Effects of Three Organic Fertilizers and Biostimulants on the Morphological Traits and Secondary Metabolite Content of Lettuce
by
, , , , , ,
Nataša Romanjek Fajdetić
1,
Ljiljana Božić Ostojić
1,
Robert Benković
1,
Dinko Zima
1,
Mihaela Blažinkov
1,
Krunoslav Mirosavljević
1,*,
Brigita Popović
2 and 
Teuta Benković-Lačić
1 1
University of Slavonski Brod, BIODpt, 35000 Slavonski Brod, Croatia
2
Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University in Osijek, 31000 Osijek, Croatia
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(11), 1288; https://doi.org/10.3390/horticulturae11111288
Submission received: 1 October 2025
/
Revised: 20 October 2025
/
Accepted: 23 October 2025
/
Published: 27 October 2025
(This article belongs to the Special Issue New Advances in Green Leafy Vegetables)
Abstract
The aim of the work was to find out the effects of three types of organic fertilizers (S-horse and cow, P-chicken, B-compost) and three types of biostimulants (BC-plants, BO-microorganisms, BS-microorganisms) on the growth of lettuce (Lactuca sativa cv. Maradona) and the secondary metabolites accumulation. The combination of manure (P) and biostimulant (BC) produced the highest yield, exceeding the control by 50% and 66% in two successive growing cycles (p < 0.05). Across all fertilizer treatments, BC application consistently improved plant performance and metabolic activity. Among secondary metabolities, the highest total phenolic content was observed in S and S + BC (≈2.56 mg g−1), phenolic acids in S + BC (≈2.54 mg g−1), antioxidant activity in P + BC (≈1.24 mg g−1), flavonoids in control with S (≈14.09 µmol/g), and proline in P + BO (≈2.45 µmol/g). These findings highlight the synergistic effects of organic fertilizers and biostimulants, suggesting their potential to improve both productivity and nutritional quality in sustainable horticultural systems.
1. Introduction
Lettuce (Lactuca sativa) is one of the most widely grown agricultural crops. Producers consistently aim to optimize and increase their yields [1]. Global agricultural productivity and food security are increasingly threatened by various challenges, including plant disease outbreaks, inefficient use of chemical fertilizers, declining soil fertility, and scarce freshwater resources. Climate change, combined with the intensive use of synthetic fertilizers and chemical pesticides, has further contributed to soil degradation, disrupting key physiological processes such as water transport, root development, and photosynthesis, which ultimately reduce crop growth and yield [2,3]. Long-term fertilization practices significantly influence changes in soil biological properties, which in turn can impact soil functionality and overall quality [4,5]. Mineral fertilizers consist of simple molecules readily available to plants, whereas organic fertilizers—derived from plant or animal materials such as farmyard manure, compost, digestates, or sewage sludge—contain complex organic compounds like humic substances and lignocellulose. These compounds not only provide nutrients for plants and soil microbiota but also enhance soil organic matter content [6,7]. The application of organic fertilizers and biostimulants represents one of the most practical and cost-effective methods for improving soil structure and fertility. Nonetheless, there remains a lack of studies examining how the optimized use of organic fertilizers can supply nutrients efficiently while minimizing environmental impacts. Since all organic fertilizers must first be transformed into plant-available forms through microbial activity [8], improving soil microbiological activity through biostimulant treatments offers a promising approach [9,10,11]. Fertilizers, and more recently biostimulants, have been increasingly applied as agronomic inputs with the potential to improve crop productivity and resource-use efficiency, thus playing a role in promoting the development of sustainable agricultural systems [12,13,14,15,16]. Biostimulants are increasingly recognized as valuable tools in modern agriculture, promoting crop growth, resilience, and quality while contributing to sustainable farming practices [17]. Derived from natural substances or beneficial microorganisms, these products stimulate plants’ natural physiological processes. Plant biostimulants are compounds or microorganisms that, when applied to plants, stimulate natural processes to improve stress tolerance and nutrient utilization [18]. They represent an ecofriendly approach to reducing chemical fertilizer dependency and reinforcing nutrient uptake and yields. The properties of biostimulants, including their bioactive constituents, mechanisms of action, and their impacts on plant morphology, biochemistry, and metabolism, have become key areas of investigation for researchers, industry stakeholders, and farmers [19]. In addition, people are increasingly realizing that organically produced food is essential for maintaining health and the market for organically produced food is growing more and more. Also, lettuce secondary metabolites are potentially associated with many health-beneficial properties, including antifree radical, anti-inflammatory, antidiabetic, anticancer, and anticardiovascular diseases (CVDs) effects [20]. In this context, the present study investigates how three types of organic fertilizers and three types of biostimulants influence the morphological characteristics and secondary metabolite formation in lettuce as similarly examined in previous studies [21,22]. This research provides new insights into the combined effects of these inputs, addressing a knowledge gap that is highly relevant for advancing sustainable agricultural practices.
2. Materials and Methods
2.1. Setting up the Experiment
The experiment was conducted at testing ground of University of Slavonski Brod in Slobodnica (Croatia) (N 45°9′58″, E 17°57′8″). It was established under greenhouse conditions (day: 20–25 °C; night: 15 °C) and relative humidity 70–80%. The research was conducted with a two-factorial experiment; three organic fertilizers (Plantella organik (P), Biopon (B) and Stallatico pellettato (S)) and three biostimulants (Čudomix (C), Organico (O) and Slavol (S)) in four repetitions. Seeds were sown in a modular tray containing 60 cells, each with a volume of 50 mL, filled with Potgrond P substrate (Klasmann-Deilmann, Geeste, Germany). The substrate had a pH of 6.0 and the following nutrient content: nitrogen (N) 220 mg/L, phosphorus (P2O5) 110 mg/L, potassium (K2O) 220 mg/L, and magnesium (Mg) 80 mg/L. The first growing period was sown on 20 February 2024, and the second on 1 April 2024. The 4-week-old seedlings were transplanted into 2 L pots filled with garden soil (pH-KCl (6.97), pH-H2O (7.88), Al-P2O5 mg/100 g soil (1), Al-K2O mg/100 g soil (16.19), humus (4.1%), and CaCO3 (1.67%)). The organic fertilizer application was performed before transplantation, mixing the three fertilizers with garden soil (2 g/pot–16 pots per each fertilizer). All biostimulants and organic fertilizers evaluated in this study were commercially available. The biostimulants were added three times during vegetation according to the biostimulator manufacturer’s instructions. First application was during the transplantation and the other two a week apart.
2.2. Organic Fertilizers
Plantella organik (manufacturer Unichem, Slovenia) is a chicken manure containing (N) 45%, (P2O5) 3%, (K2O) 2%, (CaO) 8%, (Mg) 1%, (C) 36%, and trace elements Zn, Fe, Mn.
Biopon (manufacturer Bros, Sp, Poland) is a compost-based organic fertilizer containing (N) 12%, (P2O5) 5%, (K2O) 10%, (Mg) 2%, (S) 35%, and microelements.
Stallatico pellettato (manufacturer Termocomposti S.p.A., Italy) is horse and cow manure containing total pH 6–7, (N) 24%, (C) 23%, C/N 12/12, (P2O5) 3–4%, (K2O) 3–4%, and humidity 75%.
2.3. Biostimulants
Organico biostimulant (manufacturer Green Grow Group, Serbia) contains a number of natural ingredients that stimulate the growth and development of plants. The main components include the following: amino acids (including betaine and glycine), vitamins (D, E, K, B complex), natural plant hormones (auxins, gibberellins, cytokinins), and beneficial microorganisms such as bacteria of the genus Bacillus and fungi Saccharomyces sp.
Slavol (manufacturer Agrounik, doo, Serbia) is a biostimulant that contains bacteria, natural vitamins, enzymes, and growth regulators. It mainly consists of bacteria that carry out the process of nitrogen fixation and phosphorus decomposition, as well as auxin, plant hormones that stimulate plant growth.
Čudomix biostimulant (manufacturer OPG Vedran Pezelj, Croatia) contains nettle (Urtica dioica), comfrey (Symphytum officinale), marshmallow (Althea officinalis), horsetail (Equisetum arvense) and dandelion (Taraxacum off.). In addition to herbal ingredients, it also contains nitrogen and other nutrients, as well as biologically active compounds that help protect against fungal and bacterial diseases.
2.4. Plant Sampling
The mass of heads was determined by an analytical balance of three decimal places on the Ohaus scale. The plant material was washed with distilled water, dried on filter paper and then weighed to obtain fresh weight (FW). A part of the leaves was frozen at −40 °C and was used for the analysis of phenols, phenolic acids, flavonoids, antioxidant activity, and proline. To obtain dry matter, the plants were dried in a drying oven at a temperature of 45 °C until constant mass, after which they were weighed. All analyses were performed at the Ruđer Bošković Institute (Zagreb, Croatia).
2.5. Phenols, Phenolic Acids, Flavonoids, Antioxidant Activity, and Proline
Sample homogenization was carried out by grinding fresh plant material in liquid nitrogen using a mortar and pestle, with the central leaf veins removed prior to grinding. The same procedure was applied to dry samples, but without the use of liquid nitrogen. For fine grinding, 30 mg of dry material or 100 mg of fresh material was processed using a Retsch MM 400 mill at 30 Hz for 2 min with five zirconia balls. Extraction of active compounds from the samples was performed using 80% methanol. Each sample was treated with 1 mL of methanol, briefly vortexed, then subjected to high-frequency milling for 10 min, ultrasonic extraction for 8 min, and rotary homogenization for 30 min. Following extraction, the samples were centrifuged at 16,000× g for 10 min, and the resulting supernatants were used for analysis. Total polyphenols were determined by the Folin–Ciocalteu method [23] in 80% methanol. The content of total phenols is expressed in milligrams of gallic acid equivalents per unit of fresh mass substances (f.w.) of the sample (mg GAE/g f.w.). The content of phenolic acids was determined by a colorimetric method [24] (European Pharmacopeia, 2004) and expressed as milligrams of caffeic acid equivalents per gram of fresh sample matter (mg CAE/g f.w.). The antioxidant capacities of the samples were determined by in vitro DPPH assays [25] and the results were expressed as Trolox equivalent per unit mass of fresh sample (μmol TE/g f.w.). The content of total flavonoids was determined by the method of [26]; it is expressed in milligrams of catechin equivalents (eng. catechin equivalents) per unit mass of the sample (mg CE/g f.w.). Proline content was determined by the protocol according to [27] and expressed as micromole proline per gram of fresh matter (μmol proline/g f.w.). Measurements were performed on a Shimadzu BioSpec-1601 E UV/VIS spectrophotometer or on a microtiter plate reader (Tecan M200).
Extraction of active compounds from the samples was performed using 80% methanol. Each sample was treated with 1 mL of methanol, briefly vortexed, then subjected to high-frequency milling for 10 min, ultrasonic extraction for 8 min, and rotary homogenization for 30 min. Following extraction, the samples were centrifuged at 16,000× g for 10 min, and the resulting supernatants were used for analysis.
2.6. Statistical Analysis
The experimental data were subjected to statistical evaluation using TIBCO Statistica, Version 14.1.0.8. Analysis of variance (Factorial ANOVA) was performed for all datasets. A one-way analysis of variance (ANOVA) was performed for the initial measurements, whereas a factorial ANOVA was employed for subsequent datasets. Post hoc comparisons were conducted in accordance with Fisher’s least significant difference (LSD) test, with statistical significance established at p < 0.05. For the assessment of secondary metabolites, differences between treated groups and corresponding controls were analyzed using Student’s t-test. Levels of statistical significance were denoted as follows: 0.05 > p > 0.01, 0.01 > p > 0.001, and p < 0.001, indicated by asterisks in the results.
3. Results
3.1. Morphological Measurements
In this part, the results of measuring morphological characteristics are presented in the following Table 1, Table 2, Table 3, Table 4, Table 5, Table 6, Table 7 and Table 8.
In Table 1, regarding the use of biostimulants, statistical significance was observed in all three measurements. The measurement results show that during all three measurements, the highest values were recorded with the application of fertilizer P and biostimulant BC. If we consider the third measurement, it can be seen that the best result was achieved with the application of fertilizer P and biostimulant BC. In comparison with the next lower result (fertilizer P and biostimulant BC), the plants were on average 5.88% longer, and compared to the poorest result, which was recorded in the control, the plants were 28.49% longer.
As shown in Table 2, the use of biostimulants produced statistically significant differences across all three measurement points. The results indicate that in all three measurements, the highest values were obtained with the application of fertilizer P and biostimulant BC. During the third measurement, the combination of fertilizer P and biostimulant BC produced the highest value, surpassing the second-highest value, achieved with fertilizer S and biostimulant BC, by 4.36%. Moreover, when compared to the lowest-performing treatment, control, the difference increases to 49.98%.
According to Table 3., statistically significant effects of biostimulant application were observed across all three measurements. Across all three measurements, the application of fertilizer P and biostimulant BC consistently produced the highest values. In the third measurement, when compared to the lowest-performing treatment, represented by the control, the result was 31.97% higher.
Table 4 shows that the use of biostimulants resulted in statistically significant differences in all three measurements. The highest values were consistently achieved with the application of fertilizer P in combination with biostimulant BC. Considering the third measurement, the application of fertilizer P and biostimulant BC resulted in the highest performance. When comparing the best result from the third measurement—achieved using fertilizer P combined with biostimulant BC—to the second-best result, obtained with fertilizer B and the biostimulant BO, a difference of 2.72% is evident. In the third measurement, the difference between the best result and poorest was 34.23%.
As shown in Table 5, the application of biostimulants led to statistically significant results in each of the three measurements. All three measurements revealed that the combination of fertilizer P and biostimulant BC yielded the best results. When comparing the best result from the third measurement—achieved using fertilizer P combined with biostimulant BC—to the second-best result, obtained with fertilizer S and the biostimulant BC, a difference of 1.92% is evident. Moreover, when compared to the lowest-performing treatment, represented by the control, the result was 22.22% higher.
Table 6 shows that the use of biostimulants resulted in statistically significant differences in all three measurements. The results indicate that in all three measurements, the highest values were obtained with the application of fertilizer P and biostimulant BC. If we compare the best result in the third measurement, achieved through the application of fertilizer P and biostimulant BC, with the next best result, which resulted from the use of fertilizer S and biostimulant BC, a difference of 4.36% can be observed. Furthermore, compared to the poorest result, which occurred with the control, the difference was 66.28%.
As in previous cases, Table 7 shows that the use of biostimulants led to statistically significant differences in all three measurements. In this case as well, the highest result was obtained through the application of fertilizer P and biostimulant BC. In this case, the difference between the best and worst results achieved was 20.83%.
According to Table 8, statistically significant effects of biostimulant application were observed across all three measurements. All three measurements revealed that the combination of fertilizer P and biostimulant BC yielded the best results. Considering the third measurement, if we compare the best result achieved through the application of fertilizer P and biostimulant BC with the poorest result, which occurred with the application of fertilizer B and biostimulant BO, the difference was 80.57%.
3.2. Phenols, Phenolic Acids, Antioxidant Activities, Flavonoids, and Prolines
As part of the research, phenols, phenolic acids, antioxidant activity, flavonoids and proline were analyzed (Table 9).
4. Discussion
4.1. Effects on Morphological Parameters and Yield
Organic fertilization presents a promising alternative for reducing the negative effects associated with mineral fertilizers, with its ability to raise soil pH and indirectly improve the soil’s physical, chemical, and biological properties, ultimately enhancing crop productivity [28,29,30,31]. Plant biostimulants are natural substances, or beneficial microorganisms, that improve plants’ nutrient uptake, stress resistance, and overall crop quality, without acting as a direct source of nutrients, stimulating growth and protecting against stress [32,33]. This study demonstrates that both organic fertilization and biostimulants significantly influenced lettuce growth, including head mass, number of leaves, rosette height, and dry matter accumulation. The combination of fertilizer P with biostimulant BC consistently produced the highest yields across both experiments, with increases of approximately 50–66% compared to the control. Other morphological parameters followed similar trends, indicating that BC was the most effective biostimulant for this lettuce variety. The PBC combination outperformed other treatments, likely due to the higher nitrogen content of fertilizer P, which supports enhanced vegetative growth. However, it is noteworthy that BC also improved yields when applied with fertilizers containing lower nitrogen levels, suggesting a synergistic effect that promotes nutrient uptake through bioactive compounds derived from (Urtica dioica, Symphytum officinale, Althea officinalis, Equisetum arvense, Taraxacum officinale) [8,34,35]. This enhancement may be attributed to increased microbial activity that facilitates the transformation of organic nutrients into plant-available forms. Similar positive effects of plant-based biostimulants on lettuce growth and yield have been reported by other authors [36,37,38,39].
Biostimulants derived from plants promote the growth and yield of various horticultural crops by enhancing key physiological, biochemical, and molecular processes. The enhanced availability of nutrients may be a direct consequence of the presence of nutrients, amino acids, peptides, peptones, or proteins within the formulation [40,41]. Previous studies on lettuce have also demonstrated that the application of organic fertilizers can significantly enhance yield. Because organic fertilizers provide a consistent supply of various nutrients and enhance the soil’s physical, chemical, and biological properties, they have led to increased lettuce growth as well as higher nutrient concentration and uptake [38,42].
In addition to the impact on yield, biostimulants and organic fertilizers also have an impact on the formation of secondary metabolites, which leads to the accumulation of micronutrients and antioxidant molecules [35]. In the present study, the analyses of the following secondary metabolites were performed: phenols, phenolic acids, antioxidant activities, flavonoids, and prolines. Phenolic compounds play a key role in plant defense and stress adaptation [37,43,44]. In this study, total phenolic content suggested stimulation of the phenylpropanoid pathway [45,46,47,48,49,50,51]. The second secondary metabolite examined were phenolic acids. The highest phenolic acid content was observed in the SBC treatment (2.541 ± 0.047 mg/g) and the lowest in SBO (1.373 ± 0.023 mg/g). These values align with previously reported ranges [52,53]. The results indicate that specific fertilizer–biostimulant interactions can significantly modulate phenolic acid synthesis. With regard to antioxidant activity, the highest value was recorded in the PBC treatment (1.236 ± 0.013 µmol/g) and the lowest in PBS (0.343 ± 0.013 µmol/g). Similar results were obtained by [54]. The content of flavonoides was also tested. The highest flavonoid content was found in the CBS treatment (14.092 ± 0.590 mg/g), whereas the lowest was in SBO (7.980 ± 0.026 mg/g). Similar results were obtained [46,53,54,55,56,57]. The last secondary metabolite investigated was proline. It is an amino acid that has a protective role in plants, especially under stress (e.g., drought, salinity). The lowest proline content was (0.071 ± 0.005 µmol/g) and the highest was (2.447 ± 0.193 µmol/g), consistent with literature values [58]. The highest levels were recorded under PBO, indicating enhanced activation of stress-related metabolic pathways even in the absence of external stressors.
4.2. Physiological Mechanisms and Biochemical Interpretation
The elevated accumulation of proline and antioxidants in treated plants suggests that biostimulants induced defense-related signaling, known as the priming effect. The mechanism enables plants to “prepare” for potential stress by increasing protective metabolites such as proline in advance. Previous studies have shown that exogenous proline application reduces oxidative stress and increases antioxidant enzyme activity in lettuce [59]. The current results imply that treatments such as PBC may enhance antioxidant potential through a similar mechanism involving the activation of enzymes like SOD, CAT, APX, and POD. The variation among treatments in phenolic, flavonoid, and proline levels underscores the complexity of metabolic regulation. While PBC, PBO, and PBS exhibited pronounced antioxidants and osmoprotective responses, the control group showed higher baseline phenolic and flavonoid levels, possibly reflecting an absence of induced metabolic redirection. These results collectively suggest that the observed biochemical modulation arises from the interaction between nutrient availability and biostimulant-induced signaling pathways.
4.3. Implications for Sustainable Agriculture
The integration of organic fertilizers with targeted biostimulants represents an effective and environmentally friendly strategy to improve lettuce yield, nutrient assimilation, and stress resilience. Enhanced proline and antioxidant accumulation indicates improved tolerance to abiotic stress, while variability in phenolic compound synthesis offers opportunities to optimize nutritional value. From a broader perspective, these findings demonstrate that biostimulant-assisted organic fertilization can contribute to sustainable agricultural systems by reducing dependency on synthetic inputs and enhancing crop quality. Both organic fertilizers and biostimulants significantly influenced lettuce morphology and secondary metabolism. The PBC combination consistently achieved the highest yields, confirming its strong synergistic potential. Biostimulant BC proved effective even with low-nitrogen fertilizers, enhancing nutrient uptake and plant productivity. The modulation of secondary metabolities—particularly proline, antioxidants, and phenolics—reflects an activation of stress-responsive pathways and suggests that such treatments can improve both crop performance and nutritional quality. Overall, the study advances understanding of how organic fertilizers and plant-based biostimulants jointly affect lettuce physiology. Future research should explore different formulations and application regimes to further elucidate the mechanisms underlying these interactions and to optimize biostimulant use in sustainable crop production.
5. Conclusions
The results of the experiment show that both factors (fertilizers and biostimulants) significantly affected lettuce morphological characteristics: the mass of plants, number of leaves, rosette height, and dry matter. The combination of fertilizer P with biostimulant BC consistently produced the highest yield in both experiments, with increases of 50% and 66% compared to the control. Comparisons with other combinations highlighted PBC as superior, likely due to the higher nitrogen content in the P fertilizer. The results indicate that biostimulant BC was the most effective in enhancing lettuce yield, even when combined with fertilizers containing lower nitrogen levels. In both growing periods, the PBC combination consistently outperformed other treatments (excluding the control treatment), with yield increases ranging from 4.36% to 41.20% compared to alternative combinations. Similarly, biostimulant BC demonstrated superior performance over other biostimulants (BBC vs. BBS and BBC vs. BBO), confirming its strong synergistic effect with both high- and low-nitrogen fertilizers. This study clearly demonstrates that the applied treatments also influenced the biosynthesis of secondary metabolites. The enhanced accumulation of proline and antioxidants under specific treatments indicates improved stress tolerance, whereas the elevated levels of flavonoids and phenols in the control highlight the importance of maintaining baseline metabolic regulation. The observed variability in phenolic acid content further underlines the complexity of treatment-specific metabolic responses.
The novelty of this research lies in its integrative evaluation of the combined effects of multiple organic fertilizers and biostimulants on both morphological traits and secondary metabolism of lettuce. While previous studies have typically examined these factors separately, the present work provides new insights into their synergistic interactions and the underlying biochemical mechanisms contributing to enhanced plant performance. These findings expand current understanding of how biostimulant-assisted organic fertilization can simultaneously improve yield and metabolic quality in leafy vegetables.
5.1. Limitations and Risks
The study was conducted under controlled experimental conditions, which may not fully replicate field-level environmental variability. The scope was limited to three types of organic fertilizers and three biostimulants; thus, extrapolation to other formulations should be made cautiously. Additionally, the potential variability in the biochemical composition of biostimulant preparations is a possible source of uncertainty in replicability. Future studies should include multi-season field trials, a broader range of biostimulant formulations, and molecular analyses to better elucidate signaling pathways associated with nutrient uptake and stress adaptation.
5.2. Future Directions
Further research should focus on identifying the most effective application regimes (timing, concentration, and frequency) for biostimulant—fertilizer combinations. Integrating metabolomic and transcriptomic analyses would provide deeper insight into the regulatory networks controlling lettuce metabolic responses. Moreover, evaluating environmental impacts, such as soil microbial diversity and nutrient cycling, will strengthen the case for adopting these approaches in sustainable crop production systems.
Author Contributions
Conceptualization, N.R.F. and M.B.; methodology, N.R.F.; software, R.B.; investigation, L.B.O. and D.Z.; writing—original draft preparation, N.R.F.; supervision, B.P. and K.M.; funding acquisition, T.B.-L. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the project Green Vegetables for Green Deal, financed by The Environmental Protection and Energy Efficiency Fund and by project Lettuce organic production (LOG), financed by the University of Slavonski Brod, Republic of Croatia.
Data Availability Statement
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
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Table 1.
The height of plants measured three times during the vegetation period of the 1st experiment (in cm).
Table 1.
The height of plants measured three times during the vegetation period of the 1st experiment (in cm).
| Yield Comp. | Height (cm) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 21 March 2024 | 2nd Metric 28 March 2024 | 3rd Metric 5 April 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 12.33 A | 12.53 A | 11.72 | 16.83 A | 16.71 A | 16.25 | 23.84 Ab | 25.48 Aa | 21.29 Ac |
| BS | 10.53 B | 11.2 B | 11.22 | 14.46 Bb | 15.77 ABa | 15.7 a | 20.41 Bb | 21.83 Ba | 20.96 Aab |
| BO | 10.40 B | 10.67 B | 10.92 | 16.18 AC | 16.00 AB | 16.17 | 21.14 B | 22.05 B | 21.37 A |
| C | 11.31 AB | 11.94 AB | 11.17 | 15.54 BC | 15.33 B | 15.33 | 19.97 B | 20.39 C | 19.83 B |
| FF | * (p < 0.05, F = 0.99) | n.s. (p < 0.05, F = 0.25) | * (p < 0.05, F = 12.62) | ||||||
| FBS | n.s. (p < 0.05, F = 6.24) | * (p < 0.05, F = 7.01) | * (p < 0.05, F = 30.85) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 0.56) | n.s. (p < 0.05, F =1.28) | * (p < 0.05, F = 4.31) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 2.
The mass of plants measured three times during the vegetation period of the 1st experiment (in g).
Table 2.
The mass of plants measured three times during the vegetation period of the 1st experiment (in g).
| Yield Comp. | Mass (g) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 21 March 2024 | 2nd Metric 28 March 2024 | 3rd Metric 5 April 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 58.65 Aab | 61.94 Aa | 51.52 Ab | 99.34 A | 102.38 A | 94.46 | 200.97 Aab | 209.74 Aa | 183.98 Ab |
| BS | 46.46 B | 41.7 BC | 44.23 B | 91.94 AB | 89.73 B | 88.32 | 156.43 Bb | 166.54 Ca | 158.38 BC |
| BO | 43.24 B | 47.7 B | 45.44 B | 92.8 AB | 91.71 B | 95.60 | 155.75 Bc | 190.41 Ba | 168.44 Bb |
| C | 47.15 Ba | 40.15 Cab | 39.12 Bb | 90.88 B | 92.22 B | 90.88 | 139.84 B | 154.84 C | 156.17 C |
| FF | n.s. (p < 0.05, F = 2.55) | n.s. (p < 0.05, F = 5.43) | * (p < 0.05, F = 21.49) | ||||||
| FBS | * (p < 0.05, F = 23.13) | * (p < 0.05, F = 0.51) | * (p < 0.05, F = 88.23) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 2.32) | n.s. (p < 0.05, F = 0.84) | * (p < 0.05, F = 4.83) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 3.
The number of leaves of plants measured three times during the vegetation period of the 1st measurement.
Table 3.
The number of leaves of plants measured three times during the vegetation period of the 1st measurement.
| Yield Comp. | Number of Leaves | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 21 March 2024 | 2nd Metric 28 March 2024 | 3rd Metric 5 April 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 11.67 Aa | 13 Aa | 10 b | 16 A | 15.33 A | 14.67 A | 18.67 Ab | 22 Aa | 18.33 b |
| BS | 8.33 Bb | 11.33 Ba | 9.33 b | 11.67 B | 13.67 A | 13.67 A | 18.33 AC | 19 B | 17.67 |
| BO | 11.33 A | 10 B | 10.33 | 12.67 Bb | 15 Aa | 14 Aa | 17 CBb | 19 Ba | 17.33 b |
| C | 8.33 Bb | 10.33 Ba | 10.33 a | 11.33 B | 11.33 B | 11.33 B | 16.67 B | 18 B | 17.33 |
| FF | n.s. (p < 0.05, F = 6.39) | n.s. (p < 0.05, F = 1.78) | * (p < 0.05, F = 14.24) | ||||||
| FBS | * (p < 0.05, F = 7.95) | * (p < 0.05, F = 17.80) | * (p < 0.05, F = 30.85) | ||||||
| Interaction | |||||||||
| FF-FBS | * (p < 0.05, F = 7.95) | n.s. (p < 0.05, F =1.63) | n.s. (p < 0.05, F =1.76) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 4.
The dry mass of plants measured three times during the vegetation period of the first experiment (in g).
Table 4.
The dry mass of plants measured three times during the vegetation period of the first experiment (in g).
| Yield Comp. | Dry Matter | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 21 March 2024 | 2nd Metric 28 March 2024 | 3rd Metric 5 April 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 3.81 Ab | 4.06 Aa | 2.99 Ab | 7.04 A | 7.26 A | 6.70 | 9.01 Aab | 9.41 Aa | 8.70 Ab |
| BS | 2.35 Bb | 2.75 Ba | 2.58 BCab | 6.52 AB | 6.36 B | 6.26 | 6.62 Bb | 7.47 Ba | 7.05 BCab |
| BO | 2.69 B | 2.87 B | 2.67 AB | 6.58 AB | 6.50 B | 6.78 | 6.81 Bc | 9.16 Aa | 7.56 Bb |
| C | 2.62 Ba | 2.12 Cb | 2.25 Cab | 6.44 B | 6.63 B | 6.44 | 7.04 B | 7.17 B | 7.01 C |
| FF | * (p < 0.05, F = 7.19) | n.s. (p < 0.05, F = 0.52) | * (p < 0.05, F = 29.64) | ||||||
| FBS | * (p < 0.05, F = 59.35) | * (p < 0.05, F = 5.17) | * (p < 0.05, F = 81.00) | ||||||
| Interaction | |||||||||
| FF-FBS | * (p < 0.05, F = 6.60) | n.s. (p < 0.05, F = 0.86) | * (p < 0.05, F = 8.17) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 5.
The height of plants measured three times during the vegetation period of the second experiment (in cm).
Table 5.
The height of plants measured three times during the vegetation period of the second experiment (in cm).
| Yield Comp. | Height (cm) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 2 May 2024 | 2nd Metric 2 May 2024 | 3rd Metric 2 May 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 11.96 Ab | 12.98 Aa | 12.12 Aab | 16.86 A | 17.13 A | 16.46 A | 24.41 Aa | 24.88 Aa | 21.25 b |
| BS | 10.93 B | 10.98 B | 11.17 AB | 14.25 Cb | 5.39 Ba | 15.8 AB | 22.71 Ba | 22.67 Ba | 20.78 b |
| BO | 10.77 B | 11.14 B | 11.12 B | 15.20 B | 16.00 B | 15.27 B | 22.01 B | 21.99 B | 21.24 |
| C | 10.54 Bb | 11.82 Ba | 10.94 Bab | 15.08 B | 15.34 B | 15.18 B | 20.36 C | 21.6 B | 20.63 |
| FF | * (p < 0.05, F = 3.85) | * (p < 0.05, F = 4.87) | * (p < 0.05, F = 12.62) | ||||||
| FBS | * (p < 0.05, F = 10.96) | * (p < 0.05, F = 22.94) | * (p < 0.05, F = 12.75) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 0.91) | * (p < 0.05, F = 2.74) | n.s. (p < 0.05, F = 0.91) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 6.
The mass of plants measured three times during the vegetation period of the second experiment (in g).
Table 6.
The mass of plants measured three times during the vegetation period of the second experiment (in g).
| Yield Comp. | Mass (g) | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 2 May 2024 | 2nd Metric 9 May 2024 | 3rd Metric 16 May 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 56.82 Ab | 65.42 Aa | 56.34 Ab | 102.17 A | 104.5 A | 100.24 A | 196.82 Aa | 211.43 Aa | 149.73 Ab |
| BS | 48.38 B | 41.46 B | 47.74 B | 80.69 BCb | 92.33 Ba | 87.53 Bab | 145.95 Bb | 168.55 Ca | 141.24 Ab |
| BO | 43.40 B | 47.43 B | 44.46 B | 88.09 Ba | 92.01 Ba | 78.52 Cb | 137.73 Bb | 190.18 Ba | 142.47 Ab |
| C | 40.86 Bb | 51.59 Ba | 42.33 Bb | 74.10 Cab | 79.89 Ca | 70.54 CbB | 143.64 Ba | 149.81 Da | 127.15 Bb |
| FF | * (p < 0.05, F = 8.49) | * (p < 0.05, F = 8.56) | * (p < 0.05, F = 43.99) | ||||||
| FBS | * (p < 0.05, F = 21.58) | * (p < 0.05, F = 47.58) | * (p < 0.05, F = 26.47) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 0.66) | * (p < 0.05, F = 1.68) | n.s. (p < 0.05, F = 7.31) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 7.
The number of leaves of plants measured three times during the vegetation period of the second experiment.
Table 7.
The number of leaves of plants measured three times during the vegetation period of the second experiment.
| Yield Comp. | Number of Leaves | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 2 May 2024 | 2nd Metric 9 May 2024 | 3rd Metric 16 May 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 12.67 A | 12.33 | 13.33 A | 19.00 Aa | 16.00 b | 15.67 b | 28.00 Aa | 29.00 Aa | 25.33 Ab |
| BS | 11.00 B | 12.00 | 11.67 B | 17.00 ABa | 16.33 ab | 14.33 b | 26.33 B | 26.00 AB | 25.67 A |
| BO | 12.33 AB | 11.00 | 10.67 B | 17.00 AB | 16.33 | 16.33 | 26.33 Aa | 26.00 Ba | 17.33 Bb |
| C | 11.00 B | 11.33 | 11.00 B | 16.00 B | 16.00 | 16.33 | 24.00 Bb | 26.33 Ba | 17.00 Bc |
| FF | * (p < 0.05, F = 0.03) | * (p < 0.05, F = 5.24) | * (p < 0.05, F = 62.21) | ||||||
| FBS | * (p < 0.05, F = 5.28) | * (p < 0.05, F = 1.20) | * (p < 0.05, F = 21.63) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 1.40) | * (p < 0.05, F = 1.91) | n.s. (p < 0.05, F = 13.04) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 8.
The dry matter of plants measured three times during the vegetation period of the second experiment (in g).
Table 8.
The dry matter of plants measured three times during the vegetation period of the second experiment (in g).
| Dry Matter (g) | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Date | 1st Metric 2 May 2024 | 2nd Metric 9 May 2024 | 3rd Metric 16 May 2024 | ||||||
| Biostimulant | Fertilization | Fertilization | Fertilization | ||||||
| S | P | B | S | P | B | S | P | B | |
| BC | 3.75 Ab | 4.29 Aa | 3.7 Ab | 7.24 A | 7.42 A | 7.11 A | 8.6 Ab | 9.48 Aa | 6.71 Ac |
| BS | 3.18 B | 3.03 B | 3.14 B | 5.72 BCb | 6.55 Ba | 6.21 Bb | 6.55 Bb | 7.56 Ca | 6.33 Ab |
| BO | 2.88 B | 3.11 B | 3.07 B | 6.25 Ba | 6.53 Ba | 5.57 Cb | 6.08 Bb | 8.53 Ba | 5.25 Bc |
| C | 2.68 Bb | 3.39 Ba | 2.78 Bb | 5.26 Cab | 5.67 Ca | 5 Cb | 6.44 B | 6.72 D | 6.39 A |
| FF | * (p < 0.05, F = 3.82) | * (p < 0.05, F = 8.61) | * (p < 0.05, F = 49.34) | ||||||
| FBS | * (p < 0.05, F = 17.58) | * (p < 0.05, F = 47.48) | * (p < 0.05, F = 26.93) | ||||||
| Interaction | |||||||||
| FF-FBS | n.s. (p < 0.05, F = 1.41) | n.s. (p < 0.05, F = 1.68) | * (p < 0.05, F = 7.58) | ||||||
FF—T test fertilization; FBS—F test biostimulants; *—significance; n.s.—no statistical significance. Means within a row followed by different lowercase letters differ significantly at p < 0.05; means within a column followed by different uppercase letters differ significantly at p < 0.05. BC—biostimulant Čudomix; BS—biostimulant Slavol; BO—biostimulant Organic; manure S—Stallatico pellettato; manure P—Plantella organic; manure B—Biopon; C—control.
Table 9.
Mean content of total phenols, phenolic acids, antioxidant properties, flavonoids, and proline in dry lettuce samples. Analyte content values are given as mean values ± STDEV of six biological replicates.
Table 9.
Mean content of total phenols, phenolic acids, antioxidant properties, flavonoids, and proline in dry lettuce samples. Analyte content values are given as mean values ± STDEV of six biological replicates.
| Phenols mg GAE/g f.w | Phenolic Acids mg CAE/g f.w. | Antioxidant Activity µmol TE/g f.w. | Flavonoids mg CE/g f.w. | Prolines µmol Proline/g f.w. | |
|---|---|---|---|---|---|
| Mean Value ± STDEV | Mean Value ± STDEV | Mean Value ± STDEV | Mean Value ± STDEV | Mean Value ± STDEV | |
| C | 1.977 ± 0.081 RSD 4.1% | 1.922 ± 0.047 RSD 2.42% | 0.962 ± 0.020 RSD 2.1% | 10.855 ± 0.192 RSD 1.8% | 0.761 ± 0.000 RSD 0.00% |
| CS | 2.558 ± 0.075 RSD 2.9% | 2.419 ± 0.051 RSD 2.1% | 0.731 ± 0.008 RSD 1.0% | 14.092 ± 0.590 RSD 4.2% | 1.005 ± 0.096 RSD 9.5% |
| CB | 2.246 ± 0.163 RSD 7.3% | 2.229 ± 0.033 RSD 1.5% | 0.706 ± 0.003 RSD 0.4% | 12.687 ± 0.244 RSD 1.9% | 0.071 ± 0.005 RSD 6.3% |
| CP | 1.992 ± 0.088 RSD 4.4% | 1.972 ± 0.014 RSD 0.7% | 0.553 ± 0.028 RSD 5.0% | 10.936 ± 0.256 RSD 2.3% | 0.858 ± 0.030 RSD 3.5% |
| SS | 2.395 ± 0.034 RSD 1.4% | 2.304 ± 0.074 RSD 0.032 | 0.778 ± 0.008 RSD 1.0% | 12.922 ± 0.500 RSD 3.9% | 0.100 ± 0.042 RSD ** 42.3% |
| SO | 1.406 ± 0.129 RSD 9.2% | 1.373 ± 0.023 RSD 1.7% | 0.901 ± 0.010 RSD 1.1% | 7.980 ± 0.026 RSD 0.3% | 0.220 ± 0.005 RSD 2.5% |
| SC | 2.558 ± 0.129 RSD 5.0% | 2.541 ± 0.047 RSD 1.8% | 0.696 ± 0.008 RSD 1.1% | 13.494 ± 0.000 RSD 0.0% | 0.119 ± 0.066 RSD ** 55.7% |
| BS | 2.025 ± 0.068 RSD 3.4% | 1.919 ± 0.051 RSD 2.7% | 0.692 ± 0.023 RSD 3.3% | 10.882 ± 0.410 RSD 3.8% | 0.131 ± 0.006 RSD 4.5% |
| BO | 1.905 ± 0.007 RSD 0.4% | 1.761 ± 0.005 RSD 0.3% | 0.722 ± 0.040 RSD 5.6% | 10.401 ± 0.346 RSD 3.3% | 0.655 ± 0.090 RSD 13.7% |
| BC | 1.876 ± 0.020 RSD 1.1% | 1.896 ± 0.037 RSD 2.0% | 0.896 ± 0.003 RSD 0.3% | 11.063 ± 0.308 RSD 2.8% | 1.325 ± 0.037 RSD 2.8% |
| PS | 1.904 ± 0.066 RSD 3.4% | 1.841 ± 0.147 RSD 8.0% | 0.343 ± 0.013 RSD 3.9% | 10.400 ± 0.383 RSD 3.7% | 1.088 ± 0.079 RSD 7.2% |
| PO | 1.776 ± 0.054 RSD 3.1% | 1.580 ± 0.028 RSD 1.8% | 1.003 ± 0.033 RSD 3.3% | 9.322 ± 0.385 RSD 4.1% | 2.447 ± 0.193 RSD 7.9% |
| PC | 1.771 ± 0.102 RSD 5.7% | 1.643 ± 0.014 RSD 0.9% | 1.236 ± 0.013 RSD 1.0% | 9.603 ± 0.064 RSD 0.7% | 1.309 ± 0.028 RSD 2.2% |
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Fajdetić, N.R.; Božić Ostojić, L.; Benković, R.; Zima, D.; Blažinkov, M.; Mirosavljević, K.; Popović, B.; Benković-Lačić, T. Effects of Three Organic Fertilizers and Biostimulants on the Morphological Traits and Secondary Metabolite Content of Lettuce. Horticulturae 2025, 11, 1288. https://doi.org/10.3390/horticulturae11111288
AMA Style
Fajdetić NR, Božić Ostojić L, Benković R, Zima D, Blažinkov M, Mirosavljević K, Popović B, Benković-Lačić T. Effects of Three Organic Fertilizers and Biostimulants on the Morphological Traits and Secondary Metabolite Content of Lettuce. Horticulturae. 2025; 11(11):1288. https://doi.org/10.3390/horticulturae11111288
Chicago/Turabian StyleFajdetić, Nataša Romanjek, Ljiljana Božić Ostojić, Robert Benković, Dinko Zima, Mihaela Blažinkov, Krunoslav Mirosavljević, Brigita Popović, and Teuta Benković-Lačić. 2025. "Effects of Three Organic Fertilizers and Biostimulants on the Morphological Traits and Secondary Metabolite Content of Lettuce" Horticulturae 11, no. 11: 1288. https://doi.org/10.3390/horticulturae11111288
APA StyleFajdetić, N. R., Božić Ostojić, L., Benković, R., Zima, D., Blažinkov, M., Mirosavljević, K., Popović, B., & Benković-Lačić, T. (2025). Effects of Three Organic Fertilizers and Biostimulants on the Morphological Traits and Secondary Metabolite Content of Lettuce. Horticulturae, 11(11), 1288. https://doi.org/10.3390/horticulturae11111288
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