Biostimulant potential of three chlorophyta and their consortium: application on tomato seeds

Biostimulant potential of three chlorophyta and their consortium: application on tomato seeds | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Biostimulant potential of three chlorophyta and their consortium: application on tomato seeds Lorenzo Mollo, Alessandra Norici This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5394178/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 21 You are reading this latest preprint version Abstract Microalgae offer a promising solution for enhancing agricultural sustainability and mitigating global warming. When extracts from algal cells and their spent medium are used as biostimulants on crop seeds, they can significantly influence plant physiology. This application boosts plant productivity and improves tolerance to abiotic stress. The objective of this study was to evaluate the biostimulant potential of crude extracts from Tetradesmus obliquus , Chlamydomonas reinhardtii , Auxenochlorella protothecoides , and their consortium, as well as the potential of their spent growth media, when applied to tomato seeds ( Solanum lycopersicum ). The study assessed germination indexes and seed development, including weight, root/shoot ratio, and growth speed. The results indicated that the variation in the morphology of the treated seeds was primarily influenced by the concentration of the extracts, with the algal species having a lesser impact on the observed variability. The number of germinated seeds was notably higher at the lowest concentration of biostimulants. Additionally, the algal extracts exhibited greater biostimulant potential than the spent media. Furthermore, the analysis of growth speed revealed that most treated seedlings grew significantly faster than the control seeds. Lastly, the study reported a lower biostimulant potential of the algal consortium compared to the single species, possibly due to the co-cultivation of different species. Biostimulant Spent medium Seed priming Algal consortium Chlorophyta Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Global warming represents one of the most pressing challenges of the 21st century, with rising global temperatures, shifting climatic patterns, and increasingly frequent and severe weather events being the main evidence of this phenomenon. While powerless we continue to observe record-breaking temperatures month after month ( https://climate.copernicus.eu/ ), it is imperative that we attempt a transition of the sectors that emit the most greenhouse gases. Agriculture is a key sector that significantly contributes to global warming and is profoundly impacted by its effects. Traditional agricultural practices are responsible for approximately 15% of global greenhouse gas (GHG) emissions, significantly contributing to climate change through the emission of carbon dioxide, methane, and nitrous oxide [ 1 , 2 ]. Agriculture is also uniquely vulnerable to the impacts of climate change, as altering weather patterns, temperature shifts, and increased incidences of extreme weather events threaten crop yields, soil health, and water availability [ 3 ]. Furthermore, traditional agriculture negatively impacts most of the so-called planetary boundaries, virtual limits that define the safe operating limits for humanity within which the Earth system can continue to function in a stable state [ 4 ]. Solving this issue and transitioning towards a sustainable food system is no easy feat, especially since the practices we adopt for the future must account for the increasing food demand due to a projected world population of about 10 billion people in 2050. As reported by Searchinger et al. [ 5 ], we need to fill a food and land gap of 7,400 trillion calories and 593 million hectares respectively, and we need to do that without increasing GHG emissions and, where possibly, reducing them to the target of 4 billion tons (to hold global warming below 2°C above pre-industrial temperature). It is quite an impossible challenge, but scientists worldwide have proposed multiple solutions that could help us reach this target [ 6 , 7 ]. Among these solutions, microalgae have garnered significant attention due to their diversity and versatility [ 8 , 9 ]. Microalgae are a group of microorganisms that perform oxygenic photosynthesis and convert CO 2 to biomass with much higher efficiency than higher plants. Additionally, some microalgae can perform a mixotrophic metabolism using both inorganic and organic carbon, allowing them to thrive even in carbon-rich wastewater where they are exploited as a remediation process [ 8 , 10 ]. Within the agrifood system, microalgae are already successfully employed as human food or animal feed [ 11 – 13 ]. Depending on the phylum and species, microorganisms can accumulate high protein contents [ 14 ], which could serve as alternative sources of protein to the animal-based ones [ 15 ]. Essential amino acids, polyunsaturated fatty acids, and vitamins are also accumulated within the algal biomass, making them a real superfood [ 16 ]. Unlike plants, microalgae require less input, and nutrient run-off is practically absent due to their cultivation in open ponds or photobioreactors [ 17 , 18 ]. The possibility of using non-agricultural or contaminated land can increase food production without subtracting arable land from traditional agriculture. In addition, recycling wastewater nutrients reduces the need for fertilisers, helping to maintain the N and P biogeochemical flows within safe boundaries [ 4 ]. When microalgae are not suitable for direct human consumption, other possible applications do exist in agriculture to indirectly ensure greater food production: biofertilizers, biopesticides, and biostimulants are among the sustainable methods for utilizing microalgae [ 19 – 23 ]. Biostimulants are substances and/or microorganisms that enhance nutrient uptake, nutrient efficiency, tolerance to abiotic stress, and crop quality [ 24 , 25 ]. As regulated by the EU parliament with the Regulation (EU) 2019/1009, these products do not directly provide nutrients, but they stimulate and activate the inner pathways of the plants, improving their overall growth [ 26 , 27 ]. Their use has gained interest in sustainable agriculture since it reduces fertilizer consumption and enhances abiotic stress defences (especially those related to water scarcity and salt stress [ 28 , 29 ]). Biostimulants have been used in agriculture for a long time [ 30 , 31 ]. Macroalgae or seaweed-based biostimulants have been known to be used since ancient times in northern Europe, and recently modern products made of Ascophyllum nodosum are widely employed in agriculture. In the present day, several strategies are employed to enhance the biostimulant capability of algal extracts, including enzymatic and hydrolytic treatments, and extraction of specific fractions [ 19 , 23 , 32 ]. The amino-acidic fraction has been observed as one of the most active fractions [ 33 , 34 ], but polysaccharides and algal hormones can also induce functional changes in plants [ 19 , 27 , 35 ]. Macro and microalgae possess metabolic pathways to synthesize phytohormones, with IAA and cytokinins being the most common hormones found in almost all tested algae [ 34 , 36 ]. Nonetheless, it should be highlighted that hormone concentration for biostimulants should be lower than a certain threshold, or else the resultant product must be considered a plant growth regulator [ 26 ]. Microalgae-based biostimulants are far more recent products than the seaweed ones and have gained widespread attention. Most of the microalgal extracts tested so far were made from cyanobacteria and chlorophyta [ 28 , 37 , 38 ]; the applications were successful in several plant species, including tomato, papaya, rocket, cucumber, wheat, maize, and barley [ 21 , 24 , 27 , 28 ]. Microalgal extracts are active as biostimulants at very low concentrations, even at 0.1 mg mL − 1 [ 39 ], confirming that the observed effects are not associated with a direct provision of nutrients. Biostimulants have also been produced using algae grown in wastewater, and a biostimulant effect was still observed [ 20 , 40 , 41 ]. Circular processes could be designed with agro-food wastewaters remediated by microalgae, and the same algae could later be used as biostimulants in agriculture. Biostimulants are commonly applied as foliar or seed application [ 37 ]. Seed application, also referred to as priming, requires soaking the seeds in the microalgal extracts for a minimum of 24 hours before sowing to initiate germination metabolism [ 42 , 43 ]. Using algal extracts, other pathways besides those required for germination are triggered, such as abiotic stress-tolerance pathways, and a “priming memory” within the seeds is established [ 44 , 45 ]. This memory is sustained during the development of the seeds, increasing the likelihood of germination and vigorous growth of the plant. Seed priming with biostimulants is an innovative process that could positively contribute to agricultural sustainability by increasing productivity and lowering input. The objective of this study was to evaluate the biostimulant potential of different dilutions of green algae crude-extracts, including Tetradesmus obliquus, Chlamydomonas reinhardtii, Auxenochlorella protothecoides , and their consortium, as well as their spent growth media. Biostimulant solutions were tested on tomato seeds, and their activity was evaluated through different germination indexes and on the development of the seeds at the end of the experiment, including weight, root/shoot length. The algal consortium was also cultivated in diluted digestate (e.g. wastewater produced during the anaerobic fermentation of biomass) as growth medium, and the resulting extract was tested. 2 Materials and Methods 2.1 Microalgae cultivation Tree microalgae Auxenochlorella protothecoides (CCAP 211/8D 1 ), Tetradesmus obliquus (CCAP 276/3A) and C hlamydomonas reinhardtii (RCC125 2 ) were tested. A consortium of the three species, as established in Mollo et al. [46, 47] and Chieti et al. [48] was also tested. Mono-cultures and consortium were settled in BG11 medium [49] at controlled condition: 20°C, illuminated with white, fluorescent lamps at 100 mmol m -2 s -1 and 24h light. The consortium cultures were also established in and acclimated to a medium consisting of 7% tap water-diluted digestate. This digestate was sourced from an anaerobic digester fed with chicken manure, olive mill wastewater, and silages (kindly provided by Enereco S.p.A.). The initial composition of the digestate is detailed in Table 1. Cultures were grown until they reached the stationary phase; algal biomass was then harvested by centrifugation and washed twice with deionised water. Thus, algal biomass was resuspended in deionised water to a final dry weight (DW) of 20 mg mL -1 before use. The workflow of the biostimulant preparation and application is summarised in Fig. 1. The supernatant deriving from the centrifugation was also tested as biostimulant solution. The spent media were filtered at 0.22 µm, characterised for elemental composition (Table 2) and stored at 4°C before used. Concentrations of 10%, 50% and 100% of spent media (diluted in deionized water) were tested. Elemental composition of the spent media was assessed through TXRF (Total Reflectance X Ray Fluorescence) using a TXRF spectrometer (S2 Picofox, Bruker AXS Microanalysis GmbH, Berlin, Germany) according to Fanesi et al. [50]. Table 1 chemical characterisation of the tap water diluted digestate as used to cultivate the algal consortium. Data are reported as mean ± SD (n ≥ 3). Parameters Value pH 8.8 ± 0.1 Conductivity (mS cm − 1 ) 1163.63 ± 71.35 Alcalinity (mg L − 1 ) 642.16 ± 6.39 COD (mg L − 1 ) 609.35 ± 7.09 TKN (mg L − 1 ) 138.97 ± 4.50 N-NH 4 (mg L − 1 ) 121.38 ± 6.25 N tot (mg L − 1 ) 139.06 ± 4.50 P tot (mg L − 1 ) 0.79 ± 0.18 Cl (mg L − 1 ) 71.73 ± 0.96 N-NO 2 (mg L − 1 ) 0.01 ± 0.01 N-NO 3 (mg L − 1 ) 0.09 ± 0.01 P-PO 4 (mg L − 1 ) 0.52 ± 0.05 SO 4 (mg L − 1 ) 5.51 ± 1.79 Na (mg L − 1 ) 21.14 ± 0.39 K (mg L − 1 ) 257.20 ± 5.33 Mg (mg L − 1 ) 6.44 ± 1.28 Ca (mg L − 1 ) 9.17 ± 1.82 Table 2 elemental composition of spent media from cultures of T. obliquus , C. reinhardtii, A. protothecoides and their consortium in BG11 medium. Data are reported as mean ± SD (n ≥ 3). Spent media Element (mg L − 1 ) T. obliquus C. reinhardtii A. protothecoides Consortium Consortium grown in digestate P 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 6.26 ± 0.44 S 159 ± 59 99 ± 25 139 ± 1 25.73 ± 4.64 24.32 ± 0.28 Cl 3173 ± 576 3758 ± 391 3051 ± 690 8362.76 ± 1343.47 98.19 ± 1.88 K 358 ± 42 371 ± 66 406 ± 31 294.95 ± 40.21 277.96 ± 5.56 Ca 445 ± 34 253 ± 37 333 ± 42 272.92 ± 37.48 76.59 ± 1.08 Mn 8.97 ± 0.72 7.71 ± 1.23 10.85 ± 0.08 9.16 ± 1.33 0.01 ± 0.00 Fe 2.51 ± 0.11 12.83 ± 1.48 18.26 ± 2.85 0.74 ± 0.31 0.83 ± 0.05 Co 0.19 ± 0.11 0.10 ± 0.08 0.00 ± 0.00 0.31 ± 0.09 0.00 ± 0.00 Ni 0.07 ± 0.07 0.04 ± 0.07 0.00 ± 0.00 0.06 ± 0.06 0.04 ± 0.01 Cu 0.16 ± 0.04 0.11 ± 0.02 0.09 ± 0.08 0.02 ± 0.03 0.02 ± 0.00 Zn 4.17 ± 0.27 2.66 ± 0.23 3.07 ± 0.75 2.50 ± 1.03 0.55 ± 0.06 Br 0.60 ± 0.08 0.21 ± 0.04 0.16 ± 0.14 0.27 ± 0.13 0.39 ± 0.02 Sr 1.17 ± 0.11 0.27 ± 0.03 0.30 ± 0.26 0.21 ± 0.01 0.91 ± 0.03 2.2 Extracts preparation The concentrated solutions of algal biomass were disrupted using a cell disruption bomb (Parr Instrument Company), which employs high N 2 pressure to break cell walls and membranes. A volume of 40 mL of the concentrated solution was placed in an airtight cylinder, and nitrogen gas was introduced from a connected tank until a pressure of 2000 psi was achieved. The solution was maintained under this pressure for at least 30 minutes before being collected. Prior to use, the resulting extract was examined under an optical microscope to confirm the success of the disruption process. The crude extracts were then characterize as reported in detail by Mollo et al. [ 46 ].. Pigments content was quantified spectrophotometrically by a previous methanol extraction as reported by Ritchie [ 51 ]. Proteins content was quantified spectrophotometrically by the interpolation with a BSA (Bovine Serum Albumine) standard curve as reported by Peterson [ 52 ]. Elemental composition was assessed by using an elemental analyser (EXS 4010, Costech Italy) for C and N content, and by a TXRF spectrometer for the remaining elements [ 53 ]. Semi-quantification of lipids and carbohydrates was carried out by comparing FTIR (Fourier Transformed Infrared Spectroscopy, Bruker Optics, Ettlingen, Germany) with the total protein content [ 54 , 55 ]. Biomass composition is reported in Table 3 . Algal extracts were stored at -20°C before use. Table 3 biochemical characterisation of the algal extracts from T. obliquus , C. reinhardtii, A. protothecoides and their consortium, considering a DW of the algal extract of 20 mg mL − 1 . Algal extracts Parameter T. obliquus C. reinhardtii A. protothecoides Consortium Consortium grown in digestate Protein (g L − 1 ) 9.30 ± 0.45 5.13 ± 0.02 4.55 ± 0.77 4.15 ± 0.22 3.77 ± 1.09 Carbohydrate (AU) 2.07 ± 0.01 1.00 ± 0.00 1.59 ± 0.17 2.48 ± 0.50 1.59 ± 0.13 Lipids (AU) 3.33 ± 0.00 1.00 ± 0.00 13.17 ± 2.00 4.67 ± 1.00 1.00 ± 0.33 Chlorophyll a (mg L − 1 ) 9.44 ± 0.38 44.78 ± 0.33 11.97 ± 0.55 156.25 ± 1.16 25.61 ± 1.49 Chlorophyll b (mg L − 1 ) 2.51 ± 0.45 56.47 ± 2.92 2.58 ± 0.94 197.00 ± 10.19 12.42 ± 2.70 Carotenoids (mg L − 1 ) 1.49 ± 0.04 7.52 ± 0.62 5.16 ± 0.46 26.25 ± 2.17 0.85 ± 0.41 C (%) 10.4 ± 0.4 10.36 ± 0.66 10.38 ± 0.16 10.42 ± 0.44 10.98 ± 0.46 N (%) 1.98 ± 0.08 2.34 ± 0.04 1.92 ± 0.08 2.1 ± 0.08 2.08 ± 0.02 P (mg L − 1 ) 54.69 ± 1.12 253.17 ± 16.08 221.72 ± 11.55 43.96 ± 2.77 121.08 ± 6.85 S (mg L − 1 ) 15.59 ± 0.50 64.01 ± 3.66 75.80 ± 11.29 13.41 ± 1.14 67.97 ± 7.20 Cl (mg L − 1 ) 6.73 ± 0.96 6.29 ± 0.37 13.83 ± 5.78 0.88 ± 0.11 16.08 ± 4.28 K (mg L − 1 ) 6.54 ± 0.26 17.12 ± 1.23 68.65 ± 0.14 8.06 ± 0.40 77.56 ± 4.93 Ca (mg L − 1 ) 58.08 ± 2.44 105.82 ± 5.78 30.04 ± 0.72 6.36 ± 0.42 576.90 ± 76.04 Mn (mg L − 1 ) 5.59 ± 0.29 13.52 ± 0.70 2.76 ± 0.03 0.55 ± 0.06 1.02 ± 0.13 Fe (mg L − 1 ) 18.94 ± 1.71 64.05 ± 2.90 9.31 ± 0.51 11.06 ± 2.15 5.44 ± 0.40 Ni (mg L − 1 ) 0.02 ± 0.00 0.03 ± 0.00 0.01 ± 0.01 0.01 ± 0.00 0.57 ± 0.05 Cu (mg L − 1 ) 0.28 ± 0.01 0.97 ± 0.05 0.64 ± 0.02 0.16 ± 0.01 0.22 ± 0.06 Zn (mg L − 1 ) 1.05 ± 0.07 2.36 ± 0.13 1.62 ± 0.01 0.30 ± 0.02 9.27 ± 1.88 AU: Arbitrary Units. Carbohydrate and lipid pools relative to those in C. reinhardtii whose contents were assigned a value of 1 [ 54 ]. 2.3 Priming of tomato seeds and biostimulation Minibel tomato seeds ( Solanum lycopersicum ) were acquired from Germisem Sementes LDA ( https://www.germisem.com/ ). Three concentrations of algal extracts (0.05, 0.1, 0.2 mg mL − 1 ) and three spent medium concentrations (10, 50 and 100%) were tested on 100 seeds per treatment (4 technical replicates of 25 seeds). Biostimulation was evaluated as seed priming according to Garcia-Gonzalez and Sommerfeld [ 56 ] and Rupawalla et al. [ 57 ]. Each batch of 25 seeds was surface sterilised with 10 mL of a 5% solution of sodium hypochlorite for 10 minutes. Following the sterilisation, the seeds were washed twice with deionised water and transferred to sterile petri dishes where 10 mL of the desired solution was added. A seed batch was primed with deionized water and used as control condition (CTR). Seed priming was carried out in dark condition at 4°C for 24h. After that, seeds were transferred to 1% sterilised agar plates (5 seeds per plate) and incubated for 12 days at 20°C under a 16/8 light/dark cycle. 2.4 Evaluation of germination parameters After sowing (day 0), the number of germinated seeds was recorded every day (from day 1 to day 12). Seed was considered as germinated if at least 2 mm of the radicle had emerged. After 12 days, root, shoot and total length was measured using a caliber. Fresh weight of the seedling was also measured. To compare the enhancement or inhibition effects of algal extracts, germination parameters were evaluated as reported by Kader [ 58 ] (except for growth speed which is suggested for the first time in this research). Detailed description of the parameters is reported in Table 4 . Morphological parameters (length and weight) were analysed as ratio compared to CTR values. Table 4 parameters used to study seed germination and to assess the biostimulation effect of algal extracts. Parameter Formula Description of parameter Description of values Final Germination Percentage \(\:FGP\:\left(\%\right)=\:\frac{{N}_{g}\:}{{N}_{t}}*100\) The higher FGP value, the greater the germination of the seed batch. N g : number of seeds germinated at the end of the experiment. N t : number of seeds sown at the beginning of experiment. Ng d : number of germinated seeds at day d. d: day of analysis Mean Germination Time \(\:MGT\:\left(day\right)=\:\frac{\sum\:{Ng}_{d}*d}{{N}_{g}}\) The lower the MGT value, the faster the germination. Coefficient of Velocity of Germination \(\:CVG\:\left({day}^{-1}\right)=\:\frac{100*{N}_{g}}{\sum\:{Ng}_{d}*d}\) CVG increases with increasing number of germinated seeds and with lower germination times. The highest possible CVG is 100. CVG indicates the velocity of germination. Germination Rate Index \(\:GRI\:\left(\%\:{day}^{-1}\right)=\:\sum\:\frac{{Ng}_{d}}{d}*100\) The higher GRI, the higher germinated seeds and faster germination. GRI indicates the percentage of germinated seeds each day of the experimental period. Germination Index \(\:GI=\left(12*{Ng}_{1}\right)+\left(11*{Ng}_{2}\right)\dots\:+\left(1*{Ng}_{12}\right)\) GI is related to both velocity of germination and number of germinated seeds. Higher weight is given to the fastest germinated seeds (at day 1). Weight ratio \(\:{W}_{r}=\frac{{W}_{x}}{Mean\:{W}_{ctr}}\) Ratio between the value of a treated seedling and the average value of the control condition. W: weight of seedling Shoot length ratio \(\:{LS}_{r}=\frac{{Ls}_{x}}{Mean\:{Ls}_{ctr}}\) L s : shoot length of seedling Root length ratio \(\:{LR}_{r}=\frac{{Lr}_{x}}{Mean\:{Lr}_{ctr}}\) L r : root length of seedling Total length ratio \(\:{LT}_{r}=\frac{{Lt}_{x}}{Mean\:{Lt}_{ctr}}\) L t : total length of seedling Growth speed \(\:G{S}_{L}\:\left(mm\:{day}^{-1}\right)=\frac{{L}_{t}}{{T}_{e}-MGT}\) \(\:G{S}_{W}\:\left(mg\:{day}^{-1}\right)=\frac{W}{{T}_{e}-MGT}\) It indicates the growth speed of the seedling (mm or mg per day) from the day of germination to the last day of experiment. GS: growth speed of seedling in terms of length (GS L ) or weight (GS W ) L t : total length of seedling W: weight of seedling T e : last day of experiment MGT: mean germination time 2.5 Statistical analysis Experiments were performed on 25 seeds for each treatment primed with algal extract and on 100 seeds for CTR condition primed with deionised water. Data are reported as mean ± standard deviation (SD) (if present). Graphpad prism 9.5.0 (GraphPad Software, San Diego, CA, USA) was used to perform statistical analysis. Two-way ANOVA followed by Tukey’s post-hoc test was used to analyse the parameters reported in Table 4 as a function of type (algae species) and concentration of biostimulants. All statistical analyses were performed with a significance level of α = 0.05. Asterisk (*) was used in Fig.s to distinguish significantly different groups ( p < 0.05). The p values resulting from the statistical analysis are reported in detail in Table S1 and Table S2. 3 Results 3.1 Germination parameters Tomato seeds ( Solanum lycopersicum “Minibel”, Germisem Sementes LDA, Portugal) were reported by the supplier company to have a FGP of 92% and a MGT of around 5 to 8 days. Based on the results, seeds primed with water (CTR) reported a FGP of 86%±2% (Fig. 2 ), thus quite lower than the one claimed by the company. On average, at 0.05 and 0.1 mg mL − 1 of algal extracts, the biostimulation increased the FGP up to 100% as in the case of algal extract from T. obliquus at 0.1 mg mL − 1 (Fig. 2 , Table 5 ). Reduction in the number of germinated seeds was observed at the highest concentration tested and this trend was intensified for those seeds treated with algae grown in digestate (FGP dropped from 88 to 80%, Fig. 2 ). Overall, the extract concentration was a significant source of variation of the FGP ( p < 0.0001). The application of spent media at the lowest tested concentrations (10%) resulted in an increased germination. Nonetheless, as for the algal extracts, concentration highly affected the seeds germination ( p < 0.0001), and FGP decreased with increasing concentration of spent medium: e.g. when the consortium spent medium was applied the FGP decreased from 100% (at 10% of spent medium) to 72% (at 100% of spent medium) (Fig. 2 ). Contrary to the spent medium of the consortium, the spent media of the single species always reported FGP higher or comparable to that of CTR. On average, the consortium grown in the digestate and its spent medium were the treatments with the lowest number of germinated seeds (Fig. 2 ). For each treatment condition (algal extract or spent medium) the algal source was an important source of variation ( p < 0.0001) and so was its interaction with the biostimulant concentration ( p < 0.0001). It can then be stated that the combined effect of concentration and biostimulant source had a significant effect on the germination of tomato seeds. The CTR seeds reported a MGT of 3.88 ± 0.94 d, similarly to the treatments where seeds were primed with 0.05 and 0.2 mg mL − 1 of algal extracts. On the contrary, seeds primed with 0.1 mg mL − 1 of algal extracts required more time to germinate and, except the seeds treated with the extracts of A. protothecoides and the consortium, MGT values were statistically higher than the CTR ones. Both treatment and extract concentration had a significant effect on MGT values ( p = 0.0093, p < 0.0001 respectively). Combined effect of these factors was also significant on explaining the observed variability ( p < 0.0001). Contrary to the priming with algal extracts, most of the seeds treated with the spent media reported a MGT statistically similar to the CTR one (Fig. 3 ). Few exceptions were observed using 10 and 50% of the consortium spent medium ( p = 0.0008, p = 0.0002) and the 50% spent medium of consortium grown in digestate at ( p = 0.0496) whose MGT values were higher than those of CTR (Fig. 3 ). While most of the treatments were comparable to the control, both treatment and spent medium concentration were significant in explaining the observed variance, but the treatment had a higher weight than the concentration ( p < 0.0001, p = 0.0066 respectively), opposite to what observed for the application of algal extracts. It is worth noting that longer time required for germination (MGT) moderately correlated to a higher number of germinated seeds (FGP) and vice versa . Correlation was confirmed by Pearson correlation test where a Pearson coefficient of 0.3819 and a p value of p = 0.0340 were found (Fig. 4 ). Correlation between the two variables was also visible analysing the CVG parameter which considers the time of seed germination and the number of germinated seeds. Indeed, differences among treatments were minimal, and ANOVA analysis revealed almost no statistical significance. Since a higher FGP correlated with a higher MGT, changes in CVG, which is positively correlated with the number of germinated seeds and negatively with the time of germination, were negligible. Due to its dependence on the number of germinated seeds and the time of germination, the GRI exhibited a similar trend to the CVG for both the algal extracts and the spent media. Additionally, the concentration of algal extract significantly explained the observed differences, with the most notable differences occurring at 0.01 mg/mL. Nonetheless, contrary to CVG, the treatment factor was also significant ( p = 0.0035). Indeed, while most of the treatments reported similar results, treated seeds with the extract of the consortium grown in digestate had the lowest GRI values at each extract concentration due to the low FGP (88%, 88%, 80% respectively) and the high MGT (4.76 ± 1.22, 5.36 ± 2.81, 3.65 ± 0.49 days respectively). It could be noted that at the concentration of 0.2 mg mL − 1 both GRI and CVG for the above-mentioned treatment were higher than those at the other two concentrations. Lastly, GI of seeds treated with algal extracts was both dependent on treatment condition and algal concentration ( p = 0.0024, p = 0.0007 respectively); extracts of T. obliquus and A. protothecoides were the treatments with the highest values at each tested concentration. As for the forementioned parameters, GI was lower at the intermediate extract concentration due to an increasing MGT. Nonetheless, reduction in GI was lower in 0.01 mg mL − 1 T. obliquus and A. protothecoides applications due to a high FGP (100% and 92%, respectively). Lowest results were recorded for seeds treated with extracts of consortium grown in digestate as previously reported. Differently to algal extract application, the spent media priming did not significantly change GI of seeds which was almost comparable to the CTR one. As for previous parameters, GI of the treatments with consortium spent medium was always lower than the that of other treatments within the same concentration group. To conclude, a certain relationship between concentration, velocity of germination and number of germinated seeds was observed. On average, low MGT (i.e. fast seeds) was typical of the lowest and highest concentrations which also presented a low number of germinated seeds (FGP). This relationship was particularly evident when seeds were treated with the algal extracts while changes due to the spent media applications were mostly observed in a variation of the FGP. Noteworthy, at the concentration of 0.1 mg mL − 1 MGT increased as well as the number of germinated seeds. Increasing even more the concentration led also to an increased toxicity with MGT similar to the one observed at the lowest tested concentration but with lower FGP. Different effects were caused by the application of the spent media, even so significative changes compared to CTR were found particularly in the FGP. More than the algal extracts, concentration of spent media strongly affected germination of the seeds primed with spent media from C. reinhardtii and the consortium grown in diluted digestate as the main examples of this effect. 3.2 Effect on weight and morphology of seedlings Similarly to the germination parameters, effects on seedling morphology were mostly dependent on the biostimulant concentration whereas the algal species had a less significant impact in explaining the observed differences. Significant differences were observed between the two treatment groups (algal extract and spent medium) in terms of the seedling organ most affected by the treatment. This indicates distinct mechanisms of action for the two classes of biostimulants. Looking at the shoot length the algal extract had an overall higher effect compared to that of spent media. The concentration of the extracts significantly affected the shoot length ( p < 0.0001): indeed, it was stimulated by extracts at the concentration of 0.1 mg mL − 1 whereas the other tested concentrations elicited comparable results to those of the CTR, even if a certain trend of shoot shortening was observed at the highest concentration. Conversely, the spent media did not significantly affect shoot length, except for the spent medium derived from the consortium culture in diluted digestate, which had a deleterious effect on the shoots. In fact, shoot length negatively correlated with the concentration of the medium. While shoot length saw the greatest improvement with algal extract treatment, root length was most significantly enhanced by the spent medium treatment. Notably, the increase in root length was observed with 100% spent medium treatments of T. obliquus, C. reinhardtii and A. protothecoides. On average, weight of seedlings increased when seeds were treated with both algal extracts and spent media at the lowest two tested concentrations (0.05–0.1 mg mL − 1 and 10–50%). However, the concentration of biostimulants was more significant in explaining the observed variation for the algal extract group ( p < 0.0001) compared to the spent medium group ( p = 0.0604). Nonetheless, the source of the biostimulant (i.e. the algal species) was significant for both the groups highlighting differences within the groups and between them. The greater stimulation was due to the treatment with the extract of T. obliquus and with the medium from C. reinhardtii culture. Again, it was proved that results from algal extracts and spent media were not related. Notably, at the highest concentration of spent media (100%), the weight of the seedlings did not decrease, despite changes in length and the previously discussed germination parameters. When the spent medium from consortium culture was applied, the weight was even higher than in the CTR. The higher seedling weight was not consistent with a longer seedling length. Among all the treatments, only the extract of C. reinhardtii at 0.1 mg mL − 1 was able to increase both shoot and root length together with an increase in weight too. Other treatments promoted the growth of one or another organ of the seedling. To be note is that, overall, the total length was not related to a faster germination ( p = 0.4549), indeed, while for the algal extract group the longer seeds were the one germinated at 0.1 mg mL − 1 and which displayed higher values of MGT, within the spent media group the MGT was not dependent on the concentration and the length of the seedling changed independently from the parameter. In addition to the length of shoot and root, the ratios between the organs (root/shoot) provided further insights on the effects and mechanisms of the biostimulation (Table 5 ). On average a certain reduction in the ratio compared to the CTR was observed meaning that the shoots grew more than the roots, however, response to increasing concentrations differed depending on the type of biostimulant: ratio increased at the expense of the shoot due to the spent media while it decreased because of algal extracts treatment. Notable examples include the spent medium of T. obliquus and the extract of C. reinhardtii where the opposite effects could be seen. 3.3 Effect on the growth speed As already observed, all the tested variables (i.e. type of biostimulant, treatment and concentration) induced significative changes in germination and morphology even though they were not related to each other. However, combining data on germination time (MGT) and seedling morphology revealed that despite a comparable length or weight of treated seeds to those of CTR (e.g. treatments at 50% of spent media), the GS value was higher due to a slower germination (higher MGT) (Fig. 5 ). A remarkable example is the case of seeds treated with 0.1 mg mL − 1 of algal extract: they showed longer and heavier seeds but also a higher MGT, thus resulting in a GS even higher than in the previous example (Fig. 5 ). Table 5 germination parameters of control and treated seeds. Data are divided per treatment and type of applied biostimulant: algal extract (0.05, 0.1, 0.2 mg mL − 1 ) or spent medium (10, 50, 100%). Data is reported as mean ± standard deviation. Legend: FGP (final germination percentage), MGT (mean germination time), CVG (coefficient of velocity of germination), GRI (germination rate index), GI (germination index), W r , (weight ratio), LS r (shoot length ratio), LR r (root length ratio), LT r (total length ratio), GS L (length growth speed), GS W (weight growth speed). Results of the statistical analysis are reported in detail in the supplementary material (Table S1 , TableS2). Treatment Concentration FGP (%) MGT (day) CVG (day − 1 ) GRI (% day − 1 ) GI W r LS r LR r Ratio organs GS L (mm day − 1 ) GS W (mg day − 1 ) CTR / 86% ± 2% 3.9 ± 0.9 25.7 ± 1.0 23% ± 0.9 175 ± 3 / / / 3.4 ± 1.0 7.7 ± 1.6 2.1 ± 0.4 T. obliquus Algal extract 0.05 mg mL − 1 88% ± 1% 3.4 ± ± 29.2 ± 0.6 26% ± 0.7 188 ± 2 1.4 ± 0.1 1.4 ± 0.2 1.0 ± 0.2 2.4 ± 0.8 7.9 ± 1.1 2.7 ± 0.3 0.1 mg mL − 1 100% ± 1% 4.9 ± ± 20.5 ± 0.5 24% ± 0.7 178 ± 3 1.3 ± 0.2 1.3 ± 0.3 1.2 ± 0.4 3.3 ± 0.8 11.2 ± 2.8 3.2 ± 0.5 0.2 mg mL − 1 92% ± 1% 3.6 ± ± 28.0 ± 1.0 27% ± 0.8 194 ± 3 1.0 ± 0.3 1.2 ± 0.2 0.7 ± 0.1 2.0 ± 0.6 5.9 ± 1.0 2.1 ± 0.5 Spent medium 10 % 90% ± 1% 3.7 ± ± 27.1 ± 0.6 26% ± 0.6 188 ± 2 1.2 ± 0.3 1.1 ± 0.2 1.0 ± 0.2 2.8 ± 0.4 8.2 ± 1.2 2.8 ± 0.3 50 % 86% ± 2% 3.8 ± ± 26.5 ± 0.7 24% ± 0.3 176 ± 3 1.3 ± 0.3 1.2 ± 0.2 0.9 ± 0.2 2.5 ± 0.6 9.5 ± 2.4 2.7 ± 0.4 100 % 90% ± 1% 4.3 ± ± 23.5 ± 0.7 25% ± 0.8 175 ± 2 1.1 ± 0.4 1.1 ± 0.3 1.3 ± 0.5 4.1 ± 1.3 6.5 ± 1.1 2.3 ± 0.6 C. reinhardtii Algal extract 0.05 mg mL − 1 88% ± 1% 3.6 ± ± 27.5 ± 0.8 26% ± 0.6 184 ± 2 1.1 ± 0.3 1.0 ± 0.2 1.1 ± 0.4 3.6 ± 0.7 7.6 ± 2.2 2.3 ± 0.5 0.1 mg mL − 1 92% ± 0% 5.3 ± ± 19.0 ± 1.2 21% ± 0.8 155 ± 4 1.1 ± 0.3 1.3 ± 0.2 1.3 ± 0.4 3.3 ± 0.7 12.4 ± 3.0 3.0 ± 0.8 0.2 mg mL − 1 92% ± 1% 3.5 ± ± 28.8 ± 0.3 27% ± 0.8 196 ± 2 1.0 ± 0.2 0.9 ± 0.1 0.9 ± 0.1 3.3 ± 0.7 6.4 ± 0.9 1.9 ± 0.4 Spent medium 10 % 90% ± 1% 3.6 ± ± 28.1 ± 1.0 26% ± 0.6 190 ± 3 1.4 ± 0.3 1.2 ± 0.2 1.2 ± 0.2 3.3 ± 0.9 7.5 ± 2.2 2.2 ± 0.5 50 % 90% ± 1% 3.9 ± ± 25.3 ± 1.0 24% ± 0.7 182 ± 3 1.3 ± 0.2 1.2 ± 0.2 0.9 ± 0.2 2.6 ± 0.5 10.1 ± 2.4 2.4 ± 0.7 100 % 86% ± 2% 3.3 ± ± 30.0 ± 0.3 26% ± 1.0 186 ± 3 1.3 ± 0.3 1.1 ± 0.2 1.4 ± 0.5 4.2 ± 1.5 6.3 ± 0.8 1.9 ± 0.4 A. protothecoides. Algal extract 0.05 mg mL − 1 92% ± 1% 3.7 ± ± 27.1 ± 0.4 27% ± 0.3 191 ± 2 1.1 ± 0.2 1.0 ± 0.2 1.1 ± 0.2 3.8 ± 0.9 8.0 ± 1.5 2.3 ± 0.5 0.1 mg mL − 1 92% ± 1% 4.5 ± ± 22.3 ± 0.8 23% ± 0.7 173 ± 2 1.3 ± 0.4 1.4 ± 0.3 1.3 ± 0.4 3.2 ± 0.8 11.1 ± 2.9 3.1 ± 0.9 0.2 mg mL − 1 96% ± 1% 4.2 ± ± 24.0 ± 0.6 26% ± 1.1 188 ± 2 0.9 ± 0.2 1.0 ± 0.2 0.6 ± 0.2 2.1 ± 0.8 5.6 ± 1.4 1.9 ± 0.4 Spent medium 10 % 90% ± 1% 3.6 ± ± 27.5 ± 0.7 26% ± 0.8 189 ± 2 1.3 ± 0.2 1.0 ± 0.1 1.1 ± 0.3 3.5 ± 0.6 7.9 ± 1.5 2.3 ± 0.5 50 % 90% ± 0% 4.1 ± ± 24.7 ± 0.6 23% ± 0.3 180 ± 1 1.1 ± 0.2 1.1 ± 0.2 1.1 ± 0.2 3.8 ± 0.8 10.4 ± 2.8 2.9 ± 0.8 100 % 95% ± 1% 3.3 ± ± 30.8 ± 1.2 30% ± 0.8 208 ± 3 1.2 ± 0.2 1.1 ± 0.2 1.3 ± 0.3 4.0 ± 1.0 5.0 ± 1.2 1.7 ± 0.3 Consortium Algal extract 0.05 mg mL − 1 92% ± 1% 3.9 ± ± 25.6 ± 0.6 26% ± 0.3 186 ± 2 1.4 ± 0.3 1.0 ± 0.2 1.1 ± 0.2 3.5 ± 0.7 8.2 ± 1.7 2.9 ± 0.7 0.1 mg mL − 1 88% ± 1% 4.7 ± ± 21.4 ± 0.5 21% ± 0.5 161 ± 2 1.0 ± 0.3 1.0 ± 0.2 1.1 ± 0.3 3.2 ± 1.0 8.5 ± 2.6 2.3 ± 0.6 0.2 mg mL − 1 84% ± 1% 3.2 ± ± 30.9 ± 0.6 27% ± 0.8 184 ± 2 0.9 ± 0.1 0.8 ± 0.1 0.9 ± 0.2 3.5 ± 0.5 5.9 ± 1.0 1.7 ± 0.2 Spent medium 10 % 100% ± 1% 5.0 ± ± 20.2 ± 0.6 21% ± 0.7 176 ± 1 1.2 ± 0.2 1.0 ± 0.1 1.0 ± 0.2 3.4 ± 0.4 9.6 ± 2.0 3.4 ± 0.8 50 % 90% ± 1% 5.1 ± ± 19.8 ± 0.9 19% ± 0.6 157 ± 2 1.2 ± 0.2 1.1 ± 0.1 1.0 ± 0.2 3.1 ± 0.7 9.1 ± 2.7 2.5 ± 0.6 100 % 76% ± 1% 3.6 ± ± 28.1 ± 0.5 22% ± 0.7 161 ± 2 1.4 ± 0.3 1.0 ± 0.2 1.1 ± 0.3 3.5 ± 0.4 6.0 ± 1.5 1.4 ± 0.2 Consortium grown in digestate Algal extract 0.05 mg mL − 1 88% ± 1% 4.8 ± ± 21.0 ± 0.8 19% ± 0.5 158 ± 4 1.1 ± 0.2 1.0 ± 0.2 0.9 ± 0.3 3.1 ± 0.9 8.3 ± 2.0 2.7 ± 0.6 0.1 mg mL − 1 88% ± 1% 5.4 ± ± 18.6 ± 1.2 19% ± 1.0 146 ± 4 1.2 ± 0.3 1.2 ± 0.2 1.2 ± 0.5 3.6 ± 1.5 11.6 ± 3.5 3.1 ± 0.7 0.2 mg mL − 1 80% ± 2% 3.7 ± ± 27.4 ± 0.7 22% ± 0.8 167 ± 2 1.0 ± 0.1 0.9 ± 0.2 0.9 ± 0.2 3.4 ± 1.0 6.9 ± 1.2 2.0 ± 0.2 Spent medium 10 % 90% ± 1% 4.2 ± ± 24.1 ± 0.8 22% ± 0.5 177 ± 3 1.5 ± 0.3 1.2 ± 0.2 1.2 ± 0.3 3.5 ± 0.8 6.8 ± 1.4 1.7 ± 0.4 50 % 86% ± 1% 4.2 ± ± 24.0 ± 0.4 21% ± 0.7 168 ± 1 1.1 ± 0.4 0.7 ± 0.5 0.9 ± 0.2 3.6 ± 1.0 4.7 ± 1.3 2.2 ± 0.5 100 % 81% ± 1% 3.5 ± ± 28.8 ± 0.3 24% ± 0.9 173 ± 2 1.0 ± 0.2 0.6 ± 0.3 0.8 ± 0.2 3.9 ± 1.2 5.5 ± 1.7 1.9 ± 0.2 4 Discussion 4.1 Biostimulant effect on seed germination The germination process was influenced by the algal species and the concentration of the biostimulant. This was also noted by Alling et al. [ 39 ], who found that the effects were connected to the biostimulant source ( Chlorella vulgaris or Scenedesmus obliquus ) and the amount of extract used. Despite that, contrary to what reported by the author, a linear correlation between MGT and extract concentration was not found, and the achieved results were either comparable to or higher than those in the control condition. These differences could be attributed to the use of different cultivars of Solanum lycopersicum , as well as variations in the cultivation methods of the algae, such as different growth medium and parameters. Amaya-Santos et al. [ 59 ] demonstrated that the cultivation conditions of algae, such as the use of treated or untreated wastewater and light or dark regime, resulted in different biostimulant effects on treated soybeans. However, it's important to note that the application of spent media did not change the MGT of treated seeds, regardless of the concentration or algal source, but it did alter the FGP. Similar results were found by Bahmani Jafarlou et al. [ 60 ] when using Arthrospira platensis extracts on milkweed ( Calotropis procera ) seeds. Another difference from many works found in literature is the pre-treatment of the algae and the use of specific fractions. Despite the similarity of algal extract concentrations to ours, Alling et al. [ 39 ] also tested the effectiveness of several extraction methods showing that the method of extraction and different algal fractions can significantly impact the outcome of the biostimulation. Similarly, Rupawalla et al. [ 57 ] found that the inner content of algal cells released after cell lysis treatment was the best way to improve spinach germination and development. On the other hand, other authors [ 40 ] found that even entire cells possess biostimulant activity, thus eliminating the need for a biomass pre-treatment. Based on the literature, we decided to adopt a faster, more affordable, and reagent-free method using high N 2 pressure to disrupt the cells. Since most of the literature indicated that the overall inner content has biostimulant activity, we chose a method that did not require the application of multiple fractionations. The results, in terms of FGP, were comparable to the literature and even better since a much smaller quantity of algae was used compared to many other research studies. Even the spent medium from microalgal plants can be used as a biostimulant, offering a solution to the challenge of recycling growing media. Although recycling the spent medium can be complicated due to the build-up of infochemicals and inhibitors, it is essential to minimize water and nutrient input in order to reduce algal production costs [ 61 ]. Reusing the spent medium would give a second life to this byproduct, leading to cost savings in cultivation. Unlike algal biomass, the spent medium only requires filtration to reduce particulate matter, making it a readily-usable product for agricultural purposes. In experimental conditions, the spent media exhibited biostimulant activity, consistent with existing literature [ 39 , 56 , 57 ]. The presence of infochemicals, metabolites, and possibly phytohormones [ 36 , 56 ] may have contributed to improved germination at the lowest tested concentrations (10%) but not at the highest since an excessive concentration of these molecules may have a bioherbicide effect than a biostimulant one [ 62 , 63 ]. However, the germination parameters of seeds treated with spent media of consortium grown in BG11 or in digestate were unsatisfactory at each concentration, possibly indicating issues with the use of multi-species-based biostimulants. The effectiveness of blended biostimulants (made from a combination of at least two macro/microalgal species) has been studied and confirmed by researchers such as Sarkar et al. [ 64 ] and Jafarlou et al. [ 65 ]. These studies have shown that blending extracts from different algal species can have a synergistic effect, enhancing biostimulant activity compared to individual extracts. However, in our trials, we observed lower activity of the biostimulants made from the co-cultivation of multiple species, compared to the ones made from single-species cultures. This contrasts with previous research. The differences in our results would be attributed to the way the biostimulants were formulated. In our case, the blending was the results of co-cultivation of microalgae, which is different from mixing individual biostimulants. In the last case, the properties of the resulting product were influenced by the quantity of each individual biostimulant added to the blend. Additionally, our product's quality differed from single-species biostimulants due to the co-cultivation process. Co-cultivating algae stimulates the release of specific infochemicals [ 66 – 72 ] that are typically absent in mono-specific cultures. This increased diversity in the spent medium metabolome was also reflected in the algal metabolome [ 73 ], leading to changes that could be responsible for the reduced activity observed in our biostimulants. The formulation of biostimulants turns out to be crucial; despite the higher growth performance of the consortium compared to single species, the resulting biostimulant was not performing as well [ 46 ]. Looking at the biochemical composition of algal extracts it can be observed a huge difference between algae grown in BG11 standard medium and the algal consortium that grew in digestate, especially in the element composition. The higher content of Ca in diluted digestate grown cells can be explained by the higher ion availability in the external medium and its higher precipitation on the cell wall due to the increasing pH level during the algal growth [ 48 ]. The medium composition could have drastically changed the algal cell elemental quota [ 74 ] thus affecting germination and growth of tomato seeds. Potentially, even toxic compounds uptaken by algae during growth in wastewaters (such as the phenolic compounds of Olive Mill Wastewater) could have affected the biostimulation outcomes. Nonetheless, literature is plenty of cases where wastewaters are used to make products for agricultural purposes whose effects are beneficial for the plants. For example, Navarro-López et al. [ 40 ] produced and tested biostimulants made with Scenedesmus obliquus grown in brewery wastewater and the obtained results were significantly better than in control condition (seeds treated with water). The concentration tested by the authors was far higher than the ones here presented (2-0.5 mg mL − 1 compared to 0.05–0.2 mg mL mL − 1 ), nonetheless, no evidence of toxicity was found. A similar result was also reported by Navarro-López et al. [ 75 ] with algae grown in urban wastewater. Again, GI and FGP were slightly increased due to the treatment with 0.5 and 2 mg mL − 1 algal extracts. Together with others [ 20 , 41 , 59 , 76 ] they proved that many factors may be involved in explaining the properties of the biostimulants and that the culture medium can significantly affect the quality of the product. Indeed, in the best case (the lowest concentration), both the algal extract of our consortium grown in the digestate and its spent medium were the treatments with the lowest number of germinated seeds. For what concerns the spent media, it’s likely that phycoremediation carried out by algae was not able to remove all those toxic compounds which endured in the medium and then affected the biostimulation. 4.2 Biostimulant effect on seed development All tested biostimulants exhibited phytohormone-like activity. Previous reports attributed the higher FGP to a gibberellins-like effect [ 65 , 77 , 78 ]. From a morphological perspective, auxin and cytokinin-like effects were observed, leading to increased root and shoot length. Concentration was found to have a negative impact on the overall length of the seedlings, which is consistent with the findings of Alling et al. [ 39 ] in barley and tomato seeds. Notably, the author also reported that the length of tomato seedlings was generally shorter than the length of CTR ones despite faster germination (resulting in a lower MGT). However, our results differ from those above reported, as the reduced length of the seedlings was only observed at the highest biostimulant concentrations (0.2 mg mL − 1 and 100%). Seeds treated with 0.1 mg mL − 1 of algal extracts were longer, despite experiencing delayed germination. Root growth was stimulated by biostimulants proving an auxin-like effect [ 21 ]. The highest stimulation was observed at a concentration of 0.1 mg mL − 1 of algal extracts, with even greater stimulation coming from undiluted spent media (100%). Apart from consortium (grown in standard medium or in digestate) treated seeds, whose issues were detailed in the previous paragraph, the root length ratio values of 1.3, 1.4, and 1.3 were respectively observed for the seeds treated with the spent media of T. obliquus, C. reinhardtii and A. protothecoides . It was reported by [ 57 ] that phytohormones such as cytokinins, auxins, and gibberellins were present in the soluble fraction of lysed algal cells. Additionally, Kapoore et al. [ 34 ] mentioned that phytohormones can be released into the extracellular medium. The release of these molecules, or infochemicals, was there identified as the primary cause of observed growth, even at the highest concentrations. A hypothesis is that the co-cultivation and the potential competition for nutrients led to the accumulation of a different set of phytohormones in biostimulants made from consortia cultures including abscisic acid (ABA): in algae ABA is produced under different environmental stresses [ 79 ] and could have an ecological significance in the regulation of association with other microorganisms [ 80 ], however in plants was already reported to have an opposing effect to gibberellin in seed germination [ 39 , 57 ]. Rupawalla et al. [ 57 ] further reported an overall increase in tomato seedlings' length with increasing spent media concentration; however, details about the individual growth of shoot and root were not provided, preventing a comparison of the effects of biostimulants on these two organs. Algal extracts were found to be more effective than the spent media in changing the shoot length. These differences could be due to a variation in phytohormone composition, as well as differences in the biochemical composition. Indeed, the algal biomass is rich in proteins, lipids, and carbohydrates [ 14 ] compared to the spent media and it was proved that the carbohydrate group was particularly effective in enhancing shoot length in tomato plants [ 35 ]. Spent media could contain carbohydrates in the form of Extracellular Polymeric Substance (EPS), which is known to enhance shoot length in tomato plants [ 34 ]. Nonetheless, the pre-treatment involving 0.22 mm filtration of the spent medium before its application may have removed or reduced the pool of exopolysaccharides. The scant presence of carbohydrates could contribute to a lesser variation in shoot length as compared to algal extract application. The ratio between plant organs is influenced by biostimulants, which have a strong impact on root and lateral root development [ 21 , 26 ]. Biostimulation often leads to higher root development compared to shoot development due to the activation of water stress-related pathways [ 44 ]. A study by Ferreira et al. [ 20 ] tested four algal extracts on six types of plants and found that the average root length varied more significantly than changes in shoot length. Similarly, Jafarlou et al. [ 65 ] noted a drastic decrease in root length at high concentrations, while the shoot was less affected. Our experiments showed that the variations in root/shoot ratio depended on the type and concentration of biostimulant (algal extract or spent medium), while the algal source had a less significant impact. Two trends were observed with increasing concentrations: 1) algal extracts increased shoot length, and 2) spent media increased root length. Notably, the extract of A. protothecoides and the spent medium of C. reinhardtii were significant examples of the two trends, with values changing from 3.8 to 2.1 and from 3.3 to 4.2, respectively. Although our data align with existing literature, research on spent media is limited, and information on root/shoot length variation is lacking. Nevertheless, these differences could be attributed to the varied composition and content of phytohormones. Therefore, biostimulants should be chosen carefully based on the desired outcomes, as different effects on seed development may be achieved. The weight of the seedlings increased in proportion to their length, which is consistent with similar findings in the literature [ 65 , 81 ]. Apart from quantifying biomass, an analysis of growth speed revealed that most of the treated seeds grew much faster than the control seeds. This effect was particularly noticeable in seeds treated with 0.1 mg mL − 1 of algal extracts. Despite longer mean germination time (MGT), these seeds displayed greater weight and length. Although literature lacks parameters that combine germination time and morphological features, such data could offer further insight into seed vigour and biostimulation mechanisms. Faster-growing crops with shorter growth cycles (faster maturation) would lead to larger plants in a shorter time enhancing plant resilience in adverse and unpredictable weather conditions [ 82 , 83 ]. Therefore, biostimulation would likely increase productivity through a higher number of germinated seeds and greater biomass production over time. 5 Conclusion The use of microalgae-based biostimulants is a promising approach to enhance agricultural sustainability and crop production. Both algal extracts and spent media have been proved to be effective in increasing the frequency of germination and the growth velocity of seedlings. Using spent media as biostimulants is beneficial because of the infochemicals and phytohormones released by algae during their growth. This helps to tackle the issue of discarding or recycling growth media. This discovery allows for the simultaneous production of two types of biostimulants with different activities. However, even minor changes in biostimulant concentration greatly impact the treatment outcomes. The coupling of wastewater remediation with biostimulant production has been discussed several times in the literature, demonstrating that the implementation of a circular and sustainable process is possible. However, as reported here, the type of wastewater may significantly affect the biomass and extract quality of the algae, leading to lower germination and growth of plants than in control conditions. The toxic compounds in the digestate may have been absorbed or adsorbed by the algae, subsequently remaining in the final product (e.g. biostimulant) after algal extraction. The reduced effect of the algal consortium-based biostimulant in comparison with the single species-based ones highlighted a significant issue that should be considered when producing a biostimulant. Mixing algal biomass coming from various monocultures is different from having biomass coming from a co-culture of multiple species. Co-cultivation modifies the biomass quality of the algae, and even the infochemicals and metabolites released in the medium change. While many points must be addressed before achieving significant biostimulation, the results presented are promising and show that even a small concentration of microalgae can induce notable changes in plant development. In the event that microalgae-based biostimulants prove to be sustainable and are successfully adopted in agriculture, the presented seed-priming methodology will provide a straightforward and rapid approach for screening and selecting algal extracts for use on crops. In the future, a bio-refinery approach could be implemented, allowing us to use specific algal fractions to further improve biostimulation. Abbreviations FGP: final germination percentage MGT: mean germination time CVG: coefficient of velocity of germination GRI: germination rate index GI: germination index GS: growth speed Declarations Funding The authors thank CIRCC (Progetti Competitivi 2021/CMPT212338 e 2022/CMPT222955, MIUR) for the financial support. Research for LM PhD project was partially funded by Enereco SpA, Italy. Acknowledgments We would like to thank the research group “Laboratory of Biology of the algae” of University of Rome Tor Vergata, especially PhD student Alberta Di Cave who gave clarifications on the seed priming methodology. We also thank the student trainees who helped in the manual work. Contributions Conceptualization: LM and AN. Formal analysis: LM. Investigation: LM. Methodology: LM and AN. Supervision: AN. Visualization: LM. Writing – original draft: LM. Writing – review & editing: LM and AN. Funding acquisition: AN. Ethics declarations Ethics and consent to participate The seeds used in the present study were procured from Germisem Sementes Lda (Oliveira do Hospital, Portugal), a Portuguese seed company. The research involving Tomato ( Solanum lycopersicum L.) was conducted following approved guidelines set forth by the university and national regulations. Conflict of interest The authors declare no competing interests. Data Availability The materials and data that support the findings of this study are available from the corresponding author upon reasonable request. References FAO (2020) Emissions due to agriculture. Global, regional and country trends 2000–2018. FAOSTAT Analytical Brief Series No 18 Singh R, Singh GS (2017) Traditional agriculture: a climate-smart approach for sustainable food production. Energy Ecol Environ 2:296–316. https://doi.org/10.1007/s40974-017-0074-7 Lesk C, Rowhani P, Ramankutty N (2016) Influence of extreme weather disasters on global crop production. 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Supplementary Files Supplementarymaterialtomatoseeds281024.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Dec, 2024 Reviews received at journal 15 Dec, 2024 Reviews received at journal 15 Dec, 2024 Reviews received at journal 13 Dec, 2024 Reviews received at journal 13 Dec, 2024 Reviews received at journal 09 Dec, 2024 Reviews received at journal 08 Dec, 2024 Reviewers agreed at journal 06 Dec, 2024 Reviewers agreed at journal 06 Dec, 2024 Reviewers agreed at journal 05 Dec, 2024 Reviewers agreed at journal 05 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers agreed at journal 04 Dec, 2024 Reviewers invited by journal 04 Dec, 2024 Editor assigned by journal 22 Nov, 2024 Submission checks completed at journal 19 Nov, 2024 First submitted to journal 05 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5394178","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":383773863,"identity":"d6e9d8d5-201d-475f-ae4a-c074e63ce801","order_by":0,"name":"Lorenzo Mollo","email":"","orcid":"","institution":"Università Politecnica delle Marche","correspondingAuthor":false,"prefix":"","firstName":"Lorenzo","middleName":"","lastName":"Mollo","suffix":""},{"id":383773864,"identity":"cdad6e89-eb0b-48f9-a0c4-4439c85e2cea","order_by":1,"name":"Alessandra Norici","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvklEQVRIiWNgGAWjYNACAwYefiB1AMRmI1qLZANMC5F6gLoOwFiEtPA38B58XFFgJ2N8I/fgYd4d2xj45Bvwa5E4wJdseMYgmcfsRl7CYd4zt4lw2AEeM8kGAyB5I8fg4Mw2IrTIw7QYzyBWiwFMi4FEjsGBj8RoMTzMY2zYAPSLxJk3QC1nbvOwsSXg1yJ3vMfwYcMfO3v+9hzjD4k7bsvJNx8gYA0zMoexgYGHgHp0ANQyCkbBKBgFowADAADORjvB7bZ3dQAAAABJRU5ErkJggg==","orcid":"","institution":"Università Politecnica delle Marche","correspondingAuthor":true,"prefix":"","firstName":"Alessandra","middleName":"","lastName":"Norici","suffix":""}],"badges":[],"createdAt":"2024-11-05 09:38:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5394178/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5394178/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70434775,"identity":"731ef03a-fe28-499d-b1b7-a84d5f014fda","added_by":"auto","created_at":"2024-12-03 06:51:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":612350,"visible":true,"origin":"","legend":"\u003cp\u003eworkflow of seed priming experiment to evaluate the biostimulant capacity of algal extracts and algal spent media. Three algal species were cultivated and tested: 1) \u003cem\u003eTetradesmus obliquus\u003c/em\u003e, 2) \u003cem\u003eChlamydomonas reinhardtii\u003c/em\u003e and 3) \u003cem\u003eAuxenochlorella protothecoides\u003c/em\u003e. A previously established consortium of the three species, grown in a standard medium (BG11) or in a diluted digestate, was also tested. Crude algal extracts were prepared by cell bomb disruption of the algal biomass while spent media were collected following centrifugation of algal cultures. Priming with biostimulants was carried out on at least 25 seeds in the dark, at 4°C for 24h. Primed seeds were sowed on 1% agar plates and germination of the seeds was daily recorded. After 12 days from the sowing weight and length of the seedlings were measured and parameters were calculated according to germination and morphological parameters.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/b7d6f64d7bd8543b46f95f26.jpeg"},{"id":70434773,"identity":"284e402c-ade5-414b-8287-aa88d60fc022","added_by":"auto","created_at":"2024-12-03 06:51:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42629,"visible":true,"origin":"","legend":"\u003cp\u003eFinal germination percentage (FGP) of seeds treated with the algal extracts (a) or with the spent media (b). FGP of control seeds treated with water was 86%±2% and is reported with three horizontal black dashed lines (mean±SD). Data are reported as mean±SD. Asterisks (*) represent the degree of significative difference between the CTR and treatment conditions (* p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001). Results of the statistical analysis are reported in detail in the supplementary material (Table S1, TableS2).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/4d9374a00d489d429a864470.png"},{"id":70434774,"identity":"596f9877-5f16-4e80-9431-78d5f48ef1a9","added_by":"auto","created_at":"2024-12-03 06:51:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39505,"visible":true,"origin":"","legend":"\u003cp\u003eMean germination time (MGT) of seeds treated with the algal extracts (a) or with the spent media (b). MGT of control seeds treated with water was 3.9±0.9 and is reported with three horizontal black dashed lines (mean±SD). Data are reported as mean±SD. Asterisks (*) represent the degree of significative difference between the CTR and treatment conditions (* p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001). Results of the statistical analysis are reported in detail in the supplementary material (Table S1, Table S2).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/ec0bc0be3790d70f88c75c99.png"},{"id":70434778,"identity":"db1e1f91-8b74-41f4-9c6b-f74113fab7a6","added_by":"auto","created_at":"2024-12-03 06:51:05","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":21608,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation analysis between final germination percentage (FGP) and mean germination time (MGT). Coefficient of correlation (r) and p-value are reported in the graph. Data are reported as mean±SD.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/e288af05b06c724cfc4e971d.png"},{"id":70435758,"identity":"90b39a5c-07d8-40cb-99f4-8aa62a8b7140","added_by":"auto","created_at":"2024-12-03 06:59:04","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":484328,"visible":true,"origin":"","legend":"\u003cp\u003eGrowth speed expressed as mm d\u003csup\u003e-1\u003c/sup\u003e (a-b) or mg d\u003csup\u003e-1\u003c/sup\u003e (c-d) of seeds treated with the algal extracts (a-c) or with the spent media (b-d). GS\u003csub\u003eL\u003c/sub\u003e and GS\u003csub\u003eW\u003c/sub\u003e of control seeds treated with water were 7.7±1.63 and 2.09±0.43 respectively. CTR data are reported with three horizontal black dashed lines (mean±SD). Data are reported as mean±SD. Asterisks (*) represent the degree of significative difference between the CTR and treatment conditions (ns p \u0026gt; 0.05, * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001). Results of the statistical analysis are reported in detail in the supplementary material (Table S1, TableS2).\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/a83f963e213d43b2d06d77e7.jpeg"},{"id":70437247,"identity":"42f97716-a974-46e2-9a7a-980721577707","added_by":"auto","created_at":"2024-12-03 07:15:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2668343,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/e3fe9513-532d-4d57-85a0-8be759423d0a.pdf"},{"id":70436056,"identity":"c17f8872-6dbe-4417-9031-d05026824206","added_by":"auto","created_at":"2024-12-03 07:07:04","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":20767,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterialtomatoseeds281024.docx","url":"https://assets-eu.researchsquare.com/files/rs-5394178/v1/7b9a7e576d96ee12b80d8995.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biostimulant potential of three chlorophyta and their consortium: application on tomato seeds","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGlobal warming represents one of the most pressing challenges of the 21st century, with rising global temperatures, shifting climatic patterns, and increasingly frequent and severe weather events being the main evidence of this phenomenon. While powerless we continue to observe record-breaking temperatures month after month (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://climate.copernicus.eu/\u003c/span\u003e\u003cspan address=\"https://climate.copernicus.eu/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), it is imperative that we attempt a transition of the sectors that emit the most greenhouse gases.\u003c/p\u003e \u003cp\u003eAgriculture is a key sector that significantly contributes to global warming and is profoundly impacted by its effects. Traditional agricultural practices are responsible for approximately 15% of global greenhouse gas (GHG) emissions, significantly contributing to climate change through the emission of carbon dioxide, methane, and nitrous oxide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Agriculture is also uniquely vulnerable to the impacts of climate change, as altering weather patterns, temperature shifts, and increased incidences of extreme weather events threaten crop yields, soil health, and water availability [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Furthermore, traditional agriculture negatively impacts most of the so-called planetary boundaries, virtual limits that define the safe operating limits for humanity within which the Earth system can continue to function in a stable state [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSolving this issue and transitioning towards a sustainable food system is no easy feat, especially since the practices we adopt for the future must account for the increasing food demand due to a projected world population of about 10\u0026nbsp;billion people in 2050. As reported by Searchinger et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], we need to fill a food and land gap of 7,400 trillion calories and 593\u0026nbsp;million hectares respectively, and we need to do that without increasing GHG emissions and, where possibly, reducing them to the target of 4\u0026nbsp;billion tons (to hold global warming below 2\u0026deg;C above pre-industrial temperature). It is quite an impossible challenge, but scientists worldwide have proposed multiple solutions that could help us reach this target [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong these solutions, microalgae have garnered significant attention due to their diversity and versatility [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Microalgae are a group of microorganisms that perform oxygenic photosynthesis and convert CO\u003csub\u003e2\u003c/sub\u003e to biomass with much higher efficiency than higher plants. Additionally, some microalgae can perform a mixotrophic metabolism using both inorganic and organic carbon, allowing them to thrive even in carbon-rich wastewater where they are exploited as a remediation process [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the agrifood system, microalgae are already successfully employed as human food or animal feed [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Depending on the phylum and species, microorganisms can accumulate high protein contents [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], which could serve as alternative sources of protein to the animal-based ones [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Essential amino acids, polyunsaturated fatty acids, and vitamins are also accumulated within the algal biomass, making them a real superfood [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Unlike plants, microalgae require less input, and nutrient run-off is practically absent due to their cultivation in open ponds or photobioreactors [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The possibility of using non-agricultural or contaminated land can increase food production without subtracting arable land from traditional agriculture. In addition, recycling wastewater nutrients reduces the need for fertilisers, helping to maintain the N and P biogeochemical flows within safe boundaries [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhen microalgae are not suitable for direct human consumption, other possible applications do exist in agriculture to indirectly ensure greater food production: biofertilizers, biopesticides, and biostimulants are among the sustainable methods for utilizing microalgae [\u003cspan additionalcitationids=\"CR20 CR21 CR22\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Biostimulants are substances and/or microorganisms that enhance nutrient uptake, nutrient efficiency, tolerance to abiotic stress, and crop quality [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As regulated by the EU parliament with the Regulation (EU) 2019/1009, these products do not directly provide nutrients, but they stimulate and activate the inner pathways of the plants, improving their overall growth [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Their use has gained interest in sustainable agriculture since it reduces fertilizer consumption and enhances abiotic stress defences (especially those related to water scarcity and salt stress [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]).\u003c/p\u003e \u003cp\u003eBiostimulants have been used in agriculture for a long time [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Macroalgae or seaweed-based biostimulants have been known to be used since ancient times in northern Europe, and recently modern products made of \u003cem\u003eAscophyllum nodosum\u003c/em\u003e are widely employed in agriculture. In the present day, several strategies are employed to enhance the biostimulant capability of algal extracts, including enzymatic and hydrolytic treatments, and extraction of specific fractions [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The amino-acidic fraction has been observed as one of the most active fractions [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], but polysaccharides and algal hormones can also induce functional changes in plants [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Macro and microalgae possess metabolic pathways to synthesize phytohormones, with IAA and cytokinins being the most common hormones found in almost all tested algae [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Nonetheless, it should be highlighted that hormone concentration for biostimulants should be lower than a certain threshold, or else the resultant product must be considered a plant growth regulator [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroalgae-based biostimulants are far more recent products than the seaweed ones and have gained widespread attention. Most of the microalgal extracts tested so far were made from cyanobacteria and chlorophyta [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]; the applications were successful in several plant species, including tomato, papaya, rocket, cucumber, wheat, maize, and barley [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Microalgal extracts are active as biostimulants at very low concentrations, even at 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], confirming that the observed effects are not associated with a direct provision of nutrients. Biostimulants have also been produced using algae grown in wastewater, and a biostimulant effect was still observed [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Circular processes could be designed with agro-food wastewaters remediated by microalgae, and the same algae could later be used as biostimulants in agriculture.\u003c/p\u003e \u003cp\u003eBiostimulants are commonly applied as foliar or seed application [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Seed application, also referred to as priming, requires soaking the seeds in the microalgal extracts for a minimum of 24 hours before sowing to initiate germination metabolism [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Using algal extracts, other pathways besides those required for germination are triggered, such as abiotic stress-tolerance pathways, and a \u0026ldquo;priming memory\u0026rdquo; within the seeds is established [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This memory is sustained during the development of the seeds, increasing the likelihood of germination and vigorous growth of the plant. Seed priming with biostimulants is an innovative process that could positively contribute to agricultural sustainability by increasing productivity and lowering input.\u003c/p\u003e \u003cp\u003eThe objective of this study was to evaluate the biostimulant potential of different dilutions of green algae crude-extracts, including \u003cem\u003eTetradesmus obliquus, Chlamydomonas reinhardtii, Auxenochlorella protothecoides\u003c/em\u003e, and their consortium, as well as their spent growth media. Biostimulant solutions were tested on tomato seeds, and their activity was evaluated through different germination indexes and on the development of the seeds at the end of the experiment, including weight, root/shoot length. The algal consortium was also cultivated in diluted digestate (e.g. wastewater produced during the anaerobic fermentation of biomass) as growth medium, and the resulting extract was tested.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003e2.1 Microalgae cultivation\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n \u003cp\u003e\u0026nbsp;Tree microalgae \u003cem\u003eAuxenochlorella protothecoides\u003c/em\u003e (CCAP 211/8D\u003ca href=\"#_ftn1\" name=\"_ftnref1\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e1\u003c/sup\u003e), \u003cem\u003eTetradesmus obliquus\u003c/em\u003e (CCAP 276/3A) and C\u003cem\u003ehlamydomonas reinhardtii\u003c/em\u003e (RCC125\u003ca href=\"#_ftn2\" name=\"_ftnref2\" title=\"\"\u003e\u003c/a\u003e\u003csup\u003e2\u003c/sup\u003e) were tested. A consortium of the three species, as established in Mollo et al. [46, 47] and Chieti et al. [48] was also tested. Mono-cultures and consortium were settled in BG11 medium [49] at controlled condition: 20\u0026deg;C, illuminated with white, fluorescent lamps at 100 mmol m\u003csup\u003e-2\u003c/sup\u003e s\u003csup\u003e-1\u003c/sup\u003e and 24h light. The consortium cultures were also established in and acclimated to a medium consisting of 7% tap water-diluted digestate. This digestate was sourced from an anaerobic digester fed with chicken manure, olive mill wastewater, and silages (kindly provided by Enereco S.p.A.). The initial composition of the digestate is detailed in Table 1. Cultures were grown until they reached the stationary phase; algal biomass was then harvested by centrifugation and washed twice with deionised water. Thus, algal biomass was resuspended in deionised water to a final dry weight (DW) of 20 mg mL\u003csup\u003e-1\u003c/sup\u003e before use. The workflow of the biostimulant preparation and application is summarised in Fig. 1.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eThe supernatant deriving from the centrifugation was also tested as biostimulant solution. The spent media were filtered at 0.22 \u0026micro;m, characterised for elemental composition (Table 2) and stored at 4\u0026deg;C before used. Concentrations of 10%, 50% and 100% of spent media (diluted in deionized water) were tested. Elemental composition of the spent media was assessed through TXRF (Total Reflectance X Ray Fluorescence) using a TXRF spectrometer (S2 Picofox, Bruker AXS Microanalysis GmbH, Berlin, Germany) according to Fanesi et al. [50].\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003echemical characterisation of the tap water diluted digestate as used to cultivate the algal consortium. Data are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;\u0026ge;\u0026thinsp;3).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eValue\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003epH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConductivity (mS cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1163.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcalinity (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e642.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOD (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e609.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTKN (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e138.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN-NH\u003csub\u003e4\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN\u003csub\u003etot\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e139.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u003csub\u003etot\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCl (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e71.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN-NO\u003csub\u003e2\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN-NO\u003csub\u003e3\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP-PO\u003csub\u003e4\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNa (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e257.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMg (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCa (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eelemental composition of spent media from cultures of \u003cem\u003eT. obliquus\u003c/em\u003e, C. \u003cem\u003ereinhardtii, A. protothecoides\u003c/em\u003e and their consortium in BG11 medium. Data are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;\u0026ge;\u0026thinsp;3).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"15\"\u003e\n \u003cp\u003eSpent media\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eElement\u003c/p\u003e\n \u003cp\u003e(mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eT. obliquus\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eC. reinhardtii\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eA. protothecoides\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eConsortium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eConsortium grown in digestate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCl\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8362.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1343.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e371\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e294.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e277.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e333\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e272.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e76.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCu\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Extracts preparation\u003c/h2\u003e\n \u003cp\u003eThe concentrated solutions of algal biomass were disrupted using a \u003cem\u003ecell disruption bomb\u003c/em\u003e (Parr Instrument Company), which employs high N\u003csub\u003e2\u003c/sub\u003e pressure to break cell walls and membranes. A volume of 40 mL of the concentrated solution was placed in an airtight cylinder, and nitrogen gas was introduced from a connected tank until a pressure of 2000 psi was achieved. The solution was maintained under this pressure for at least 30 minutes before being collected. Prior to use, the resulting extract was examined under an optical microscope to confirm the success of the disruption process.\u003c/p\u003e\n \u003cp\u003eThe crude extracts were then characterize as reported in detail by Mollo et al. [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e].. Pigments content was quantified spectrophotometrically by a previous methanol extraction as reported by Ritchie [\u003cspan class=\"CitationRef\"\u003e51\u003c/span\u003e]. Proteins content was quantified spectrophotometrically by the interpolation with a BSA (Bovine Serum Albumine) standard curve as reported by Peterson [\u003cspan class=\"CitationRef\"\u003e52\u003c/span\u003e]. Elemental composition was assessed by using an elemental analyser (EXS 4010, Costech Italy) for C and N content, and by a TXRF spectrometer for the remaining elements [\u003cspan class=\"CitationRef\"\u003e53\u003c/span\u003e]. Semi-quantification of lipids and carbohydrates was carried out by comparing FTIR (Fourier Transformed Infrared Spectroscopy, Bruker Optics, Ettlingen, Germany) with the total protein content [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]. Biomass composition is reported in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. Algal extracts were stored at -20\u0026deg;C before use.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ebiochemical characterisation of the algal extracts from \u003cem\u003eT. obliquus\u003c/em\u003e, C. \u003cem\u003ereinhardtii, A. protothecoides\u003c/em\u003e and their consortium, considering a DW of the algal extract of 20 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"15\"\u003e\n \u003cp\u003eAlgal extracts\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eT. obliquus\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eC. reinhardtii\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eA. protothecoides\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eConsortium\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eConsortium grown in digestate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProtein (g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarbohydrate (AU)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLipids (AU)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChlorophyll \u003cem\u003ea\u003c/em\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChlorophyll \u003cem\u003eb\u003c/em\u003e (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e197.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarotenoids (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e253.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e221.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e75.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCl (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eK (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCa (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e105.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e576.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMn (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFe (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNi (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCu (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZn (mg L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026plusmn;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"16\"\u003e\n \u003cp\u003eAU: Arbitrary Units. Carbohydrate and lipid pools relative to those in \u003cem\u003eC. reinhardtii\u003c/em\u003e whose contents were assigned a value of 1 [\u003cspan class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Priming of tomato seeds and biostimulation\u003c/h2\u003e\n \u003cp\u003eMinibel tomato seeds (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e) were acquired from Germisem Sementes LDA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.germisem.com/\u003c/span\u003e\u003c/span\u003e). Three concentrations of algal extracts (0.05, 0.1, 0.2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and three spent medium concentrations (10, 50 and 100%) were tested on 100 seeds per treatment (4 technical replicates of 25 seeds). Biostimulation was evaluated as seed priming according to Garcia-Gonzalez and Sommerfeld [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e] and Rupawalla et al. [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]. Each batch of 25 seeds was surface sterilised with 10 mL of a 5% solution of sodium hypochlorite for 10 minutes. Following the sterilisation, the seeds were washed twice with deionised water and transferred to sterile petri dishes where 10 mL of the desired solution was added. A seed batch was primed with deionized water and used as control condition (CTR). Seed priming was carried out in dark condition at 4\u0026deg;C for 24h. After that, seeds were transferred to 1% sterilised agar plates (5 seeds per plate) and incubated for 12 days at 20\u0026deg;C under a 16/8 light/dark cycle.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Evaluation of germination parameters\u003c/h2\u003e\n \u003cp\u003eAfter sowing (day 0), the number of germinated seeds was recorded every day (from day 1 to day 12). Seed was considered as germinated if at least 2 mm of the radicle had emerged. After 12 days, root, shoot and total length was measured using a caliber. Fresh weight of the seedling was also measured. To compare the enhancement or inhibition effects of algal extracts, germination parameters were evaluated as reported by Kader [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e] (except for \u003cem\u003egrowth speed\u003c/em\u003e which is suggested for the first time in this research). Detailed description of the parameters is reported in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Morphological parameters (length and weight) were analysed as ratio compared to CTR values.\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eparameters used to study seed germination and to assess the biostimulation effect of algal extracts.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eParameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFormula\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription of parameter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescription of values\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinal Germination Percentage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:FGP\\:\\left(\\%\\right)=\\:\\frac{{N}_{g}\\:}{{N}_{t}}*100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe higher FGP value, the greater the germination of the seed batch.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eN\u003csub\u003eg\u003c/sub\u003e: number of seeds germinated at the end of the experiment.\u003c/p\u003e\n \u003cp\u003eN\u003csub\u003et\u003c/sub\u003e: number of seeds sown at the beginning of experiment.\u003c/p\u003e\n \u003cp\u003eNg\u003csub\u003ed\u003c/sub\u003e: number of germinated seeds at day \u003cem\u003ed.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003ed: day of analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean Germination Time\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:MGT\\:\\left(day\\right)=\\:\\frac{\\sum\\:{Ng}_{d}*d}{{N}_{g}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe lower the MGT value, the faster the germination.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCoefficient of Velocity of Germination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:CVG\\:\\left({day}^{-1}\\right)=\\:\\frac{100*{N}_{g}}{\\sum\\:{Ng}_{d}*d}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCVG increases with increasing number of germinated seeds and with lower germination times. The highest possible CVG is 100.\u003c/p\u003e\n \u003cp\u003eCVG indicates the velocity of germination.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermination Rate Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:GRI\\:\\left(\\%\\:{day}^{-1}\\right)=\\:\\sum\\:\\frac{{Ng}_{d}}{d}*100\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThe higher GRI, the higher germinated seeds and faster germination. GRI indicates the percentage of germinated seeds each day of the experimental period.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGermination Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:GI=\\left(12*{Ng}_{1}\\right)+\\left(11*{Ng}_{2}\\right)\\dots\\:+\\left(1*{Ng}_{12}\\right)\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGI is related to both velocity of germination and number of germinated seeds. Higher weight is given to the fastest germinated seeds (at day 1).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWeight ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{W}_{r}=\\frac{{W}_{x}}{Mean\\:{W}_{ctr}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eRatio between the value of a treated seedling and the average value of the control condition.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eW: weight of seedling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eShoot length ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{LS}_{r}=\\frac{{Ls}_{x}}{Mean\\:{Ls}_{ctr}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u003csub\u003es\u003c/sub\u003e: shoot length of seedling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoot length ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{LR}_{r}=\\frac{{Lr}_{x}}{Mean\\:{Lr}_{ctr}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u003csub\u003er\u003c/sub\u003e: root length of seedling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal length ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{LT}_{r}=\\frac{{Lt}_{x}}{Mean\\:{Lt}_{ctr}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u003csub\u003et\u003c/sub\u003e: total length of seedling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGrowth speed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:G{S}_{L}\\:\\left(mm\\:{day}^{-1}\\right)=\\frac{{L}_{t}}{{T}_{e}-MGT}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:G{S}_{W}\\:\\left(mg\\:{day}^{-1}\\right)=\\frac{W}{{T}_{e}-MGT}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eIt indicates the growth speed of the seedling (mm or mg per day) from the day of germination to the last day of experiment.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\"\u003e\u003cp\u003eGS: growth speed of seedling in terms of length (GS\u003csub\u003eL\u003c/sub\u003e) or weight (GS\u003csub\u003eW\u003c/sub\u003e)\u003c/p\u003e\u003cp\u003eL\u003csub\u003et\u003c/sub\u003e: total length of seedling\u003c/p\u003e\u003cp\u003eW: weight of seedling\u003c/p\u003e\u003cp\u003eT\u003csub\u003ee\u003c/sub\u003e: last day of experiment\u003c/p\u003e\u003cp\u003eMGT: mean germination time\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e\u003cp\u003eExperiments were performed on 25 seeds for each treatment primed with algal extract and on 100 seeds for CTR condition primed with deionised water. Data are reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) (if present). Graphpad prism 9.5.0 (GraphPad Software, San Diego, CA, USA) was used to perform statistical analysis. Two-way ANOVA followed by Tukey\u0026rsquo;s \u003cem\u003epost-hoc\u003c/em\u003e test was used to analyse the parameters reported in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e as a function of type (algae species) and concentration of biostimulants. All statistical analyses were performed with a significance level of \u0026alpha;\u0026thinsp;=\u0026thinsp;0.05. Asterisk (*) was used in Fig.s to distinguish significantly different groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The \u003cem\u003ep\u003c/em\u003e values resulting from the statistical analysis are reported in detail in Table\u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table S2.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Germination parameters\u003c/h2\u003e \u003cp\u003eTomato seeds (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e \u0026ldquo;Minibel\u0026rdquo;, Germisem Sementes LDA, Portugal) were reported by the supplier company to have a FGP of 92% and a MGT of around 5 to 8 days. Based on the results, seeds primed with water (CTR) reported a FGP of 86%\u0026plusmn;2% (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), thus quite lower than the one claimed by the company. On average, at 0.05 and 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts, the biostimulation increased the FGP up to 100% as in the case of algal extract from \u003cem\u003eT. obliquus\u003c/em\u003e at 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Reduction in the number of germinated seeds was observed at the highest concentration tested and this trend was intensified for those seeds treated with algae grown in digestate (FGP dropped from 88 to 80%, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, the extract concentration was a significant source of variation of the FGP (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The application of spent media at the lowest tested concentrations (10%) resulted in an increased germination. Nonetheless, as for the algal extracts, concentration highly affected the seeds germination (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), and FGP decreased with increasing concentration of spent medium: e.g. when the consortium spent medium was applied the FGP decreased from 100% (at 10% of spent medium) to 72% (at 100% of spent medium) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Contrary to the spent medium of the consortium, the spent media of the single species always reported FGP higher or comparable to that of CTR. On average, the consortium grown in the digestate and its spent medium were the treatments with the lowest number of germinated seeds (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For each treatment condition (algal extract or spent medium) the algal source was an important source of variation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and so was its interaction with the biostimulant concentration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). It can then be stated that the combined effect of concentration and biostimulant source had a significant effect on the germination of tomato seeds.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe CTR seeds reported a MGT of 3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94 d, similarly to the treatments where seeds were primed with 0.05 and 0.2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts. On the contrary, seeds primed with 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts required more time to germinate and, except the seeds treated with the extracts of \u003cem\u003eA. protothecoides\u003c/em\u003e and the consortium, MGT values were statistically higher than the CTR ones. Both treatment and extract concentration had a significant effect on MGT values (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0093, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 respectively). Combined effect of these factors was also significant on explaining the observed variability (\u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.0001). Contrary to the priming with algal extracts, most of the seeds treated with the spent media reported a MGT statistically similar to the CTR one (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Few exceptions were observed using 10 and 50% of the consortium spent medium (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0008, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0002) and the 50% spent medium of consortium grown in digestate at (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0496) whose MGT values were higher than those of CTR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While most of the treatments were comparable to the control, both treatment and spent medium concentration were significant in explaining the observed variance, but the treatment had a higher weight than the concentration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0066 respectively), opposite to what observed for the application of algal extracts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIt is worth noting that longer time required for germination (MGT) moderately correlated to a higher number of germinated seeds (FGP) and \u003cem\u003evice versa\u003c/em\u003e. Correlation was confirmed by Pearson correlation test where a Pearson coefficient of 0.3819 and a \u003cem\u003ep\u003c/em\u003e value of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0340 were found (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Correlation between the two variables was also visible analysing the CVG parameter which considers the time of seed germination and the number of germinated seeds. Indeed, differences among treatments were minimal, and ANOVA analysis revealed almost no statistical significance. Since a higher FGP correlated with a higher MGT, changes in CVG, which is positively correlated with the number of germinated seeds and negatively with the time of germination, were negligible.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDue to its dependence on the number of germinated seeds and the time of germination, the GRI exhibited a similar trend to the CVG for both the algal extracts and the spent media. Additionally, the concentration of algal extract significantly explained the observed differences, with the most notable differences occurring at 0.01 mg/mL. Nonetheless, contrary to CVG, the treatment factor was also significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0035). Indeed, while most of the treatments reported similar results, treated seeds with the extract of the consortium grown in digestate had the lowest GRI values at each extract concentration due to the low FGP (88%, 88%, 80% respectively) and the high MGT (4.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22, 5.36\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81, 3.65\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49 days respectively). It could be noted that at the concentration of 0.2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e both GRI and CVG for the above-mentioned treatment were higher than those at the other two concentrations.\u003c/p\u003e \u003cp\u003eLastly, GI of seeds treated with algal extracts was both dependent on treatment condition and algal concentration (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0024, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0007 respectively); extracts of \u003cem\u003eT. obliquus\u003c/em\u003e and \u003cem\u003eA. protothecoides\u003c/em\u003e were the treatments with the highest values at each tested concentration. As for the forementioned parameters, GI was lower at the intermediate extract concentration due to an increasing MGT. Nonetheless, reduction in GI was lower in 0.01 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e \u003cem\u003eT. obliquus\u003c/em\u003e and \u003cem\u003eA. protothecoides\u003c/em\u003e applications due to a high FGP (100% and 92%, respectively). Lowest results were recorded for seeds treated with extracts of consortium grown in digestate as previously reported. Differently to algal extract application, the spent media priming did not significantly change GI of seeds which was almost comparable to the CTR one. As for previous parameters, GI of the treatments with consortium spent medium was always lower than the that of other treatments within the same concentration group.\u003c/p\u003e \u003cp\u003eTo conclude, a certain relationship between concentration, velocity of germination and number of germinated seeds was observed. On average, low MGT (i.e. fast seeds) was typical of the lowest and highest concentrations which also presented a low number of germinated seeds (FGP). This relationship was particularly evident when seeds were treated with the algal extracts while changes due to the spent media applications were mostly observed in a variation of the FGP. Noteworthy, at the concentration of 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e MGT increased as well as the number of germinated seeds. Increasing even more the concentration led also to an increased toxicity with MGT similar to the one observed at the lowest tested concentration but with lower FGP. Different effects were caused by the application of the spent media, even so significative changes compared to CTR were found particularly in the FGP. More than the algal extracts, concentration of spent media strongly affected germination of the seeds primed with spent media from \u003cem\u003eC. reinhardtii\u003c/em\u003e and the consortium grown in diluted digestate as the main examples of this effect.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Effect on weight and morphology of seedlings\u003c/h2\u003e \u003cp\u003eSimilarly to the germination parameters, effects on seedling morphology were mostly dependent on the biostimulant concentration whereas the algal species had a less significant impact in explaining the observed differences. Significant differences were observed between the two treatment groups (algal extract and spent medium) in terms of the seedling organ most affected by the treatment. This indicates distinct mechanisms of action for the two classes of biostimulants.\u003c/p\u003e \u003cp\u003eLooking at the shoot length the algal extract had an overall higher effect compared to that of spent media. The concentration of the extracts significantly affected the shoot length (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001): indeed, it was stimulated by extracts at the concentration of 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e whereas the other tested concentrations elicited comparable results to those of the CTR, even if a certain trend of shoot shortening was observed at the highest concentration. Conversely, the spent media did not significantly affect shoot length, except for the spent medium derived from the consortium culture in diluted digestate, which had a deleterious effect on the shoots. In fact, shoot length negatively correlated with the concentration of the medium. While shoot length saw the greatest improvement with algal extract treatment, root length was most significantly enhanced by the spent medium treatment. Notably, the increase in root length was observed with 100% spent medium treatments of \u003cem\u003eT. obliquus, C. reinhardtii and A. protothecoides.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eOn average, weight of seedlings increased when seeds were treated with both algal extracts and spent media at the lowest two tested concentrations (0.05\u0026ndash;0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 10\u0026ndash;50%). However, the concentration of biostimulants was more significant in explaining the observed variation for the algal extract group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) compared to the spent medium group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0604). Nonetheless, the source of the biostimulant (i.e. the algal species) was significant for both the groups highlighting differences within the groups and between them. The greater stimulation was due to the treatment with the extract of \u003cem\u003eT. obliquus\u003c/em\u003e and with the medium from \u003cem\u003eC. reinhardtii\u003c/em\u003e culture. Again, it was proved that results from algal extracts and spent media were not related. Notably, at the highest concentration of spent media (100%), the weight of the seedlings did not decrease, despite changes in length and the previously discussed germination parameters. When the spent medium from consortium culture was applied, the weight was even higher than in the CTR. The higher seedling weight was not consistent with a longer seedling length.\u003c/p\u003e \u003cp\u003eAmong all the treatments, only the extract of \u003cem\u003eC. reinhardtii\u003c/em\u003e at 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was able to increase both shoot and root length together with an increase in weight too. Other treatments promoted the growth of one or another organ of the seedling. To be note is that, overall, the total length was not related to a faster germination (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.4549), indeed, while for the algal extract group the longer seeds were the one germinated at 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and which displayed higher values of MGT, within the spent media group the MGT was not dependent on the concentration and the length of the seedling changed independently from the parameter.\u003c/p\u003e \u003cp\u003eIn addition to the length of shoot and root, the ratios between the organs (root/shoot) provided further insights on the effects and mechanisms of the biostimulation (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). On average a certain reduction in the ratio compared to the CTR was observed meaning that the shoots grew more than the roots, however, response to increasing concentrations differed depending on the type of biostimulant: ratio increased at the expense of the shoot due to the spent media while it decreased because of algal extracts treatment. Notable examples include the spent medium of \u003cem\u003eT. obliquus\u003c/em\u003e and the extract of \u003cem\u003eC. reinhardtii\u003c/em\u003e where the opposite effects could be seen.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Effect on the growth speed\u003c/h2\u003e \u003cp\u003eAs already observed, all the tested variables (i.e. type of biostimulant, treatment and concentration) induced significative changes in germination and morphology even though they were not related to each other. However, combining data on germination time (MGT) and seedling morphology revealed that despite a comparable length or weight of treated seeds to those of CTR (e.g. treatments at 50% of spent media), the GS value was higher due to a slower germination (higher MGT) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). A remarkable example is the case of seeds treated with 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extract: they showed longer and heavier seeds but also a higher MGT, thus resulting in a GS even higher than in the previous example (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003egermination parameters of control and treated seeds. Data are divided per treatment and type of applied biostimulant: algal extract (0.05, 0.1, 0.2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) or spent medium (10, 50, 100%). Data is reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Legend: FGP (final germination percentage), MGT (mean germination time), CVG (coefficient of velocity of germination), GRI (germination rate index), GI (germination index), W\u003csub\u003er\u003c/sub\u003e, (weight ratio), LS\u003csub\u003er\u003c/sub\u003e (shoot length ratio), LR\u003csub\u003er\u003c/sub\u003e (root length ratio), LT\u003csub\u003er\u003c/sub\u003e (total length ratio), GS\u003csub\u003eL\u003c/sub\u003e (length growth speed), GS\u003csub\u003eW\u003c/sub\u003e (weight growth speed). Results of the statistical analysis are reported in detail in the supplementary material (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, TableS2).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"37\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c17\" colnum=\"17\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c18\" colnum=\"18\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c19\" colnum=\"19\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c20\" colnum=\"20\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c21\" colnum=\"21\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c22\" colnum=\"22\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c23\" colnum=\"23\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c24\" colnum=\"24\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c25\" colnum=\"25\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c26\" colnum=\"26\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c27\" colnum=\"27\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c28\" colnum=\"28\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c29\" colnum=\"29\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c30\" colnum=\"30\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c31\" colnum=\"31\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c32\" colnum=\"32\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c33\" colnum=\"33\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c34\" colnum=\"34\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c35\" colnum=\"35\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c36\" colnum=\"36\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c37\" colnum=\"37\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eConcentration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eFGP\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eMGT\u003c/p\u003e \u003cp\u003e(day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c13\" namest=\"c11\"\u003e \u003cp\u003eCVG\u003c/p\u003e \u003cp\u003e(day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c16\" namest=\"c14\"\u003e \u003cp\u003eGRI\u003c/p\u003e \u003cp\u003e(% day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c19\" namest=\"c17\"\u003e \u003cp\u003eGI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c22\" namest=\"c20\"\u003e \u003cp\u003eW\u003csub\u003er\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c25\" namest=\"c23\"\u003e \u003cp\u003eLS\u003csub\u003er\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c28\" namest=\"c26\"\u003e \u003cp\u003eLR\u003csub\u003er\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c31\" namest=\"c29\"\u003e \u003cp\u003eRatio organs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c34\" namest=\"c32\"\u003e \u003cp\u003eGS\u003csub\u003eL\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(mm day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c37\" namest=\"c35\"\u003e \u003cp\u003eGS\u003csub\u003eW\u003c/sub\u003e\u003c/p\u003e \u003cp\u003e(mg day\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCTR\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eT. obliquus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAlgal extract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e 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align=\"left\" colname=\"c14\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e 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align=\"left\" colname=\"c14\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e 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colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e 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colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e 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colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e 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colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpent medium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e 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colname=\"c17\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e 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colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e 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\u003cp\u003e\u003cb\u003eA. protothecoides.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAlgal extract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e8.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpent medium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e23%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e30.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e30%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eConsortium\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAlgal extract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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\u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e 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\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e 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align=\"left\" colname=\"c34\"\u003e \u003cp\u003e2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e84%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e 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colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e 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align=\"left\" colname=\"c14\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eConsortium grown in digestate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAlgal extract\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e19%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003emg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e27.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eSpent medium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e 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colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c17\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c18\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c19\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c20\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c21\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c22\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c23\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c24\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c25\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c26\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c27\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c28\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c29\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c30\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c31\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c32\"\u003e \u003cp\u003e5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c33\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c34\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c35\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c36\"\u003e \u003cp\u003e\u0026plusmn;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c37\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Biostimulant effect on seed germination\u003c/h2\u003e \u003cp\u003eThe germination process was influenced by the algal species and the concentration of the biostimulant. This was also noted by Alling et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], who found that the effects were connected to the biostimulant source (\u003cem\u003eChlorella vulgaris\u003c/em\u003e or \u003cem\u003eScenedesmus obliquus\u003c/em\u003e) and the amount of extract used. Despite that, contrary to what reported by the author, a linear correlation between MGT and extract concentration was not found, and the achieved results were either comparable to or higher than those in the control condition. These differences could be attributed to the use of different cultivars of \u003cem\u003eSolanum lycopersicum\u003c/em\u003e, as well as variations in the cultivation methods of the algae, such as different growth medium and parameters. Amaya-Santos et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] demonstrated that the cultivation conditions of algae, such as the use of treated or untreated wastewater and light or dark regime, resulted in different biostimulant effects on treated soybeans. However, it's important to note that the application of spent media did not change the MGT of treated seeds, regardless of the concentration or algal source, but it did alter the FGP. Similar results were found by Bahmani Jafarlou et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] when using \u003cem\u003eArthrospira platensis\u003c/em\u003e extracts on milkweed (\u003cem\u003eCalotropis procera\u003c/em\u003e) seeds.\u003c/p\u003e \u003cp\u003eAnother difference from many works found in literature is the pre-treatment of the algae and the use of specific fractions. Despite the similarity of algal extract concentrations to ours, Alling et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] also tested the effectiveness of several extraction methods showing that the method of extraction and different algal fractions can significantly impact the outcome of the biostimulation. Similarly, Rupawalla et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] found that the inner content of algal cells released after cell lysis treatment was the best way to improve spinach germination and development. On the other hand, other authors [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] found that even entire cells possess biostimulant activity, thus eliminating the need for a biomass pre-treatment. Based on the literature, we decided to adopt a faster, more affordable, and reagent-free method using high N\u003csub\u003e2\u003c/sub\u003e pressure to disrupt the cells. Since most of the literature indicated that the overall inner content has biostimulant activity, we chose a method that did not require the application of multiple fractionations. The results, in terms of FGP, were comparable to the literature and even better since a much smaller quantity of algae was used compared to many other research studies.\u003c/p\u003e \u003cp\u003eEven the spent medium from microalgal plants can be used as a biostimulant, offering a solution to the challenge of recycling growing media. Although recycling the spent medium can be complicated due to the build-up of infochemicals and inhibitors, it is essential to minimize water and nutrient input in order to reduce algal production costs [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Reusing the spent medium would give a second life to this byproduct, leading to cost savings in cultivation. Unlike algal biomass, the spent medium only requires filtration to reduce particulate matter, making it a readily-usable product for agricultural purposes. In experimental conditions, the spent media exhibited biostimulant activity, consistent with existing literature [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The presence of infochemicals, metabolites, and possibly phytohormones [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] may have contributed to improved germination at the lowest tested concentrations (10%) but not at the highest since an excessive concentration of these molecules may have a bioherbicide effect than a biostimulant one [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. However, the germination parameters of seeds treated with spent media of consortium grown in BG11 or in digestate were unsatisfactory at each concentration, possibly indicating issues with the use of multi-species-based biostimulants.\u003c/p\u003e \u003cp\u003eThe effectiveness of blended biostimulants (made from a combination of at least two macro/microalgal species) has been studied and confirmed by researchers such as Sarkar et al. [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] and Jafarlou et al. [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. These studies have shown that blending extracts from different algal species can have a synergistic effect, enhancing biostimulant activity compared to individual extracts. However, in our trials, we observed lower activity of the biostimulants made from the co-cultivation of multiple species, compared to the ones made from single-species cultures. This contrasts with previous research. The differences in our results would be attributed to the way the biostimulants were formulated. In our case, the blending was the results of co-cultivation of microalgae, which is different from mixing individual biostimulants. In the last case, the properties of the resulting product were influenced by the quantity of each individual biostimulant added to the blend. Additionally, our product's quality differed from single-species biostimulants due to the co-cultivation process. Co-cultivating algae stimulates the release of specific infochemicals [\u003cspan additionalcitationids=\"CR67 CR68 CR69 CR70 CR71\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] that are typically absent in mono-specific cultures. This increased diversity in the spent medium metabolome was also reflected in the algal metabolome [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], leading to changes that could be responsible for the reduced activity observed in our biostimulants. The formulation of biostimulants turns out to be crucial; despite the higher growth performance of the consortium compared to single species, the resulting biostimulant was not performing as well [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLooking at the biochemical composition of algal extracts it can be observed a huge difference between algae grown in BG11 standard medium and the algal consortium that grew in digestate, especially in the element composition. The higher content of Ca in diluted digestate grown cells can be explained by the higher ion availability in the external medium and its higher precipitation on the cell wall due to the increasing pH level during the algal growth [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The medium composition could have drastically changed the algal cell elemental quota [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] thus affecting germination and growth of tomato seeds. Potentially, even toxic compounds uptaken by algae during growth in wastewaters (such as the phenolic compounds of Olive Mill Wastewater) could have affected the biostimulation outcomes. Nonetheless, literature is plenty of cases where wastewaters are used to make products for agricultural purposes whose effects are beneficial for the plants. For example, Navarro-L\u0026oacute;pez et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] produced and tested biostimulants made with \u003cem\u003eScenedesmus obliquus\u003c/em\u003e grown in brewery wastewater and the obtained results were significantly better than in control condition (seeds treated with water). The concentration tested by the authors was far higher than the ones here presented (2-0.5 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compared to 0.05\u0026ndash;0.2 mg mL mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), nonetheless, no evidence of toxicity was found. A similar result was also reported by Navarro-L\u0026oacute;pez et al. [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] with algae grown in urban wastewater. Again, GI and FGP were slightly increased due to the treatment with 0.5 and 2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e algal extracts. Together with others [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] they proved that many factors may be involved in explaining the properties of the biostimulants and that the culture medium can significantly affect the quality of the product. Indeed, in the best case (the lowest concentration), both the algal extract of our consortium grown in the digestate and its spent medium were the treatments with the lowest number of germinated seeds. For what concerns the spent media, it\u0026rsquo;s likely that phycoremediation carried out by algae was not able to remove all those toxic compounds which endured in the medium and then affected the biostimulation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Biostimulant effect on seed development\u003c/h2\u003e \u003cp\u003eAll tested biostimulants exhibited phytohormone-like activity. Previous reports attributed the higher FGP to a gibberellins-like effect [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. From a morphological perspective, auxin and cytokinin-like effects were observed, leading to increased root and shoot length. Concentration was found to have a negative impact on the overall length of the seedlings, which is consistent with the findings of Alling et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] in barley and tomato seeds. Notably, the author also reported that the length of tomato seedlings was generally shorter than the length of CTR ones despite faster germination (resulting in a lower MGT). However, our results differ from those above reported, as the reduced length of the seedlings was only observed at the highest biostimulant concentrations (0.2 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 100%). Seeds treated with 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts were longer, despite experiencing delayed germination.\u003c/p\u003e \u003cp\u003eRoot growth was stimulated by biostimulants proving an auxin-like effect [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The highest stimulation was observed at a concentration of 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts, with even greater stimulation coming from undiluted spent media (100%). Apart from consortium (grown in standard medium or in digestate) treated seeds, whose issues were detailed in the previous paragraph, the root length ratio values of 1.3, 1.4, and 1.3 were respectively observed for the seeds treated with the spent media of \u003cem\u003eT. obliquus, C. reinhardtii\u003c/em\u003e and \u003cem\u003eA. protothecoides\u003c/em\u003e. It was reported by [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] that phytohormones such as cytokinins, auxins, and gibberellins were present in the soluble fraction of lysed algal cells. Additionally, Kapoore et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] mentioned that phytohormones can be released into the extracellular medium. The release of these molecules, or infochemicals, was there identified as the primary cause of observed growth, even at the highest concentrations. A hypothesis is that the co-cultivation and the potential competition for nutrients led to the accumulation of a different set of phytohormones in biostimulants made from consortia cultures including abscisic acid (ABA): in algae ABA is produced under different environmental stresses [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] and could have an ecological significance in the regulation of association with other microorganisms [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e], however in plants was already reported to have an opposing effect to gibberellin in seed germination [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Rupawalla et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] further reported an overall increase in tomato seedlings' length with increasing spent media concentration; however, details about the individual growth of shoot and root were not provided, preventing a comparison of the effects of biostimulants on these two organs.\u003c/p\u003e \u003cp\u003eAlgal extracts were found to be more effective than the spent media in changing the shoot length. These differences could be due to a variation in phytohormone composition, as well as differences in the biochemical composition. Indeed, the algal biomass is rich in proteins, lipids, and carbohydrates [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] compared to the spent media and it was proved that the carbohydrate group was particularly effective in enhancing shoot length in tomato plants [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Spent media could contain carbohydrates in the form of Extracellular Polymeric Substance (EPS), which is known to enhance shoot length in tomato plants [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Nonetheless, the pre-treatment involving 0.22 mm filtration of the spent medium before its application may have removed or reduced the pool of exopolysaccharides. The scant presence of carbohydrates could contribute to a lesser variation in shoot length as compared to algal extract application.\u003c/p\u003e \u003cp\u003eThe ratio between plant organs is influenced by biostimulants, which have a strong impact on root and lateral root development [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Biostimulation often leads to higher root development compared to shoot development due to the activation of water stress-related pathways [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. A study by Ferreira et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] tested four algal extracts on six types of plants and found that the average root length varied more significantly than changes in shoot length. Similarly, Jafarlou et al. [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] noted a drastic decrease in root length at high concentrations, while the shoot was less affected. Our experiments showed that the variations in root/shoot ratio depended on the type and concentration of biostimulant (algal extract or spent medium), while the algal source had a less significant impact. Two trends were observed with increasing concentrations: 1) algal extracts increased shoot length, and 2) spent media increased root length. Notably, the extract of \u003cem\u003eA. protothecoides\u003c/em\u003e and the spent medium of \u003cem\u003eC. reinhardtii\u003c/em\u003e were significant examples of the two trends, with values changing from 3.8 to 2.1 and from 3.3 to 4.2, respectively. Although our data align with existing literature, research on spent media is limited, and information on root/shoot length variation is lacking. Nevertheless, these differences could be attributed to the varied composition and content of phytohormones. Therefore, biostimulants should be chosen carefully based on the desired outcomes, as different effects on seed development may be achieved.\u003c/p\u003e \u003cp\u003eThe weight of the seedlings increased in proportion to their length, which is consistent with similar findings in the literature [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]. Apart from quantifying biomass, an analysis of growth speed revealed that most of the treated seeds grew much faster than the control seeds. This effect was particularly noticeable in seeds treated with 0.1 mg mL\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e of algal extracts. Despite longer mean germination time (MGT), these seeds displayed greater weight and length. Although literature lacks parameters that combine germination time and morphological features, such data could offer further insight into seed vigour and biostimulation mechanisms. Faster-growing crops with shorter growth cycles (faster maturation) would lead to larger plants in a shorter time enhancing plant resilience in adverse and unpredictable weather conditions [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Therefore, biostimulation would likely increase productivity through a higher number of germinated seeds and greater biomass production over time.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe use of microalgae-based biostimulants is a promising approach to enhance agricultural sustainability and crop production. Both algal extracts and spent media have been proved to be effective in increasing the frequency of germination and the growth velocity of seedlings. Using spent media as biostimulants is beneficial because of the infochemicals and phytohormones released by algae during their growth. This helps to tackle the issue of discarding or recycling growth media. This discovery allows for the simultaneous production of two types of biostimulants with different activities. However, even minor changes in biostimulant concentration greatly impact the treatment outcomes.\u003c/p\u003e \u003cp\u003eThe coupling of wastewater remediation with biostimulant production has been discussed several times in the literature, demonstrating that the implementation of a circular and sustainable process is possible. However, as reported here, the type of wastewater may significantly affect the biomass and extract quality of the algae, leading to lower germination and growth of plants than in control conditions. The toxic compounds in the digestate may have been absorbed or adsorbed by the algae, subsequently remaining in the final product (e.g. biostimulant) after algal extraction. The reduced effect of the algal consortium-based biostimulant in comparison with the single species-based ones highlighted a significant issue that should be considered when producing a biostimulant. Mixing algal biomass coming from various monocultures is different from having biomass coming from a co-culture of multiple species. Co-cultivation modifies the biomass quality of the algae, and even the infochemicals and metabolites released in the medium change.\u003c/p\u003e \u003cp\u003eWhile many points must be addressed before achieving significant biostimulation, the results presented are promising and show that even a small concentration of microalgae can induce notable changes in plant development. In the event that microalgae-based biostimulants prove to be sustainable and are successfully adopted in agriculture, the presented seed-priming methodology will provide a straightforward and rapid approach for screening and selecting algal extracts for use on crops.\u003c/p\u003e \u003cp\u003eIn the future, a bio-refinery approach could be implemented, allowing us to use specific algal fractions to further improve biostimulation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eFGP: final germination percentage\u003c/p\u003e\n\u003cp\u003eMGT: mean germination time\u003c/p\u003e\n\u003cp\u003eCVG: coefficient of velocity of germination\u003c/p\u003e\n\u003cp\u003eGRI: germination rate index\u003c/p\u003e\n\u003cp\u003eGI: germination index\u003c/p\u003e\n\u003cp\u003eGS: growth speed\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank CIRCC (Progetti Competitivi 2021/CMPT212338 e 2022/CMPT222955, MIUR) for the financial support. Research for LM PhD project was partially funded by Enereco SpA, Italy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the research group \u0026ldquo;Laboratory of Biology of the algae\u0026rdquo; of University of Rome Tor Vergata, especially PhD student Alberta Di Cave who gave clarifications on the seed priming methodology. We also thank the student trainees who helped in the manual work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: LM and AN. Formal analysis: LM. Investigation: LM. Methodology: LM and AN. Supervision: AN. Visualization: LM. Writing \u0026ndash; original draft: LM. Writing \u0026ndash; review \u0026amp; editing: LM and AN. Funding acquisition: AN.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe seeds used in the present study were procured from Germisem Sementes Lda (Oliveira do Hospital, Portugal), a Portuguese seed company. The research involving Tomato (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e L.) was conducted following approved guidelines set forth by the university and national regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe materials and data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFAO (2020) Emissions due to agriculture. Global, regional and country trends 2000\u0026ndash;2018. FAOSTAT Analytical Brief Series No 18 \u003c/li\u003e\n\u003cli\u003eSingh R, Singh GS (2017) Traditional agriculture: a climate-smart approach for sustainable food production. 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Annu Rev Environ Resour 37:195\u0026ndash;222. https://doi.org/10.1146/annurev-environ-020411-130608\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ccap.ac.uk/\u003c/span\u003e\u003cspan address=\"https://www.ccap.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://roscoff-culture-collection.org/\u003c/span\u003e\u003cspan address=\"https://roscoff-culture-collection.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-plants","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Plants](https://link.springer.com/journal/44372)","snPcode":"44372","submissionUrl":"https://submission.springernature.com/new-submission/44372/3","title":"Discover Plants","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Biostimulant , Spent medium , Seed priming , Algal consortium , Chlorophyta ","lastPublishedDoi":"10.21203/rs.3.rs-5394178/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5394178/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicroalgae offer a promising solution for enhancing agricultural sustainability and mitigating global warming. When extracts from algal cells and their spent medium are used as biostimulants on crop seeds, they can significantly influence plant physiology. This application boosts plant productivity and improves tolerance to abiotic stress. The objective of this study was to evaluate the biostimulant potential of crude extracts from \u003cem\u003eTetradesmus obliquus\u003c/em\u003e, \u003cem\u003eChlamydomonas reinhardtii\u003c/em\u003e, \u003cem\u003eAuxenochlorella protothecoides\u003c/em\u003e, and their consortium, as well as the potential of their spent growth media, when applied to tomato seeds (\u003cem\u003eSolanum lycopersicum\u003c/em\u003e). The study assessed germination indexes and seed development, including weight, root/shoot ratio, and growth speed. The results indicated that the variation in the morphology of the treated seeds was primarily influenced by the concentration of the extracts, with the algal species having a lesser impact on the observed variability. The number of germinated seeds was notably higher at the lowest concentration of biostimulants. Additionally, the algal extracts exhibited greater biostimulant potential than the spent media. Furthermore, the analysis of growth speed revealed that most treated seedlings grew significantly faster than the control seeds. Lastly, the study reported a lower biostimulant potential of the algal consortium compared to the single species, possibly due to the co-cultivation of different species.\u003c/p\u003e","manuscriptTitle":"Biostimulant potential of three chlorophyta and their consortium: application on tomato seeds","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-03 06:50:59","doi":"10.21203/rs.3.rs-5394178/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-17T03:38:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-15T21:21:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-15T12:37:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-13T13:04:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-13T05:14:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-09T07:35:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-08T15:41:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"217894117510960564392503195156354103324","date":"2024-12-06T15:55:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25405858799155146481077367286358454570","date":"2024-12-06T08:47:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110310239995803624393748608339812392260","date":"2024-12-06T03:37:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73033728935373022578066582509702144594","date":"2024-12-05T17:42:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257310199894276158072086880058340322566","date":"2024-12-05T04:05:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31707515447670635132042509304316585914","date":"2024-12-05T00:53:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116423126565021612284715250077287375334","date":"2024-12-04T13:36:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227120482390019508360825702560236483855","date":"2024-12-04T10:45:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"82385046293761583213351595463727589737","date":"2024-12-04T10:39:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"207905307600774102602795170787700652872","date":"2024-12-04T09:47:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-12-04T08:43:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-11-22T08:45:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-11-19T11:17:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Plants","date":"2024-11-05T09:30:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-plants","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Plants](https://link.springer.com/journal/44372)","snPcode":"44372","submissionUrl":"https://submission.springernature.com/new-submission/44372/3","title":"Discover Plants","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25c4d103-b53a-4337-a667-94a0405c64a6","owner":[],"postedDate":"December 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-04-15T02:23:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-03 06:50:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5394178","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5394178","identity":"rs-5394178","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}