The impact of spring wheat species and sowing density on soil biochemical properties, content of secondary plant metabolites and the presence of Oulema ssp.

Site description and crop management

Field tests and soil, plant and entomological sampling were carried out in 2018–2020, at the beginning of June in the flag leaf stage of spring wheat (BBCH 39). The research was conducted on spring wheat grown in OPS and CPS. The experimental factors were: factor Ix—spring wheat species (Fig. 1); Indian dwarf wheat (Triticum sphaerococcum Percival) and Persian wheat (Triticum persicum Vavilov); factor II—sowing density 400, 500, 600 (seeds m). The experiments were performed in a split-plot arrangement in four replicates. The single plot size of 21 m². Triticum sphaerococcum Percival cv. Trispa and Triticum persicum Vavilov cv. Persa used in our field experiments are the cultivars, which has been bred by the Bydgoszcz University of Science and Technology in 2020. The Breeder’s Right, granted by the director of Research Centre for Cultivar Testing, is exercisable on the territory of Poland at the national Plant Breeders’ Rights protection level. Details on soil characteristics prior to the experiments can be found in Lemanowicz et al. (2020a) and Lemanowicz et al. (2020b). The forecrops for the tested species of OPS and CPS cultivated spring wheats were cereals (triticale or winter wheat). Immediately after harvesting the forecrop, an intercrop of peas of the tendril-leaved variety ‘Tarchalska’ were sown at a rate of 240 kg ha¹. Pre-winter ploughing was carried out to a depth of 0.22–0.23 m. Sowing parameters, as well as methods of fertilization and plant protection against weeds, diseases and pests were provided by Lemanowicz et al. (2020a) and Lemanowicz et al. (2020b).

Soil analysis

Air-dried disturbed soil samples were sieved through a ø2-mm mesh and the selected physicochemical properties in soil were determined as follows: the content of clay fraction composition by laser diffraction method using a Masterssizer MS 2000 analyser (Malvern Panalytical, Worchestershire, UK); the soil pH in CaCl₂ (0.01 M) was measured potentiometrically (PN-ISO, 1997); organic carbon (OC) was measured using a Skalar TOC Primacs analyser (Skalar, The Netherlands). Fresh soils enzymatic activities were determined on soil samples that had been stored at 4 °C for no more than two weeks. The activity of three redoxidoreductase enzymes was determined. The activity of DEH (E.C.1.1.1) and CAT (E.C.1.11.1.6) in soil was determined by methods described by Bartkowiak, Breza-Boruta & Lemanowicz (2016). Analyses of (PER) activity (EC 1.11.1.7) were carried out using the Bartha and Bordeleau method (Bartha & Bordeleau, 1969) by measuring the amount of purpurogallin (PPG) formed as a result of the oxidation of pyrogallol in the presence of H₂O₂. The absorbance of the solution was measured colorimetrically at λ = 460 nm using a spectrophotometer.

Based on the enzymatic activities of the samples, the geometric mean of enzyme activities (GMea) was calculated using a method (Hinojosa et al., 2004) as follows: (1)${\displaystyle GMea=\sqrt[3]{\left(CAT\ast DEH\ast PER\right)}}$

where: CAT, DEH, PER are referred to catalase, dehydrogenase and peroxidase respectively.

Plant analysis

Fifty generative tillers were randomly collected from each plot and used for analysis.

Samples preparation

Plant samples were collected for laboratory analyses in individual experimental plots. Five consecutive stalks (which were cut with a sharp knife above the soil) were taken completely randomly in five places. The samples were put in a plastic bag, labelled immediately upon arrival from the field. The tillers were incubated in the laboratory storage at 5 °C and 90% RH. After 3 days the samples were cut and well mixed. A representative from each sample was frozen and stored at least at −20 °C in a freezer (Whirpool AFG 6402 E-B, Benton Harbor, MI, USA). For laboratory analyses the frozen material was freeze-dried (Alpha model 1–4 LSC, Martin Christ, Osterode, Germany). The materials were lyophilized to permanent weight with a moisture content <2%. Dried wheats were also milled to obtain a fine powder (particle size 0.3–0.5 mm mesh) using an Ultra-Centrifuge Retsch mill ZM 100 (Retsch, Germany). The ground samples were stored in the dark in air-tight bags in desiccators.

The TP content analysis

The determination of TP content was conducted using the method developed by Fang et al. (2006), which includes the measurement of absorbance with the usage of Folin–Ciocalteu reagent. The assay was conducted as follows: 200 µL of a suitably diluted sample (1/10 lyophilized sample/methanol) was transferred to a test tube and 800 µL of dionized water was added. After thorough mixing, five mL of 0.2 N Folin–Ciocalteu reagent was added to the test tube and vortexed. After 3 min of incubation at room temperature, 4 mL of sodium carbonate was added (75 g L¹). The prepared samples were then incubated in a dark room for two hours. Absorbance was measured (Shimadzu UV-1800, UV Spectrophotometer System, Kyoto, Japan) at the layer thickness of one cm and at a wavelength of 735 nm. The TP was calculated based on the standard curve prepared from chlorogenic acid.

The CA content analysis

The CA content was determined colorimetrically by the method of Griffiths, Bain & Dale (1992). Briefly, freeze-dried wheat powder (100 mg) was suspended in a two mL of urea solution (0.17 M) and acetic acid (0.10 M). One mL of sodium nitrite (0.14 M) was added to this solution and incubated for 2 min at room temperature before adding one mL of sodium hydroxide (0.5 M). The reaction was then centrifuged (Hettina Zentrifugen, Rotina 420 R, Tuttlingen, Germany) at 2250 g for 10 min and the absorbance of the cherry red complex formed of the supernatant was read at 510 nm (Shimadzu UV-1800, UV Spectrophotometer System, Kyoto, Japan). A standard curve was prepared using different concentrations of CA.

Evaluation of the antioxidant capacity (FRAP method)

Antioxidant capacity was determined by FRAP (ferric reducing antioxidant power assay) method as described by Benzie & Strain (1996). A total of 250 mL of acetate buffer (POCH, Gliwice) at pH 3.6 was mixed with 25 mL of TPTZ-2,4,6-tripyridyl-s-triazine solution (Sigma–Aldrich, St. Louis, MO, USA) and 25 ml of iron (III) chloride hexahydrate solution (Chempur, Piekary Śląskie, Poland). The reaction mixture was prepared immediately prior to assay. The solution was incubated at 37 °C, throughout the analysis. A total of 6 mL of reaction mixture was mixed with 200 µL of sample and 600 µL of H₂O. The absorbance of the mixture was measured at 593 nm (Shimadzu UV-1800, UV Spectrophotometer System, Kyoto, Japan) after 4 minutes. Acetate buffer was used as a control. The control sample absorbance value was subtracted from the test sample values. Based on the performed measurements, absorbance values’ dependence on sample concentrations was plotted. That was used to determine the absorbance value at the mean concentration of the applied dilutions, and anti-oxidative capacity was calculated at the same absorbance using the standard curve determined for Fe²⁺ ions.

Entomological analysis

Insect abundances of Oulema spp. adults and larvae were assessed after insects were collected by entomological net (Tratwal et al., 2015; Lamparski, 2016). Observations were made in the flag leaf stage of spring wheat, i.e., BBCH (Hinojosa et al., 2004). Cereal leaf beetle adults and larvae abundances were made in four replicates. The results are presented in specimens per plot.

Statistical analysis

The three-year research results were statistically verified by analysis of variance. The significance of differences was evaluated using the Tukey multiple confidence intervals for the significance level of α = 0.05. The analysis of data variance was calculated using Statistica^® software, and the main effects were tested by ANOVA. To evaluate the dependence between soil compositions and chemicals compounds in the plants the correlation coefficients (linear Pearsons correlation) was determined. All laboratory tests were carried out with three replications. Averages of results as well as standard deviation are shown in tables.

Enzymatic activity and soil properties

Granulometric composition analysis of the soil samples showed that the clay fraction was low. It ranged from 3.77 to 4.59% for OPS and from 4.70 to 5.48% for CPS (Table 1). According to the USDA (USDA, 2006) classification, all tested soil samples belonged to a single granulometric group–sandy loam. The soils were characterised by pH in 0.01 M CaCl₂, with values ranging in OPS from 5.02 to 6.08 (which is characterised as acid and slightly acid soil) and in CPS from 7.07 to 7.22 (neutral and alkaline soil).

Only the species of primary wheat grown in OPS significantly influenced soil OC content (Table 2). The highest accumulation of this macro-element (0.735%) was obtained in the soil with a plant density of 500 seeds m² of T. persicum. The cultivation of T. persicum contributed to a 10% increase OC content over T. sphaerococcum. Sowing density significantly (p ≤ 0.05) affected OC content. In OPS, higher OC content was obtained (0.699% on average for the two wheats) using a sowing density of 400 seeds m². By contrast, in CPS, 600 seeds m² resulted in the highest accumulation of OC in soil samples (0.821% on average for the two wheats). The OC content for the cultivation of ancient wheat species was higher in CPS than OPS. Based on the European Soil Database (Gonet, 2007) classes of OC content in soils, the studied soils are classified as having a very low OC content (<1%). It is assumed that OC = 2% is a critical level and that soils with a lower carbon content need to be exploited using methods (including such agrotechnical measures) that will increase their organic matter resources.

Variance analysis established that the applied experiment factors significantly influenced (p ≤ 0.05) the activity of enzymes from the oxidoreductase class (Table 3). However, this effect varied depending on the enzyme tested. The cultivated species of spring wheat significantly changed CAT activity, but only in soil samples from CPS. The CAT activity was significantly higher in the soil hosting T. sphaerococcum (average 0.840 mg H₂O₂ kg¹ h¹) than in that from T. persicum (average 0.809 mg H₂O₂ kg¹ h¹). In the case of DEH activity, in OPS, spring wheat species was found have a significant influence (p ≤ 0.05). The DEH activity was 5% higher in soil samples from T. sphaerococcum than in those from T. persicum. Wheat species significantly (p ≤ 0.05 affected soil PER activity in both OPS and CPS. In both production systems, activity was significantly higher in T. sphaerococcum compared with T. persicum.

Sowing density was demonstrated to have a significant effect on the activity of studied soil enzymes under both production systems for the examined primary wheat species. The highest CAT activity (average 0.854 mg H₂O₂ kg¹ h¹), DEH activity (0.667 mg TPF kg¹ 24 h¹) and PER activity (1.561mM PPG kg¹ h¹) were found in soil samples with sowing density increased to 600 seeds m² (CPS). These values were 42%, 27% and 20% respectively, higher relative to OPS values.

The enzyme activity results were used to calculate the soil fertility index. Figure 2 shows the soil GMea values calculated from two primary wheat production systems. Higher GMea values were obtained in soil samples from the CPS experiment (average 0.925). They were 30% higher relative to OPS. It can therefore be concluded that this production system was much more beneficial for the soil for both wheat species. Increasing sowing density caused an increase in soil GMea values, regardless of wheat species. Higher GMea values for soils CPS suggest that the use of this type of production system has a much higher impact on the biological parameters of the soil. This may be due to the lower content of nutrients or their higher availability. According to García-Ruiz et al. (2008) the geometric mean of enzyme activities (GMea) index was used to estimate soil quality by changes in soil management.

The calculated correlation coefficient revealed a relationship between clay and the activity of DEH, CAT and PER alike under OPS, at the 0.05 level (Table 4). Based on the coefficient of determination (R ²), the influence of clay on the activity of the tested enzymes was only 35%, 31% and 45%, respectively. Similarly, pH significantly affected the activity of CAT (r =0.556, p ≤ 0.05). The OC content was significantly positively correlated only with PER activity (r =0.422, p ≤ 0.05), and only in CPS. By contrast, OC did not correlate with DEH or CAT. In OPS, a significant negative correlation was observed between OC and the activity of DEH (r = −0.623, p ≤ 0.05), CAT (r =−0.843, p ≤ 0.05) and PER (r =−0.778, p ≤ 0.05). The coefficient of determination showed that OC had a 39%, 71%, 61%, influence on the activity of the three respective enzymes. Significant positive correlations were also found between the studied soil enzymes in both production systems.

Phenolic compounds content and antioxidant potential in wheats

The content of TP and CA depended significantly (p ≤ 0.05) on wheat species and plant density (Table 5). T. sphaerococcum plants contained significantly more p-phenolic compounds and CA as compared to T. persicum in both CPS and OPS. For the two species (T. sphaerococcum, T. persicum), contents of TP were on average 8.71% and 11% higher, and CA contents were 0.6% and 3.4% higher, respectively. Wheat plants sown in a density of 400 seeds m² had the highest content of the tested compounds, and increasing the density contributed to a reduction in contents. A similar pattern was ascertained for the anti-oxidative potential of FRAP. An average level of anti-oxidative potential of 9.165 mmol Fe²⁺ kg⁻¹ DM and 8.736 mmol Fe²⁺ kg⁻¹ DM (CPS) was obtained in OPS and CPS, respectively.

Relationship between the soil parameters and wheats quality characteristics

The obtained results showed a relationship between the tested soil parameters and wheat quality characteristics. Under OPS (Table 4), increases in the studied soil enzyme activities resulted in a decrease in polyphenolic compound contents in plants. This is evidenced by the significantly negative correlations between TP contents and the activity of the enzymes DEH (r =−0.516, p ≤ 0.05), CAT (r =−0.580, p ≤ 0.05) and PER (r =−0.648, p ≤ 0.05) Meanwhile, in CPS (Table 6), TP content increased because of fell OC content in the soil: OC (r =−0.721, p ≤ 0.05).

Moreover, the activity of the soil enzymes DEH, CAT and PER were also found to have an inverse relationship with CA content and anti-oxidative potential in the tested CPS grown wheats (Table 6). This is confirmed by the negative correlation coefficients for CA: r =−0.677 (p ≤ 0.01), r =−0.636 (p ≤ 0.01), r = −0.511 (p ≤ 0.05), and for anti-oxidative potential: r =−0.512 (p ≤ 0.05), r = −0.474 (p ≤ 0.05), r =−0.454 (p ≤ 0.05), respectively. Additionally, it was noted that among the studied soil enzymes, only the activity of CAT and PER was inversely dependent on the anti-oxidative potential of the wheats cultivated organically: r =−0.681 (p ≤ 0.01), r =−0.622 (p ≤ 0.01) (Table 4).

The abundance of Oulema spp. depends on the quality features of soil and wheats. In the flag leaf stage (of T. sphaerococcum and T. persicum), more Oulema spp.—both adults and larvae—were collected from the OPS grown wheat than from the CPS grown wheat (Table 7). Although the number of larvae for OP and CP was not statistically compared, it is clearly visible that in the entomological net there were many times more Oulema spp. larvae in OPS than in CPS (57 and 1 no per plot, respectively; no per plot = 21m²). However, in OPS, no significant differences in the number of Oulema spp. adults were found between the assayed spring wheat species. The applied sowing density of wheat significantly (p ≤ 0.05) affected the presence of the pest in the crop. At the flag leaf stage, the density of 500 seeds per m² proved to be least preferred by adult Oulema spp. (Table 7) while in CPS, this was only observed in T. sphaerococcum wheat. On the other hand, Oulema spp. larvae were least abundant at the lowest sowing density, i.e., 400 seeds m², of both wheat species, in both OPS and CPS. It should be emphasised that in neither production system were any constant trends found in the influence of sowing density on abundance of Oulema spp.

In the OPS of spring wheat, a high correlation was demonstrated between CA content and the pests, both in the larval and adult form, at r =0.806 and r =0.531, respectively (Table 4). Also, a significant relationship (p ≤ 0.01) was obtained between TP content and the presence of adult pests (r =0.732). However, the correlation between antioxidant capacity and adults was significant (r =0.429), but at the level of 0.05. No such relationships were obtained in intensive cultivation.