Optimizing Soybean Productivity: A Comparative Analysis of Tillage and Sowing Methods and Their Effects on Yield and Quality

Abstract

This study underscores the critical role of tillage methods in optimizing soybean yield and quality. Plowed tillage + strip-drill sowing (PSD) offers a balance between crop productivity and quality by maintaining soil structure while enhancing nutrient availability. Reduced tillage methods such as zero tillage + strip-drill (ZSD) and no-plowed tillage + strip-drill (NSD) can improve leaf greenness by about 10–15% and pod numbers by 6.7% and 3.5%, respectively. However, such methods may reduce seed quality and germination capacity, impacting the overall yield. In contrast, plowed tillage + conventional row sowing (PCR) promotes balanced nutrient composition and carbohydrate production under optimal soil conditions. Tillage practices significantly influence nutrient components such as ash content, which ranges from 55.8 g kg⁻¹,(PCR) to 57.4 g kg⁻¹ (ZSD). ZSD was found to enhance protein levels by 3% at the expense of carbohydrates, likely due to improved nutrient retention. The present analysis highlights ZSD as an effective method for stabilizing protein yield (mean value 843.8 kg ha⁻¹) and fat yield (mean value 449.3 kg ha⁻¹) across variable environments, supporting the use of ZSD in conservation agriculture. Future studies should explore how tillage practices affect soil health, economic sustainability, and yield stability over time, especially under changing climatic conditions. Optimizing plant density, enhancing seed traits, and improving germination can collectively drive significant improvements in soybean productivity across diverse agro-ecological zones.

1. Introduction

Soybean [Glycine max (L.) Merr.] is an important legume crop worldwide due to its rich protein content, oil content, and functional components [1,2]. As a food, soy consumption has historically been associated with Asian countries such as China and Japan, rather than the United States [3]. The basis for food production in many countries is seeds. In addition to their direct consumption, seeds serve as a processed food used in animal feed production [4]. Thus, the importance of soybean (Glycine max L.) as a global crop cannot be overstated, given its dual value as a source of high-quality protein and oil for food production, animal feed, and biofuel industries [5]. The global demand for soybean has been increasing in recent years, due to rapid economic growth in the developing world and depreciation of the US dollar [6]. In response to this demand, its production has been increasing worldwide, through a combination of increased production area and greater yield [7]. At the same time, the growing demand for sustainable production in the face of climate change and resource scarcity emphasizes the need for optimized agronomic practices that enhance productivity without compromising environmental integrity [8]. Soil tillage methods are particularly influential in this context, shaping soil structure, nutrient dynamics, and water availability, all of which directly affect crop performance [9]. The increasing demand for protein in food and fodder has led to efforts to expand soybean cultivation in Poland [10]. For economic, environmental, and climatic reasons, soil cultivation methods without the use of a plow have become increasingly popular in recent decades [11]. Partial plowed tillage with strip-drill sowing has gained attention as an effective strategy that balances yield optimization and soil preservation. This method minimizes the trade-offs associated with other systems, such as direct sowing (zero tillage), which improve the biometric features of plants but often reduce seed quality and germination capacity. Conversely, conventional plowing promotes nutrient availability, particularly enhancing carbohydrate levels, but may not support the long-term goals of conservation agriculture due to its impact on soil degradation. Moreover, strategies to increase the soil carbon pool include soil restoration and woodland regeneration, no-till farming, cover crops, nutrient management, manuring and sludge application, improved grazing, water conservation and harvesting, efficient irrigation, agroforestry practices, and growing energy crops on spare lands [12]. These findings underscore the need for a nuanced understanding of tillage systems tailored to specific agro-ecological conditions. Integrating moderate tillage approaches such as plowed tillage using strip-drilling with sustainable management practices can support soil health, resilience, and productivity. Crop and soil management systems that help to improve soil health parameters (i.e., physical, biological, and chemical) and reduce farmer costs through the development of appropriate equipment are essential for these systems to be successfully adopted by farmers in practice [13]. Modern machinery has made it possible to till strips in a single pass and, at the same time, apply fertilizers and sow seeds. In strip-tillage, strips of deeply loosened soil that are several centimeters to several tens of centimeters wide are prepared for sowing seeds. These strips are separated by strips of untilled soil. The loosened soil strip is narrow, while the width of the non-loosened interrow is greater than that in traditional seed drilling [14]. Creating the right conditions for germination and temperature increases in cultivated strips with plants provides more favorable conditions for development [15]. The cultivation method used by Bojarszczuk and Księżak [1] had a relatively small effect on soybean yield, the content of selected nutrients, morphological features, and elements of the yield structure. However, soil cultivated using the strip-tillage method was more compact than that cultivated with the conventional tillage method. After harvesting soybean at a depth of 30 and 40 cm, the compactness of the soil cultivated with strip-tillage or reduced tillage was much lower than that in spring, indicating the beneficial effect of soybean on loosening the arable layer. Moreover, the benefits of not using plow cultivation with a relatively small reduction in yield compared to that of reduced tillage and strip-tillage show that a lack of plowing does not have significant negative consequences on yield but does reduce time, fuel consumption, and carbon dioxide emissions [11]. These factors are especially important given the commitment to meet the European requirements for reductions in GHG emissions [14]. As it can improve soil quality and reduce the negative impacts of agriculture on the environment, strip-till cultivation technology has the opportunity to be much more widely used in Poland, and may potentially replace traditional plow tillage [15]. Future research should investigate the long-term impacts of these systems under variable climatic and resource conditions to provide a robust framework for sustainable soybean production. Legumes, including soybean, are becoming increasingly popular in Poland due to the demand for fodder protein. Specifically, the area of soybean cultivation is increasing exponentially [15]. Ultimately, the present study hypothesizes that different tillage methods connected with strip drill sowing significantly improve soybean yield and quality by affecting soil structure, nutrient availability, and seed composition.

2. Materials and Methods

2.1. Field Experiment

The present study was carried out from 2017 to 2019 at the Experimental Station in Brody (52°26′ N; 16°18′ E), part of the Agronomy Department at Poznań University of Life Sciences. This station is situated 50 km west of Poznań in the Wielkopolska Region of western Poland. The experiment was designed using a one-factor randomized block design, conducted in four replicates on loam soil, which has a sandy loam texture with underlying loams, classified under soil quality class IIIb-IVa. The chemical properties of the field soil are presented in

Table 1. Selected chemical properties of soil at the study site.

Chemical Soil Properties
pH in 1 M KCl	6.80
C (g kg−1)	7.93
N (g kg−1)	0.75
P (available mg kg−1)	125
K (available mg kg−1)	103
Mg (available mg kg−1)	40.1

.

The climatic conditions during the study period (2017–2019) significantly influenced soybean growth and development. Soybean phenology, from germination to maturity, depends on temperature and moisture availability, making these factors crucial in determining crop productivity and quality (

Table 2. Air temperature (°C) and rainfall sum (mm) during the vegetation period in 2017–2019. Data source: Meteorological Station, Brody, Poland.

Day of Month	Mean Air Temperature (°C)							Rainfall Sum (mm)
	Month/Year
	Apr	May	Jun	Jul	Aug	Sep	$\overline{\mathbf{x}}$	Apr	May	Jun	Jul	Aug	Sep	∑
	2017
1st–10th	10.6	8.8	16.5	16.9	21.1	14.8	14.8	3.0	26.8	45.7	31.9	89.6	35.4	232.4
11th–20th	5.9	15.6	18.1	18.4	18.3	13.0	14.9	19.6	1.1	14.7	27.2	53.1	8.3	124.0
21st–30th/31st	6.7	17.5	18.3	19.9	17.4	13.1	15.5	3.1	21.3	45.6	101.7	7.9	11.1	190.7
$\overline{\mathrm{x}}$ */∑ **	7.7 *	14.0	17.7	18.4	18.9	13.6	15.0	25.7 **	49.2	106.0	160.8	150.6	54.8	547.1
	2018
1st–10th	10.0	15.1	20.8	19.6	24.8	18.1	18.1	14.4	6.7	19.7	10.8	0.1	8.5	60.2
11th–20th	14.6	16.4	19.4	19.1	21.1	18.0	18.1	34.2	12.5	2.2	124.1	10.4	9.1	192.5
21st–30th/31st	14.1	19.8	17.0	23.4	18.4	11.7	17.4	16.7	0.0	9.6	0.0	9.5	43.1	78.9
$\overline{\mathrm{x}}$ */∑ **	12.9 *	17.1	19.1	20.7	21.4	15.9	17.8	65.3 **	19.2	31.5	134.9	20.0	60.7	331.6
	2019
1st–10th	9.4	9.0	21.2	17.0	20.2	16.4	15.5	0.0	12.3	0.7	5.4	13.1	28.6	60.1
11th–20th	7.8	12.1	23.2	18.2	19.5	13.1	15.6	4.7	41.1	1.4	25.2	9.7	8.1	90.2
21st–30th/31st	13.9	14.9	22.6	22.6	22.3	14.0	18.4	7.2	24.4	6.3	32.7	5.4	27.1	103.1
$\overline{\mathrm{x}}$ */∑ **	10.4 *	12.0	22.3	19.3	20.7	14.3	16.5	11.9 **	77.8	8.4	63.3	28.2	63.8	253.4
Long term mean value	8.2	13.3	16.7	18.3	17.7	13.5	14.6	37.7	56.4	64.8	84.1	66.9	48.3	358.2

* Mean monthly air temperature (°C); ** monthly rainfall sum (mm).

). The year 2017 was characterized by moderate temperatures and abundant rainfall, particularly in July and August, when soybean plants enter the pod-setting and seed-filling stages. The high precipitation in these months (160.8 mm in July and 150.6 mm in August) created favorable conditions for soybean growth but may have also increased the risk of excessive soil moisture, potentially affecting root aeration and disease prevalence. Overall, 2017 was the most favorable year for soybean production, with sufficient moisture throughout the growing season, ensuring optimal vegetative growth and reproductive development. On the other hand, 2018 was the warmest year, with an average air temperature of 17.8 °C, exceeding the long-term mean. Despite higher temperatures, rainfall distribution was uneven, with a notable deficit in August (20.0 mm). The warm temperatures accelerated phenological stages, potentially shortening the seed-filling period and affecting final seed quality. Moreover, 2018 was a year of thermal stress, with high temperatures likely shortening critical phenological stages, leading to a potential reduction in final yield and quality. The year 2019 had the lowest annual precipitation, with a total deficit of 104.8 mm compared to the long-term average. The extremely low rainfall in June (8.4 mm) and July (63.3 mm) likely created drought stress during flowering and early pod development, which are critical phases for determining yield potential. However, relatively warm conditions (22.3 °C in June and 20.7 °C in August) may have partially mitigated the negative effects of drought stress by supporting active photosynthesis. In addition, 2019 presented the most challenging conditions due to a combination of drought stress during key reproductive phases and below-average precipitation, which likely limited yield formation.

The size of a single test plot was 500 m² (10 × 50 m). The first factor in the field experiment was the different ranges of tillage before sowing according to the following scheme (Figure 1):

(1)

Plowed tillage + conventional row sowing (PCR) with plots number: 102, 203, 302 and 401 (Figure 2).

(2)

Plowed tillage + strip-drill sowing (PSD) with plots number: 101, 202, 303 and 404

(3)

No-plow tillage + strip-drill (NSD) with plots number: 103, 204, 301 and 403

(4)

Zero tillage + strip-drill (ZSD) with plots number: 104, 201, 304 and 402 (Figure 3 and Figure 4)

The agrotechnical and cultivation treatments were carried out in accordance with the principles of good agricultural and experimental practice. Seeds of soybean cv. Merlin were sown with a row spacing of 18 cm (PCR plots) and 33 cm (PSD, NSD, and ZSD plots), a sowing rate of 80 germinating seeds per m², and a sowing depth of 4 cm in plots after winter wheat cultivation. After harvesting the previous crop, PCR and PSD were tilled using a 2.5 m-wide disk harrow to a depth of 8 cm, with fertilization in August. In the third week of October, autumn plowing was carried out to a depth of 30 cm using a 3-furrow reversible plow. In the spring, one week before sowing, pre-sowing tillage was accomplished with a field cultivator, followed by harrowing and rolling to a depth of 8 cm. In August, glyphosate herbicide was applied to NSD plots (3 L ha⁻¹) to control perennial weeds and volunteers, along with fertilization. In the third week of October, only a stubble cultivator (2.5 m wide) was used. In the spring, one week before sowing, pre-sowing tillage was performed with a field cultivator, followed by harrowing and rolling to a depth of 8 cm. After harvesting winter wheat, we applied glyphosate herbicide (3 L ha⁻¹) to ZSD, with fertilization in August. In the spring, glyphosate herbicide was also applied to ZSD (3 L ha⁻¹) with sowing into the stubble of the previous crop. Fertilization was consistently across all tillage systems and experimental years, with 80 kg P ha⁻¹ and 100 kg K ha⁻¹ applied. No nitrogen fertilization was applied. Soybean seeds on PCR plots were drilled mechanically with a seeder (Great Plains, Solid Stand) and in other combinations using a Vaderstad Spirit Strip Drill ST 400C. During the growing season, recommended pesticides were used for particular target species. During each year, plants were harvested from the whole plot area at the full maturity stage of soybean in September.

2.2. Plant and Seed Assessment

During the soybean growing season, the leaf greenness index (SPAD) was measured on fully developed leaves using a Minolta SPAD-502 chlorophyll meter once per plot. At the stage of full plant maturity, 15 plants were randomly selected from each plot, and the number of pods per plant (PP), seeds per plant (PS), and seeds per pod (PSP) were recorded. The plant number per 1 m² (PN) was evaluated before harvest using the frame method over a 1 m² area. After harvesting, the weight of 1000 seeds (WTS) was measured (2 × 500 seeds from each replication were counted and weighed). The seed yield from each plot was adjusted on a per-hectare basis and calculated at a 15% moisture level.

The standard germination test, as per the International Seed Testing Association [16], was conducted on 100 randomly selected seeds from each replication using the between-paper method at 20 ± 1 °C. Germination capacity (GC) was visually assessed after 8 days, and the results were expressed as percentages.

The chemical compositions of soybean seeds (milled into a fine powder) were analyzed using standard methods at the laboratory of the Department of Agronomy at Poznań University of Life Sciences. Crude protein was determined according to the AOAC [17], while fiber content was measured following the Van Soest [18] method. Oil content was assessed using the Soxhlet method. Nitrogen-free extracts were calculated by subtracting the contents of the other components from 100%. All measurements were expressed on a dry weight basis. Seed protein and fat content, expressed on a dry weight basis (g kg⁻¹), were then recalculated as protein and fat yields (kg ha⁻¹).

2.3. Statistical Analysis

The results were statistically analyzed using a one-way analysis of variance (ANOVA) with the Statistica v. 12.0 software (StatSoft, Kraków, Poland). Tukey’s multiple comparison test was applied to assess differences between the treatments, and confidence intervals for the means were calculated using the Least Significant Difference (LSD) method (α = 0.01 and α = 0.05). The correlation coefficient (Pearson’s method) was determined to examine the relationships between selected parameters.

3. Results and Discussion

Table 3. The effects of soil tillage and sowing methods on the biometrical features of plants/seeds and yield components.

ST/SM	Specification
	PN	PP	PS	PSP	WTS	SPAD	GC
SD	2.59	1.02	1.76	0.06	2.46	8.89	1.90
PCR	73.4	13.2	22.3	1.7	173.0	428.3	69.5
PSD	69.1	14.6	22.7	1.6	179.7	498.7	75.2
NSD	76.0	15.3	23.5	1.5	167.2	493.3	58.2
ZSD	78.3	12.6	21.1	1.7	167.3	471.7	68.6
LSD value	5.32 **	2.09 *	ns	0.13 *	5.05 **	22.29 *	3.90 **

* p < 0.05 and ** p < 0.01. SD: standard deviation. Specifications: ST/SM, soil tillage and sowing method; PCR, plowed tillage with conventional row sowing; PSD, plowed tillage with strip-drill sowing; NSD, no-plowed tillage with strip-drill sowing; ZSD, zero tillage with strip-drill sowing; PN, plant number (no. m²); PP, number of pods per plant; PS, number of seeds per plant; PSP, number of seeds per plant pod; WTS, weight of 1000 seeds (g), SPAD, leaf greenness index of plants, GC, germination capacity of seeds (%).

presents the effects of soil tillage and sowing methods (ST/SM) on several plant features: (PN) plant number per 1 m², (PP) number of pods per plants, (PS) number of seeds per plant, (PSP) number of seeds per pod pf plant, (WTS) weight of 1000 seeds (g), (SPAD) leaf greenness index of plants, and (GC) germination capacity (%). ST/SM was found to modify some biometric features and yield components. Compared to PCR, NSD significantly decreased PSP by 13.3%, WTS by 3.5%, and GC by 11.3 but increased PP and SPAD by about 15.0–16.0%. Moreover, there were no significant differences between these ST and SM values in PN. The highest value was observed in ZSD (78.3 plants per square meter), while the lowest occurred in PSD (69.1). Meanwhile, significant differences were detected with LSD = 5.32. ZSD decreased the WTS by 5.7 g, increased SPAD by 10.1%, and improved the GC of PSD by 5.7% when compared to PCR. ZSD generally offered lower performance metrics, which is also in line with findings from various studies suggesting that this tillage method can negatively impact yield quality. ZSD practices often result in less soil aeration, reduced soil warmth, and less nutrient availability, which can affect seed development and plant growth [19]. However, alternatives to plows still offer advantages through savings in terms of fuel, labor, and wear and tear of farm implements [20]. We observed significant increases in the PP and SPAD of NSD plots, despite a decrease in PSP, WTS, and GC. In a previous study by Różewicz et al. [11], the tillage method significantly affected photosynthesis intensity. The increase in SPAD indicates enhanced chlorophyll content in leaves, which is often associated with better photosynthetic efficiency. There are no Polish studies on the strip-till cultivation of soybean [15]. However, Księżak and Bojarszczuk [1] assessed the influence of the tillage method on sowing values such as vigor for soybean seeds using the electrical conductivity vigor test to indicate field emergence. In these trials, the electrical conductivity (EC) test showed the effects of soil cultivation methods for soybean based on the EC of stagnant water. The highest electrical conductivity of standing waters was observed among soybean seeds grown under the strip-tillage method (mean for both cultivars, 12.3 μS∙cm⁻¹∙g⁻¹), while the lowest was observed under the conventional tillage method (mean, 15.2 μS∙cm⁻¹∙g⁻¹). Reduced seed quality and germination capacity under NSD have been commonly observed in other studies evaluating no-till practices. The PSD system yielded the best outcomes for WTS, SPAD, and GC, which aligns with research suggesting that moderate tillage systems balancing soil protection and nutrient availability can improve crop yields. PSD, which likely involves shallower tillage, may create better conditions for root development, water retention, and nutrient availability without compromising the soil structure, as is often the case with full tillage systems [19]. Studies have also shown that integrated tillage systems combining elements of both conventional and no-till practices can offer optimal results for soil properties and crop production. The observed trend of higher plant density in ZSD (78.3 plants/m²) compared to PSD (69.1 plants/m²) could be attributed to differences in seedbed conditions. In a study by Księżak and Bojarszczuk [1], the assessed cultivation methods had a relatively minimal effect on the morphological features and elements of the yield structures of both cultivars, Merlin and Aldana. Although the cultivation method slightly changed the root systems of both soybean cultivars in our study, these differences were observable in the early development phase of soybean (Figure 5).

Table 4. The effect of soil tillage and sowing method on the chemical content of seeds (g kg⁻¹ DM).

ST/SM	Chemical Component
	Crude Protein	Crude Lipids	Crude Fiber	Crude Ash	N-Free Extract
SD	5.94	3.64	6.03	0.40	5.08
PCR	365.5	221.1	84.1	55.8	273.3
PSD	369.9	221.1	87.4	56.3	265.3
NSD	368.6	219.6	93.6	56.6	261.5
ZSD	376.5	215.9	93.6	57.4	256.4
LSD value	ns	ns	ns	0.89 *	16.50 **

ns: not significant; * p < 0.05 and ** p < 0.01. SD: standard deviation. Specifications: ST/SM, soil tillage and sowing method; PCR, plowed tillage with conventional row sowing; PSD, plowed tillage with strip-drill sowing; NSD, no-plow tillage with strip-drill sowing; ZSD, zero tillage with strip-drill sowing; DM, dry matter.

shows the reported chemical composition of the soybean on a dry matter basis. In the soybean seeds, organic components such as protein, lipids, and fiber were not affected by the levels of experimental factors. Similarly to the results of Księżak and Bojarszczuk [1], the assessed cultivation methods had a minimal effect on the concentration of more important nutrients in the seeds of soybean cultivars such as Merlin and Aldana. However, Farmaha et al. [21] noted that the strip-till cultivation of soybean offers positive effects related to yield quality because seeds from strip-till soybean contain more oil and protein compared to those under no-till. Various studies on crop nutrition have shown that organic components, such as proteins and lipids, are often more strongly influenced by genetic factors, plant variety, and environmental conditions [22,23,24]. In an experiment by Fecák et al. [22], the seed protein and oil of soybean were very significantly (p ≤ 0.01) affected by weather conditions; this influence, compared to that of tillage systems and those using nitrogen fertilization, was much higher. These findings agree with the results of Šariková and Fecák [23], who also reported the highest influence of weather conditions on seed protein and oil. Based on a regression analysis, seed protein has a negative relationship with seed oil. According to Długosz [25], reducing soil tillage via the application of catch-crop green mass as a mulch is a conservation practice used in agriculture to improve the soil ecosystem. In our study, significant differences were observed in ash content, with the ZSD treatment yielding a higher value (57.4 g kg⁻¹) than PCR (55.8 g kg⁻¹). Moreover, ZSD had the lowest NFE (256.4 g kg⁻¹), while PCR had the highest (273.3 g kg⁻¹). This result suggests that ZSD might have increased the mineral content of the soybeans. Ash content is primarily composed of inorganic minerals such as calcium, potassium, magnesium, and phosphorus, and its variation can reflect differences in soil nutrient availability. This cultivation method enhances soil organic matter quantity and quality by improving soil biological activity and nutrient availability while reducing soil disturbances [25]. Zero tillage systems that maintain the soil structure and improve nutrient retention may lead to higher concentrations of mineral elements in the seeds due to reduced leaching and enhanced nutrient cycling [15]. Therefore, the higher ash content observed in ZSD could be a result of better soil nutrient conservation and availability. Reduced tillage systems are an important component of soil management in sustainable agriculture [25].

Table 5. The effect of soil tillage and sowing method on seed yield (t ha⁻¹).

ST/SM	Year (Y)
	2017	2018	2019	Mean
	Seed Yield
PCR	2.7	3.0	1.5	2.4
PSD	2.7	3.4	1.2	2.4
NSD	2.4	3.3	1.2	2.3
ZSD	2.5	3.0	1.9	2.5
LSD value	0.22 *	ns	0.41 *	ns
Mean	2.6	3.2	1.4	-
Synthesis LSD value	Y − 0.26 **; T × Y − 0.44 **

ns: not significant; * p < 0.05 and ** p < 0.01. SD: standard deviation. Specifications: ST/SM, soil tillage and sowing method; PCR, plowed tillage with conventional row sowing; PSD, plowed tillage with strip-drill sowing; NSD, no-plow tillage with strip-drill sowing; ZSD, zero tillage with strip-drill sowing.

investigates the combined influence of ST/SM on seed yield (t ha⁻¹) over three years, providing annual data and the overall mean. This interaction highlights the combined effects of tillage and yearly conditions. In 2017, all methods produced similar yields (2.4–2.7 t ha⁻¹), with no significant differences. Overall, 2018 emerged as the most favorable year across all methods, with yields significantly higher than those in 2017 and 2019. The yield peaked, ranging from 3.0 t ha⁻¹ (PCR, ZSD) to 3.4 t ha⁻¹ (PSD), but the differences were not significant. ZSD outperformed the alternatives in 2019 and had the highest average yield. This result may indicate the resilience of ZSD under less favorable conditions. No significant differences were observed across mean yields. However, overall, ZSD (2.5 t ha⁻¹) had the highest average yield. PCR and PSD offered equal yields (2.4 t ha⁻¹), while NSD had the lowest (2.3 t ha⁻¹) yield. The variability in soybean yield across the three years (2017–2019) in our study underscores the influence of annual environmental conditions, a finding supported by numerous studies. Our results are similar to those of Fecák et al. [22], in which the environmental conditions (years) played a crucial role in determining the seed yield of soybean. In this study, the highest average yield was observed in 2008 (2.77 t/ha), followed by 2.34 t/ha in 2006. The lowest yield was 1.98 t/ha in 2007, during which the stage of seed-filling was found to be the most sensitive to water stress, resulting in a yield reduction. Döttinger et al. [26] emphasized that yearly weather patterns, such as precipitation and temperature, significantly affect soybean productivity. In our study, the significantly higher yields observed in 2018 across all methods reflect favorable climatic conditions, likely optimal moisture and temperature levels during critical growth stages, as described by Tang et al. [27] and Hatfield and Prueger [28]. The effect of weather conditions on soybean seed yields was confirmed by Księżak and Bojarszczuk [1], who found that the soybean yields of two cultivars were significantly influenced by alternating weather conditions (temperature, total precipitation, and distribution) during the growing season and the cultivation methods used in soybean production. The tillage method in years with lower total precipitation had no significant effect on soybean productivity. Only in the last year of experimentation did soybean grown using the conventional tillage method offer a better yield.

The results shown in

Table 6. The effect of soil tillage and sowing method on protein yield (kg ha⁻¹).

ST/SM	Year (Y)
	2017	2018	2019	Mean
	Protein Yield
PCR	835.6	928.1	453.2	739.0
PSD	864.6	1057.2	390.3	770.7
NSD	746.8	954.9	385.2	695.6
ZSD	809.8	1121.6	600.1	843.8
LSD value	74.06 *	146.90 **	143.66 *	78.10 **
Mean	814.2	1019.1	458.5	-
Synthesis LSD value	Y − 71.54 **; T × Y –135.27 **

* p < 0.05 and ** p < 0.01. SD: standard deviation. Specifications: ST/SM, soil tillage and sowing method; PCR, plowed tillage with conventional row sowing; PSD, plowed tillage with strip-drill sowing; NSD, no-plow tillage with strip-drill sowing; ZSD, zero tillage with strip-drill sowing.

indicate the significant effect of experimental factors and weather conditions on the protein yield of soybean. The differences were significant between PCR and NSD in 2017 (88.8 kg ha⁻¹) and ZSD in 2018 and 2019 (193.5 kg ha⁻¹ and 146.9 kg ha⁻¹, respectively). The relatively uniform protein yield across methods (746.8–864.6 kg ha⁻¹) in 2017 suggests limited environmental stress, allowing for similar performance between tillage and sowing methods. These favorable climatic conditions minimized the influence of soil management practices on yield variability. The peak of protein yield in 2018, particularly with ZSD (1121.6 kg ha⁻¹), reflects optimal growing conditions. The significant performance of ZSD suggests its efficacy in leveraging favorable conditions, possibly due to improved root development and nutrient uptake under reduced soil disturbances [13]. The sharp decline in protein yield across methods (385.2–600.1 kg ha⁻¹) in 2019 highlights the impact of adverse environmental conditions such as drought and excessive rainfall. Protein synthesis in soybean is sensitive to abiotic factors such as temperature, soil moisture, and nutrient availability [28]. In a study by Księżak and Bojarszczuk [1], the most favorable conditions affecting soybean productivity occurred in the third year of research (2020), with seed and protein yields being 80% higher than those in 2019 and approximately 50% higher than those in 2018. According to Hatfield and Prueger [28], adequate precipitation and moderate temperatures enhance nitrogen assimilation, a key factor in protein production. This phenomenon increased the protein yield per hectare, which is particularly important for this crop in terms forage protein production [15]. On average, ZSD significantly increased the protein yield by about 14% compared to the results under PCR. Conservation tillage methods such as ZSD outperformed others, demonstrating resilience under stress by better maintaining soil moisture and reducing compaction [29].

The data in

Table 7. The effect of soil tillage and sowing method on fat yield (kg ha⁻¹).

ST/SM	Year (Y)
	2017	2018	2019	Mean
	Fat Yield
PCR	508.5	564.4	274.2	449.1
PSD	516.8	632.4	233.5	460.9
NSD	443.1	618.9	230.4	430.8
ZSD	463.5	545.5	339.1	449.3
LSD value	56.56 *	Ns	71.44 *	ns
Mean	483.0	590.3	269.3	-
Synthesis LSD value	Y − 63.79 **; T × Y − 89.20 **

ns: not significant; * p < 0.05 and ** p < 0.01. SD: standard deviation. Specifications: ST/SM, soil tillage and sowing method; PCR, plowed tillage with conventional row sowing; PSD, plowed tillage with strip-drill sowing; NSD, no-plow tillage with strip-drill sowing; ZSD, zero tillage with strip-drill sowing.

highlight the significant influence of tillage practices, sowing methods, and environmental conditions on fat yield. On average, there were no significant differences between the control (PCR) and other ST/SM options, nor were there differences in 2018 and 2019. In 2017, NSD decreased fat yield by 65.4 kg ha⁻¹ compared to that under PCR. NSD consistently underperformed, with the lowest mean fat yield (430.8 kg ha⁻¹). The results of our experiment suggest that soil tillage and sowing methods influenced fat yield even under relatively stable environmental conditions. Conservation tillage methods such as ZSD may have increased soil organic matter retention, thereby improving soil quality and indirectly affecting fat content in soybean seeds [30]. This situation could directly influence fat yield based on the counting method. The substantial annual variation in fat yield underscores the importance of environmental conditions. High fat yields in 2018 coincide with favorable growing conditions, while decreases in 2019 highlight the impact of stress factors. Conservation tillage methods are better equipped to mitigate these stresses by improving soil health and moisture retention [31]. The significant Tillage × Year interaction (LSD = 89.20, p < 0.01) emphasizes that a combination of tillage methods and environmental conditions strongly influences fat yield. As soybean fat content is sensitive to abiotic stresses such as water deficits and extreme temperatures [32], conservation tillage methods such as ZSD can help stabilize yields under variable conditions. Moreover, soybean is mainly used as an oilseed crop. Consequently, higher oil content in the seed is important to ensure seed quality, but the remaining post-extraction soybean meal after oil pressing is also an important protein component for feed production [15].

The present correlation analysis underscores the complex relationships among biometric and yield-related traits in soybean cultivation (Figure 6). We observed a nearly perfect correlation between plant density (PN) and germination capacity (GC). TeKrony and Egli [33] noted that seed viability and vigor directly affected the performance of seeds planted to regenerate the crop. Although seed quality can influence many aspects of performance (e.g., total emergence and rate of emergence), the objective of this research was to examine the relationship between seed vigor and one aspect of performance: crop yield. The strong positive correlations among seed yield (SY), protein yield (PY), and fat yield (FY) align with the experiment of Singh et al. [34], who demonstrated that seed composition and overall yield are co-dependent traits influenced by genetic and environmental factors. This finding emphasizes the interconnected nature of yield components and the potential for breeding programs to enhance multiple traits simultaneously. The robust relationship between pods per plant (PP) and PN supports the hypothesis of resource competition under high plant densities, as noted by Board and Kahlon [35]. These authors observed that higher densities often limit individual plant access to sunlight, nutrients, and water, thereby reducing pod production per plant. This analysis highlights the need for balanced strategies to optimize plant density and enhance resource use efficiency. Future studies should consider integrating environmental variables such as soil fertility and moisture levels alongside management practices such as tillage and row spacing. These approaches align with the adaptive management strategies suggested by Kelly et al. [36], which emphasize the importance of tailored interventions for site-specific conditions to maximize soybean yield and quality. Indeed, the sustainability of all cropping systems could be increased by implementing better management techniques such as zero and reduced tillage with residue retention and using better nutrient sources [37]. Determining how management approaches affect different crops and cropping systems is crucial to achieving high food production and comparing crop management practices under different cropping systems [38].

4. Conclusions

This study underscores the significant impacts of tillage methods on soybean productivity, seed quality, and soil properties. The obtained findings suggest that tillage methods play a crucial role in soybean production, with PSD generally providing the best balance between crop yield and quality. While reduced tillage methods such as ZSD and NSD can increase leaf greenness and pod number, they often result in lower seed quality and germination capacity, which can negatively impact overall productivity. The study’s findings suggest that soil tillage methods can significantly impact certain nutrient components, such as ash content and NFE, while having limited effects on protein, lipid, and fiber levels. ZSD contributed to higher protein content but at the expense of carbohydrate levels, suggesting a trade-off between macronutrient composition and yield stability. Overall, integrating adaptive tillage strategies that optimize yield, maintain seed quality, and enhance soil fertility could provide a sustainable framework for soybean production across diverse agro-ecological zones.

Further studies could explore the long-term impacts of these methods on seed quality and overall soil health.