statistically significant differences at p < 0.05 by Tukey test.
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Figure 3. Biplot for the first two component weights. Culture treatments: T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimun of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Abbreviations for measured variables: Anterax—anterxanthin; Total carot—Total carotenoids; Camp—campesterol; α-cryptox—α-cryptoxanthin; DW—dry weight; EC—electrical conductivity; Luteox—uteoxanthin; β-sitost—β-sitosterol; St—sterols; Stigm—stigmasterol; Sq—squalene; T3—tocotrienols; Tp—tocopherols; Violax—violaxanthin; and Zax—zeaxanthin. AnB: Ascophyllum nodosum biostimulant. RoB: Rugulopteryx okamurae biostimulant.
Figure 3. Biplot for the first two component weights. Culture treatments: T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimun of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. Abbreviations for measured variables: Anterax—anterxanthin; Total carot—Total carotenoids; Camp—campesterol; α-cryptox—α-cryptoxanthin; DW—dry weight; EC—electrical conductivity; Luteox—uteoxanthin; β-sitost—β-sitosterol; St—sterols; Stigm—stigmasterol; Sq—squalene; T3—tocotrienols; Tp—tocopherols; Violax—violaxanthin; and Zax—zeaxanthin. AnB: Ascophyllum nodosum biostimulant. RoB: Rugulopteryx okamurae biostimulant.
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Table 1. Bioactive compounds and trace metals content in the biostimulants assayed in this work.
Table 1. Bioactive compounds and trace metals content in the biostimulants assayed in this work.
A. nodosum
(Jospalga 25) a		R. okamurae
Biofertilizer b		Regulation (EU) 2019/1009 [16]
Alginate (g 100 g−1 dw)14.519.4 ± 1.4-
Mannitol (g 100 g−1 dw)5.67.9 ± 0.5-
Phlorotannins (g 100 g−1 dw)0.560.35 ± 0.0-
Arsenic (As) (mg kg−1 dw)2519 ± 140 mg kg−1 dw
Cadmium (Cd) (mg kg−1 dw)0.50.7 ± 0.21.5 mg kg−1 dw
Lead (Pb) (mg kg−1 dw)6046 ± 4120 mg kg−1 dw
a Detailed value on the commercial product label; b experimental values obtained in the present work, which correspond to the mean and SD of three replicates.
Table 2. Composition of the nutrient solution of the fertigation used in each of the treatments.
Table 2. Composition of the nutrient solution of the fertigation used in each of the treatments.
Nutrient SolutionBiostimulant Extracted From:
MacronutrientMicronutrientR. okamuraeA. nodosum
T0100%√--
TR100%√√-
TA100%√-√
t050%√--
tR50%√√-
tA50%√-√
T0 = Nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution, suboptimun of fertigation conditions; tR = t0 + RoB; and tA = t0 + AnB. AnB: Ascophyllum nodosum biostimulant; RoB: Rugulopteryx okamurae biostimulant.
Table 3. Average biostimulation values for fertigation uptake and yield of an extract of Rugulopteryx okamurae and Ascophyllum nodosum applied by standard and deficient fertigation expressed as a percentage increase over a standard solution.
Table 3. Average biostimulation values for fertigation uptake and yield of an extract of Rugulopteryx okamurae and Ascophyllum nodosum applied by standard and deficient fertigation expressed as a percentage increase over a standard solution.
Standard Optimum FertigationSuboptimal Fertigation
TRTAtRtA
UptakeWater6.123.8215.953.06
Nitrate8.027.2721.562.04
Potassium3.032.761.99−8.79
YieldFresh weight33.2916.399.79−6.69
Dry weight39.9032.126.09−1.83
Mean18.0712.4711.08−2.44
T0 = nutrient solution, standard conditions of fertigation; TR = T0 + RoB; TA = T0 + AnB; t0 = ½ nutrient solution (suboptimum of fertigation conditions); tR = t0 + RoB; and tA = t0 + AnB. AnB: Ascophyllum nodosum biostimulant; and RoB: Rugulopteryx okamurae biostimulant.
Table 4. Carotenoid contents (mg 100 g−1 fw) of lettuce samples.
Table 4. Carotenoid contents (mg 100 g−1 fw) of lettuce samples.
Samples dAll-trans-
Violaxanthin		9′-cis-NeoxanthinLuteoxanthinAntheraxanthinLuteinAll-trans-Zeaxanthinα-Cryptoxanthinβ-CryptoxanthinAll-trans-β-CaroteneTotal Carotenoids
mg 100 g−1 fw
T00.9 ± 0.1 d1.8 ± 0.1 d0.3 ± 0.0 b0.1 ± 0.0 a6.3 ± 0.3 c0.1 ± 0.0 atracestraces1.2 ± 0.1 b10.8 ± 0.4 b
TA1.6 ± 0.3 b2.3 ± 0.5 bc0.4 ± 0.1 b0.2 ± 0.0 a8.8 ± 0.4 b0.1 ± 0.0 a0.1 ± 0.0 a0.1 ± 0.0 a2.3 ± 0.3 a15.8 ± 0.8 a
TR1.1 ± 0.1 cd1.9 ± 0.0 cd0.8 ± 0.0 a0.1 ± 0.0 a9.8 ± 0.3 a0.1 ± 0.0 atraces0.1 ± 0.0 a1.2 ± 0.2 b15.1 ± 0.3 a
t02.1 ± 0.0 a2.7 ± 0.1 a0.5 ± 0.1 ab0.2 ± 0.0 a4.4 ± 0.5 c0.1 ± 0.0 a0.2 ± 0.0 a0.1 ± 0.0 a1.1 ± 0.1 b11.4 ± 0.5 b
tA1.6 ± 0.1 b2.8 ± 0.3 a0.4 ± 0.1 b0.1 ± 0.0 a8.8 ± 0.4 b0.1 ± 0.0 a0.1 ± 0.0 a0.1 ± 0.0 a1.3 ± 0.2 b15.3 ± 0.6 a
tR1.5 ± 0.1 bc2.4 ± 0.2 ab0.3 ± 0.1 b0.1 ± 0.0 a9.4 ± 0.2 ab0.1 ± 0.0 a0.1 ± 0.0 a0.1 ± 0.0 a1.5 ± 0.2 b15.5 ± 0.4 a
Data represent mean ± standard deviation of five lettuce plants, each analyzed in triplicate. Differences in carotenoid amounts were tested according to one-way ANOVA followed by Duncan’s test. In a column, means followed by the same superscript letters are not different according to Duncan’s test (p < 0.05). Sample codes as in Table 2.
Table 5. Tocols, sterols, and squalene contents in lettuce samples.
Table 5. Tocols, sterols, and squalene contents in lettuce samples.
Species
/Codes		Tocols (mg 100−1 g fw)Total Tc
mg 100 g−1 fw		Sterols (mg 100−1 g fw)Total St
mg 100 g−1 fw		Squalene
mg 100 g−1 fw
α-T3α-Tpγ-Tpδ-TpStigmasterolCampesterolβ-Sitosterol
T00.02 ± 0.00 b0.15 ± 0.01 bc0.26 ± 0.00 btraces0.44 ± 0.01 b20.9 ± 2.8 bc2.2 ± 0.2 d0.2 ± 0.0 b23.3 ± 2.8 cd0.1 ± 0.0 a
TA0.08 ± 0.02 a0.12 ± 0.00 c0.24 ± 0.08 btraces0.45 ± 0.08 b17.9 ± 2.6 c3.9 ± 0.4 c0.4 ± 0.1 a22.2 ± 2.6 d0.1 ± 0.0 a
TR0.03 ± 0.01 b0.14 ± 0.01 bc0.25 ± 0.04 btraces0.42 ± 0.04 b25.6 ± 0.7 a3.2 ± 0.1 c0.4 ± 0.0 a29.1 ± 0.7 ab0.1 ± 0.0 a
t00.03 ± 0.01 b0.18 ± 0.03 ab0.26 ± 0.05 btraces0.46 ± 0.06 b21.1 ± 2.1 b5.9 ± 0.6 b0.4 ± 0.1 a27.4 ± 1.2 bctraces
tA0.03 ± 0.01 b0.14 ± 0.00 bc0.26 ± 0.02 btraces0.42 ± 0.02 b21.8 ± 2.1 b3.0 ± 0.4 cd0.3 ± 0.0 ab25.1 ± 2.2 c0.1 ± 0.0 a
tR0.02 ± 0.00 b0.20 ± 0.01 a0.35 ± 0.03 atraces0.57 ± 0.03 a22.6 ± 1.3 ab7.7 ± 0.6 a0.5 ± 0.0 a30.8 ± 1.0 a0.2 ± 0.0 a
Data represent means ± standard deviation of five lettuce plants, each analyzed in triplicate. Differences in Tc, St, and squalene amounts were tested according to one-way ANOVA followed by Duncan’s test. In a column, means followed by the same superscript letters are not different according to Duncan’s test (p < 0.05). Sample codes as in Table 2.
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Cunha-Chiamolera, T.P.L.; Chileh-Chelh, T.; Ezzaitouni, M.; Urrestarazu, M.; Carrillo Montalbán, J.d.D.; Guil-Guerrero, J.L. A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce. Horticulturae 2025, 11, 558. https://doi.org/10.3390/horticulturae11050558

AMA Style

Cunha-Chiamolera TPL, Chileh-Chelh T, Ezzaitouni M, Urrestarazu M, Carrillo Montalbán JdD, Guil-Guerrero JL. A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce. Horticulturae. 2025; 11(5):558. https://doi.org/10.3390/horticulturae11050558

Chicago/Turabian Style

Cunha-Chiamolera, Tatiana P. L., Tarik Chileh-Chelh, Mohamed Ezzaitouni, Miguel Urrestarazu, Juan de Dios Carrillo Montalbán, and José Luis Guil-Guerrero. 2025. "A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce" Horticulturae 11, no. 5: 558. https://doi.org/10.3390/horticulturae11050558

APA Style

Cunha-Chiamolera, T. P. L., Chileh-Chelh, T., Ezzaitouni, M., Urrestarazu, M., Carrillo Montalbán, J. d. D., & Guil-Guerrero, J. L. (2025). A Rugulopteryx okamurae-Based Biostimulant Enhances Growth and Phytochemicals in Lettuce. Horticulturae, 11(5), 558. https://doi.org/10.3390/horticulturae11050558

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