The increasing consumer interest in organic products is driving the rise of the agricultural sector. However, organic farming productivity was lower than conventional due to the reduction of external inputs, synthetic fertilizers, and pesticides. In this context, the use of organic biostimulant emerged as a promising solution. It is showed the benefit of integrating the biostimulant uses in organic agriculture management to improve plant development, thereby enhancing crop productivity.
Introduction
Organic farming is an agricultural approach aimed at producing food through natural substances and processes. It represents a complete production management system that fosters and improves the health of agroecosystems, encompassing aspects such as biodiversity, biological cycles, and soil biological activity. It is based on reducing dependency on external inputs and eliminating the use of synthetic fertilizers and pesticides. Ecological agriculture is a fast-growing sector in European Union (EU) agriculture, driven by the increased consumer interest in organic products. In 2021, organic agriculture covered an estimated 15.9 million hectares of agricultural land in the EU, equivalent to 9.9% of the total utilized agricultural area. This marked a significant increase from the 9.5 million hectares dedicated to organic agricultural production in 2012. This expansion has been supported in recent years by ‘From the Farm to Fork’ strategy of the European Green Deal. This strategy aims to tackle the challenges of making a sustainable, healthy, and environmentally friendly food system. To achieve this, it proposes to have 25% of EU’s total agricultural land under certified organic farming by 2030 among others.
Several reports have emphasized that organic farming tend to yield less than conventional. Meta-analysis highlighted that variations in yield, ranging from 5 to 34% lower in organic systems, are highly dependent on system and site characteristics. In a subsequent meta-analysis, there was 18.4% lower yield in organic farming compared to conventional methods with the largest variation in warm temperature subtypes, specific crops, regions, and soil types. Addressing this limitation and challenge in organic agriculture requires the integration of new technologies and management strategies, which becomes crucial.
The utilization of biostimulants is emerging as a promising solutions to improve the productivity of sustainable agriculture. This is attributed to their bioactivity, absence of toxic effects on non-target organisms, and low ecological persistence. The composition of biostimulants is based on a complex combination of natural compounds such as amino acids, seaweed extracts, acid humic and fulvic and botanical extract among others. Their mechanisms of action are distinguished by fostering tolerance to abiotic stress, enhancing the quality of plants, soil, and the rhizosphere, and improving the efficient utilization of nutrient. Biostimulants designed to improve rooting become particubiostimulanty relevant because the development of root system architecture (RSA) is crucial for ensuring the survival and productivity of plants. This importance is attributed to the diverse functions of RSA, encompassing nutrient and water uptake, anchoring and mechanical support, and acting as the primary interface between the plant and various stress factors in the soil environment. Especially in organic agriculture, where organic fertilizers supply nutrients in lower amounts over an extended period, the effective development of RSA holds great significance. This is because it results in achieving robust growth with minimal nutrient concentrations.
Materials and Methods
Biostimulant Composition
An innovative organic biostimulant based on amino acids and seaweed extract.
Plant Material, Cultural Conditions, and Treatment
Cucumber plants (Cucumis sativus L). cv. Marketmore were cultivated under controlled conditions, with a 24/21 ℃ day/night, 70% RH and 16/8 h light/dark photocycle. Seed germination was conducted in vermiculite as an inert substrate. Following three weeks, 275 seedlings were transplanted into a hydroponic growing system. Each seedling was positioned in 500 mL polyethylene vessel. The composition of the modified nutrient solution was as follows: 5 mM KNO3, 2.5 mM Ca(NO3)2, 2 mM MgSO4, 1 mM KH2PO4, 7 μM MnCl2, 0.7 μM ZnSO4, 0.8 μM CuSO4, 0.8 μM Na2MoO4, 25 μM Fe-EDDHA, and 2 μM H3BO3. The nutrient solution (pH 6.5) was replaced when the electrical conductivity was ≤ 0.8 dS m-1. It is important to highlight that the application of biostimulant at different doses was done at the same time as the replacement of new nutrient solution. Rooting treatments commenced following 7 days of plant growth in the nutrient solution. The biostimulant treatments, served at low, medium, and high doses (0.1, 0.2, and 0.3 mL per plant, respectively) were applied to the nutrient solution every 10 days as recommended by the manufacturer, four applications at the end of the experiment. Each treatment consisted of fifty-five plants, randomized-distributed among 6 blocks, and these rooting treatments were compared to the control (nutrient solution without biostimulant).
Vegetative Growth Parameters
Plant growth parameters were assessed at five different time points, every 10 days, commencing one day after the first application (1, 10, 20, 30, and 40 days). At each interval, six plants from each treatment were harvested to determine physical parameters. The number of leaves was counted once they were fully opened and the width of the main stalk was measured at base of the stem by digital Vernier caliper. Plant height was measured from the base to the apical stem meristem, while root length was measured from the stem base to the apical root meristem using a meter scale. Root volume was determined by immersing a previously washed and dried root system in a graduates cylinder filled with a known volume of water, the increase in water volume was then recorded. The number of root ramification was determined counting the main root branches. The plant was separated into shoot and root at the stem base, and the fresh weight of each was measured using an electronic balance. Subsequently, shoot and root samples were air-dried in an oven at 50 ℃ for 48 h and then reweighed to determine dry weight (DW). All these root measurements contributed to understanding the spatial arrangement of roots, which collectively defines the root system architecture (RSA). The relative growth rate (RGR, g g-1 d-1) were calculated using the formula proposed by Hunt (1982): RGR = (InW2 – InW1)/(t2 – t1), where W1 and W2 represent the dry weight for the entire plant at time t2 and t1. The leaf area (A, cm2) was estimated using a regression model A = - 8.56-9.85(L) + 0.78(L2) + 9.96(W) where L is the length (cm) and W is the width.
Mineral Analysis
After 40 days mineral analyses were performed, dried leaf sample (0.1 g) were mineralized with HNO3 using a microwave wet-oxidized digestion system and the digested samples were diluted in 15 mL ultrapure water. Macronutrients (Ca, Mg, K, Na and P) were analyzed using Inductively Coupled Plasma-Optical Emission Spectrometry and micronutrients (Mn, Fe, Ni, Cu and Zn) were measured by Inductively Coupled Plasma-Mass Emission Spectrometry. The total nitrogen was determined by elemental analysis. Three replicates were used for each determination.
RNA-Seq Analysis
After three days following the fourth application, three plants per treatment, control, and biostimulant High, were harvested. Roots were removed and rinsed in distilled water. Subsequently, the roots were powdered in liquid nitrogen and stored at -80ºC until RNA purification by mRNA purification Kit. Library preparation and RNA sequencing were conducted using the Illumina Hiseq4000 platform by Macrogen. The total RNA quality and quantity from the samples were assessed using a 2100 Bioanalyzer. For library preparation, it was ensured that all samples had RNA integrity values of ≥ 7 and rRNA ratios of > 1. Library construction was carried out using the TruSeq Stranded mRNA sample prep Kit by Macrogen. Processed reads were aligned to reference genome data using HISAT2 (version 2.1.0). Subsequently, the transcript was assembled using StringTie (version 2.1.3b). The expression level of each transcript was normalized to fragments per kilobase per million mapped reads (FPKM). For the differential expression gene (DEG) analysis, genes with a count value of 0 in at least one sample were excluded to ensure the data quality. Subsequently, read counts were log2-transformed and normalized using the relative Log expression (RLE) method by DESeq2 R Library, and the statistical analysis was performed using Fold change. DEGs were considered significant when log2 fold change values (FC) ≥ 2 and p ≤ 0.05. For significant list, hierarchical clustering analysis was performed to group the similar samples genes, and the result were graphically depicted using heatmap. Furthermore, gene-set enrichment analysis was conducted using g:Profiler tool, which identifies over-representation of information from gene ontology data base, biological pathways, regulatory DNA elements, gene annotation and protein-protein interaction network. To identify biological functions and pathways associated with the DEGs, the Gene Ontology (GO) and Kyoto encyclopedia of gene and genomes (KEGG) database were searched for annotation using ShinyGO 0.80v.
Results
Effects of Different Dose of biostimulant on Plant Growth
The application of different biostimulant doses had a noticeable impact on the plant growth. The height of the aerial section indicated that the low dose exhibited a development similar to the control until day 30 after first application (Fig. 1a). Afterward, it experienced significant growth, surpassing even the medium and matching the high doses. Both the medium and high doses displayed significant height increment at 20 days compared to the control. Following this, both doses manifested a sustained increase in height maintenance with a significant difference compared to the control at 30 and 40 days. The three doses of biostimulant exhibited a significant impact on fresh aerial weight in comparison to the control at 20, 30 and 40 days, with the high dose standing out (Fig. 1b). Both high and medium doses displayed a significant increase in dry aerial weight compared to the control at 30 and 40 days (Fig. 1c). The low dose maintained the dry aerial weight equivalent to the control, but by 40 days, it increased significantly surpassing the medium dose. Regarding the leaf count, the high dose significantly increased the number of leaves compared to the medium, low doses and control at 20 days (Fig. 1d). The improvement in leaf count persisted significantly with the medium and high doses compared to the control at 30 and 40 days. The low dose also exhibited a significant increase compared to the control at 40 days. Concerning the main stalk width, the high dose demonstrated ongoing growth statistical significant in comparison to the other treatments until the 30 days (Fig. 1e). Subsequently, at 40 days, the medium dose experienced a rise, reaching an equivalent value to that of the high dose. The low dose did not show statistical significance when compared to the control. Following the trend, all three doses of biostimulant enhanced a higher leaf area and accelerated the leaf area development compared to the control, reaching maximum development of the leaves at 30 days the control did not achieve a similar growth even at 40 days (Fig. 1f).
The different dose of biostimulant significantly modify the RSA. As the biostimulant dose increased, the root length decreased significantly compared to the control in all time points (Fig. 2a). Root volume significantly increased at all time points across the three biostimulant dose compared to the control (Fig. 2b). The medium dose exhibited the highest root volume at 10 days compared to the high, low biostimulant dose and control. This growth stabilized until 30 days, with the high dose equalizing it at 20 days and surpassing it at 30 and 40 days. As the biostimulant dose increased, the root volume increased at 40 days.
The assessment was discontinued after day 20 due to challenges in accurately indentifying the number of ramificationes (Fig. 2c). At 20 days, all doses exhibited a significantly higher number of root ramifications compared to the control, with the medium and high doses standing out, presenting an average between 24 and 25 root ramifications compared to 15 in the control. The fresh weight was enhanced by all dose in all time points compared to the control (Fig. 2d). Although both medium and low dose exhibited greater fresh weight at 10 days than the high dose, by 20 days, the three doses were equalized. At 30 and 40 days, an inversion ocurred, the high dose an incresase compared to low and medium dose. As dose increases, the fresh root weight increases at 40 days.
All dose exhibited a positive effect to the dry root weight (Fig. 2e). The high dose required 20 days to begin enhancing the dry root weight compared to the other treatments, while the medium and low doses showed improvement after 30 days compared to the control. As dose increases, the dry root weight increases at 40 days, with the high dose being outstanding with a significant difference.
The root volume to length ratio indicated that the application of biostimulant triggered a modification of RSA, as it showed in Fig. 3a-c. The biostimulant doses elevated the ratio values compared to control across all time points. This suggests that as the biostimulant dose increased, the root volume to length ratio increased. This was attributed to the decrease in root length and the increase in volume.
The RGR demonstrated that all three doses of biostimulant enhanced the plant growth in all evaluated times points compared to the control (Fig. 3b). As the biostimulant doses increased, the RGR also increased. Particularly noteworthy is the high dose, which exhibited a superior daily growth rate compared to the others biostimulant doses and control. The low dose surpassed the RGR of the medium dose at 40 days.
Effects of Various Dose of biostimulant on the Mineral Analyses
The application of biostimulant doses did not significantly affect the uptake of macronutrients N, Mg, K, Ca, P, and the micronutrient Fe compared to the control. Biostimulant doses did impact the assimilation of certain micronutrients. Specifically, the uptake of Mn was enhanced by three doses of biostimulant compared to the control. The uptake of Cu was increased by medium dose compared to the low, high dose and control. The uptake of Zn was boosted by the low and medium biostimulant doses compared to the high dose and control.
| Nutrient | Control | Low | Medium | High | Sig1 |
| Ca (%) | 3.7 ± 0.4 | 4.2 ± 0.5 | 3.8 ± 0.1 | 4.0 ± 0.1 | ns |
| Mg (%) | 1.1 ± 0.1 | 1.2 ± 0.1 | 1.15 ± 0.03 | 1.22 ± 0.02 | ns |
| K (%) | 2.7 ± 0.2 | 2.5 ± 0.2 | 2.6 ± 0.2 | 2.4 ± 0.2 | ns |
| N (%) | 4.6 ± 0.5 | 4.7 ± 0.1 | 4.5 ± 0.1 | 5.1 ± 0.6 | ns |
| P (%) | 0.50 ± 0.01 | 0.52 ± 0.03 | 0.50 ± 0.03 | 0.49 ± 0.01 | ns |
| Mn (mg kg−1) | 140 ± 4b | 168 ± 14a | 157 ± 12a | 176 ± 8a | *** |
| Fe (mg kg−1) | 114 ± 13ab | 109 ± 4b | 128 ± 7a | 120 ± 3a | ** |
| Cu (mg kg−1) | 13.6 ± 0.4b | 13.4 ± 0.9b | 16.5 ± 1.3a | 12.7 ± 0.8b | ** |
| Zn (mg kg−1) | 104 ± 9c | 165 ± 12a | 152 ± 8a | 122 ± 3b | ** |
Results are expressed in average ± standard deviation (n = 6). Mean values followed by different letter indicate statistically significant differences according to Duncan’s test (p < 0.05)
Sig1 is ns: sig > 0.05; *: 0.01 < sig < 0.05; **: 0.001 < sig < 0.01; ***: sig < 0.001
Transcriptome Sequencing and Analysis Differential Gene Expression Analysis
Transcriptome analyses were conducted to obtain a comprehensive understanding of the mechanism of action of biostimulant in root development RNA sequencing of the 6 samples resulted in a cumulative total of 277 million raw reads. Following primer trimming and the removal of low-quality reads, the dataset was refined to 273 million clean reads. These selected DEGs were utilized for subsequent analysis. Heatmap and volcano plot provided a global view of transcriptome expression changes induced by biostimulant. The heatmap revealed that biostimulant treatment led to modification in gene expression compared to the control conditions (Fig. 4a).
The volcano plot likely revelated that biostimulant treatment resulted in a significant number of differentially expressed genes (DEGs) (Fig. 4b). Particularly, 1764 DEGs were identified, comprising 1146 were up-regulated, and 618 were down-regulated. This indicated that biostimulant treatment had a substantial impact on the transcriptome of the roots, significantly altering the expression of a large number of genes.
KEGG Pathway Enrichment Analysis of Roots Under biostimulant Treatment
The KEGG pathway enrichment analysis was conducted to emphasize the functional annotation of enzymes, and the biochemical metabolic pathways associated with the DEGs in root development. The result showed that annotated DEGs were distributed in 7 metabolic pathways ranked from the least to the most fold enrichment: sesquiterpenoid and triterpenoid biosynthesis, MAPK signaling pathways, phenylpropanoid biosynthesis, plant hormone signal transduction, carbon metabolism, biosynthesis of secondary metabolites and metabolic pathways (Table 1).
Discussion
The potential of biostimulants to enhance crop productivity has gained considerable interest, particularly in organic farming where nutrient inputs are often limited. The amino acids from enzymatic hydrolysis of plant-origin proteins are one of the bioactive compounds widely studied that promoted vegetative growth. In addition, they play an essential role in metabolic processes and as a building block of proteins. The direct application of these amino acids to the roots had a direct effect on plant growth. In the present study, the root application of biostimulant significantly enhanced shoot development, characterized by increased height, fresh and dry weight, leaf count, and leaf area. High doses of biostimulant showed superior results, with significant differences in shoot development observed as early as 20 days after the first application. In contrast, lower dose necessitated a longer period (40 days after first application) to manifest improvements in aerial development. This enhancement observed in the aerial parts was directly influenced by the RSA.
The root structure displays remarkable adaptability, facilitating efficient resources utilization in the rhizosphere. This RSA plasticity is modulated by interaction with environmental conditions and genetic components, driving the plant to respond to external cues and soil exploration. Thus, the application of biostimulant induced modification in RSA, resulting in reduced root length but increased root volume, as well as fresh and dry root weight, with escalating doses of biostimulant. Root volume increased with low, medium, and high doses by 66.2, 83.2, and 165%, respectively (Fig. 2b). Fresh weight stimulation was observed at 45, 61, and 97.3% with low, medium, and high doses, respectively (Fig. 2d). Dry weight promotion occurred at 7, 23.4, and 53.7% with low, medium, and high doses, respectively, compared to the control. This indicated that biostimulant promoted the lateral root development while inhibiting primary root elongation (Fig. 2e). This finding is in accordance with Yang et al. since they demonstrated that exogenous application of basic-, hydroxyl-, sulfur-containing, and aromatic amino acids significantly inhibited primary root growth in Arabidopsis. The most pronounced inhibition was observed with lysine meanwhile there was a simultaneous stimulation of lateral root density. This observation agrees with lysine being the predominant amino acid in the formulation.
Although metabolic studies on the effect of biostimulant based on amino acids and seaweed extracts on cucumber growth were not carried out in this work, transcriptome analysis supports the potential of biostimulant. It highlighted several biological processes, compressing the response to stimulus, the enhancement of regulation of cellular metabolic process, and the response to chemical. These processes are closely associated with improvements in DNA binding, increased transcription regulator activity, and DNA-binding transcription factor activity at the molecular function level.. These factors are particubiostimulanty significant in the root elongation and differentiation zones, encompassing the outgrowth of lateral root. Taking into account that plant root exhibits a fixed radial pattern of organization, involving various cell types, functions, and developmental stages along the growth axis.
Concerning cell division and the biosynthesis and remodeling of the wall cell. In young stem cells undergo rapid cell division, leading to the formation of new cell walls. According to the transcriptome analysis, the stimulation of the cell division was facilitated by increased cytoskeletal and microtubule motor activity, along with the activation of the kinase complex. This coordination is vital for various cellular processes, including membrane trafficking, signaling, and morphogenesis. The Kinesin complex plays a crucial role in the formation, maintenance, and function of cytoskeletal arrays, as well as in coordinating cell plate formation, contributing to primary cell wall generation at the growing cell plate. This primary cell wall generation is further promoted by biostimulant, which stimulates the metabolic processes of macromolecules, hemicellulose, and polysaccharides according to the transcriptome analysis. This newly formed cell wall exhibits high dynamism, playing a crucial role in supporting rapid and anisotropic cell expansion. In the differentiated cell types, cell wall composition and structure may change to adapt and support different cellular functions. Thus, the importance of the cell wall in root growth lies in its diverse composition and remarkable flexibility, which enable it to support the complex processes of cell expansion, differentiation, and adaptation during root development.
Aromatic amino acids like tryptophan, phenylalanine, and tyrosine are essential for protein synthesis and serve as precursors for various natural products in plants, including pigments, alkaloids, hormones, and components of cell walls. Thus, exogen application of this aromatic amino acid also stimulate the phenylpropanoid biosynthesis pathway. Different studies demonstrated that lysine play a crucial role as a signaling amino acid mediating cascades involved in regulate various aspect of plant growth and responses to environmental cue. Particubiostimulanty, lysine catabolism by saccharopine pathway activated the phenylpropanoid pathway (PePP) impacting on the secondary metabolism. These are in consonance with the result of KEGG pathway analysis. Therefore, the application of biostimulant stimulates the activation of the phenylpropanoid biosynthesis pathway by activating crucial enzymes necessary for lignin biosynthesis, such as 4-coumarate-CoA ligase and peroxidases. The activation of these enzymes is indispensable to produce various secondary metabolites such as flavonoids, lignans, coumarins, and hydroxycinnamic acid conjugates, some of which are precursor of lignin units. Lignin is a constituent of the secondary cell wall along with cellulose, hemicellulose and cell wall proteins. This secondary cell wall is particularly important for mechanical support providing strength and stability to the cell and the plant. A secondary cell wall is found in specific cell types that constitute secondary tissues with rigid structures, such as fibers, tracheid, or vessel elements, especially within the xylem vessel responsible for transporting water and nutrients to the aerial parts of the plant. The hydrophobic nature of lignin effectively prevents water loss from cells, thereby conferring highly efficient water transport capabilities.
The modulation of cell wall remodeling plays a crucial role in the breakout and growth of the lateral root, which are promoted by biostimulant. This finding aligns with multiple studies indicating that seaweed extract elicits positive responses in various specific aspects of plant growth, production, and fruit quality across different crops. Specifically related to this study, seaweed has been shown to enhance root size and architecture stimulating root cell division and lateral root development. The root growth-promoting capabilities of the seaweed extract are attributed to their phytohormones-like activity, including auxin, which plays an essential role in regulating RSA by controlling primary root elongation and lateral root formation. A similar effect on parameters such as yield, number of fruits, dry weight, color, flesh thickness, skin thickness, plastid pigments, and tocopherol content of cucumbers was reported in another recent study in which two commercial biostimulants based on the seaweed Ascophyllum nodosum L. were applied by foliar spray.
The up regulation of certain genes in the auxin signaling pathway regulates the outgrowth of lateral root, initiating a local maximum in the founder cell in the pericycle and preparing the overlying endodermal cells for subsequent lateral root emergence. The outgrowth of lateral root primes the overlying cell by up regulating several cell wall-modifying proteins, including EXPANSINs, pectate lyases, XTH family proteins (xyloglucan endotransglucosylase /hydrolase) and indirectly aquaporins.
According with the up regulation of auxin-related genes by Laminaria sp., also the glucose affects the root length, root hair, the number of lateral roots and modulate the root growth direction by interacting with phytohormones, especially with the auxin response pathway modulating the auxin-related genes. Sugars are metabolic substrates that have an active role in modulating various stimulus response and metabolic process carried out in deference phases of plant development. This implies the promotion of metabolic pathways, the carbon metabolism, and the biosynthesis of secondary metabolism.
Therefore, this study suggests that it has a beneficial impact on growth development, modifies the RSA, and activates different metabolic processes, providing evidence of its effectiveness. Particularlty, the increase of secondary roots contributes to expanding the root area to obtain nutrient and water, which is crucial in organic farming where these resources are limited.
Conclusions
To conclude, this study demonstrated the significant potential of biostimulant based on amino acids and seaweed extract for enhancing plant growth, particularly in the context of organic farming where nutrient availability is restricted. The application of biostimulant exhibited significant improvement in both shoot and root development of Cucumis sativus. Distinguishing the modification of the RSA by promoting the lateral root development while inhibiting primary root elongation, thereby increasing the surface area for nutrient and water uptake. The effectiveness of biostimulant is due to the synergy of bioactive compounds including amino acid from enzymatic hydrolysis of plant protein, seaweed extract and carbohydrates. Transcriptome analysis revelated that biostimulant modulates several biological processes, such as cell division and cell wall biosynthesis and remodeling, crucial for root elongation and differentiation. The upregulation of key genes associated with this function further supported the physical changes observed. Future investigations will evaluate the effectiveness of different amino acid blended with seaweed extract different crops, substrates, under real field conditions, and different abiotic stresses to validate its efficacy.
