Adaptive Cultivation System as a Factor That Increases the Fertility and Productivity of Marginal Soils

Abstract

Modern agricultural production faces challenges, caused by soil degradation, declining natural fertility, and a lack of organic matter and productive moisture in the arable layer, which is especially relevant in the context of global climate change and rising prices for fuel and lubricants, mineral fertilizers, and plant protection products. Five tillage systems (moldboard, flat-cut, adaptive, shallow and surface) and three fertilization options (no fertilization, by-product, by product + N₆₅P₆₀K₇₀) were tested. The combination of adaptive cultivation and organic-mineral fertilization resulted in the highest input of crop by-products (up to 1.26 g cm⁻³), elevated humus reserves (69.2 t ha⁻¹ in the 0–40 cm layer), reduced bulk density in the root zone (down to 1.26 g cm⁻³), improved soil moisture conditions, and, consequently, the highest grain yield—4.34 t ha⁻¹, which is 7.4–21.4% higher than in other treatments. The use of adaptive cultivation with differentiation of the depth and type of loosening allowed the humus reserve to be increased to 66.4 t ha⁻¹, the productive moisture in the 0–40 cm layer to reach 86 mm, and ensured an increase in the yield of the grain units to 4.34 t ha⁻¹. The obtained results prove the validity of the efficient integration of the plant biomass on light-textured soils with low physicochemical parameters and humus content as a renewable resource in sustainable agriculture technologies, especially in conditions of climate instability and the rising costs of the resources.

1. Introduction

In the face of growing environmental, socioeconomic, and demographic challenges, modern systems and technologies for soil cultivation must primarily ensure the rational use, conservation, and enhancement of soil fertility, while also preventing degradation processes in agricultural landscapes [1,2].

Under contemporary conditions, especially in countries with unstable economies, rising prices for fuel, lubricants, mineral fertilizers, and plant protection products compel agricultural producers to seek ways to reduce resource and energy costs per unit of output [3].

Additionally, the diversity of soil and environmental conditions, stochastic weather patterns, and the multicultural specialization of crop production require a balanced approach to soil cultivation. This includes combining various agrotechnical solutions in terms of method (moldboard and non-moldboard) depth; resource efficiency—achieved through modernization of agricultural machinery fleets; and the use of wide-wheel tillage implements, with a reduction in traditional plowing volumes [4].

A study conducted in Lithuania assessed the long-term impact of different tillage practices on organic carbon content and CO₂ emissions in light loamy soils. Among deep plowing, shallow tillage, and no-tillage systems, the best results were achieved with no-tillage combined with straw return to the field. This method significantly increased SOC (soil organic carbon) concentration in the topsoil, reduced emissions, and improved soil physical properties. The results highlight the potential of no-till systems for sustainable agriculture under changing climate conditions [5].

Similarly, a study that analyzed the long-term impact of no-till and short-rotation crop rotation systems on saline soils demonstrated that the no-till method not only reduces soil salinity but also significantly increases organic matter content and improves soil structure.

The yields under such systems increased by 10–30% compared to traditional methods. These findings underscore the potential of the no-tillage method in the development sustainable agriculture under saline conditions [6].

A study analyzing the productivity of short-rotation crop rotations under different soil cultivation and fertilization systems confirmed the effectiveness of adaptive systems in conditions of a changing climate. The highest yield indicators were achieved through adaptive treatment combined with organo-mineral fertilization, yielding 5.31 t ha⁻¹ for winter wheat; for soybeans, it reached 3.37 t ha⁻¹.

This treatment increased yields by 35–54% compared to the control, while also improving soil structure and nutrient availability. The results confirm the efficiency of adaptive systems in a changing climate [7].

The minimizing the use of soil cultivation technologies, alongside economic demands (increased productivity, reduced costs, and competitiveness of the crop production), will also contributes to the greening, the restoration of soil fertility, and ultimately, ensures the sustainability of the agro-industrial sector of the economy [8,9].

An investigation conducted in the southern steppe of Ukraine analyzed the economic efficiency of different tillage systems in short term grain crop rotations. Among the compared methods, differentiated disc cultivation using the plant residues provided the highest profitability—73.5%—and the shortest payback period of only 1.4 years. This approach demonstrates high resource efficiency and financial sustainability in dryland regions [10].

Considering global trends and previous research findings [11,12], we are convinced that rational (adapted, differentiated, combined, etc.) mechanical tillage will remain an integral part of most farming systems, albeit with continuous evolution—toward reduced depth, frequency, and improved technological efficiency of application.

In the context of global climate change, including global warming, declining biodiversity, and increasing desertification—solving environmental problems has become a priority. The Paris Agreement on mitigating climate change, signed in December 2015, focuses exclusively on forest arrays. Undoubtedly, vegetation, including trees, is a powerful factor in the binding of atmospheric carbon dioxide through photosynthesis. However, the reserves of organic carbon in vegetation amount to 500 GtC, which is approximately four times less than in soils [13]. Therefore, soil is the largest carbon reservoir in the biosphere, and its role in the absorption and regulation of organic carbon is significant.

Soil may be a key factor regulating the carbon cycle and influencing changes in greenhouse gas concentrations in the atmosphere. Unsustainable use of agricultural and arable land can increase soil carbon emissions into the atmosphere in the form of carbon dioxide (CO₂), leading to higher greenhouse gas concentrations and accelerating climate change. The gradual transformation of grasslands and forests into cropland over the past few centuries has resulted in the loss of soil carbon stocks. Therefore, methods to restore degraded agricultural lands and increase organic carbon in the soil should play an important role in reducing greenhouse gas emissions and enhancing resilience to climate change [14,15].

To protect arable soils from declining organic carbon content, including losses caused by erosion, carbon-saving technologies have been developed that make it possible not only to preserve but also to increase carbon accumulation. The main approaches to maintaining or enhancing carbon reserves in arable soils include minimizing soil tillage, applying organic fertilizers, using crop rotations with grass sowing, and reducing fallow periods [16].

The novelty and relevance of the conducted research lie in the fact that light-textured soils with low humus content and poor physicochemical properties tend to develop high equilibrium bulk density, which limits the application of reduced tillage practices. We have attempted to find such agrotechnical processing techniques that will reduce the anthropogenic load during processing, while ensuring the restoration of the soil fertility and increasing the productivity of crops in crop rotation.

The aim of this research is to determine the impact of different cultivation and fertilization systems, with maximum utilization of plant production by-products as organic fertilizers, on changes in soil fertility indicators and the productivity of short-rotation grain crops.

2. Materials and Methods

Field investigations were conducted from 2021 to 2023 at a stationary experimental site (49.303206, 31.930814), located on coarse-grained light loamy soils with groundwater levels exceeding 5 meters in depth. The relief is flat with a slight lateral slope.

Gray forest soils are formed in the forest-steppe zone under conditions of periodically flushing water beneath the canopy of broad-leaved (oak with admixtures of linden, maple, and ash), mixed (birch with admixtures of fir and pine, or pine-birch with larch), and small-leaved (birch with admixtures of aspen) forests, characterized by diverse and abundant herbaceous vegetation. These soils are widespread throughout the temperate zone of the Northern Hemisphere. The parent materials in the European part of the continent include loess, loess-like deposits, mantle loams, and occasionally moraine sediments. Climate warming may enhance the fertility of gray forest soils by increasing organic matter content and extending the vegetation period. However, it can also lead to soil degradation due to intensified erosion and reduced moisture availability. Under climate change conditions, it is essential to apply agrotechnical practices that promote moisture retention and humus accumulation, such as appropriate fertilization and soil management techniques.

The experimental plot soil is characterized by low humus content, slightly acidic pH, high levels of available phosphorus, and low mobile potassium, with insufficient base saturation (76–78%). A typical feature of the granulometric composition of the cultivated layer is a high content of coarse dust fraction (53–63%) and a low amount of silt particles (13–18%), which genetically determines its high equilibrium bulk density (1.50 ± 0.1 g cm⁻³), thereby limiting the possibility of complete tillage minimization.

The short-rotation grain crop sequence in the stationary experiment included winter wheat, millet, oats, and soybean. Annual crop rotation was maintained throughout the research period.

Three fertilization treatments were applied:

a—no fertilizers (crop + root residues);

b—ncorporation of predecessor by-products (6.5–7.0 t ha⁻¹);

c—incorporation of predecessor by-products (6.5–7.0 t ha⁻¹) + N₆₅P₆0K₇₀ per hectare.

The total area of the plot was 200 m², with an accounting area of 120 m². The experiment was replicated three times with staggered sequential placement of experimental variants. Pest, disease, and weed control was carried out using an integrated system with a modern complex of pesticides.

Five primary tillage systems were examined in the research, as shown in Table 1.

Table 1. Primary tillage systems of soil.

Tillage System	Crops of the Crop Rotation, Depth of Tillage, cm
	Winter Wheat	Millet	Oats	Soya
Variable-depth mouldboard tillage (reference)	20–22	22–24	10–12	25–27
Variable-depth flat-cut tillage	16–18	22–24	10–12	25–27
Combined (adaptive) tillage	10–12	22–24	10–12	40–42
Shallow disk tillage	10–12	10–12	10–12	10–12
Surface disk tillage	6–8	6–8	6–8	6–8

Technological operations for primary tillage of soil are shown in Table 2.

Table 2. Technological operations for primary tillage of soil.

Tillage System	Technical Data
	Aggregate	Working Width, cm	Working Depth, cm
Variable-depth mouldboard tillage (reference)	ploughshare plough	105	27
Variable-depth flat-cut tillage	flat cutter–subsoiler	250	16–25
Chisel tillage	Chisel-deep ripper	250	0–45
Disk tillage	disk plough with a harrow	2.1	0–12
Pre–sowing illage	combined aggregate	3.6	4–8

The observations, analyses, and calculations presented in this study, including harvest accounting and yield structure indicators, were conducted in accordance with established methodological guidelines. The yield of feed units (f.u.), grain units (g.u.), and digestible protein (d.p.) was calculated using conversion factors: winter wheat (grain) 1.2 f.u., 1.0 g.u.; millet (grain) 0.96 f.u., 0.81 g.u; oats (grain): 1.0 f.u., 0.7 g.u; soybean: 1.38 f.u., 1.8 g.u [17].

Experimental data were processed using analysis of variance (ANOVA), a statistical method for comparing group means to determine significant differences. ANOVA decomposes the overall variability into components associated with different factors and tests whether the differences between means are statistically significant using the F-test. The null hypothesis of equal means is tested. For two groups, ANOVA is equivalent to the two-sample Student’s t-test for independent samples, with the F-statistic equal to the square of the corresponding t-statistic. Statistical reliability of the results was assessed using confidence intervals, standard deviation (S), and the coefficient of variation (V, %). All statistical analyses were performed using Microsoft Excel 2019 (Microsoft Corp., Redmond, WA, USA) and Statistica 13.5 (TIBCO Software Inc., Palo Alto, CA, USA).

3. Results

The research established that 5.59–6.93 t ha⁻¹ of crop by-products entered the soil annually across the crop rotation area, with the highest input observed under the adaptive cultivation system (+5.5% compared to the control). Gradually lower values were recorded under no-till technologies: flat-cut tillage (−6.8%), shallow disk (−7.5%), and surface disk tillage (−14.9%). Aboveground crop residues (3.46–4.32 t ha⁻¹) accounted for 61.7–62.3% of the total organic matter input, with the remainder consisting of root residues (Table 3).

Table 3. Mass of by-products in the grain crop rotation in various tillage systems, t ha⁻¹, 2021–2023.

Primary Tillage System	Mass of the Non-Marketable Part of the Crop *			± to Control, (Reference), %
	Crop Residues	Root Remains	Total Plant Residues
Variable-depth mouldboard ploughing, 10–30 cm (control, reference)	4.09	2.48	6.57
Variable-depth flat-cut tillage, 10–30 cm	3.80	2.33	6.12	−6.8
Combined (adaptive) tillage, 10–42 cm	4.32	2.61	6.93	5.5
Shallow disk tillage, 10–12 cm	3.77	2.31	6.08	−7.5
Surface disk tillage, 6–8 cm	3.46	2.14	5.59	−14.9
$\overline{\mathrm{X}}\pm S\overline{x}$	3.89 ± 0.15	2.37 ± 0.08	6.26 ± 0.23	–
S	0.33	0.18	0.51	–

* Average for four crops on a balanced fertilization background: by-products + N₆₅P₆K₇₀.

A multi-level redistribution of crop residues was confirmed (using winter wheat as an example) within the 0–30 cm soil layer, depending on the tillage method and depth. A relatively uniform layer-by-layer distribution of dry phytomass occurred only with annual ploughing. Chisel tillage occupied an intermediate position in terms of residue placement. Continuous disking (6–8 cm and 10–12 cm) resulted in residue concentration in the 0–10 cm layer (75% and 81%, respectively), leading to significant depletion of organic matter in deeper layers.

The investigated primary tillage and fertilization systems on coarse-dust light loamy soils revealed low humus content and reserves in the cultivated layer. The use of crop by-products as organic fertilizer, combined with permanent shelf cultivation or non-mouldboard adaptive systems, led to more uniform humus distribution throughout the soil profile (Table 4).

Table 4. The humus status depending on the tillage system and fertilization, mg kg⁻¹, 2021–2023.

Primary Tillage System	Soil Layer, cm	Fertilization System
		Without Fertilizers (Crop + Root Residues)		* by-Product of the Predecessor 6.5–7.0 t ha−1		* by-Product of the Predecessor 6.5–7.0 t ha−1 + N65P60K70
		Humus %	Humus Reserves, t ha−1	Humus, %	Humus Reserves, t ha−1	Humus, %	Humus Reserves, t ha−1
Variable-depth mouldboard ploughing, 10–30 cm (control, reference)	0–10	1.10	15.9	1.28	18.5	1.36	19.6
	10–20	1.24	17.9	1.23	17.7	1.48	21.4
	20–30	1.07	15.4	1.09	15.7	1.23	17.7
	30–40	0.86	12.4	0.91	13.1	0.90	12.9
	0–40	–	61.6	–	65.0	–	71.6
Variable-depth flat-cut tillage, 10–30 cm	0–10	1.20	17.2	1.20	17.2	1.46	21.0
	10–20	1.12	16.1	1.16	16.7	1.21	17.4
	20–30	0.98	14.1	0.97	13.9	0.99	14.2
	30–40	0.74	10.6	0.79	11.4	0.74	10.6
	0–40	–	58.0	–	59.3	–	63.3
Combined (adaptive) tillage, 10–42 cm	0–10	1.20	17.2	1.33	19.2	1.52	21.9
	10–20	1.09	15.7	1.27	18.2	1.44	20.7
	20–30	1.01	14.6	1.17	16.9	1.25	18.1
	30–40	0.67	9.6	0.84	12.1	0.95	13.7
	0–40	–	57.1	–	66.4	–	74.4
Shallow disk tillage, 10–12 cm	0–10	1.35	19.4	1.53	22.0	1.53	22.0
	10–20	1.05	15.1	1.16	16.7	1.32	19.0
	20–30	0.97	13.9	0.98	14.1	1.04	14.9
	30–40	0.84	12.1	0.74	10.6	0.83	11.9
	0–40	–	60.4	–	63.4	–	67.0
Surface disk tillage, 6–8 cm	0–10	1.29	18.5	1.58	22.7	1.48	21.4
	10–20	1.16	16.7	1.37	19.7	1.28	18.4
	20–30	0.95	13.7	0.93	13.4	1.23	17.7
	30–40	0.77	11.1	0.70	10.1	0.84	12.1
	0–40	–	60.1	–	65.9	–	69.6
$\overline{\mathrm{X}}\pm S\overline{x}$	0–40	–	59.4 ± 0.8	–	64.0 ± 1.3	–	69.4 ± 1.9
S	0–40	–	1.8	–	2.9	–	4.2

* By-products: the non-marketable part of the above-ground mass + crop residues + root residues.

The largest humus reserves were found in the 0–20 cm and 0–30 cm layers, representing 57% and 82% of the total, respectively. Incorporation of crop biomass and mineral fertilizers into the 0–30 cm layer ensured stable and uniform humus distribution.

Under adaptive cultivation (disking at 10–12 cm, ploughing at 22–24 cm, and chisel loosening at 40–42 cm), combined with by-products and mineral fertilizers, humus reserves reached 74.4 t ha⁻¹. This system provided not only uniform humus distribution in the 0–20 cm layer but also the highest organic matter reserve in the 20–40 cm layer (31.8 t ha⁻¹), exceeding surface disk tillage by 8.28 t ha⁻¹ (20%).The same differentiation is characteristic of the shallow disk system at 10–12 cm.

According to the latest data, the humus reserves had a fairly pronounced differentiation across the soil profile. In the upper 0–20 cm layer, the humus reserves accounted for more than 62.7% of the volume of organic matter in the 0–40 cm layer, and within 37%, or 1.7 times less, in the lower 30–40 cm soil layer, which indicates a significant impact of the shallow and surface disk tillage upon the distribution of by–products and mineral fertilizers in the soil profile, and generally affects the soil fertility due to the mixing of biomass only in the upper 10–12 cm layer.

The soil density is subject to its granulometric composition, the organic carbon content, weather conditions and it is adjusted in a pre-set mode by systemic processing measures, which, through the different-quality localization of mineral fertilizers, and especially by-products of plant growing as an alternative to classical agricultural resources (manure, compost, etc.), or vice versa, inhibit the processes of cultural soil formation [12].

A significant decrease in bulk density in the 0–10 cm layer was observed during crop emergence: from 1.35 g cm⁻³ (ploughing) to 1.26–1.27 g cm⁻³ (flat-cut and adaptive tillage), and 1.24–1.25 g cm⁻³ under shallow and surface disk tillage (Table 5). By mid-season (flowering-grain filling), the 10–30 cm layer under no-till systems remained denser (1.35–1.49 g cm⁻³) compared to ploughing (1.31–1.42 g cm⁻³), and was over-compacted (1.51–1.57 g cm⁻³) before harvest. This explains reduced moisture accumulation from precipitation under simplified tillage systems.

Table 5. Soil bulk density in the main phases of grain crop development, 2021–2022.

Tillage System in Crop Rotation	Soil Layer, cm	Soil Bulk Density, g cm−3
		Emergence	Flowering	Full Ripeness
Variable-depth mouldboard ploughing, 10–30 cm (control, reference)	0–10	1.35	1.37	1.45
	10–20	1.31	1.35	1.43
	20–30	1.38	1.42	1.50
Variable-depth flat-cut tillage, 10–30 cm	0–10	1.27	1.33	1.42
	10–20	1.34	1.39	1.49
	20–30	1.42	1.46	1.53
Combined (adaptive) tillage, 10–42 cm	0–10	1.26	1.31	1.41
	10–20	1.33	1.38	1.46
	20–30	1.39	1.43	1.51
Shallow disk tillage, 10–12 cm	0–10	1.24	1.34	1.40
	10–20	1.35	1.44	1.51
	20–30	1.44	1.48	1.55
Surface disk tillage, 6–8 cm	0–10	1.25	1.34	1.41
	10–20	1.37	1.46	1.53
	20–30	1.46	1.49	1.57
Least Significant Difference (LSD05), g cm−3	0–10	0.07	0.06	0.04
	10–20	0.05	0.05	0.04
	20–30	0.05	0.04	0.03

In winter wheat sowings, the lowest productive moisture content in the 0–100 cm layer was recorded under surface disk tillage (140 mm), 13.4% lower than under mouldboard ploughing (162 mm). In oat sowings, moisture reserves in the 0–20 cm and 0–40 cm layers were 38.8 mm and 93.1 mm, respectively—13.8% and 15.7% lower than under ploughing—due to reduced infiltration and increased evaporation (Table 6).

Table 6. Available soil moisture reserves in cereal sowings depending on the primary tillage systems, mm, 2021–2023.

Primary Tillage System	Soil Layer, cm	Winter Wheat				Oats
		Restoration of Vegetation (a)	Harvest (b)	± to the Control (Reference), %		Emergence (a)	Harvest (b)	± to the Control (Reference), %
				a	b			a	b
Variable-depth mouldboard ploughing 10–30 cm (control, reference)	0–20	39.9	31.2	–	–	45.0	35.6	–	–
	0–40	87.1	61.8	–	–	110	89.7	–	–
	0–100	162	102	–	–	175	169	–	–
Variable-depth flat-cut tillage, 10–30 cm	0–20	47.1	31.8	18.1	2.1	49.9	46.4	10.9	30.3
	0–40	99.3	59.9	14.0	−3.1	103	92.5	−6.4	3.1
	0–100	180	103	11.4	0.7	188	160	7.4	−5.6
Combined (adaptive) tillage, 10–42 cm	0–20	44.4	37.3	11.3	19.8	50.4	11.0	11.9	−69.2
	0–40	93.8	69.3	7.7	12.1	103	64.2	−6.4	−28.4
	0–100	156	106	−3.5	4.5	197	115	12.6	−32.3
Shallow disk tillage, 10–12 cm	0–20	45.7	26.9	14.5	−13.6	59.2	19.4	31.4	−45.5
	0–40	90.1	61.2	3.5	−0.93	115	48.0	4.3	−46.5
	0–100	166	104	2.7	1.7	198	88.5	13.5	−47.7
Surface disk tillage, 6–8 cm	0–20	36.2	30.3	−9.2	−2.8	38.8	20.0	−13.8	−43.8
	0–40	76.0	66.9	−12.7	8.2	93.1	56.4	−15.7	−37.1
	0–100	140	100	−13.4	−1.6	175	131	0.1	−22.9
$\overline{X}\pm S\overline{x}$	0–100	161 ± 6.5	103± 1.0	–	–	187 ± 5.1	133 ± 14.7	–	–
S	0–100	14.6	2.2	–	–	11.3	32.9	–	–

Note: When introducing by-products of the predecessor 6.5–7.0 t ha⁻¹ + N₆₅P₆₀K₇₀.

Moisture reserves decreased during harvest across all tillage systems, depending on precipitation and crop water use. In the 0–20 cm layer, reserves ranged from 11.0 to 46.4 mm; in the 0–40 cm layer, they reached 48–92.5 mm in oats and 59.9–69.3 mm in winter wheat, indicating satisfactory moisture levels under all systems, positively affecting yield formation.

During winter wheat harvest, adaptive tillage resulted in higher moisture reserves than mouldboard ploughing: +19.8% (0–20 cm), +12.1% (0–40 cm), and +4.5% (0–100 cm). The greatest decrease occurred under shallow and surface disk tillage (−13.6% and −2.8%, respectively)

At the time of oat harvesting, the reserves of productive moisture depended on the amount of precipitation during the growing season and the primary tillage system; there was a significant decrease in them with differentiated, shallow and superficial disc tillage in layers of 0–20 cm (11–20 mm), 0–40 cm (48–64 mm) and 0–100 cm (88–131 mm), which was due to a decrease in the depth of the soil tillage and a deficit of precipitation during May–June. The July (2021–2023) precipitation influenced the formation of good reserves of productive moisture during harvesting with the mouldboard and flat-cut soil tillage systems at 16–18 cm, where in the 0–40 cm layer, depending on the tillage system, they reached 89.7–92.5 mm and 160–169 mm in the 0–100 cm soil layer. However, it should be noted that the precipitation that fell in the second half of the growing season (2021–2023) of oat plants did not have a significant impact on the formation of its productivity but only replenished the soil layer with moisture and partially realized the potential of the plants which was laid during flowering in June.

The variability in grain crop productivity was linked to layer-by-layer differentiation of the soil profile (0–45 cm) in terms of physical, chemical, and biological fertility indicators under long-term tillage systems, systemic fertilization, integrated plant protection, and partly unfavorable weather conditions.

The results of the research have established a proportional increase in the yield of the grain units as a determining criterion for the assessment of economic efficiency, with the intensification of the agricultural background in the direction of: 2.79 t ha⁻¹ grain units when using natural soil fertility; 3.28 t ha⁻¹ grain units (+17.6%) in the variants of the biological fertilization system and 3.90 t ha⁻¹ grain units (+39.8%) in modern models of combined organo-mineral fertilization (6.5–7.0 t ha⁻¹ by-products + N₆₅P₆₀K₇₀), on average, from five polar soil cultivation systems (Table 7).

Table 7. Productivity of the grain short-rotation crop rotation depending on various primary tillage and fertilization systems, average for 2021–2023.

System		Crop Rotation Productivity, t ha−1
Soil Tillage	Fertilizers	Grain Harves–Ting	± to the Control (Reference)		Feed Units	Grain Units	Protein Collection
			t ha−1	%
Variable-depth mouldboard ploughing 10–30 cm (reference)	a	2.80	–	–	3.18	3.02	0.39
	b	3.38	–	–	3.85	3.65	0.47
	c	3.86	–	–	4.41	4.21	0.55
Variable-depth flat-cut tillage, 10–30 cm	a	2.69	−0.11	−3.9	3.07	2.90	0.38
	b	3.07	−0.31	−9.2	3.51	3.34	0.44
	c	3.57	−0.29	−7.5	4.08	3.90	0.51
Adaptive (combined) tillage, 10–42 cm	a	2.88	0.08	2.9	3.28	3.11	0.40
	b	3.37	−0.01	−0.3	3.84	3.64	0.47
	c	4.00	0.14	3.6	4.57	4.34	0.56
Shallow disk tillage, 10–12 cm	a	2.56	−0.24	−8.6	2.92	2.73	0.35
	b	2.96	−0.42	−12.4	3.36	3.16	0.41
	c	3.50	−0.36	−9.3	3.98	3.74	0.48
Surface disk tillage, 6–8 cm	a	2.04	−0.76	−27.1	2.33	2.21	0.29
	b	2.41	−0.97	−28.7	2.75	2.61	0.34
	c	3.12	−0.74	−19.2	3.54	3.31	0.43
LSD05, g cm−3		0.26	–	–	0.33	0.31	0.05

Note. Fertilizers: a—without fertilizers (natural fertility); b—application of by–products of the predecessor 6.5–7.0 t ha⁻¹; c—application of by-products of the predecessor 6.5–7.0 t ha⁻¹ + N65P60K70.

The lowest productivity level of the experimental grain crop rotation in the context of three-level fertilization backgrounds was obtained with annual surface disc cultivation to a depth of 6–8 cm (2.21–3.31 t ha⁻¹ grain units), that is, in the most simplified system of primary tillage, and the highest (3.11–4.34 t ha⁻¹ grain units)—under the condition of a clear distinction between both the method and the depth of mechanical loosening of the soil, taking into account the biological characteristics of each crop, namely: shallow disc tillage (at 10–12 cm) for winter wheat and oats; strip chisel tillage (40–42 cm) for soybeans; and plowing at 20–22 cm for soybeans with mandatory adjustment of the fertilization system and the integrated crop protection system from harmful organisms (Figure 1).

Figure 1. Harvesting of grain, cereals and fodder units in the most productive soil cultivation options (6.5–7.0 t ha⁻¹ + N₆₅P₆₀K₇₀).

The average crop rotation productivity for 2021–2023 with the adaptive (differentiated) primary tillage system (4.34 t ha⁻¹ grain units) is slightly higher (+3.1%) than with moldboard ploughing. At the same time long-term use of: variable-depth flat-cut, shallow, and, especially, surface disc tillage leads to a significant decrease (−10.1–28.6%) in the yield of a hectare of the crop rotation area (up to 3.90–3.10 t ha⁻¹ grain units).

Assessment of economic and energy efficiency showed that the use of an adaptive (combined) soil cultivation system ensured the production costs at the level of 91–98 €∙t⁻¹, a conditional net income of 433–594 €∙ha⁻¹, and a profitability level of 149–160%.

In addition, the energy efficiency coefficient (K_ee) reached the level of K_ee = 3.2–4.2. The most effective was the introduction of 6.5–7.0 t ha⁻¹ of by-products against the background N₄₀P₅₀K₆₀, where K_ee = 3.2 (Table 8).

Table 8. Economic and energy efficiency of growing crops in a short-rotation crop rotation depending on the primary tillage and fertilization, 2021–2023.

Soil Tillage System (Factor A)	Fertilizers *	Prime Cost of Grain, €∙t−1	Conditional Net Income, €∙ha−1	Profitability Level, %	** Kee
Variable-depth ploughing, 10–30 cm (reference)	a	106	377	129	3.9
	b	101	466	140	3.7
	c	107	531	128	3.0
Variable-depth flat-cut tillage, 10–30 cm	a	110	345	122	4.0
	b	106	421	131	3.6
	c	112	461	118	2.9
Adaptive (combined) tillage, 10–42 cm	a	96	433	153	4.3
	b	91	523	166	3.9
	c	98	594	149	3.2
Shallow disk tillage, 10–12 cm	a	108	345	126	3.9
	b	103	419	138	3.6
	c	113	458	115	2.9
Surface disk tillage, 6–8 cm	a	132	233	85	3.2
	b	123	297	98	3.0
	c	124	366	97	2.5

Note. * a—without fertilizer (natural fertility); b—application of by-products from the previous crop—5.0–6.0 t ha⁻¹; c—application of by-products from the previous crop 6.5–7.0 t ha⁻¹ + N40P50K60 for soybeans and N60P60K70 for millet. ** Kee—energy efficiency coefficient.

Based on the obtained research results, there was established the impact of long-term use of various tillage and fertilization systems upon changes in fertility indicators of coarse-dust light loamy soils and the productivity of short-rotation grain crop rotation. Clear differentiation of the soil profile was noted in terms of the humus content and reserves, the bulk density, the productive moisture reserves depending on the method and depth of the soil tillage, the amount and nature of introduction of by-products of the predecessors.

The analysis showed that a direct correlation was established between the output and introduction into the soil of the total (by-products (non-marketable part of the above-ground mass), + crop and root residues) amount of plant residues and the content and reserves of humus, at the level of strong correlation (R = +0.71–0.75, R² = 0.50–0.56), and for 1 ton of the incorporated plant residues there is an increase of 0.078% and 5.2 t ha⁻¹ in the content and reserves of humus. An inverse correlation was found between the amount of the plant residues collected and the the soil bulk density during the vegetation phases, which increased from the sowing (R = −0.73, R² = 0.53) to the flowering phase (R = 0.91, R² = 0.83) and decreased slightly (R = −0.86, R² = 0.74) during the harvesting period. According to the regression coefficients the highest soil loosening was during the flowering phase where the regression coefficient was 1.7–2.5 times higher than during sowing and harvesting when the increase in the application of a ton of the crop residues accounted for a soil loosening of 0.05 g cm⁻³ with a correlation coefficient of R = −0.91, R² = 0.82 (Table 9).

Table 9. Regression equations for the relationship between the main soil indicators and the output of by-products *.

Indicators	Regression Equation	Determination, R2
Yield (Output) of the Crop Residues, t∙ha−1
Humus content, %	y = 0.84 + 0.078x	0.47
Humus content, t ha−1	y = 37.0 + 5.15x	0.50
Bulk density, g cm−3 (seeding)	y = 1.45 − 0.02x	0.53
Bulk density, g cm−3 (flowering)	y = 1.69 − 0.05x	0.83
Bulk density, g cm−3 (harvesting)	y = 1.67 − 0.03x	0.73
Soil moisture reserves, mm
0–100 cm	y = 129.7 + 6.93x	0.21
0–20 cm	y = −10.9 + 7.72x	0.48
0–40 cm	y = 59.3 + 4.02x	0.50

* By-products: non-marketable part of the crop + crop residues + root residues.

The relationship between the amount of the introduced plant residues and the moisture reserve in a meter-thick layer was at the level of a weak direct correlation, but between the moisture reserve in a 0–20 cm and 0–40 cm layers the correlation increased to a direct correlation at the average level (R = +0.63–0.65, R² = 0.40–0.42), and introduction of 1 ton of the crop residues contributed to the accumulation of 4.02–7.72 mm of the productive moisture reserve.

The accumulation of productive moisture reaches its peak at the flowering stage of 30–40, confirming its critical role in the formation of the crop yields. Thus the results of the research underline the importance of adaptive soil tillage at all the growth stages in order to ensure sustainable and efficient agriculture.

Increasing the humus reserves in the 0–30 cm thickness per 1 t, the density of the structure during sowing decreases by 0.035 g cm⁻³, during the flowering phase—by 0.025 g cm⁻³, as well as during the harvesting phase. It has been revealed that there is a direct strong correlation between the bulk density of the 0–30 cm soil layer at sowing, the density in the flowering phase and full ripeness, but at the time of sowing the bulk density increases by 0.01 g cm⁻³, in the flowering and full ripening phase the bulk density increases by 0.02–0.03 g cm⁻³.

In the equations of dependence of the value of the bulk density at the time of sowing and in the phases of flowering and full maturity, the regression coefficients have high values, which indicates that a high level of the sowing density determines rapid compaction of the soil in subsequent phases of the crop development and, conversely, when the density during sowing is low, then compaction in the subsequent phases was insignificant, which occurs during sowing, when the soil density does not exceed 1.25–1.27 g cm⁻³. The regression equations of the relationship show that an inverse correlation was found between the grain harvesting and the compaction density at the level of strong inverse correlation (R = −0.73–0.89 ± 0.02, R² = 0.53–0.79).

A direct correlation was found between the humus reserve in a 0–30 cm layer and the harvested grain at an average level, and with the yield of the grain units and protein, the relationship weakened to the level of weak correlation (R = 0.48–0.49) (Table 10).

Table 10. Regression equations for the dependence of grain yield on the main soil indicators.

Grain Output (Yield), t∙ha−1		Determination, R2
Indicators	Regression Equation
Humus content, %	y = 0.95 + 0.11x	0.12
Humus content t ha−1	y = 44.3 + 6.88x	0.30
Bulk density, g cm−3 (sowing)	y = 1.43 − 0.024x	0.53
Bulk density, g cm−3 (flowering)	y = 1.65 − 0.07x	0.86
Bulk density, g cm−3 (harvesting)	y = 1.65 − 0.048x	0.76
Soil moisture reserves, mm
0–100 cm	y = 131.2 + 11.6x	0.24
0–20 cm	y = −3.56 + 11.3x	0.37
0–40 cm	y = 62.6 + 5.9x	0.42

The calculation showed that a strong inverse correlation was established between the bulk density and the productivity indicators during the sowing period (R = −0.67–0.73, R² = 0.44–0.53), between the bulk density during the flowering period and productivity the correlation increased to R = −0.94–0.97, R² = 0.88–0.94, and the strength of relationship between these parameters was maintained during the ripening period of the crops. Between the productivity indicators and the moisture reserves in the 0–20 cm and 0–40 cm layers, the relationship weakened to a direct strong correlation: R = 0.55–0.64, R² = 0.30 − 0.41.

In the sowing–flowering–harvesting sequence the correlation coefficient value increases between the grain harvest and the bulk density. During the sowing period R = −0.73, R² = 0.53, during the flowering period the correlation coefficient increases by 1.3 times, and during the harvesting period by 1.2 times, and the determination coefficients increase within the range of 1.49–1.60 times.

The regression coefficients in the dependence equations increase from the sowing period to the flowering phase by 2.9 times and decrease slightly relative to the flowering phase by 1.4 times, and increase relative to sowing by 2 times, which indicates the need to achieve the lowest value of the bulk density in the flowering phase to obtain the highest grain yield.

The correlation between the grain yield and moisture content in the 0–100 cm layer in spring was at the level of direct correlation of average level (R = 0.49, R² = 0.24). A higher correlation was established between the reserve of the productive moisture in the 0–40 cm layer and grain harvest (R = 0.65, R² = 0.43). According to the regression coefficient it was found that for every unit of the grain yield growth there is a 0.066 units of productive moisture reserve.

An important aspect is the attempt to classify the parameters that were used to evaluate the indicators of the humus status, the bulk density, the moisture reserve, and indicators of productivity and quality of the crop according to the experimental variants, as a whole, which makes it possible to standardize their change in agrocenosis under various agrotechnological impacts on the agrocenosis of coarse-dust light loamy soils (Table 11).

Table 11. Typification of the main parameters for the experimental variants, as a whole.

Indicators	Average	Median	Amplitude Range, ∆a		Quantiles		Δa	K, %
			Min.	Max.	L0.25	L0.75
By-product, t ha−1	6.26	6.12	5.59	6.93	6.08	6.57	1.34	8.2
Humus content, % (0–30 cm)	1.33	1.33	1.22	1.41	1.31	1.36	0.19	5.3
Humus content, t ha−1 (0–30 cm)	69.2	69.6	63.3	74.7	67.0	71.6	11.4	6.3
Bulk density, g cm−3
Sowing	1.34	1.34	1.33	1.36	1.34	1.35	0.03	0.85
Crop flowering	1.40	1.39	1.37	1.43	1.38	1.42	0.06	1.85
Harvesting	1.48	1.48	1.46	1.51	1.47	1.48	0.05	1.26
Moisture reserve, mm (sowing)
0–100 cm	173.2	176.0	157.0	185.0	166.0	182.0	28.0	6.7
0–20 cm	37.4	38.0	28.0	45.0	35.0	41.0	17.0	17.2
0–40 cm	84.4	86.0	80.0	88.0	82.0	86.0	8.0	3.9
Moisture reserve, mm (harvesting)
0–20 cm	29.4	25.0	23.0	40.0	25.0	34.0	17.0	24.8
0–40 cm	67.4	67.0	55.0	77.0	62.0	76.0	22.0	13.9
0–100 cm	111.2	111.0	97.0	121.0	111.0	116.0	24.0	8.1
Grain output (yield), t ha−1	3.63	3.57	3.15	4.05	3.51	3.86	0.90	9.5
Feed output (yield), t ha−1	4.12	4.08	3.55	4.57	3.98	4.41	1.02	9.7
Grain yield (output), t ha−1	3.90	3.91	3.31	4.34	3.74	4.21	1.03	10.4

The average output (yield) of the plant residues was 6.26 t ha⁻¹ with an amplitude range of 1.34 t ha⁻¹, which determined the coefficient of variation of the plant residue introduction to be 8.6%. The average humus content in the 0–30 cm soil layer was 1.33% with an amplitude range of ∆_a = 0.19%, which provided an oscillation coefficient of 14.3%, and the coefficient of variation of the humus content was 5.3%. The average humus reserve was at the level of 69.2 t∙ha⁻¹ with an amplitude range of ∆_a = 11.4 t ha⁻¹ with an oscillation coefficient of Kos = 16.5% and a variation coefficient of 6.3%.

The average value of the bulk density during the sowing period was 1.34 g cm⁻³ with an amplitude range of ∆_a = 0.03 g cm⁻³ (K_oc = 2.2%), which provided a correlation coefficient at the level of 0.85%. During the flowering phase, the bulk density was 1.40 g cm⁻³ (+0.06 g cm⁻³) with ∆_a = 0.06 g cm⁻³ and K_oc = 4.2%, which provided K_v = 1.85%.

The average value of the bulk density was 1.48 g cm⁻³ (+0.14 g cm⁻³) at ∆_a = 0.05, K_oc = 3.38%, which provided K_v = 1.26%. The humus and agrophysical state indicators have low values of K_oc and K_v, which indicates the stability of the soil system against the agrotechnical effects of processing coarse-dust light loamy soil. The average reserve of productive moisture in spring in the 0–100 cm layer was 173.2 mm, but the median was 176 mm, which by its value tended to the upper typical value (L_0.75 = 182 mm). The amplitude range of the moisture content was 28 mm with K_oc = 16.2% and K_v = 6.7 mm.

On average, the moisture content in the 0–20 cm layer was 29.4 mm at ∆_a = 17 mm and K_os = 5.8%, which affected K_v, which reached the level of 24.8%. In a 0–40 cm thickness the average moisture reserve was 84.4 mm, a which the median was more inclined towards the upper typical value (L_0.75 = 87 mm) with ∆_a = 8 mm, K_oc = 9.5% and K_v = 3.9%. The productive moisture supply block was characterized by insignificant deviations in amplitude in the 0–20 cm and 0–40 cm layers with high variability of moisture reserves in the 0–20 cm layer, and in the meter layer, the variability indicators indicate a significant difference in the formation of the moisture reserves under the influence of different tillage and fertilization systems. The average grain yield was 3.63 t ha⁻¹ with ∆_a = 0.90, K_oc = 26.8% and a variation coefficient <10%. On average, the ouput (yield) of the feed units (f. u.) was 4.12 t ha⁻¹ with ∆_a = 1.02, K_os = 24.8% and K_v < 10%. The average output (yield) of the grain units was 3.90 t ha⁻¹, ∆_a = 1.03, K_oc = 26.1% at K_v > 10% (Table 10).

Clustering of the productivity indicators with the fertility parameters of the coarse-silted light loamy soil showed that the grain yield (t ha⁻¹), bulk density of the 0–30 cm soil layer (g cm⁻³) by periods of growth of the agrophytocenosis crops and the humus content (%) are combined into one cluster (K − 1) at a distance level of 8–10%. The moisture reserve indicators in the 0–20 cm layer during sowing and harvesting form a new cluster (K − 2), combining with K − 1 at a distance of 18–20%. The moisture reserves in the 0–100 cm layer (harvesting), in the 0–40 cm layer at the time of sowing and harvesting and the humus reserves (t ha⁻¹) form a consistently growing cluster, which is combined with K − 1 − 2 at a distance of about 50%. The moisture reserve in the 0–100 cm layer at the time of sowing had a distance from K − 1 − 3 at the level of 100%, which showed a low level of correlation with the formation of agrocenosis productivity.

4. Discussion

Thus, the significant impact of soil tillage methods and fertilization systems on coarse-dust light loamy soils is reflected in the formation of the moisture regime. Indicators such as humus content, bulk density, and crop rotation productivity vary within a narrow range, yet they exert a substantial influence on yield formation. This highlights the relative inertness of coarse-dust light loamy soils to agrotechnical interventions.

To ensure efficient and competitive agricultural production, it is essential to maintain sufficiently high soil quality indicators, which primarily depend on the organic matter content [18]. Our research confirms that achieving a deficit-free balance of organic matter in the soil—while reducing mineral fertilizer input—largely depends on the regular replenishment of the arable layer with non-marketable aboveground biomass and crop residues.

In particular, the use of by-products as organic fertilizer, combined with permanent mouldboard cultivation or non-mouldboard tillage of varying depths (adaptive tillage system), results in more uniform distribution of humus content and reserves throughout the soil profile.

Deep tillage promotes moisture penetration into deeper soil layers, enhancing crop root development and improving the uptake efficiency of ash and nitrogen nutrients [19,20].

According to our data, such conditions in adaptive tillage systems for short-rotation crops are achieved through autumn ploughing for millet and deep chisel tillage for soybean. The autumn–winter period is critical for these crops to accumulate sufficient moisture before sowing. For cereal crops, shallow disk cultivation at 10–12 cm is effective when applied after ploughing and deep chisel tillage.

An investigation conducted at the research farm of the Latvian University of Life Sciences and Technologies confirmed the possibility of reducing tillage intensity when growing winter wheat. The main factors influencing stable yields were crop predecessors and meteorological conditions [21].

Results from another study showed that the tillage system had a significant (p < 0.05) effect on the area and length of the flag leaf. On average, flag leaf area was 5.1 cm² larger and length 4.5 cm greater under conventional tillage compared to minimum tillage. A strong positive correlation between spring wheat yield and flag leaf area was observed: r = 0.854 under conventional tillage and r = 0.958 under minimum tillage [22].

Experimental field results indicated a 1.9–14.8% decrease in crop rotation yields when only shallow no-till cultivation was used, compared to differentiated (adaptive) systems [23].

The advantage of traditional tillage was confirmed by research in Serbia on heavy soils with 3.10% humus content. The use of non-mouldboard ploughing, especially no-till technology, led to a 12.1–28.9% reduction in winter wheat yields [24].

Chinese researchers propose optimizing soil cultivation by combining traditional ploughing with no-till technology to reduce investment costs, improve soil conditions, increase grain yields, enhance agroecosystem stability, and ensure consistent production under extreme climatic conditions [25].

Consequently, adaptive (differentiated) tillage systems improve soil physical properties, enhance precipitation accumulation, and increase initial moisture reserves in the 1-meter soil layer by 10–30 mm. They also boost short-rotation grain crop productivity by 0.44–1.03 t ha⁻¹ compared to non-mouldboard systems such as flat-cutting, shallow disking (10–12 cm), and especially surface disking (6–8 cm).

In conclusion, economically justified results from adaptive tillage technologies are achievable only when implemented timely and in strict accordance with application guidelines. This ensures sustainable crop yields, preservation and enhancement of soil fertility, and improved ecological conditions in agricultural landscapes.

Our studies show that adaptive primary tillage systems, combined with organic fertilizers (crop by-products), positively affect the agrophysical state of light loamy soils. Stable correlations were found between plant residue quantity, humus status, bulk density, and water conditions in the arable layer. Adaptive tillage with differentiated depth and loosening type increased humus reserves to 66.4 t ha⁻¹, productive moisture in the 0–40 cm layer to 86 mm, and grain unit yield to 4.34 t ha⁻¹. These results confirm the effectiveness of integrating biomass as a renewable resource into sustainable farming, especially under climate instability and rising resource costs.

The Forest-Steppe soils in arid conditions are more sensitive to the climate changes (air temperature and the amount of precipitation) than the Polesie soils with increased moisture. The dynamics of the soil properties, determined by the climatic factor in the territory of the European Forest-Steppe, made it possible to identify the influence of short-term climate changes on surrounding natural objects, such as chernozems and gray forest soils [26]. A moderate relationship was found between the soil moisture and the hydrothermal coefficient according to Selyaninov. In addition, there is a 2–3-year delay of the changes in the soil moisture values from the changes of hydrothermal conditions. It has been established that a climate change can significantly affect the soils and their properties. In particular, the investigations, conducted in Central Canada, show a response of the organic matter of soil to the climate dynamics [27]. Another aspect, concerning soil erosion, related to the amount of precipitation that fell between 1989 and 2007, was discussed in an article by the German researchers [28]. Having identified the trend of the climate change, they developed forecast models up to 2100, reflecting the rate of the soil erosion processes. Negative changes in the water-physical properties of Forest-Steppe soils lead to reduced precipitation absorption during winter–spring and growing seasons. Soils become increasingly dependent on weather and climate, and vulnerable to degradation processes such as active dehumification across the entire profile. This results in reduced agrocenosis productivity and diminished agricultural potential of Forest-Steppe soils [29,30].

One of the key tasks in preventing further soil degradation is optimizing moisture conditions in chernozems and gray forest soils within Forest-Steppe agrocenoses. This involves applying soil-protective and moisture-saving agrotechnologies that reduce moisture loss, promote accumulation and conservation during autumn–winter and spring vegetation periods, and create conditions for humus formation. These measures support the realization of agricultural potential under global climate change.

A comparison of available data on atmospheric carbon dioxide deposition by agrophytocenoses, nitrogen fixation in the rhizosphere, agrophysical optimization, and humus formation in agrocenoses reveals strong interconnections. These processes are closely linked, with a direct strong correlation (R = >+0.75; R² = 0.56).

A schematic representation of these interactions is shown in Figure 2. It illustrates that atmospheric CO₂ deposition by agrophytocenoses in multi-rotational crop systems and soil formation (organic matter deposition into humus) should be considered structural components of a unified system. These components interact synergistically and accumulate cumulatively under the influence of soil-protective cultivation practices in agrocenoses (Figure 2).

Figure 2. Diagram of the interaction of the process of atmospheric CO₂ deposition, humus formation, improvement of the agrophysical condition, the process of strengthening the soil moisture conditions during the realization of the agropotential of former soils under the conditions of climate warming in the Forest-Steppe.

It is well known that the irrational use of agricultural land resources leads to the deterioration of the soil’s physical, agrochemical, and biological properties. Consequently, this results in reduced fertility, lower income, and degradation of the natural environment as a whole. Soil fertility and its value depend on indicators such as sufficient levels of organic carbon, total nitrogen, phosphorus, humic acids, and other components [31]. The choice of pre-sowing cultivation methods and crop rotation also plays an important role in determining soil quality.

Over the past 200 years, losses of soil organic carbon have increased significantly due to the expansion of agricultural land and the intensification of soil cultivation. This has led to a noticeable decline in initial humus reserves in the 0–30 cm and 0–100 cm soil layers—by 26% and 16%, respectively [32]. Thus, the loss of organic carbon in agricultural soils reduces soil quality, threatens food security, and contributes to climate change by increasing atmospheric CO₂ levels [33].

One method for preserving the fertility of gray forest soils is the adoption of soil-protective (adaptive) cultivation systems, which have become increasingly popular worldwide. Zero tillage, as one form of adaptive agriculture, is a key component of resource-saving farming, as sowing is performed through the soil cover with minimal disturbance [34]. Some sources note that this significantly increases humus content across various soil types, climatic conditions, and agricultural systems [35,36].

An important issue is the potential of adaptive tillage to contribute to carbon sequestration. Some data suggest that the difference in humus content between ploughed and adaptively tilled soils is minimal or absent when samples are taken deeper than 30 cm [37], which is attributed to insufficient root-derived carbon supply to deeper soil layers [38,39,40]. While adaptive tillage generally promotes the accumulation of soil organic carbon in surface layers and increases microbial biomass [41], several studies have shown that this effect may be partially or fully offset by higher humus content in deeper layers under full-rotation tillage.

In most studies conducted over five years, humus content was significantly higher under adaptive tillage compared to surface tillage. However, at depths of 21–25 cm—corresponding to the average ploughing depth (23 cm)—humus content was notably higher with conventional ploughing [41]. Regarding the increased input of carbon and nitrogen fertilizers, regardless of the tillage system, this leads to significant humus binding in surface layers of carbon-depleted soils [40,41,42]. Several studies have shown that humus losses in deeper soil layers may result in overall profile depletion, both in conventionally cultivated soils and those managed with adaptive systems [43,44,45,46].

5. Conclusions

The investigation confirmed that the efficient formation of productive moisture reserves in coarse-silted light loamy soils is significantly enhanced by primary cultivation methods (adaptive and mouldboard ploughing) and the targeted placement of predecessor by-products within the cultivated organic matter layer. This approach exhibits a moisture-accumulating effect and promotes additional moisture retention in the topsoil layer (13.2–15.0%), even under conditions of a one-third deficit in off-season atmospheric precipitation.

It was also found that a reliable reduction in bulk density in the 0–10 cm soil layer is achievable during the resumption of winter wheat vegetation and full emergence of oats—from 1.36 g cm⁻³ (variable-depth ploughing) to 1.27–1.28 g cm⁻³ (flat-cut and adaptive cultivation), and further, to 1.25–1.26 g cm⁻³ under surface and shallow disk tillage.

The average productivity of short-rotation grain crops under a differentiated primary tillage system (4.34 t ha⁻¹ grain units) exceeded that of mouldboard ploughing by only 3.1%. However, annual non-mouldboard tillage—flat-cutting, shallow disking (10–12 cm), and especially surface disking (6–8 cm)—resulted in a significant decrease in productivity (by 7.4–21.4%), reducing yields to 3.31–3.90 t ha⁻¹ grain units.

A proportional increase in grain unit yield, as a key criterion for assessing economic efficiency, was observed with the intensification of the agricultural background: 2.79 t ha⁻¹ grain units when using stubble and the root residues; 3.28 t ha⁻¹ grain units (+ 17.6%)—in the variant of introduction of the by–products of the predecessor and 3.90 t ha⁻¹ grain units (+ 39.8%) in modernized models of combined organo–mineral fertilizer (6.5–7.0 t ha⁻¹ by–product + N₆₅P₆₀K₇₀) on average, of the five presented soil cultivation systems, the most efficient was the adaptive (combined) soil tillage system at 10–42 cm.

Since complete decomposition of by-products may take 5–8 years, it is advisable to continue experiments using a similar methodology over a comparable cycle. Including leguminous crops (e.g., clover, alfalfa) in the crop sequence could further enrich the soil with organic matter and enhance long-term fertility.