Extraction of phytostimulant molecules from Scenedesmus almeriensis using different extractor systems

There is an increasing demand for bio-based fertilizers and phytostimulants. Microalgae biomass contains a number of compounds that have positive effects on plant growth (for instance, phenolic compounds). Other valuable substances are simultaneously produced in the biomass, enabling a biorefinery approach to be applied. Downstream processing optimization for sustainable economic biostimulant production must involve the use of microalgal wet paste instead of dry biomass. The present study investigated the effect of different parameters, such as the solvent, temperature, and time, on the extraction of biostimulant molecules from Scenedesmus almeriensis microalgal biomass. The extraction process optimization was determined by calculating the germination index in the watercress seed bioassays. Since phenols and other bioactives are extracted together, and purification should be avoided, biological methods are preferred for assessing biostimulation. Water was compared to organic solvents of lower polarity such as acetone, ethanol (96%), and an ethanol:hexane:water (76:18:6 v/v/v) mixture. Different solvent extraction ratios (0.5–8 mL solvent g−1 of dry biomass), temperatures (25–50 ºC), and extraction times (0.5–6 h) were tested, after which the best combination was selected for each solvent. The optimal conditions were obtained with organic green solvents (acetone or ethanol), which resulted in a Germination Index above 120% (at least 20% above the distilled water control). Consequently, from a biorefinery perspective, this process was considered to be the most suitable for microalgal biomass exploitation.


Introduction
There is an increasing demand for sustainable fertilizers and plant stimulants. Huge quantities of chemical fertilizers are used each year (to the scale of 10 6 t) (Chojnacka et al. 2020). The world population continues to grow while food production still relies on non-sustainable resources. Notwithstanding, the use of biofertilizers is growing (Daniel et al. 2022). These are based on microorganism biomass (Rhizobium, Azotobacter, Azospirillum, microalgae, phosphate-solubilizing bacteria, mycorrhiza, and others). Furthermore, many of the fertilizers currently used can cause secondary pollution in water bodies, which directly impacts the environment and human health (when water intended for human consumption is affected). It is estimated that up to 50% of the N and P from fertilizers are dumped into the environment. This is especially important for P since it is a non-renewable resource, the reserves of which could be exhausted by 2050 (van Dijk et al. 2016). Sustainable approaches to agriculture, based mainly on biomass, have been undertaken to improve crop productivity and avoid further environmental degradation (Calvo et al. 2014). In addition to biofertilizers, biostimulants can also be obtained from renewable sources. These substances are increasingly being applied in intensive crop cultivation due to their positive effect on plant yield, nutrient-use efficiency, stress tolerance and resistance to disease (Calvo et al. 2014).
Biostimulants are a heterogenic group of molecules, extracts or whole biomass that may contain several compounds; for instance, phenols, salicylic acid, humic and fulvic acids, protein hydrolases, and bacterial biomass (among 1 3 others) (Chiaiese et al. 2018). Humic acid and microalgal biomass are the main sources of biostimulants (EL Boukhari et al. 2020). The transition from non-renewable resources to sustainable bio-based products necessarily involves recovering nutrients from the waste streams. For this, microalgae cultivation is one of the most promising alternatives (Castro et al. 2020). However, the microalgal bioprocess must be significantly improved, particularly the downstream stages, and the economic case demonstrated. Whilst certain process steps are required to produce microalgal biofertilizers (Castro et al. 2020), the biostimulant production process is more straightforward, although extraction steps may be required (Kapoore et al. 2021). The main difference between biostimulants and biofertilizer is that the first don't contain many nutrients, while the biofertilizers do.
Biostimulants coming from microalgae contains a number of compounds that have a known positive effect on plant growth (Kapoore et al. 2021). Amongst these are peptides, amino acids, phytohormones (e.g., cytokinins, auxins, and gibberellins) and other plant growth-promoting substances (Khan et al. 2009;Stirk et al. 2013). For example, these hormones regulate processes such as root initiation and elongation. The biostimulant effect needs to be evaluated in vivo since hormones (and other active substances) operate via complex pathways (Berens et al. 2017).
The downstream stage of the microalgae culture is a crucial step since enormous volumes of low concentration broth need to be processed. The downstream processing of the microalgae biomass alone can account for up to 30% of the total production cost (Acién et al. 2012). Thus, most processes tend to avoid drying the algae. The energetic cost savings are substantial if freeze-drying or low-temperature drying are dispensed with. Microalgal drying can be circumvented with a number of wet-biomass-based techniques such as supercritical extraction, organic solvent systems, sonication, ultrasound, and microwaves. These techniques, which can be used alone or in combination, have to maximize the yield of the desired products and co-products while minimizing energy use and waste. They must also be scalable. At the very least, biostimulant production must include a cell recovery and a cell disruption step. The latter is obligatory in the case of microalgae with a rigid cell wall, since the cell wall hampers the extraction of biocompounds. Although mechanical, thermal, chemical and enzymatic methods have been described in the literature, it is the mechanical and enzymatic methods that are generally preferred since heat and certain solvents can damage bioactive compounds (Michalak and Chojnacka 2014;Stirk et al. 2020). The solvents need to penetrate the cell and, depending on their polarity, extract the target molecule. For example, modified Bieleski's solvent (methanol, formic acid and water, 15:1:4) can extract various plant hormones simultaneously (such as auxins, abscisic acid, cytokinins and jasmonic acid,) (Hoyerová et al. 2006). For the extraction of individual plant hormones, many different solvents have been used successfully; for instance, methanol, acetone, and propanol, in addition to modified Bieleski's solvent (Du et al. 2012). The best solvent in each case and its optimal solvent ratio need to be determined by performing certain experiments. Especially useful are those based on functional assays since they allow one to determine the overall (sometimes synergistic) biological effect on the extract. These simple processing steps have a definite influence on the biostimulant activity when evaluated using bioassays (Navarro-López et al., 2020a, b).
The aim of this work was to optimise the biostimulant extraction process from microalgal biomass based on the watercress germination index bioassay. The evaluation of the type of solvent, the solvent/biomass ratio, application dilution ratio, extraction time and temperature were considered.

Microalgae and chemicals
Wet paste biomass from Scenedesmus almeriensis (CCAP 276/24) was obtained from the culture collection of the Department of Chemical Engineering at the University of Almería (Spain) and was used at the pilot-scale plant located at "Las Palmerillas, Cajamar" facilities (El Ejido, Almería, Spain). Cultures were grown in an outdoor vertical tubular photobioreactor (3000 L) with modified Arnon medium (Allen and Arnon 1955) operating in continuous mode at a 0.3 day −1 dilution rate and was maintained for four months. Agricultural fertilizers were used in place of pure chemicals at a sodium nitrate concentration of 11 mM, in accordance with the commercial algal medium (Aqualgae S.L., A Coruña, Spain). The cultures were grown at pH 8.0, regulated by the on-demand injection of CO 2 , and the temperature was maintained within the 23-25ºC range by passing thermostatically controlled water through a heat exchanger located inside the reactor. The biomass was harvested daily by centrifugation with a flow rate of 15 L h −1 at room temperature (RINA continuous centrifuge, Riera Nadeu SA, Spain) and then frozen at -18 ºC until use.

Cell disruption
To increase the extraction yield of the biomolecules, the wet microalgal biomass, which had an initial concentration of 100 g of dry biomass L −1 , was pretreated by high pressure homogenization (HPH) using a Panda plus 2000 homogenizer (model s.n.8963 S.p.A, Parma, Italy). This cell disruption method was applied at 200 bar, as this was the optimized conditions for the highest germination index (GI) of watercress seeds after treatment with Scenedesmus sp. extracts (Navarro-López et al. 2020a).

Optimization of the biostimulant molecule extraction from the wet microalgal biomass
The extraction was carried out using the disrupted S. almeriensis biomass. For the solvent extraction optimization, 5 mL samples (0.5 g if expressed as dry biomass) were treated with water, ethanol, acetone, or a tri-component mixture of ethanol:hexane:water (76:18:6 v/v/v) (Fernández Sevilla et al. 2016).
Different conditions were optimized within the indicated range: the extraction ratio expressed as the solvent volume/ water volume/g DB (0-8 mL solvent/5 mL water/g DB), application dilution ratio (1/100 -1/1000), temperature (25-50ºC) and extraction time (0.5-6 h). Table 1 shows the final dry biomass corresponding to each application condition (note that this is only a way of estimating how much biostimulant solution volume can be produced from each gram of dry biomass). The assays were carried out sequentially and the 2-3 best conditions were successively evaluated in the next optimization step. First, the extraction and application dilution ratios were investigated. Then, different temperatures were tested, and finally extraction times were evaluated ( Fig. 1). All extractions were carried out in 50 mL bottles with screw caps that were placed in a heating magnetic stirrer (Multimix Heat D, Spain) at 300 rpm. The mixture obtained was then centrifuged at 10,835 xg for 5 min and the supernatants diluted to concentrations of 1, 0.5 and 0.1 g L −1 (corresponding to application dilutions of 1/100,  1/200 and 1/1000, respectively) for testing in the bioassays. Each condition was assayed by duplicate using two screw cap bottles and the aliquots obtained from them were tested using 200 watercress seeds (100 seeds for each bottle).

Determination of the biostimulant activity
The biostimulant activity of the microalgal extracts obtained ( Fig. 1) was determined by measuring the germination index of watercress seeds (Lepidum sativum L., Sonnentor) according to the method of Zucconi et al. (1981). A total of 100 watercress seeds were tested in each assay. The seeds were placed on Whatman No. 5 filter paper in four sterilized 90 mm Petri dishes and then treated with 8 mL distilled water ( control) or with the diluted extracts resulting from applying each extraction condition. Organic solvents inhibited seed germination. This was observed for several extract concentrations in a previous run of assays. Therefore a evaporation step was added to allow solvents to evaporate. The seeds were placed at 24ºC in darkness for 3 days and then the software Image J was used to measure the length of the radicals. All measurements were duplicated. The germination index of each sample was determined by the following equation: where G and L are the number of germinated seeds and their length in the case of the microalgal extracts, while G w and L w are the same parameters obtained for the control assay (distilled water). The data shown in the biostimulant activity experiments, therefore, are the result of measuring 200 seeds for each condition.

Extraction and determination of the total phenol content by spectrophotometric methods
The total phenol content of the supernatant samples obtained was measured following extraction with each solvent system. The total phenol content was determined using the Folin-Ciocalteu method (F&C) as described by Waterman and Mole (1994). Aliquots of 0.1 mL were taken from each supernatant, transferred into test tubes, and their volumes made up to 6 mL with distilled water. After adding 0.5 mL Folin reagent, 1.5 mL 20% sodium carbonate solution was added between 1 and 8 min, and the volumes adjusted to 10 mL by adding 1.9 mL distilled water. The tubes were agitated and then the absorbance of the blue-coloured samples was measured after 2 h at 760 nm, comparing them against a blank containing 0.1 mL extraction solvent and the other reagents in the same proportion. The total polyphenol content was calculated as gallic acid equivalents from the gallic acid calibration curve (covering a concentration range between 0 and 0.6 mg mL −1 and expressed as mg gallic acid g −1 of DB). The measurement of each aliquot of the supernatant obtained was carried out in triplicate.

Polarity index and Hildebrand solubility parameters
To determine the polarity index (PI) of the mixture solvents, Eq.
(2) was used, as described by López-Rodríguez et al. (2020): where i represents the pure solvent i and X i is the volumetric fraction of the solvent i in the mixture (Poole and Poole 1991).
The solubility parameters that appear in Eq. (3) were described by Hansen (2007). The total solubility parameter (∂) is calculated as shown in Eq. (3): To consider the different optimal extraction temperatures obtained for each solvent, the total solubility parameter was recalculated as proposed by Barton (1983).
where ∂ is the total solubility parameter calculated with Eq. (3), ∂T is the same parameter adjusted to the optimal extraction temperature, T 2 is the optimal extraction temperature obtained for each solvent (from 25 to 40 ºC; Table 3), and T 1 is the reference temperature (25ºC).

Statistical analysis
Statistical data analyses were performed using the Statgraphics Centurion XVII software package. Data, in percentage, were arcsin (× 1/2) transformed. The normality and homogeneity analyses were performed using the Kolmogorov-Smirnov and Levene tests, respectively.
Multifactor ANOVA tests were used to study the effect of the factors (volume of solvent, dilution applied, solvent type, temperature and time) at a 95% confidence level for the germination index, the aim being to decide the most influential factor in the germination index of the watercress seeds.

Influence of the solvent, extraction ratio and application dilution on the germination index
As can be seen in the Fig. 2, all the solvents assayed showed a GI index close to distilled water (100%). For the tests using only water as the extractor system, the GI results confirmed that the biostimulants were being extracted from the wet biomass (≥ 100%), but there was no pattern or condition that clearly showed that the GI was maximised ( Fig. 2A). The dilution that seemed to outperform the rest was when the 1/100 dilution was applied to the seeds, although the dilution applied had no significant effect on the GI of the watercress seeds. The concentrations used in this study ranged from 0.06-0.95 g L −1 . For the aqueous extract at 25 °C, the best conditions were observed at concentrations ranging from 0.1-0.83 g L −1 with a dilution of 1/100 and extraction ratios of 0/10/1 and 2/10/1, respectively.

Influence of the extraction temperature on the germination index
In the case of water, all 4 extraction ratios were tested since no significant difference was observed between them in the previous step. The temperatures resulting in the highest GIs were 25 and 30ºC, with slight improvements at the lower extraction ratios. Maximum GI values of 110% (1/100 and 2/10/1) were obtained (Fig. 3).
In the case of ethanol, practically all the tests were over 100% GI. Extracts produced at 25 and 30 °C were those showing the best results. The optimal condition was 30ºC and 4/10/1 with 120.0% ± 5.8, meaning a GI 20% higher than the control. Unlike water and ethanol, acetone and the ethanol:hexane:water mixture performed better at higher temperatures. In both cases, the optimum temperature was 40ºC. The best GI values were 118% (2/10/1) and 110% (2/10/1) for acetone and ethanol:hexane:water, respectively.

Influence of the extraction time on the germination index
When evaluating the optimal conditions for each of the systems, the GI values greatly exceeded 100% in almost all cases. For all the solvents tested in this work, 2 h proved to be the most suitable period (See Fig. 4).
The Fig. 4 insert shows the best results for each system. The ethanol:hexane:water mixture resulted in the highest GI (123%). Acetone and ethanol gave similar but slightly lower values whereas the water yielded a value close to 90% of the value for the ethanol:hexane:water system.
Results obtained for the three experiments were tested for statistical differences. A multifactor ANOVA (See Table 2) was carried out considering the following factors: extraction mix (VS), the dilution applied (DU), the solvent type (ST), temperature (T) and time (t), and the response variable was the watercress seeds GI. The extraction time (t) was the main factor affecting the GI of the seeds (Table 2). Nevertheless, the temperature (T), the volume of the solvent added to the

Extraction of phenols and the biostimulant effect
In the case of complex samples such as the microalgal biomass used in this work, solvent selection following the Hildebrand solubility parameter approach should be considered (Saha et al. 2015;López-Rodríguez et al. 2020). For the solvents used, solubility and polarity parameters have been obtained and presented in Table 3.
The lowest germination index (112 ± 3.5%) was obtained for water; this is the most polar solvent, having a polarity index (PI) of 9. For the other solvents (all of them having a PI from 5.4-5.6), the GIs were higher than those observed using water (Table 3). Likewise, when water was used as the solvent, the solubility parameter -adjusted to the extraction temperature (Table 3) was almost double that of the other solvents. Solvents with similar ∂ are usually miscible with each other and dissolve the same types of substances; hence, the GIs obtained when using ethanol, acetone or the ethanol:hexane:water mixture are very similar (122.4, 121 and 123.3%), differing greatly from those obtained using water as the extracting solvent (112.3%).
The phenolic compounds group includes thousands of structurally diverse compounds (Singla et al. 2019). Thus, an equivalent gallic acid (GA) concentration was provided. For the temperature evaluation in total phenol extraction, the previously found optimal extraction time of 2 h was taken (Fig. 5A). It can be observed that temperature only favoured Fig. 3 Germination Index (%) for different temperatures, solvent/water/biomass ratios (mL/mL/g DB) and different application dilutions (mL/mL). The ethanol:hexane:water volumetric proportion was 76:18:6. Results are shown as mean ± SE (n = 2). Different letters indicate significant differences (p < 0.05) within each treatment Germination Index (%) for different extraction times, application dilutions (mL/mL), optimum temperatures, solvent/water/biomass ratios (mL/mL/g DB). The ethanol:hexane:water volumetric proportion was 76:18:6. Insert: Best Germination Index (%) for each solvent. Results are shown as mean ± SE (n = 2). Different letters indicate significant differences (p < 0.05) within each treatment extraction for water and minimally for ethanol:hexane:water. For the mixture an optimum temperature was observed for 30 °C. For water, it was shown that the higher the temperature the higher the phenol concentration measured. Regarding extraction time, there was a significant difference in phenol extraction with the increasing extraction time for all the solvents. Notwithstanding, in the case of water differences for times higher than 2 h were minimal.
In comparison to acetone and ethanol, water and the solvent mixture (ethanol:hexane:water) removed nearly twice as much phenols (Fig. 5). Even though acetone is a far less Table 2 Multifactor ANOVA testing the effect of the volume of solvent added to the extraction mix (VS), the dilution applied (DU), the solvent type (ST), temperature (T) and time (t), on the germination index (%) of the watercress seeds. The data variability is attributable to the main effect of each factor and the interactions found, as indicated by the p value. The contribution of each factor was expressed as the percentage variation of the response (F ratio of each factor relative to the sum of all F ratios)  The optimum conditions for the solvent/water/biomass ratios (mL/mL/g DB) and application dilutions (mL/mL) are shown. Results are shown as mean ± SE (n = 3). Different letters indicate significant differences (p < 0.05) within each treatment polar organic solvent than methanol, it extracted almost as many phenols in the current study (Fig. 5). The Fig. 6 represents the GI versus the total phenols for the four solvents used. The objective was to establish if there was a correlation between GI and phenols content. The highest total phenol content was determined in the aqueous extract (Fig. 6, dashed blue line). Similar total phenol extraction was observed for the ethanol:hexane:water mixture. On the other hand, ethanol showed the lowest ability to extract phenols for the conditions assayed. For every solvent, a maximum GI can be read which was in the central value of the phenols extracted.

Discussion
As described by Kapoore et al. (2021), microalgal biostimulants are grouped into phytohormones (auxins, gibberellins, cytokinins and brassinosteroids, ethylene, abscisic, jasmonic and salicylic acids, polyamines and betaines), protein hydrolysates, amino acids, humic substances, polysaccharides, and antioxidants (vitamins, carotenoids, phenolics and chlorophylls) and finally terpenoids and free fatty acids and can be used as an environmentally friendly alternative to those obtained from synthetic agrochemicals. Since chemical analysis cannot account for all the effects (even synergistic or antagonistic) biological assays are preferred. There are various applications for biostimulants in agriculture, for example, applying the extracts to the soil, foliar spray application or priming (seed soaking). Priming involves placing the plant seeds in liquid containing the biostimulants; this improves germination success and initial growth. With respect to the bioassay, germination index assay is especially useful for studying the extraction alternatives of biostimulant from biomass. It is also relevant since it acts as a proxy for the gibberellin content which are a group of plant hormones that play an important role in initiating seed germination and stem elongation (Tarakhovskaya et al. 2007;Plaza et al. 2018;Navarro-López et al. 2020b). Moreover, germination and emergence stages have been proposed as the most critical stages on plant growth (Dehnavi et al. 2020). In the present study, the extract process optimization was determined studying different variables as solvent type, dilution applied, temperature or extraction time.
To date, the preferred solvent for algal biostimulant extraction has been water. There is a scarcity of research focused on seed soaking using microalgal extracts, although a few successful examples can be found. For example, Acutodesmus dimorphus extracts (0.75 g L −1 ) accelerated seed germination of tomato plants (2 days earlier than the control) (Garcia-Gonzalez and Sommerfeld 2016). In other cases, the plant biostimulant activity of the aqueous extracts from other species such as Oscillatoria sp. was tested using the GI assay and reported a GI of the watercress seeds of 120 ± 13% when the aqueous extract was used with a concentration of 0.5 g L −1 which is slightly higher to those obtained with the aqueous extracts from Scenedesmus used in this work (Morillas-España et al. 2022). Similar results were obtained in a previous work (Navarro López et al., 2020a) using Scenedesmus sp. as raw material. In this case, the aqueous extract without a cell disruption method was applied at different concentrations of 0.1, 0.5 and 1 g L −1 obtaining GI around 100%, that is the same that with the distilled water. However, this GI was improved after a pre-treatment by high pressure homogenization (HPH), and increased to 112% at 0.1 g L −1 .
Our initial comparison showed that organic solvents were suitable for extracting microalgal biostimulants.
As shown in a previous study, microalgal aqueous extracts showed that lower temperatures favoured the extraction of polyphenols (⁓25 C) whereas higher temperatures resulted in phenol decomposition (> 40 C) with no correlation between phenols and the GI (Michalak et al. 2015). In another study, higher temperatures (⁓70 C) did extract micro-and macro-elements from the biomass and improved the extraction of active compounds (Neveux et al. 2020). In previous studies (Navarro-lópez et al. 2020a) we determined that the temperature had no significant effect on the germination index when aqueous extracts were used. However, lower GI were obtained in this study at the highest temperature (50ºC) for the four solvents tested. It could be due to the higher concentration of bioactive compounds that are extracted at this temperature and could lead to an inhibitory effect on the seed growth. This behaviour could be observed in Fig. 5A where the concentration of total phenols are the highest at 50ºC in the case of using water as solvent and decreased as the temperature decreased as well.
When targeting certain metabolites, solvent selection is an important step in optimizing the extraction process. It depends not only on the type of microalgae but also on the target metabolites. Phenolic compounds, which have been demonstrated as possessing biostimulant properties, were among the biomolecules present in the microalgae biomass. The extraction solvents are selected based on certain properties such as the polarity, the boiling point (to make recovery easier) or their classification in terms of health, safety and environmental criteria (Prat et al. 2015). Special attention should be paid to the polarity since this is critical in isolating specific types of molecules (Kaczorová et al. 2021) and to the Hildebrand solubility parameters. Therefore, solvent selection using the Hildebrand solubility parameter technique should be taken into account in the case of complex samples as the microalgal sample utilised in this study (Saha et al. 2015;López-Rodriguez et al. 2020).
The values measured for the phenol content were similar to those obtained for Dunaliella salina, Tetraselmis chuii and Isochrysis galbana (aqueous extracts) but higher than those found by for methanolic extracts of different species (Pereira et al. 2015;Widowati et al. 2017). When water was used, the temperature had a positive impact on the total phenols extracted. Conversely, the trend for the organic solvents was that higher temperatures had no effect or resulted in lower concentrations. The assays carried out to determine the best temperature for each system and extraction time showed that the higher the extraction time, the higher the phenol concentration in the supernatant. The water and solvent mixture (ethanol:hexane:water) extracted more phenols than the acetone and ethanol solvents (almost twice as much) (Fig. 5). This does not accord with other published works that have shown better results for organic solvents. In this regard, methanol has been reported as one of the best alternatives for extracting polar compounds such as phenolic compounds and flavonoids (Safafar et al. 2015). Nevertheless, in the present work, acetone extracted nearly as many phenols as ethanol, even though acetone is a much less polar organic solvent (Fig. 6). The maximum GI, as discussed above, was obtained for an extraction time of 2 h and was not related to the maximum phenol concentration.
In microalgal extracts, phenolic compounds are responsible for up to 77% of the total antioxidant properties (Safafar et al. 2015). However, these compounds may not account for the same biostimulant effect percentage. Phenolic compounds can inhibit seed germination or delay it, mainly when the soaked seeds are placed on germination paper (Krogmeier and Bremner 1990). This inhibitory effect has also been observed when studying the biostimulant activity of Triticum aestivum var. Pusa Gold (Kumar and Sahoo 2011).
Microalgae produce a large number of phenols, some of which have not yet been characterized. Phenolic compounds produced by microalgae include salicylic and caffeic acid, gallate, cinnamate, chlorogenate, pinostrobate, p-OH-benzoates and others (Klejdus et al. 2009;Goiris et al. 2014). The polarity of the solvents used greatly influences the phenolic compound extraction yield so, supposedly, the less polar solvents would extract lesser amounts of phenolic compounds (Kaczorová et al. 2021). The extraction conditions for maximizing the overall phenolic compound yield may not be adequate for extracting other compounds that have a stimulatory effect. Given the wide variety of biomolecules that have a supposed biostimulant effect, it might not be enough to just consider the solvent polarity when selecting the optimal solvent for the extraction process. In the present study, the lowest GI was obtained with water, the most polar solvent. This might be due to more phenolic compounds being extracted from the Scenedesmus microalgal biomass since an inhibitory effect was observed on watercress seed germination. This is the most likely cause of the lower GIs observed for the aqueous extracts. Similar results were obtained in a previous work (Navarro-Lopez et al., 2020a), in which the salicylic acid concentration of Scenedesmus sp. (after cell disruption treatment by high pressure homogenization) indirectly correlated with the GI.

Conclusions
Solvents of different polarity were successfully used to extract biostimulants from homogenized wet microalgal biomass. No direct correlation was found between the phenolic compounds and the germination index, with only the latter potentially leading to a better phytostimulant product. Consequently, it was proven that a bio-guided search is more efficient for complex biomass extracts. The optimum extraction time was 2 h for all the solvents, probably due to the excess of phenolic compounds present in the extract. In general, the organic solvents outperformed the water. Since the polarity of water is almost double that of organic solvents, the most probable cause is that polar bioactives (e.g., phenols) were extracted in greater quantities, thus resulting in inhibition rather than stimulation. Under the optimal conditions determined in this work, GIs of over 120% (at least 20% more than the distilled water control) were obtained for organic green solvents (e.g., acetone or ethanol). Consequently, this process can be considered to be the most appropriate for microalgal biomass exploitation within a biorefinery approach.