Suitability of Various Parameters for the Determination of the Condition of Soil Structure with Dependence to the Quantity and Quality of Soil Organic Matter

Abstract

Soil structure (SS) plays an important role in relation to climatic change, with the most important task the decreasing of CO₂ in the atmosphere by carbon sequestration in the soil and the prevention of floods by better water infiltration into the soil. However, the evaluation of its condition is very different because of the various parameters and their inappropriate uses. The aim of this study was to determine the responses of the parameters of SS on the soil type and tillage system as the most important factors that influence it through changes in the soil organic matter and soil texture. The soil factor, which was represented by seven soil types (EF, Eutric Fluvisol; MF, Mollic Fluvisol; HC, Haplic Chernozem; HL, Haplic Luvisol; ER, Eutric Regosol; EG, Eutric Gleysol; DS, Distric Stagnosol), should be included in all evaluations of SS because of the specifics of each soil type. The tillage factor (shallow non-inversion-reduced, RT; deeper with inversion-conventional, CT) was chosen because of a high sensitivity of SS to soil disruption by cultivation, which represents high potential for the mitigation of climate change. The study included 126 sampling places in different parts of Slovakia on real farms (7 soil types × 3 localities × 3 crop rotations × 2 tillage systems × 2 soil depths). The soils were analysed for the aggregate fraction composition, particle size distribution, and parameters of organic carbon. The data of different parameters of SS were calculated and evaluated. The most sensitive parameter of the tested ones was the coefficient of structure (K_st), which manifested up to the level of the fractions of humus substances and indicated a better condition of SS in more productive soils than less productive soils. The coefficient of soil structure vulnerability (K_v) and mean weight diameter in water-resistant macroaggregates (MWD_w) showed a worse condition of SS in the soils, which developed on Neogene sediments. A better condition of SS in RT was predicted particularly by the primary parameters (index of crusting, I_c; critical content of soil organic matter, S_t), and in CT, they were mainly the secondary parameters (K_st; water-resistant of soil aggregates, K_w). Overall, the suitability of the parameters of SS should be evaluated in relation to a specific soil type with its characteristics and should not be used universally.

1. Introduction

The sustainable condition of the soil structure, in a period of significant climatic change, has high priority. It determines the rainfall infiltration into the soil [1] and thus the elimination of floods or erosion, the carbon sequestration [2,3] and thus decreasing of emissions, and the preservation of the soil productive capacity [4,5] and thus ensuring food security.

On the one hand, the formation of soil aggregates contributes to the stabilisation of soil organic matter (SOM) [6,7,8]; on the other hand, the organic matter is a key element in the formation of soil aggregates [9,10]. The interrelationship between the soil structure and organic matter is dynamic [8], and the characters of bonds between the soil organic and mineral particles constantly change [11]. SOM is a heterogeneous mixture of labile and stabile substances, which enter into the interactions with mineral particles of different sizes that result in the formation of soil aggregates of different sizes and stability [12]. This is also determined by the soil texture [13,14], while the sand fraction (20–2000 μm), due to the characters of bonds, plays an important role in the short-term dynamics of organic matter but clay (<2 μm) and silt (2–20 μm) in long-term ones [15]. The fractional composition of soil aggregates is, to some extent, determined by the soil type [16], but it importantly changes in agroecosystems, with the most significant effect on tillage [8,17,18,19].

For one thing, there are less invasive tillage systems such as no-till, strip-till, or similar ones, which are presented as the most suitable for carbon sequestration because of the better carbon protection inside of aggregates [20,21], though they cannot be applied in all cases. Zhao et al. [22] presented for carbon sequestration under other conditions, as the best tillage system, moldboard plow tillage with the wheat residue returning. There are also more invasive tillage systems, such as moldboard plow tillage, disking, subsoiling, or similar ones, but due to the possibility of crop residue incorporation or a better pore architecture for water infiltration or its capture, these are more suitable [23,24]. Unfortunately, again, they cannot be applied in all cases. Budhathoki et al. [25] presented, under different conditions, well-developed pore networks of macropores in a no-till system.

According to Malobane et al. [26], the tillage is the main factor influencing aggregate stability, which is linked to the aggregate microstructure. Moreover, each soil is characterised by its specific properties, which means what is the best for one soil does not have to suit for another. The highest impact on the decision of a suitable tillage system has the soil texture and soil organic matter content. For example, soils with a high content of clay and are poor organic carbon are susceptible to soil compaction, mainly under a no-till system. Blanco-Canqui et al. [27] concluded that no-till is not better than reduced tillage to reduce soil compaction. Zhang et al. [28] also reported that tillage under straw return is more efficient for carbon sequestration than no-tillage. In all cases, the organic carbon return into the soil is important. On the other hand, soils with a higher proportion of sand support the mineralisation of soil organic carbon. This means that the soil texture strongly predicts the soil organic carbon sequestration potential [29].

Overall, then, the final changes are the result of a used tillage system and a certain resistance of soil type to its influence. Therefore, it is important to evaluate its impact in the context of the concrete soil type and specifics of the concrete region: semiarid [30], subtropical monsoon climate [31], and so on. Zhang et al. [32] drew attention to climatic (mainly precipitation) variables that dominated water-resistant macroaggregate variability at the regional scale. In relation to temperature, together with elevated CO₂, Xiong et al. [33] showed increased macro-, but lowered micro-, aggregation. Macro- and microaggregates are the main contributors to organic carbon sequestration in soil [34].

Macroaggregates are richer in organic carbon [12,35], while a more efficient stabilisation of organic carbon is in fractions of smaller aggregates (0.5–1 mm) than larger ones (1–4 mm), namely through both mineral interactions and by physical occlusion [36]. Moreover, macroaggregates of the size 0.84–3 mm are influenced by clay mineralogy [37]. This is approximately the size range of agronomically the most valuable aggregates (0.5/1–3 mm). Thus, macroaggregates can be stabilised through both organic and inorganic bonds [38]. It is often stated that the organic carbon in microaggregates is more stabilised [10,39]; however, there are also studies that have proven the opposite [40,41]. In soil with a lower clay content, a greater amount of organic carbon is retained in smaller microaggregates, and the soil texture affects the carbon content in them indirectly through the distribution of carbon in different aggregate fractions [42]. Free microaggregates are fragments of macroaggregates after their disintegration [41]. An increased proportion of smaller aggregates (<1.2 mm) is an important indicator of soil degradation [43]. The results of this are the significant differences in the assessment of the conditions of the soil structure due to the use of various parameters for its assessment, the use of which is also linked to the specifics of soil and the purpose of using the given evaluation.

The parameters of the soil structure can be divided into primary and secondary indicators and the combination of both. The first of them assumes the characters of the formation of soil aggregates: soil crusting index (I_c) [44] and critical content of soil organic matter (S_t) [45], and they carry in themselves the dependence between the basic factors initially determining the mechanism of aggregate formation (soil organic matter and soil texture). The second are already a reflection of a certain fraction composition of aggregates and thus the condition of the soil structure: mean weight diameter (MWD) [46], coefficient of soil structure vulnerability (K_v) [47], coefficient of water-resistance of soil aggregates (K_w) [48], coefficient of structure (K_st) [48], and WSA 0.5–3 mm. The last of them are a combination of the previous ones, e.g., aggregate stability index (S_w) [44]. While the primary ones are rather a kind of assumption of future conditions, the secondary ones are already its reality. Thus, assessing the suitability of agricultural land is essential for planning sustainable and agricultural systems [49].

This study aimed to evaluate the suitability of various SS parameters in order to find the best and most sensitive parameters for the evaluation of the soil structure. Since the parameters of the soil structure are built on several bases, the obtained results from them should also be necessarily interpreted in a given context. Therefore, the aims of this study were: (i) to determine the responses of selected parameters of the soil structure to the soil type and tillage system; (ii) to evaluate their sensitivity by analysing different fractions of the soil organic matter and soil texture; (iii) identify the most suitable parameters for assessing the influence of various factors on the conditions of the soil structure.

2. Materials and Methods

2.1. Characterisation of Localities and Variants Included in the Study

The areas of soil sampling were located in various parts of Slovakia on real farms, which were spread out on Podunajska lowland (Nové Zámky, Šaľa, Vráble, and Piešťany) and Eastern Slovak lowland (Trebišov, Michalovce, and Sobrance). The climatic regions were moderately warm to warm. The soils were formed from different geological substrates (

Table 1. Localisation of the soil types in geological climatic conditions.

Soil Type	Locality	Coordinates Lat./Long.	A (m)	Climatic Region	Parent Material
EF	Trebišov	48°38′ N/21°43′ E	98–252	moderately warm	River sediments
MF	Nové Zámky	47°59′ N/18°09′ E	110–202	warm	River sediments
HC	Piešťany	48°35′ N/17°50′ E	150–229	warm	Neogene sediments
HL	Vráble	48°14′ N/18°18′ E	160–458	moderately warm	Neogene sediments
ER	Šaľa	48°09′ N/17°52′ E	111–135	warm	Neogene sediments
EG	Michalovce	48°44′ N/21°54′ E	330–823	moderately warm	Proterozoic rocks
DS	Sobrance	48°44′ N/22°10′ E	194–850	moderately warm	Palaeozoic rocks

EF—Eutric Fluvisol, MF—Mollic Fluvisol, HC—Haplic Chernozem, HL—Haplic Luvisol, ER—Eutric Regosol, EG—Eutric Gleysol, DS—Distric Stagnosol; A—Average altitude.

) [50].

The study incorporated 252 soil samples. Each area included 3 localities with the same soil type (Figure 1). Each of them included three crop rotations and two tillage systems. Soil samples were taken separately from two depths. The soil types [51] were characterised by different production abilities, which were given by the production potential, which was expressed by point values. More productive soils, high to very high productive soils with an index productivity of 80–83 points, included Haplic Chernozem (HC), Mollic Fluvisol (MF), and Eutric Fluvisol (EF); less productive soils, productive and medium productive soils with an index productivity of 63–78 points, included Haplic Luvisol (HL), Eutric Regosol (ER), Eutric Gleysol (EG), and Distric Stagnosol (DS) (http://www.podnemapy.sk/portal/verejnost/bh_pp/bh.aspx, accessed on 17 April 2023).

Two different tillage systems, which represent different levels of disturbance intensity, were used: a shallow non-inversion tillage system—reduced tillage (RT), which included disking to a depth of 0.10–0.12 m, and deeper tillage system with inversion—conventional tillage (CT), which included mouldboard deep ploughing. The depth of soil sampling was 0.0–0.1 m and 0.0–0.3 m in each field, with different crop residue management (Figure 2).

The organic inputs in all fields for the period of the last 10 years were calculated according to the method of Jurčová and Bielek [53] and varied approximately 8–20 tC/ha. In all fields, the cereals were dominant. The basic soil properties of all the fields are included in

Table 2. Average values of the basic pedological characteristics of the soil types.

Soil Type	CL (g/kg)	CNL (g/kg)	pH/CaCl2	Clay (%)
EF	1.766 ± 0.413 bc	19.56 ± 2.52 b	5.52 ± 0.47 c	34.28 ± 3.05 a
MF	2,971 ± 0.104 a	29.52 ± 1.57 a	7.00 ± 0.92 a	32.31 ± 5.94 a
HC	1.965 ± 0.471 bc	16.12 ± 4.03 b	6.07 ± 1.12 bc	25.60 ± 1.60 b
HL	1.713 ± 0.438 bc	15.16 ± 2.78 b	6.19 ± 0.74 bc	22.95 ± 4.48 b
ER	2.089 ± 0.558 bc	16.41 ± 2.42 b	6.43 ± 0.89 ab	13.59 ± 3.88 c
EG	2.349 ± 1.302 ab	19.94 ± 4.49 b	6.09 ± 0.69 bc	32.46 ± 5.34 a
DS	1.565 ± 0.448 c	15.20 ± 3.04 b	5.66 ± 0.95 c	21.55 ± 4.49 b

EF—Eutric Fluvisol, MF—Mollic Fluvisol, HC—Haplic Chernozem, HL—Haplic Luvisol, ER—Eutric Regosol, EG—Eutric Gleysol, DS—Distric Stagnosol, C_L—labile carbon oxidisable by KMnO₄, and C_NL—non-labile carbon.

.

2.2. Preparing of Soil Samples and Used Analytical Methods

The soil samples were collected during three replicates in the spring up to depths of 0.0–0.1 m and 0.0–0.3 m. Each depth represents the layer from the soil surface down to that depth. These are not only the average values from the different depths of the soil profile but separate samplings of both depths (0.0–0.1 m and 0.0–0.3 m). Soil samples for the determination of the soil aggregates were taken from three separate samples in a block 0.3 × 0.3 × 0.3(0.1) m and then processed by hand by removing disturbed parts of the soil from the smooth compressed walls of this block. After homogenisation of these three samples, 2 kg of soil was weighted (

Table 3. List of input and output data of this study.

Inputs	Variable	Units	Outputs
Soil structure	Fractions of dry-sieved macroaggregates (>7; 5–7; 3–5; 1–3; 0.5–1; 0.25–0.5 mm)	%	Index of crusting, Critical content of soil organic matter, Mean weight diameter, Coefficient of soil structure vulnerability, Coefficient of water-resistant soil aggregates, Coefficient of structure, Index of aggregate stability, Aggregate stability of small wet-sieved macroaggregates, Aggregate stability of large wet-sieved macroaggregates
	Fractions of wet-sieved macroaggregates (>5; 3–5; 2–3; 1–2; 0.5–1; 0.25–0.5 mm)	%
Soil texture	Sand (coarse 0.25–2 mm; fine 0.05–0.25 mm)	%
	Silt (coarse 0.01–0.05 mm; fine 0.001–0.01 mm)	%
	Clay (<0.001 mm)	%
Parameters of carbon	Total organic carbon	mg/kg
	Labile carbon oxidisable by potassium permanganate	mg/kg
	Cold and hot water extractable organic carbons	mg/kg
	Optical parameters of humus substances and humic acids	mg/kg
	Fractions of humus substances (humic acids free and bound with mobile R2O3, humic acids bound with bivalent cations, mainly Ca2+, humic acids bound with mineral components of the soil and stabile R2O3, free aggressive fulvic acids, fulvic acids free and bound with mobile R2O3, fulvic acids bound with bivalent cations, mainly Ca2+, fulvic acids bound with mineral components of the soil and stabile R2O3)	%

).

After drying in a laboratory temperature of 20 °C, the soil samples were processed to analyse the aggregate fraction composition and particle size distribution. To determine the fractions of the soil aggregates (soil structure), the soil samples were divided by sieves [54] to obtain fractions of dry-sieved (DSA) (>7; 5–7; 3–5; 1–3; 0.5–1; 0.25–0.5 mm) and wet-sieved (WSA) (>5; 3–5; 2–3; 1–2; 0.5–1; 0.25–0.5 mm) macroaggregates. To determine the particle size distribution (soil texture), the soil samples were adjusted by the dissolution of CaCO₃ (with 2 mol/dm³ HCl), oxidation of organic matter (with 30% H₂O₂), repeatedly washed, and dispersed (with Na(PO₃)₆). Sand (coarse 0.25–2 mm, fine 0.05–0.25 mm), silt (coarse 0.01–0.05 mm, fine 0.001–0.01 mm), and clay (<0.001 mm) were determined by the pipette method [55].

The soil samples to determine the chemical properties were sieved (<2 mm and <0.25 mm sieves) to determine the total organic carbon (TOC) and labile carbon oxidisable by potassium permanganate (C_L). TOC was determined by K₂Cr₂O₇ oxidation (wet combustion), according to Orlov a Grišina [56], and C_L by KMnO₄ oxidation, according to Loginov et al. [57], and cold (CWEOC) and hot (HWEOC) water-extractable organic carbons, according to Ghani et al. [58], with the final determination of organic carbon by wet combustion [56]. Stabile fractions of organic carbon were calculated as non-labile carbon (C_NL), according to Blair et al. [59], and the fraction compositions of humus substances were determined, including the optical parameters (Q_HS and Q_HA; HS—humus substances and HA—humic acids), measured by wavelength 465/650, according to Orlov a Grišina [56]. The fractions of the humus substances were as followed: humic acids free and bound with mobile R₂O₃ (HA1), humic acids bound with bivalent cations, mainly Ca²⁺ (HA2), humic acids bound with mineral components of the soil and stabile R₂O₃ (HA3), free aggressive fulvic acids (FA1a), fulvic acids free and bound with mobile R₂O₃ (FA1), fulvic acids bound with bivalent cations, mainly Ca²⁺ (FA2), and fulvic acids bound with mineral components of the soil and stabile R₂O₃ (FA3). Labile nitrogen (N_L) was analysed as potentially mineralizable nitrogen [45]. Soil pH was potentiometrically measured in a supernatant suspension of a 1:2.5 soil: liquid mixture [60] in liquid 0.02 mol/dm³ CaCl₂.

The soil structure was evaluated through the different parameters calculated from the results of the analyses. The index of crusting (I_c) (Equation (1)) and critical content of the soil organic matter (S_t) (Equation (2)) were based on the soil texture and soil organic matter content.

I_c = (1.5S_f + 0.75S_c)/(Cl + 10SOM)

(1)

where S_f is fine silt (%), S_c is coarse silt (%), Cl is clay (%), and SOM is the soil organic matter content (%) [44].

S_t (%) = SOM/(Clay + Silt)

(2)

where SOM is soil organic matter (%), and its authors proposed the following limits of the SOM concentration for characterising of the soil structure:

S_t

=< 5%, loss of soil structure and high susceptibility to erosion;

S_t

= 5 to 7%, unstable structure and risk of soil degradation;

S_t

=> 9%, stable soil structure [45].

The mean weight diameter (MWD) (Equation (3)), coefficient of soil structure vulnerability (K_v) (Equation (4)), coefficient of water-resistant soil aggregates (K_w) (Equation (5)), and coefficient of structure (K_st) (Equation (6)) were based on the fraction compositions of dry- and wet-sieved aggregates.

$$\mathrm{MWD} (\mathrm{mm})={{\displaystyle \sum }}_{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{x}}_{\mathrm{i}}{\mathrm{w}}_{\mathrm{i}}$$

(3)

where x_i is the mean diameter of each size fraction (mm), w_i is the proportion of the total sample weight occurring in the corresponding size fraction, and n is the number of the size fraction [46].

K_v = MWD_D/MWD_W

(4)

where MWD_D is the mean weight diameter of dry-sieved macroaggregates, and MWD_w is the mean weight diameter of wet-sieved macroaggregates [47].

K_w = a/b

(5)

where a is the weight of water-resistant aggregates of the size 0.25–10 mm, and b is the weight of water-resistant aggregates of the size < 0.25 mm [48].

K_st = A/B

(6)

where A is the weight of dry-sieved aggregates of the size 0.25–7 mm (in dry areas) or 0.25–10 mm (in wet areas), and B is the weight of dry-sieved aggregates of the size < 0.25 mm and >7(10) [48].

The index of aggregate stability (S_w) (Equation (7)) was a combination of previous parameters and based on the particle size distribution and soil aggregates.

S_w = (WSA − 0.09sand)/(100 − sand)

(7)

where WSA is the percentage proportion of water-resistant macroaggregates (>0.25 mm).

Together with the mentioned parameters of the soil structure, two auxiliary parameters were created. Provided that, agronomically, the most valuable WSA was the size of 1–3 mm, the first auxiliary parameter was the aggregate stability of small WSA (A_SW) (Equation (8)), and the second was the aggregate stability of large WSA (A_LW) (Equation (9)).

A_SW = WSA_1–3/(WSA_0.5–1 + WSA_0.25–0.5 + WSA_<0.25)

(8)

where WSA_1–3 (%) is the proportion of, agronomically, the most valuable WSA, and WSA_0.5–1 and WSA_0.25–0.5 + WSA_<0.25 are the fractions of WSA smaller than the optimum size (1–3 mm).

A_LW = WSA_1–3/(WSA_3–5 + WSA_>5)

(9)

where WSA_1–3 (%) is the proportion of, agronomically, the most valuable WSA, and WSA_3–5 and WSA_>5 are the fractions of WSA larger than the optimum size (1–3 mm).

2.3. Statistical Analysis Used in the Study

The obtained data were analysed using Statgraphic Plus 5.1 and Centurion 17 statistical software. Firstly, the normality and homogeneity of the variances were tested, and then, an analysis of variance was applied. The two-way ANOVA model was used for individual treatment comparisons at p < 0.05, with separation of the means by the LSD test, which was applied to test for differences between the tillage systems and soil types. The results are presented in the tables as the means and in the boxplots as the mean, bottom, 2Q box, 3Q box, and error bars. Two datasets of n = 252 and n = 126 were included. A half-number of the soil samples (depth of sampling; 0.0–0.1 m or 0.0–0.3 m) was used because of the tillage influence (RT and CT). The difference was significant at p < 0.05. Pearson’s method was used to analyse the correlations between variables. A correlation analysis was used to determine the relationships between the parameters of the soil structure (coefficients or indexes) and soil organic matter parameters or particle size distribution. Significant Pearson’s correlation coefficients were tested at p < 0.05 and p < 0.01.

3. Results and Discussion

3.1. The Relationships between the Parameters of Soil Structure and Soil Organic Matter

If we exclude the soil structure parameters, which includes the organic carbon (I_c and S_t), the K_st and the content of WSA at 0.5–3 mm seem to be the most sensitive (

Table 4. Correlations between the parameters of the soil structure and organic carbon.

	TOC	CL	CWEOC	HWEOC	NL	CL/NL	QHS465/650	QHA465/650
Kv	−0.313 **	−0.215 *	ns	ns	ns	−0.181 *	−0.346 **	−0.349 **
Sw	ns	ns	ns	ns	ns	ns	ns	ns
Ic	−0.537 **	−0.457 **	−0.282 **	−0.338 **	−0.297 **	−0.366 **	0.224 *	ns
St	0.961 **	0.793 **	0.324 **	0.621 **	0.528 **	0.440 **	ns	ns
MWDD	ns	ns	ns	ns	ns	ns	0.255 *	0.360 **
MWDW	0.281 **	0.227 *	ns	ns	ns	0.239 *	0.405 **	0.469 **
Kst	ns	ns	ns	0.196 *	0.271 *	ns	−0.293 **	−0.303 **
Kw	ns	ns	ns	ns	ns	ns	0.270 *	0.310 **
WSA 0.5–3 mm	−0.183 *	−0.193 *	ns	ns	ns	−0.314 **	−0.299 **	−0.343 **

** p < 0.01; * p < 0.05; ns—not significant; TOC—total organic carbon; C_L—labile carbon oxidisable KMnO₄; CWEOC—cold water extractable organic carbon; HWEOC—hot water extractable organic carbon; N_L—labile nitrogen; C_L/N_L—ratio of labile carbon and labile nitrogen; Q_HS⁴⁶⁵/₆₅₀—colour coefficient of humus substances; Q_HA⁴⁶⁵/₆₅₀—colour coefficient of humic acids; K_v—coefficient of soil structure vulnerability, S_w—index of aggregate stability, I_c—index of crusting, S_t—critical content of soil organic matter, MWD_D—medium weight diameter of dry-sieved aggregates, MWD_W—medium weight diameter of wet-sieved aggregates, K_st—coefficient of structure, K_w—coefficient of water-resistant soil aggregates, and WSA—water-resistant macroaggregates. The values are presented as correlation coefficients (i.e., without units); the fractions processed (including units) were: TOC, C_L, CWEOC, HWEOC, and N_L (mg/kg); S_t (%); and MWD_D, MWD_W, and WSA (mm).

and

Table 5. Correlations between the parameters of the soil structure and fractions of humus substances.

	HA1	HA2	HA3	ΣHA	FA1a	FA1	FA2	FA3	ΣFA
Kv	ns	ns	ns	ns	ns	ns	ns	ns	ns
Sw	ns	ns	0.381 *	ns	ns	ns	ns	0.377 *	ns
Ic	0.631 **	ns	ns	ns	0.778 **	0.614 **	ns	ns	ns
St	−0.327 *	ns	ns	ns	ns	−0.486 **	ns	ns	ns
MWDD	ns	ns	−0.330*	ns	ns	ns	−0.455 **	ns	−0.382 *
MWDW	ns	ns	ns	ns	ns	ns	ns	ns	ns
Kst	ns	ns	0.562 **	0.388 *	ns	ns	0.665 **	ns	0.384 *
Kw	−0.443 **	ns	ns	−0.339 *	ns	ns	ns	ns	ns
WSA 0.5–3 mm	ns	ns	0.335 *	ns	ns	ns	ns	ns	ns

** p < 0.01; * p < 0.05; ns—not significant; HA1—humic acids free and bound with mobile R₂O₃; HA2—humic acids bound with Ca²⁺; HA3—humic acids bound with mineral components of the soil and stabile R₂O₃; ΣHA—sum of humic acids; FA1a—free aggressive fulvic acids; FA1—fulvic acids free and bound with mobile R₂O₃; FA2—fulvic acids bound with Ca²⁺; FA3—fulvic acids bound with mineral components of the soil and stabile R₂O₃; ΣFA—sum of fulvic acids; K_v—coefficient of soil structure vulnerability, S_w—index of aggregate stability, I_c—index of crusting, S_t—critical content of soil organic matter, MWD_D—medium weight diameter of dry-sieved aggregates, MWD_W—medium weight diameter of wet-sieved aggregates, K_st—coefficient of structure, K_w—coefficient of water-resistant soil aggregates, and WSA—water-resistant macroaggregates. The values are presented as correlation coefficients (i.e., without units); the fractions processed (including units) were: fractions of humic and fulvic acids, S_t (%) and MWD_D, MWD_W, and WSA (mm).

).

The influence of soil organic matter on the parameters of the soil structure was mainly qualitative. Its positive influence was recorded mainly in the case of stabile components and not only in the amount of humus substances but also in their individual fractions or in the stability itself (Q_HS⁴⁶⁵/₆₅₀ and Q_HA⁴⁶⁵/₆₅₀). Vegetation [61] or tillage [62] influence the processes of soil aggregate formation, and simultaneously, these are the factors that limit the aromaticity of humic acids [63]. Humus substances (HS) are primarily a part of macroaggregates [64,65], mainly >2 mm, which points to the importance of these aggregates in carbon sequestration [18]. Simultaneously, humus substances support the formation of macroaggregates of the size 0.25–2 mm [66], which was also reflected in the positive correlations between the K_st and content of humic acids (HA) and fulvic acids (FA). In the cases of K_st and WSA 0.5–3 mm, there were recorded positive correlations with HA3 (fraction bound with mineral components), which proves that HA are an important part of soil aggregates and the important element in the formation of most valuable aggregates. Macroaggregates >2 mm have a positive correlation with nutrient pools [67], which include iron bound with HA3. Humus substances in connection with aggregates are influenced by the pH, oxides, and clay content [65]. Fractions of free HA and FA had negative correlations with the soil pH and clay content (

Table 6. Correlations between the fractions of humus substances and soil acidity and particle size distribution.

	pH/CaCl2	H	sand	silt	clay
HA1	−0.385 *	0.437 **	ns	0.364 *	−0.689 **
HA2	ns	ns	ns	ns	ns
HA3	ns	−0.493 **	0.515 **	−0.478 **	ns
ΣHA	ns	ns	0.516 **	ns	−0.335 *
FA1a	−0.465 **	0.395 *	ns	0.487 **	−0.551 **
FA1	−0.468 **	0.737 **	ns	−0.424 *	−0.527 **
FA2	ns	−0.365 *	ns	−0.386 *	0.367 *
FA3	ns	ns	0.340 *	ns	ns
ΣFA	ns	ns	ns	ns	ns

** p < 0.01; * p < 0.05; ns—not significant; HA1—humic acids free and bound with mobile R₂O₃; HA2—humic acids bound with Ca²⁺; HA3—humic acids bound with mineral components of the soil and stabile R₂O₃; ΣHA—sum of humic acids; FA1a—free aggressive fulvic acids; FA1—fulvic acids free and bound with mobile R₂O₃; FA2—fulvic acids bound with Ca²⁺; FA3—fulvic acids bound with mineral components of the soil and stabile R₂O₃; ΣFA—sum of fulvic acids; H—hydrolytic acidity. The values are presented as correlation coefficients (i.e., without units); the fractions processed (including units) were: fractions of humic and fulvic acids, sand, silt, and clay (%); H (mmol/kg).

).

Unless the formation of a humus–mineral complex does not occur, the humus substances do not contribute to the improvement of the condition of the soil structure, which is proven in the positive correlations of HA1 and FA1 (fractions of free acids) and FA1a (fraction of free aggressive acids) with I_c and their negative correlations with S_t. HS importantly influences not only the soil pH but also water-soluble organic carbon [68].

The values of K_st were positively influenced by labile forms of organic matter, especially HWEOC and N_L, which, in turn, points not only to the positive influence of the microbial component on the formation of soil aggregates but simultaneously of the stabile substances of the organic matter and not only of the humus substances. During the extraction of HWEOC at 80 °C, the vegetative cells are also extracted, and a significant amount of non-microbial carbon is extracted [69]; therefore, the labile fractions of nitrogen are also released into the environment. Since organic nitrogen is also a part of humus substances, it can be a significant contribution to the stabilisation of soil aggregates, thereby improving the condition of the soil structure. In the case of the often-used parameter MWD_W, this parameter is influenced more by the amount of soil organic carbon, which is proven by a positive correlation with TOC that has also been recorded by Cao et al. [70] on soils affected by erosion. In this case, it was mainly C_L and simultaneously, as there were lower stabilities in the humus substances and humic acids. Macroaggregates contain a greater diversity of chemical compounds [64] and are also richer in labile carbon, and its positive correlation with MWD has also been recorded by Briedis et al. [71]. Higher values of MWD_W are at wider C_L/N_L ratios. Different components of organic matter participate in the formation of soil aggregates, which also supports the different categorisations of soil pores influencing the microbial decomposition of these inputs [72].

3.2. Differences in the Parameters of Soil Structure with Dependence on Soil Type and Tillage System

The influence of soil type manifested more or less on all the studied parameters of the soil structure. On the soils developed on Neogene sediments (HC, HL, and ER), significantly higher values of K_v (Figure 3a) and WSA 0.5–3 mm (Figure 3b) were recorded and, simultaneously, the lowest values of K_w (Figure 3c) and MWD_W (Figure 3d). The mentioned parameters, with the exception of WSA 0.5–3 mm, pointed to a worse condition of the soil structure for these soils, which were significantly affected by erosion. A worse structural condition for soils more affected by erosion (dolomite soils worse than limestone soils) was also recorded by Wang et al. [73]. In the case of WSA 0.5–3 mm, a negative correlation with the clay fraction (r = −0.221; p < 0.05) and a positive with the sand fraction (r = 0.274; p < 0.05) were recorded. Although clay increased the cohesion of the soil aggregates [74], it dominated as a cementing agent in the smaller aggregates [75,76] and participated especially in the formation of microaggregates [77]. In the case of the dominance of the sand fraction, also due to the limiting contents of Fe and Al oxides, the cementing effect of the organic substances increased [74].

Interesting is that the dependence of MWD_W (Figure 3e) and MWD_D (Figure 3f) within the soil types were opposite but identical within the tillage systems (

Table 7. Differences in the parameters of the soil structure in different soil types and tillage systems.

		Kv	Sw	Ic	St	MWDD	MWDW	Kst	Kw	WSA 0.5–3 mm
EF	RT	1.57 a	0.98 a	0.83 a	2.45 a	3.90 a	2.50 a	1.37 a	14.68 a	40.74 b
	CT	1.69 a	1.01 a	0.89 a	2.14b	3.21 b	1.92 b	2.14 a	16.58 a	58.35 a
MF	RT	1.60 a	1.11 a	0.78 a	3.26 a	4.27 a	2.69 a	1.27 b	13.77 a	36.97 b
	CT	1.61 a	1.07 a	0.61 a	4.51 a	2.77 b	1.74 b	2.48 a	12.95 a	58.59 a
HC	RT	2.91 b	0.89 a	0.95 b	2.44 a	3.30 a	1.18 a	1.58 b	2.91 b	49.77 b
	CT	4.66 a	0.88 a	1.12 a	1.70 b	3.01a	0.68 b	1.90 a	4.66 a	56.76 a
HL	RT	2.37 a	1.33 a	0.94 a	2.74 a	2.69 b	1.24 a	1.51 a	6.53 a	58.33 a
	CT	2.71 a	0.99 b	1.12 a	1.82 b	3.90 a	1.49 a	1.25 a	8.32 a	59.25 a
ER	RT	2.90 a	1.00 a	1.11 a	2.36 a	3.50 a	1.37 a	1.45 a	6.78 a	53.67 a
	CT	2.43 a	0.96 a	1.06 a	1.94 b	3.17 a	1.29 a	1.92 a	6.32 a	58.85 a
EG	RT	1.64 a	0.97 b	0.83 a	2.46 a	3.88 b	2.44 a	1.27 a	13.26 a	43.2 4a
	CT	1.73 a	1.12 a	0.90 a	2.56 a	4.15 a	2.45 a	1.11 a	17.73 a	46.47 a
DS	RT	1.70 a	1.05 a	1.68 a	1.71 b	3.25 b	1.92 b	1.29 a	9.72 a	52.29 a
	CT	1.44 b	1.01 a	1.15 b	2.08 a	3.88 a	2.69 a	1.35 a	17.09 a	38.23 b

EF—Eutric Fluvisol, MF—Mollic Fluvisol, HC—Haplic Chernozem, HL—Haplic Luvisol, ER—Eutric Regosol, EG—Eutric Gleysol, DS—Distric Stagnosol, RT—reduced tillage, CT—conventional tillage, K_v—coefficient of soil structure vulnerability, S_w—index of aggregate stability, I_c—index of crusting, S_t—critical content of soil organic matter (%), MWD_D—medium weigh diameter of dry-sieved aggregates (%), MWD_W—medium weigh diameter of wet-sieved aggregates (%), K_st—coefficient of structure, K_w—coefficient of water-resistant soil aggregates, and WSA—water-resistant macroaggregates (%). Different letters (a and b) between the factors show statistically significant differences (p < 0.05)—LSD test.

), which also proved that the choice of tillage system should be derived from the soil type. In DSA, the concentration of the soil solution was higher, and the soil aggregates were strongly bound together through strong van der Waals forces and hydrogen and chemical bonds [78], while, in the WSA, it was the opposite. In the soils of drier areas of the Neogene sediments (HC, HL, and ER), the values of MWD_D were higher, and on the contrary, in the soils influenced by a high level of underground water (EF, MF, and DS), or stagnant water in the soil profile (DS), the values of MWD_W were higher. The MWD parameter was therefore significantly influenced by the soil type [76]. In the case of K_st (Figure 3f), the values were higher in more productive soils (MF > HC, EF) than in less productive (ER > HL > SP > DS). A higher value of this parameter meant that the size-favourable fractions of the aggregates dominated in the soil, the formation of which was supported by the organic matter, in which more productive soils were richer. Soil organic carbon is a key indicator of soil productivity [79]. Since the accumulation of organic carbon in larger aggregates is a part of carbon sequestration [80], the K_st can play the role of an indicator for the quantification of these mechanisms.

In general, the influence of a tillage system manifested in the Kst and WSA 0.5–3 mm parameters. Higher values of both parameters were in CT compared to RT (Figure 4a,b), while the statistically significantly lower contents of HA1 and FA1 (fractions of free acids) were recorded in CT compared to RT (Figure 5). Non-complexed organic carbon was not only unprotected from decomposition, but also it was not a part of the mechanisms of protection of the soil structure [81]. Overall, the influence of tillage manifested more in the parameters of the soil structure in more productive soils (EF, MF, and MF) than in less productive ones (HL, ER, and EG), with the exception of the DS (Table 7). It is a soil type that is specific by the seasonal stagnation of water, which is considered a consequence rather than a main paedogenesis process [82]. This can be the reason that soil usually has the opposite response to various factors than soils in which properties are the result of their genesis. DS was characterised by the highest content of FA, mainly FA1 and FA1a, and simultaneously the lowest content of FA2, the highest content of silt and also the lowest content of labile forms of organic carbon (C_L, CWEOC, and HWEOC) and nitrogen (N_L). In the process of ferrolysis, the clay decomposition and cyclic reduction and oxidation of iron and a part of aluminium occur [83]. In these conditions, there is a strong acidification of the soil, mainly the production of low-molecular organic substances, a dominance of fulvic acids in the humus-forming process. The proportion of free FA increases, those bounds with bivalent cations decrease, and labile organic forms manage to oxidise during the period of aeration.

In more productive soils, a higher number of larger aggregates are formed, the formation of which are also supported by higher organic inputs [4], so they are richer in carbon; therefore, the tillage effect manifested especially in the parameters of the soil structure in more productive soils. Within individual soil types, the influence of tillage manifested in more parameters of the soil structure. The proportions of macroaggregates and microaggregates in a certain soil type point to total aggregate stability [84], which can react differently to tillage, with dependence on a given soil type. It is interesting that the parameters of K_st and WSA 0.5–3 mm, which generally reacted with more sensitively to tillage, pointed, also within individual soil types, to a more favourable condition in CT, others (S_t, I_c, and MWDw) in RT, but there are also those (MWD_D), which indicated a more favourable condition in CT or in RT with a dependence on the soil type. The study of González-Rosado et al. [85] pointed to the fact that, if the soil is without vegetation, even no-till (NT) does not contribute to the increase of organic carbon in the individual fractions of aggregates, and overall, CT participates in the increasing of soil organic carbon more than NT. Simultaneously, they recorded more macroaggregates in CT and a smaller proportion of microaggregates in A-horizon compared to deeper parts of the soil profile than in the NT.

In the case of K_st and WSA 0.5–3 mm, there were also more significant correlations with the stabile organic (HA and FA) and nitrogen components, which proved that the aggregates, formed by stabile organic substances, were more resistant to disturbance [86]. Apart from the parameters of I_c and S_t, which included the organic carbon, some parameters (MWD_D, MWD_W, and K_w) pointed to the better condition of the soil structure at a lower stability of organic carbon. This fact was the result of, the smaller soil aggregates were, the less organic carbon they contained but were more stabilised. Lignin, lipids, or polysaccharides degrade and form complexes, e.g., ligno-saccharides, which are amphiphilic and tend to form aggregates [87]. This explains the findings that a lower stability of organic substances (Q_HS⁴⁶⁵/₆₅₀, Q_HA⁴⁶⁵/₆₅₀) corresponded to higher MWD_D or MWD_W values and a lower content of C_L, and a wider C_L/N_L ratio corresponded to a higher K_v value, etc. Intercropping increases the contents of labile carbon and nitrogen [88], which means that, if these inputs are absent, the condition of the soil structure is worse, which also reflects on the K_v value.

3.3. Suitability of the Parameters of Soil Structure for the Evaluation of Its Condition

Between the primary and secondary parameters, some dependence should be there; however, correlations between them have been recorded rarely (Figure 6). Ontl et al. [89] reported that physically protected organic matter was significantly influenced by the soil texture. Since the soil texture is a relatively stable soil parameter, the differences will be caused mainly by the quantity and quality of SOM, which is, on the contrary, a very dynamic parameter [8]. This was also confirmed by the correlations of the newly created parameters, the aggregate stability of small WSA (A_SW) and aggregate stability of large WSA (A_LW), with the SOM parameters (Figure 7a) and grain size fractions (Figure 7b). In the case of A_SW, in which WSA < 1 mm are included, a correlation with the soil texture is especially dominant, and in the case of A_LW, in which WSA > 3 mm are included, the effects of both the SOM and soil texture are relatively balanced. If we compare these dependences in the case of A_SW and A_LW, they are the opposite. Moreover, while in the case of A_SW, there is a negative correlation with the humus substances and a positive one with the clay fraction, in the case of A_LW, these correlations are the opposite. Fernandes et al. [75] found that clay is an important cementing agent in aggregates with sizes up to 2 mm, while organic carbon is in aggregates above 4 mm. A_SW has a negative correlation with the labile fractions of carbon (CWEOC and HWEOC), but A_LW has a negative correlation with non-labile carbon. This corresponds to findings of the authors that larger aggregates are richer in organic matter [35,90]; however, they are not the only labile components that are dominant. It is also true that smaller aggregates are poorer in organic carbon [91], though this does not have to be only the carbon of humus substances but also otherwise-stabilised organic substances. It follows that, for the evaluation of the sustainable condition of the soil structure, the K_st seems to be the most suitable of the tested parameters. This includes the ratio of, agronomically, the most valuable aggregates (WSA 0.5–3 mm) with the size shift of “acceptable” water-resistant aggregates (WSA 0.5–7 mm) and the aggregates indicating a deteriorating of the condition of soil structure, which are too small (WSA < 0.5 mm) or too large (>7 mm).

Since larger aggregates are more significantly influenced by tillage [92], and simultaneously, the changes in the SOM are very dynamic, the K_st, which reacted to the SOM the most sensitively, seems to be the most suitable one from the tested parameters. Moreover, according to Eze et al. [79], the organic carbon in macroaggregates seems to be a suitable indicator of the changes in SOC stocks.

4. Conclusions

The responses of the parameters of the soil structure to the soil type depended on the soil texture and soil organic carbon parameters. The effects of both manifested with a dependence on whether larger or smaller aggregates were a part of the parameters of the soil structure. They were more significantly influenced by the quality of the soil organic matter, especially the stabile humus substances, rather than the quantity. The tested parameters showed different results, which reflected the specifics of the soil types. They also indicated the different suitability of the tillage system to various soils. A special suitability of some of the soil structure parameters to the specific group of soils (more or less productive soils; soils of Neogene sediments) were recorded. The most suitable parameter for the evaluation of the sustainable condition of the soil structure seemed to be the coefficient of the structure (K_st), and the highest number of tested parameters manifested in Haplic Chernozem. Overall, the use of a particular parameter depended on many factors, which influence should be evaluated by the same parameter of the soil structure.