Introduction

Today, one of the most urgent global issues is the worldwide degradation of soils. The main reason of this negative tendency on soil conditions is the application of improper agricultural practices. Over-tillage, as well as intensive use of synthetic fertilizers and pesticides results in losses of natural soil functions essential for agricultural production and for the balance of the whole agroecosystem (Bai et al. 2018; Liu et al. 2023; Nkonya et al. 2016). Several studies provide data of the strong correlation between soil quality, fertility, and the qualitative parameters of crops, i.e., dry matter, vitamin C, and essential mineral contents, such as calcium, magnesium, iron, and chromium (Adesemoye et al. 2009; Barański et al. 2014; Heaton 2001; Ye et al. 2020). These parameters define the products’ value for human nutrition (Divéky-Ertsey et al. 2012). Tomato contains important antioxidants, e.g., carotenoids (lycopene, ß-carotene), polyphenols, and vitamin C, and it is widely consumed all over the World (Elbadrawy & Sello 2016; Helyes 2000; Sipos et al. 2017). Lycopene, a strong antoxidant compound, is suggested to contribute to the prevention of certain cancer types, and the age-related diseases of cells and tissues with a direct positive impact on human health and well-being (Caseiro et al 2020, Laayouni et al. 2023). Among polyphenolic compounds, flavonoids and hydroxycinnamic acids are abundant in tomato, their intake is suggested to interfere with the suppression of cancer development in human body (Martí et al 2015). Tomato is a good source of vitamin C, which has DNA and lipid protecting properties in human cells, thus contributing to the anti-cancer function of the other antioxidants in tomato (Mellidou et al 2021). Compounds with radical scavenging ability are known to have a significant role in human health and in preventing the formation of certain cancer types (Nasir et al. 2015; Woodside et al. 1999). Research has shown that products from organic farming have generally better nutritional quality and contain higher levels of antioxidants, especially polyphenols, compared with those from conventional farming systems (Aldrich et al. 2010; Barański et al. 2014; Dudás et al. 2017a, b).

Methods for increasing soil organic matter content and restoring soil ecology to obtain professional crop production need more research and attention. However, experiments on microbial inoculums and their effectiveness have been ongoing for a long time. The use of microbial industrial products, including living microorganisms, is continuously increasing in agriculture and horticulture. The technology might offer an attractive way to replace chemical fertilizers, pesticides, and other xenobiotic supplements (Dudás et al. 2017a, b; Maheshwari et al. 2013). Beneficial bacteria and fungi can colonize plant roots and enhance plant growth by a wide variety of mechanisms (Biró et al. 2000). The use of microbial industrial products, including living microorganisms, is continuously increasing in agri- and horticulture. Several beneficial microorganisms, colonized around the plant root system, can promote plant growth and development through direct and indirect mechanisms. Many studies report, that these can improve the yield and quality parameters of agricultural crops (Warwate et al. 2017; Mirzaei et al. 2020; Sánchez et al. 2022; Gashash et al. 2022; Nkebiwe et al. 2024). Microorganisms increase the solubility and the mobility of nutrients to make them available for plants and support the efficiency of nutrition uptake by producing plant growth-regulating materials (Khan et al. 2009; Richardson & Simpson 2011). Beneficial microorganisms in the rhizosphere can occupy the potential niche of pathogens or can kill them directly by producing secondary biocide metabolic compounds (Sarma et al. 2015).

Additionally, they can improve the stress tolerance of the plant (Biró et al. 2000; Yang et al. 2009). The enhancement of sensory characteristics, i.e., better sugar-acid ratio and better taste by applying bioeffector inoculums was also confirmed by Dudás et al. (2017a, b). There are many studies which prove the efficacy of some inoculums on tomato fruit quality (Loganathan et al. 2014; Ordookhani et al. 2010; Gashash et al 2022; Iacomino et al. 2022; Lee et al. 2022). Most of these studies reported that microbes also have positive effect on bioactive compounds and total antioxidant capacity (Katsenios et al. 2021; Iacomino et al. 2022; Lee et al. 2022; Issifu et al. 2023; Mahajan et al. 2023). The effectiveness of the microbial inoculants highly depends on certain factors in the soil–plant-climate multifactorial systems. The influence of native indigenous microorganisms and abiotic stress factors are the most known effects. In some cases, microbial inoculums—i.e., the biofertilizer applications—do not perform as expected, and the reasons of these disorders remain rather unclear (Nugroho et al. 2023; Pabar et al. 2020). Some recent research results showed that the addition of micronutrients parallel with microbial soil inoculums can increase the positive effect of the treatments (Bradáčová et al. 2016). Studies also reported that microbial inoculants containing a combination of microbial strains can increase plant growth more effectively than single-strain inoculants (Sarma et al. 2015; Iacomino et al. 2022; Gashash et al 2022).

In this research, single inoculation containing Trichoderma harzianum, Pseudomonas sp., and Bacillus amyloliquefaciens strains was applied. The combined treatment consisted of biotic Trichoderma harzianum, Pseudomonas fluorescens, and Bacillus subtilis strains with abiotic zinc micronutrients (Zn) and manganese (Mn). Trichoderma harzianum is primarily known as a biocontrol agent against pathogens but also concerned with improving plant growth parameters and the uptake of nutrients (Ghisalberti and Rowland 1993; Yedidia et al. 2001; Sharma et al. 2012). Trichoderma also performed well at improving quality of crops as well as of tomato (Nzanza et al. 2012). Recent studies have reported that the lycopene content of tomato has significantly increased by applying Trichoderma inoculum (Carillo et al. 2020). Loganathan et al. (2014) examined Bacillus subtilis and Bacillus amyloliquefaciens and found that both strains had a positive effect on lycopene. A recent study also found that both of the Bacillus strains increased the yield and some quality parameters of tomato (Gashash et al 2022). Moreover, they worked the best in combination with each other.

Pseudomonas strains showed promising results as plant growth promoters (Sah et al. 2021). According to Ordookhani et al. (2010), Pseudomonas increased the lycopene of tomato. In the study of Issifu et al. (2023), four Pseudomonas strains increased bioactive compounds, primarily tannins, carotenoids, lycopene, and total phenols in tomato fruit. TPC was significantly higher in the inoculated fruits, Contrary the microbes did not increase the antioxidant capacity measured by DPPH assay.

There are many studies about the effect of microbial inoculums on the growth and yield of the plant, and less studies about the quality parameters of the tomato fruit. The quality analysis is mainly examined by sugar-acid ratio and lycopene and the total antioxidant capacity is less studied. The aim of this study is providing a comprehensive research of lycopene content and total antioxidant capacity of microbially treated tomato with single and combined inoculations in organic agriculture conditions. Three analytical assessments (FRAP, TPC, and DPPH) were used to provide a more complete result about the total antioxidant capacity of the treated tomato fruits.

Materials and Methods

Experimental Site and Bioeffective Inoculations

The experiment was set at the Organic Farming Experimental Research Site of Hungarian University of Agriculture and Life Sciences, Soroksár (47° 23′ 34.6″ N 19° 08′ 53.7″ E), on a certified organic field in two consecutive years, in 2016 and 2017. The most important soil parameters of the experimental area are shown in Table 1.

Table 1 Main characteristics of soil at Soroksár site
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The weather parameters of the two experimental years are shown in Fig. 1.

Fig. 1
figure 1

Average temperature and precipitation of experimental years (2016–2017) in the ripening period of tomato fruits, Soroksár, Hungary

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For the open field trial, Solanum lycopersicum L. ‘Mobil’ (determinate growing type) variety was used, treated by single bioeffector (BE) and combined bioeffector, called as Combifector (CF) soil inoculums (Table 2) in 4 repetitions. The applied inoculants were selected by an international consortium of researchers and provided by the project partners, based on previous scientific results. Pre-tests were conducted jointly within the project consortium, and therefore, no further analysis, including compatibility investigations, was done before application within the present experiment.

Table 2 Components of microbial inoculants and details of application
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Microbial inoculants were used twice during the treatments. The first application was done at sowing. When the seedlings were planted, the second treatment was applied with the irrigation water, early in the morning so that to avoid the damage of inoculants by UV radiation. The exact composition of each inoculant, as well as the exact doses of the two applications, is found in Table 2.

The experimental plots were set in random layout with four replications. Each plot contained 15–15 tomato plants, in 70 × 50 cm spacing arrangement. Woven plastic fabric was applied to cover the soil under the drip irrigated plants.

Tomato Fruit Quality Analysis

The fruit samples of tomato were collected both years during the main fruit producing period in August, parallel in the same time from each treatment. From every plot, 1 kg of tomato fruit was collected and an average sample was made for every treatment.

After washing and removing of stems, the fruits were chopped and homogenized without dilution by a laboratory homogenizer at high speed for 2 min. After the samples were stored at − 23 °C until analysis. The determination of lycopene content was carried out directly from the homogenates, while antioxidant capacity was determined using the supernatant that was collected from homogenates after centrifugation at 2000×g.

To determine lycopene content of the samples, the method of Fish et al (2002) was used. Three analytical assessments based on spectrophotometric measurements were applied parallel for antioxidant capacity. The FRAP (ferric reducing antioxidant power) method was used according to Benzie and Strain (1996), and results are expressed in mg/100 g ascorbic acid equivalent (AAE) dimension. TPC (total phenolic content) method was done by the methodology of Singleton and Rossi (1965), and results are expressed in mg/100 g gallic acid equivalent (GAE) dimension. DPPH (2,2-diphenyl-1-picryl-hydrazyl-hydrate) radical scavenging activity was measured by the methodology of Molyneux (2003), using mg/100 g AAE dimension.

Analysis of Data

Data were analyzed with IBM SPSS Statistics ver. 25, where Multivariate analysis of variance (MANOVA) was applied and was evaluated by Wilk’s Lambda test. In the case of significance, single factor variance analysis (ANOVA) was applied with Tukey or Games–Howell post hoc test, depending on the homogeneity of variance checked by Levene-test. The significance level was 95% (p < 0.05).

Principal Component Analysis

Principal component analysis (PCA) was run to reduce the data set’s dimensionality and map the correlations among the variables. PCA was run after standardization and centering and Bartlett’s sphericity test (p < 0.05) was used to check the correlation matrix, while Kaiser–Meier–Olkin measure of sample adequacy (KMO = 0.652) was also calculated. Optimal number of principal components was determined using the scree plot. PCA was run using XL-Stat (ver. 2019.4.2.64226) (Addinsoft 2019).

Cluster Analysis

Agglomerative hierarchical clustering (AHC) was used to group the tomatoes based on the PCA scores. Different distance metrics and agglomerative schedules were tested using Silhouette clustering index which resulted Euclidean distance and Ward’s method as the best performing combination. AHC was run using XL-Stat (ver. 2019.4.2.64226) (Addinsoft 2019).

Sum of Ranking Differences

Sum of ranking differences (SRD) is a multicriteria decision supporting tool with a wide range of possible applications (Gere et al. 2021). The major strength of SRD is that it solves problems when the task is to rank multiple cases according to multiple variables. The final result of SRD is always a rank, which clearly shows the order in which the cases follow each other.

SRD was introduced by Héberger (2010), while its first validation approach was published by Héberger and Kollár-Hunek (2011), followed by the publication solving the problem of repeated measurements (ties) in the data set (Kollár-Hunek & Héberger 2013). Recent developments include the robust validation of SRD results using analysis of variance (Héberger & Kollár-Hunek 2019).

To sum up the logic behind SRD, we should define four main steps:

  1. 1.

    A reference variable (golden standard) should be defined, which could be either the mean, median, minimum, or maximum values of the input data set. An additional option (so-called read) is also available when the reference variable is not computed from the input data set but provided by other measurements.

  2. 2.

    After the rank transformation of all variables, ranks of the input variables are compared to the reference variable column-wise and their absolute rank differences are calculated.

  3. 3.

    By summing up these absolute rank differences, the sum of ranking difference (SRD) values is obtained.

  4. 4.

    The final move includes the cross-validation, which assigns uncertainties to the SRD values. SRD values are then normalized between 0 and 100 for easy comparability between various datasets.

Results

Lycopene Content in Tomato Fruits by Bioeffective Treatments

The microbial inoculum treatment had significant effect on the lycopene content of tomato fruit. In both years, the Combifector treatment had a significantly higher value of lycopene content than the control (Table 3). In 2016, it meant 15.7% more lycopene, while in 2017 it showed 165% higher lycopene content compared to C. In 2016, BE1 and BE2 treatment resulted slightly higher lycopene content, while BE3 resulted lower lycopene content than the control, but these differences were not significant. In 2017, all the treatment had significantly higher lycopene content than the control; BE1, BE2, and BE3 resulted 60, 97.6, and 132% higher lycopene levels, respectively, in tomato fruit.

Table 3 Lycopene content and antioxidant capacity of tomato samples following to single and combined microbiological treatments in 2 years (2016–2017), mean ± s.d
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Antioxidant Capacity of Tomato Fruits by Bioeffective Treatments

Significant differences were found between treatments regarding antioxidant capacity, but it was inconsistent in the two consecutive years according to antioxidant assays (Table 3). The efficacy of soil inoculants on antioxidant capacity was rather low in both years. BE1 treatment performed well according to all assays in 2017 (FRAP: + 4.59; TPC: + 1.96; DPPH: + 1.2), but in 2016 it was one of the least successful treatments (FRAP: − 11.2; TPC − 0.8%; DPPH: − 13%). Contrary, BE3 had greater values in average according to TPC (+ 5.7%) and DPPH (+ 2.8%) in 2016 and had only lower values compared to the control in 2017 (FRAP: − 1%; TPC: − 12.6%; DPPH: − 5.1%). BE2 treatment performed poorly in antioxidant capacity in both years. CF treatments had higher antioxidant values in 2016 according to TPC method (+ 9.7%) compared to the control. However, according to the other methods, lower values were measured than the control, which was a significant difference in the case of FRAP method (− 19.1%). In 2017, CF showed higher antioxidant status according to FRAP method (+ 7.5%) and lower according to TPC method (− 7.6%) when compared to the control.

Principal Component Analysis of the Annual Treatment Variability

Principal component analysis was run as a pattern recognition method to uncover the underlying relationships among the variables and the samples (Fig. 2). The first two principal components explained 53.48% of the total variance (PC1: 30.48%, PC2: 23.0%). The PCA BiPlot shows that between sample differences are explained by PC1, while PC2 is responsible for within sample differences. Main contributors to PC1 are lycopene and FRAP values (from both years) with a squared cosine around 0.5. PC2 was defined mainly by TPC17 having a strong 0.854 squared cosine value. It is interesting to see, however, that the variables show a high time-dependence, for example the vectors of FRAP16 and FRAP17 show a completely different direction. Additionally, DPPH and FRAP results show positive correlation in both years.

Fig. 2
figure 2

Biplot of principal components analysis along with the first and second principal components. Cumulative explained variance is 53.48%. Numbers after the loading vector names denote the year of measurement. (CF—Combifector Trichoderma harzianum OMG16, Pseudomonas fluorescens, Bacillus subtilis + Zn, Mn, BE1—single bioeffector contains Trichoderma harzianum T22 strain, BE2—single bioeffector contains Pseudomonas sp. strain, BE3—bioeffector contains Bacillus amyloliquefaciens strain, C-control)

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As the explained variance of the first two PCs is rather low, the relationship between the treatments was evaluated using agglomerative hierarchical cluster analysis, where the PCA scores of all PCs were used as input variables and samples were clustered based on the similarities and differences of their score values. The obtained dendrogram shows a clear clustering of CF, BE2, and BE3 treatments, but BE1 treatment showed no difference compared to the control treatments (Fig. 3).

Fig. 3
figure 3

Dendrogram obtained from an agglomerative hierarchical clustering using Euclidean distance and Ward’s method. Optimal cluster number (5) was determined by Silhouette index. (CF—Combifector Trichoderma harzianum OMG16, Pseudomonas fluorescens, Bacillus subtilis + Zn, Mn, BE1—single bioeffector contains Trichoderma harzianum T22 strain, BE2—single bioeffector contains Pseudomonas sp. strain, BE3—bioeffector contains Bacillus amyloliquefaciens strain, C-control)

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Multicriteria Optimization

Sum of ranking differences method shows a clear ranking among the treatments (Fig. 4). The maximum values were used as a reference column, meaning that the treatment closest to the zero SRD point contained the highest amounts of the measured nutraceutical properties. Figure 3 shows us that CF was placed on the lowest SRD value, meaning that it was the closest to the reference column. It was followed by BE2 and BE3 which cannot be discriminated, they are tied on the second rank. These treatments were followed by BE1, and on the last rank, the control sample is located, meaning that the control sample was the most different to the reference column. As all of the samples are located on the left side of the dashed XX1 range, therefore, we can conclude that these rankings are significant and not random.

Fig. 4
figure 4

The SRD values (scaled between 0 and 100) of nutraceutical properties of organically grown tomato by sum of ranking differences. The maximum value was used as reference (benchmark) column. Scaled SRD values are plotted on x axis and left y axis, right y axis shows the relative frequencies of random ranking distribution function: black curve). The probability ranges are also given 5% (XX1), Median (Med), and 95% (XX19). (CF—Combifector Trichoderma harzianum OMG16, Pseudomonas fluorescens, Bacillus subtilis + Zn, Mn, BE1—single bioeffector contains Trichoderma harzianum T22 strain, BE2—single bioeffector contains Pseudomonas sp. strain, BE3—bioeffector contains Bacillus amyloliquefaciens strain, C-control) (Color figure online)

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Discussion

According to the results of MANOVA, a general conclusion of the nutraceutical properties according to the inoculums cannot be drawn, as the results show different trends in the two consecutive years. However, when lycopene results are evaluated separately, it seems that the combined inoculants containing the biocontrol agent Trichoderma harzianum, Pseudomonas fluorescens, and the P-mobilizing, sporeforming Bacillus subtilis as well as micronutrients (Zn and Mn) have higher positive effect on the lycopene content of tomato fruits in comparison with single inoculation of Pseudomonas sp., Bacillus amyloliquefaciens, or Trichoderma harzianum strains. Certain studies suggest that combined inoculants can be more effective due to the combined mechanism of microorganism (Sarma et al. 2015; Kumar et al. 2016; Warwate et al. 2017) The tendency that the combined inoculants had a more positive effect on lycopene compared to the single strains is in accordance with previous scientific results (Biró et al. 2000; Ordookhani et al. 2010).

The reason for the antioxidant capacity had inconsistent result according to MANOVA in the two consecutive years and antioxidant assays could be that the synthesis of antioxidants is highly weather- and climate-dependent and that the different soil inoculums can behave differently in various environmental conditions. In 2016, August was cool and wet (mean temp.: 19.4 °C); in 2017, it was warmer and drier (mean temp.: 21.6 °C). Antioxidant synthesis is differently influenced by abiotic stress factors. Some compounds will increase with warmer temperature, while others are blocked above a certain high temperature value (Brandt 2007). Lycopene synthesis is gradually reduced, while ß-carotene and polyphenol synthesis is increased with the temperature rise (Duma et al. 2015; Siddiqui et al. 2015). Flavonoids and vitamin C are affected mainly by solar radiation changes and show positive correlation with increasing sunlight (Ilahy et al. 2011). In each year, antioxidant assays show a different ranking of the total antioxidant capacity, which supports the statement that applying only one assay is not sufficient for analysis and for making proper decisions about its nutritive value. In order to exclude the selectiveness of the applied antioxidant assessment methods, parallel application of at least three or more methodology is advisable (Csambalik et al. 2014; Prior & Cao 1999). The antioxidant assays do not have selective measurement capability; compounds react differently with the different and variable free radicals (Huang et al. 2005; Prior & Cao 1999). DPPH radical scavenging activity can measure mainly the lipophilic antioxidants like carotenoids and vitamin-E. FRAP method is known to be unable of detecting, for example, the thiols and the proteins (Karadag et al. 2009). Regardless to its name, TPC detects different compounds with antioxidant effects, besides the phenolic compounds (Singleton & Rossi 1965). This tendency appeared also in the work of Issifu et al. (2023), where the antioxidant capacity increased significantly in microbially inoculated tomato fruit according to the TPC assay; however, it did not show increase according to DPPH assay. In the work of Katsenios et al. (2021), however, its reverse was observed: some Bacillus strains had significant effect on DPPH, but they had no effect on TPC of the tomato fruit.

As nutritional data show some seasonal variation, weather condition can be also defining in the behavior of the applied microbial strains. This can be seen at the different results of BE1 and BE3 in the 2 years. That could mean that the impact of certain microbe strains on antioxidant compounds is environment-dependent. Trichoderma harzianum inoculum may work effectively in warmer conditions like it was in 2017, but Bacillus amyloliquefaciens may perform better in cooler and wet conditions, like in 2016.

As results showed in the case of antioxidant capacity the Combifector (CF) treatment proved oneself to be less environment-dependent; or, with other words, the risk of negative environmental influence of soil inoculums might be reduced by using multiple strains and other necessary plant-nutrients within one industrial biofertilizer product.

Regarding the principal component analysis, the separation of the 2 year’s dataset also demonstrates the seasonal effect on the measured parameters. It can be seen mostly in the case of FRAP method where vectors of FRAP16 and FRAP17 show a completely different direction, and therefore, their correlation is rather weak. The analysis suggests that the dataset of 2016 shows a more supportive effect on antioxidant capacity than in 2017. In contrast, the conditions of the second year were more favorable for lycopene than those of the first year (Mpanga 2020).

Sum of ranking difference (SRD) ranks the microbial soil inoculations based on their nutraceutical properties measured throughout 2 years. CF was ranked on the lowest SRD value, meaning that it was the most similar to the reference column (e.g., the maximum values of the measured nutraceutical properties). This phenomenon is confirmed by Sarma et al. (2015), who found that the more microbe strains in the inoculants present, the higher the antioxidant capacity is. Additionally, abiotic elements could contribute to a better functioning of microorganism. In some other studies, this combination of microbial strains and stress-protective microelements is performed well in the increasing plant growth and P accumulation in the shoots (Mpanga 2020). Contrary to our results, Loganathan et al. (2014) found that the bacteria Bacillus subtilis resulted in higher lycopene content in tomato alone, than Bacillus amyloliquefaciens inoculation. In other studies, separately, all the three strains of bacteria showed positive effect on antioxidant compounds in tomato fruit (Gashash et al. 2022; Carillo et al. 2020; Issifu et al. 2023). However, the combination of microbes performed well in this study. In SRD, CF treatment was followed by BE2 and BE3 which cannot be discriminated, as they are tied on the second rank. There are other studies also, where Pseudomonas sp. and Bacillus amyloliquefaciens (BE2, BE3) had a positive effect on antioxidant capacity (Gashash et al 2022; Ordookhani et al. 2010). However, in the study of Bona et al. (2017), antioxidant compounds did not change following to plant inoculation with Pseudomonas sp. Regarding Bacillus amyloliquefaciens, it caused significantly higher lycopene content in tomato fruit compared to a non-inoculated plant according to Loganathan et al. (2014) and Gashash et al. (2022). In SRD ranking, the last treatment was BE1 followed by the control, which means that Trichoderma harzianum had the lowest impact on the antioxidant capacity of tomato in our study. The dendrogram (Fig. 3) showed that BE1 treatments showed no difference compared to the control treatments. However, in other studies, Trichoderma harzianum increased the lycopene level of tomato (Nzanza et al. 2012; Carillo et al. 2020).

This study reports no effect of treatments on tomato’s antioxidant activity, total flavonoids, or vitamin C content. According to Mona et al. (2017), an obvious increase in phenolic and flavonoid content was observed in the fruit of tomato inoculated by Trichoderma harzianum. In another study, results clearly showed that fruits of Trichoderma-treated plants had higher mineral content and antioxidant activity than the pathogen-inoculated control (Singh et al. 2013).

Conclusion

Based on the results of the assessments at the two consecutive years, it can be summarized, that Combifector—containing three microbial strains and abiotic elements—treatment had a significantly positive effect on the measured lycopene content, which is known as the most important antioxidant compound of tomato. SRD results ranked Combifector on the first rank. This shows that for the nutritional enhancement of microbial inoculant effectiveness on lycopene, the inclusion of more than one microbial strain is recommended in the soil–plant-systems. Inclusion of multiple strains induces fruit quality promoting mechanisms; utilization of the synergistic interaction can multiply their potential efficiency. According to the bioeffective way of thinking, the combination of both biotic (microbial inoculums) and abiotic (macro- and micronutrient elements) environmental factors is the right way of applications. The combined treatment was less environment-dependent, which is a very valuable perspective for any future product containing microbial inoculants. It can also be concluded, that despite the antioxidant capacity showed various results according to the three measuring methods, abiotic factors possibly had an impact on the antioxidant capacity. The different strains can behave according to the environmental effects, although SRD results show that all the microbial inoculums have positive effect on antioxidant capacity compared to the control. According to this study, the utilization of microbial inoculums and the discussed strains are recommended to use not only because of the quantity of the tomato fruit which is a more common direction of use of these inoculums, but also because of its effect on the nutraceutical properties of tomato fruit.