The field experiment, installed in 2016, is situated on a Calcaric Cambisol at the Anjiapo catchment of Loess Plateau in Dingxi under the Department of Soil and Water Conservation Administration, Gansu Province, Northwestern China (35°34′53′′ N, 104°38′30′′ E), as shown in Figure 1. The study site relief is gently sloped, and the altitude is 2,000 m above sea level. The research county has semi-arid climatic conditions. The type of soil in the study region is a Huangmian sandy loam texture (sand: 60.5%, silt: 24.3%, and clay: 15.2%) according to WRB (IUSS Working Group, 2006), having low soil organic carbon with a slightly alkaline pH (Chinese Soil Taxonomy Cooperative Research Group, 1995).

The average temperatures in this area are −22°C and 35°C in the coolest and warmest months, respectively, and regular frosts in the winter (Xingchen et al., 2019). We have 50 years of continuous climatic data from 1971 to 2020 for this research. The 50-year average annual rainfall from 1971 to 2020 was 400 mm per year, with an irregular distribution. The 50-year average annual radiation is 5,930 MJ m⁻² with 2,480 h of sunshine per year. This area has 140 days of frost-free period, an average annual evaporation of 1,531 mm, and an annual temperature of 6.9°C from 1971 to 2020. The monthly average of rainfall and temperature for the study period in 2021 is presented in Figure 2.

Before the experiment in 2016, the research field area was bare, which was cut and cleared for spring wheat cultivation. Then, spring wheat was introduced and cultivated at different sowing times (early, normal, and late) under tillage systems. The tillage practices were the same for all spring wheat sowing dates. The Dingxi in Gansu, China, is a research hub and has an extensive wheat cultivation history, and wheat straws were frequently removed prior to the subsequent crop cycle. A comprehensive experiment field site description has been provided in previous studies (Niu et al., 2016; Xu et al., 2020; Sadiq et al., 2021a).

This experimental study was conducted in 2021, from March to August. The research comprised four treatments, including one conventional tillage (CT) control and three different conservation tillage regimes, specifically stubble incorporation with conventional tillage (CTS), no-tillage system (NT), and straw-return with no-tillage (NTS). The conservation tillage regimes were compared with conventional tillage control. The experimental treatments were replicated three times in an 8 m × 3 m plot size under randomized complete block design (RCBD), giving a total of 12 individual plots with a total area of 24 m². These conservation tillage regimes have been practiced since 2016, with 5 years of non-stop spring wheat cultivation. At the beginning of the research, soil samples contained an average bulk density (BD) of 1.41 ± 0.02 g cm⁻³, soil porosity (P) 47.05 ± 3.31%, total nitrogen (TN) 0.59 ± 0.02 g kg⁻¹, total phosphorous (TP) 0.43 ± 0.03 g kg⁻¹, total potassium (TK) 18.48 ± 0.01 g kg⁻¹, soil organic carbon (SOC) 5.85 ± 0.34 g kg⁻¹, and pH 8.34 ± 0.05 in 0–15 cm depth (Table 1).

The soil tillage management practices compared in this trial were conventional tillage (CT), stubble incorporation with conventionally tilled soil (CTS), no-tillage (NT), and no-till with straw-retention (NTS). Descriptions of these tillage treatments are presented in Table 2. For the CT system, land cultivation was performed three times with moldboard plow in a year at 20 cm, 10 cm, and 5 cm, respectively, and harrowed two times, followed by planting in the absence of stubble. In order to manage CTS, after harvesting the wheat crop, the fields were plowed with moldboard plow, harrowed, and followed by planting exactly as for the CT practice (three plow passes and harrows two times), but stubble incorporation was done at the time of first plowing. After threshing, all the wheat-straw from the earlier spring wheat crop was returned to the original plot instantly and then incorporated into the field. The spring wheat was planted exactly as in the CT system. In the NT-treated plots, after harvesting the spring wheat, all stubbles were removed and crop planting was performed with a no-tillage crop planter; nevertheless, in the NTS practice, after harvesting the wheat, all stubble was returned to the field and crop sowing was done with a no-tillage crop planter. The wheat-stubble chemical composition is shown in Table 3. The wheat-straw nitrogen, phosphorous, potassium, and carbon were 0.79 ± 0.2%, 0.08 ± 0.01%, 0.49 ± 0.04%, and 39.24 ± 2.8%, respectively. Nitrogen at the rate of (146 kg ha⁻¹) and phosphorous at the rate of (63 kg ha⁻¹) were applied as basal doses in all treatments, counting control in the form of diammonium phosphate and urea. Semi-arid Dingxi in the Loess Plateau zone of China has a suitable concentration of soil potassium (Li et al., 2014), which was satisfactory for encouraging wheat growth and germination; therefore, potassium was not applied in basal fertilization. The spring wheat (cultivar Dingxi 42) crop was sown by hand in mid-March (seed rate was 187.5 kg seeds ha⁻¹) and allowed to grow until late-August (Table 3). The wheat crop was sown using 20 cm row-to-row spacing and a plant density of 400 plant m⁻². In order to control the weeds, the red sun herbicide with glyphosate (30%) was used according to the manufacturer’s instructions, and when weeding was required during the growing season, it was done manually.

The agronomic attributes of plant height, spike number per plant, seed m², root yield, aboveground biomass yield, grain yield, 1,000-grain weights, dry matter yield, and harvest index were determined. The wheat plant height was measured using the procedure described by Dokuyucu et al. (2002) and Demuner-Molina et al. (2014).

At the spring wheat harvest stage in 2021, five disturbed and undisturbed soil samples were collected with an auger having a diameter of 4 cm from different experimental treatments (CT, CTS, NT, and NTS), including three replications for the determination of soil physicochemical, biochemical, and biological properties. All soil quality indicators were observed at a soil layer of 0–10 cm depth.

The oven-dry method was used for the determination of gravimetric soil water content (SWC) (O’Kelly, 2004), water-filled pore space (WFPS) in percent, and soil water storage (SWS), which was calculated as described by O’Kelly (2004). Soil temperature (ST) was measured using a geothermometer (Lu, 1999). The procedure described by Campbell (1994) was used for soil bulk density (BD) determination with the core sampler method. and soil pore space (P) percent was calculated in accordance with the procedure described by Campbell (1994). The wet-sieved method was used for measurements of soil aggregates (Yang et al., 2018). Auger-hole method using the Guelph Permeameter was used for the determination of saturated soil hydraulic conductivity (Ks) (Reynolds et al., 2008).

The soil organic carbon (SOC) was determined by the standard method of Walkley-Black dichromate oxidation (Nelson and Sommers, 1983), while the density fractionation approach was used for the isolation of light fraction organic carbon (Gregorich and Ellert, 1993), and C and N analyzer (Elementar Vario MACRO cube) was used for its determination. The calculation of soil organic carbon storage (t hm⁻²) was done using the procedure described by Wu et al. (2021). The estimation of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) was done by the fumigation-extraction method (Vance et al., 1987).

Soil total nitrogen (TN), total phosphorous (TP), total potassium (TK), available nitrogen (AN), available phosphorous (AP), available potassium (AK), electrical conductivity (ECe), and pH were determined by using standard procedures (Lu, 1999). Nitrogen storage was calculated, followed by the equation of Wu et al. (2021). Soil microbial propagules (colony forming units, CFUs) were determined using the enumeration of luminescent colonies on agar media (Li et al., 1996). Soil urease activity was estimated following the procedures by Dick and Burns (2011), soil alkaline phosphates were estimated as described by Zhao and Jiang (1986), soil invertase activity was determined by the method of Frankeberger and Johanson (1983), soil cellulase activity was estimated following the method of Guan (1986), and soil catalase activity was determined as described by Yan (1988).

The procedure of greenhouse gas sampling, such as CO₂, CH₄, and N₂O, was conducted during different crop growth stages of spring wheat in 2021. On the basis of the static dark chamber and gas chromatography method described by Yuesi and Yinghong (2003), gas sampling and flux measurements were done. A stainless-steel base with a collar (50 × 50 × 10 cm) was installed to support sampling chamber placement (50 × 50 × 50 cm) for greenhouse gas sampling in each plot (a total of 12 plots). The samples of air were drawn from the chambers simultaneously, including three replications of each treatment. At five different times (0, 9, 18, 27, and 36 min), respectively, by using 150 mL gas-tight polypropylene syringes, the air samples were drawn and released into 100 mL aluminum foil sampling bags (Shanghai Sunrise Instrument Co. Ltd., Shanghai). Then the samples of gas were analyzed in the laboratory with a GC system (Echrom GC A90, China) equipped with a flame ionization detector for methane and carbon dioxide and electron capture detector for nitrous oxide analysis. At 250°C temperature and 35 cm³ min⁻¹ H₂ flow rate, the flame ionization detector operates. Methane, carbon dioxide, and nitrous oxide peak areas were analyzed in the Echrom-ChemLab software. Calibrations were done with standard gas obtained from Shanghai Jiliang Standard Reference Gases Co., Ltd., China, before the sample gas analyses. Standard gas concentrations were 2.00 ppmv, 456.00 ppmv, and 0.355 ppmv for methane, carbon dioxide, and nitrous oxide, respectively. In order to obtain the concentration change over sampling time, the concentrations of the sample gas obtained for the five sampling times were plotted against time. Emissions of carbon dioxide in terms of ecosystem respiration, methane, and nitrous oxide fluxes were calculated as described by Wei et al. (2014), followed by equation (1):(1) F = d C d t · M V 0 · P P 0 · T T 0 · H where dC/dt is the rate of gas concentration change; M is the molar mass of nitrogen or carbon (28 for N₂O and 12 for CO₂ and CH₄); V_o is standard molar air volume (22.41 mol⁻¹), P is the sampling site air pressure; P_o is the standard air pressure, T is the chamber air temperature at the sampling time, T_o is the standard air temperature; and H is the height of the chamber. The cumulative flux of methane, carbon dioxide, and nitrous oxide in kg ha⁻¹ was estimated using the following equation (2):(2) M = ∑ F i + 1 + F i × t i + 1 − t i × 24 2 × 100 where M is the gas cumulative emission during the whole growth period of spring wheat (kg ha⁻¹); F is the gas emission flux (mg/m⁻²h⁻¹); i is the sampling number; t is the sampling time (d).

In order to estimate global warming potential (GWP) of greenhouse gases, the cumulative flux of CO₂ in µmol m⁻²s⁻¹ was converted to mg CO₂–C and typically taken as the reference gas; therefore, methane and nitrous oxide emissions are converted into “CO₂ equivalents” (CO₂-e). The methane GWP is 34 (based on a 100-year time horizon), the carbon dioxide GWP is 1, and the nitrous oxide GWP is 298 (IPCC, 2013). Net global warming potential (GWP) in kg CO₂-eq ha⁻¹ was determined by using equation (3):(3) N e t G W P = C H 4 flux × 34 + N 2 O flux × 298 + N e t C O 2 flux

Greenhouse gas intensity (GHGI) was determined by using equation (4):(4) GHGI = G W P Grain yield

The sign convention adopted is that positive (+) means emission, whereas negative (−) means absorption.

The experimental data were processed using Excel 2016 (Microsoft Corp., United States). The procedure used to analyze the data obtained from the experiment was one-way factor interaction analysis of variance (ANOVA), suitable for randomized complete block design (RCBD). The linear model procedure of the appropriate computer software program Statistical Package for Social Science (SPSS) window version 25.0 (IBM Corp., Chicago, IL, USA) was used for all statistical analysis. The significant differences among different treatments were separated by Duncan’s test at 5% significance level (p < 0.05). Data obtained from treatments are displayed as the mean of three replications with standard deviation and computer software Origin 2021 was used for drawing figures. Additionally, in order to explore the multivariate variability introduced by the various tillage practices for soil properties, crop yield, and greenhouse gases, the principle component analysis (PCA) was performed. The Pearson heatmap correlation analysis was used to describe the relationship among the factors.

Conservation tillage management had an influence on spring wheat agronomic features, including growth, yield, and yield-attributing traits. The NTS practice generated maximum 95.26 ± 3.08 cm plant height, 44.66 ± 5.12 number of spikes per plant, seeds number per meter square 9321.97 ± 623, root yield (RY) 532.88 ± 24 kg ha⁻¹, aboveground biomass yield (ABY) of 5225.31 ± 327 kg ha⁻¹, thousand-grain weight (TSW) 50.95 ± 2.02 g, grain productivity (GY) of 2543.88 ± 275 kg ha⁻¹ and 2681.43 ± 257 kg ha⁻¹ dry matter yield (DMY) while lowest values of all investigated agronomic characters were associated with CT technique. The agronomic parameters of wheat followed the trend of CT > NT > CTS > NTS, except for plant height and spike number per plant, where no-till depicted better performance over CTS. However, CT produced pointedly highest 48.76 ± 1.33% harvest index (HI) compared with other tested conservative tillage treatments (Table 4). This research verified our hypothesis that a conservation tillage technique can improve productivity; it would be a sustainable and reliable agronomical practice in dry regions.

Soil inversion elimination and crop stubble implementation are the most significant practices in the agriculture production system. The data reveal that different conservation tillage systems are suitable for producing spring wheat in the semi-arid Dingxi belt. The significant maximum agronomic trait values of conservative tillage systems indicate the competent use of stubbles (Zhao et al., 2019; Jat et al., 2021; Li et al., 2023), water, and nutrients. The better wheat agronomic performance was due to straw-retention because crop stubble has the potential to retain essential soil nutrients, which led to increased crop agronomic parameters (Han et al., 2020). This is consistent with previous results (Sadiq et al., 2021b), in which they recorded increased crop yield under conservation agricultural practices and associated it with residue retention. The higher wheat yield and yield-attributing traits under NTS, CTS, and NT systems than CT can further be ascribed to increased soil organic matter, which improves soil quality and leads to increased crop agronomic parameters (Sadiq et al., 2021a). Maximum crop production under straw-return and residue incorporation and the NT system over CT might also be due to better hydrothermal soil characteristics (Huang et al., 2012; Wang et al., 2017). Our current study results are in agreement with the findings of Alhassan et al. (2021), as they verified that stubble return and residue incorporation and no-till systems enhanced wheat yield compared with CT in a dry region farming system.

Conservation tillage systems have noteworthy impact on soil properties, for instance, soil water content (SWC), water-filled pore space (WFPS), soil water storage (SWS), soil temperature (ST), soil bulk density (BD), soil porosity (P), aggregates, soil saturated hydraulic conductivity (Ks), soil organic carbon (SOC), light fraction organic carbon (LFOC), carbon storage (CS), microbial biomass carbon (MBC), total nitrogen (TN), available nitrogen (AN), nitrogen storage (NS), microbial biomass nitrogen (MBN), total phosphorous (TP), available phosphorous (AP), total potassium (TK), available potassium (AK), microbial counts (MC), urease, alkaline phosphatase, invertase, cellulase, and catalase at a soil depth of 0–10 cm (Figure 3 and Table 5). The concentration of SWC (p < 0.05) was maximum (10.35 ± 0.64%) in the NTS treatment variant with two other CTS and NT conservative tillage treatments, while CT had a minimum (8.70 ± 0.40%) SWC value. The conservation tillage practices NTS, CTS, and NT increased SWC by 9.35, 9.13, and 9.05%, respectively, over the CT system. The WFPS was highest (20.80 ± 0.81%) under the NT system, which was followed by NTS and CTS techniques, while the lowest WFPS was associated with CT practice. Additionally, the same trend was observed in the case of SWS, with the highest value in NT and the lowest in CT. The rise in SWC, WFPS, and SWS under CTS and NTS measures may be owing to crop straw-retention, thus decreasing evaporation losses, improving water availability and infiltration rate, and conserving soil water (Yadav et al., 2018; Zhang et al., 2018). Additionally, crop stubble addition to soil increases SOM and thus improves soil water retention capacity. The increase in SWC, WFPS, and SWS under NT practice over the CT system might be due to the earth flip inherent to CT practice, resulting in a big water loss due to evaporation. This water loss is avoided in NT, which lacks the requirement for stubble addition (Liebhard et al., 2022). Parallel findings were found by Yuan et al. (2023a).

The CT had the highest ST, whereas the NTS had the minimum ST values. The temperature moderation influence was observed in conservative tillage treatments as decreased ST by NTS, NT, and CTS systems (Figure 3). This is due to the accumulation of crop straws. The surface of the soil is abstemiously shielded by stubble remnants from prior crops in conservative tillage systems, encouraging the soil to absorb minimum solar radiation (Wang et al., 2009). Furthermore, the CT practice makes the soil more porous, and therefore, the soil under CT possibly has minor thermal conductivity (Sarkar and Singh, 2007). In addition, conservative tillage treatments increased the infiltration rate, which helped water movement toward the bottom (Liebhard et al., 2022) and reduced ST (Yuan et al., 2023a). Similar observations were noted by Sadiq et al. (2021a).

On average, conservation tillage systems NTS, CTS, and NT reduced BD by 29, 33, and 37%, respectively, over CT. The maximum soil BD under CT was connected to the soil disturbance by tillage implementation, which resulted in soil compactness (Gathala et al., 2011). In addition, due to traffic physical compaction by direct heavy machinery (Jat et al., 2018). In addition, as BD values are connected with soil porosity values, these conservative tillage systems improved the p-values, with the highest under NTS and the lowest recorded in CT. The NTS, CTS, and NT increased the soil porosity because of the organic matter accumulation under conservation tillage, which led to decreased BD and improved p-values (Ordoñez-Morales et al., 2019). Similar results were noted by Khorami et al. (2018), who recorded that conservation tillage decreased the BD and increased pore space over CT.

Almost similar to SWC, NTS attained the highest soil aggregates, followed by CTS, which was statistically on par with NT, while CT linked with the lowest soil aggregates. The CT strongly disturbs the soil due to plowing, which can diminish the aggregate degree and aggregate stability (Yeboah et al., 2018). Higher aggregates in conservation tillage might be due to residue retention (Niu et al., 2016). Similar results are reported in accordance with (Yuan et al., 2023a). Additionally, conservation tillage practices increased the Ks over CT; the highest value of Ks was reported in NTS, which was statistically at par with NT, followed by CTS, while the lowest Ks value was associated with CT. The minimum soil Ks in CT and CTS might be ascribed to the destruction of soil aggregation and reduction of macro-porosity (Singh et al., 2002). In arid and semi-arid cropping systems, the soil property variations under conservation tillage influences are habitually slow to arise, attributable to the limited production of plant biomass (Mikha et al., 2006).

The SOC, LFOC, CS, and MBC differed significantly (p < 0.05) in all tested tillage systems, whereas the non-significant (p < 0.05) differences were noted among CTS and NT for SOC and LFOC as well as NT and NTS had also non-significant differences for carbon storage, and in case of MBC, the NTS and CTS are statistically at par (Table 5). The NTS system had the highest values of SOC, LFOC, and carbon storage except for MBC, where CTS was related to higher values, while the CT system had the lowest values. The SOC, LFOC, carbon storage, and MBC contents were low in the CT system because of extensive tillage operations, breakdown of aggregates, and exposure of the soil carbon contents. More values of carbon-associated parameters in CTS, NTS, and NT systems soil were attributable to residue retention and no soil physical disturbance (Chen et al., 2009). In conservative tillage systems, the SOC solid stratification, which was significantly attributable to surface residue retention, is identical to that in other studies (Blanco-Canqui and Lal, 2008; Yuan et al., 2023b). Soil carbon storage is the retention of carbon in the ecosystem and a chief index to measure the gauge and quantity of ecosystem primary productivity. A study by Yeboah et al. (2018) revealed that NTS can significantly increase the soil organic carbon content so as to progress soil carbon storage. This study also found that compared with CT, conservation tillage systems were more helpful in improving soil carbon storage. The higher values of MBC appear because of high microbial biomass and soil organic matter contents. Organic stubbles are used as carbon source inputs for the microorganisms’ activities, activation with the support of microbial biomass, conservation tillage systems enrich the soil carbon contents (Liu et al., 2017). The role of straw-retention and residue incorporation in increasing carbon elements was also stated by numerous scholars (Zhao et al., 2019; Sadiq et al., 2021a; Yuan et al., 2023b). The conservation tillage system is a straw addition or plowless tillage with a minimum number of tillage operations, and its beneficial impact on soil functions and quality has been extensively identified (Han et al., 2020; Wulanningtyas et al., 2021; Sadiq et al., 2021b).

Conservation tillage practices (NTS, CTS, and NT) significantly improved total and available soil nutrients, namely TN, AN, TP, AP, TK, and AK, compared to CT. In addition, NC and MBN were notably increased under these investigated conservative tillage systems over CT. Higher TN, AN nitrogen storage, and TP were related to CTS but the NTS system had dominant MBN, AP, TK, and AK values, while CT had the lowest values. Beneficial influence of NTS, CTS, and NT on nutrient accumulation and storage might be due to multiple reasons:

Higher total and available soil nutrients, for instance, nitrogen, phosphorous, and potassium in CTS and NTS, might be because of straw-retention because straw has the potential to add essential nutrients to the soil system (Zhao et al., 2019).

Our findings concur with those of Zhao et al. (2019), Han et al. (2020), Sadiq et al. (2021a), Wulanningtyas et al. (2021), Lv et al. (2023), who found that nutrient elements and their storages were higher under conservation tillage than plowed ones.

The ECe, pH, C:N ratio, C:P ratio, and N:P ratio under different conservation tillage measures were inconsistent and non-significant. However, CTS, NT, and NTS showed a trend of increased ECe and decreased pH compared with CT. The dropping of pH under conservative tillage was previously described by numerous scholars (Jat et al., 2018; Sinha et al., 2019). Soil pH reduction in CTS, NT, and NTS conservation-based tillage regimes may be owed to organic acid production during retained stubble decomposition (Sinha et al., 2019). The C:N ratio was lower in CTS and NT than in CT, which might be due to slower decomposition under these systems. Our results are in line with those (Jat et al., 2018), which pointed out the minor values of C:N ratio under conservative tillage over CT. In general, the soil C:P and N:P ratios were highest under CT and NTS treatment, respectively. These results are in agreement with Feng et al. (2014), who stated that NT practice coupled with straw increases the soil N:P ratio.

Conservation tillage system had a great influence on soil microbial count and enzymatic activities. The highest values of soil microbial count, urease, alkaline phosphatase, invertase, cellulase, and catalase were obtained under NTS treatment, followed by CTS and NT, while the CT system had the lowest values of all these parameters. The conservative tillage systems NTS, CTS, and NT increased microbial count by 31.34, 17.61, and 21.19%, respectively; urease activity by 6.88, 4.45, and 4.85%, respectively; activity of alkaline phosphatase by 29.33, 13.35, and 20%, respectively; invertase activity by 35.53, 10.07, and 16.85%, respectively; cellulase activity by 64.73, 33.99, and 43.03%, respectively; and catalase activity by 5.30, 2.16, and 2.55%, respectively, over CT. The microbial count and enzyme activity depicted the trend of CT < CTS < NT < NTS. The soil microorganisms are a significant portion of the cropland ecosystem and are involved in the decomposition of SOM, nutrient circulation in the soil system, humus formation, and soil fertility (Yu, 2015). Soil microbes’ stability is a vital indicator of soil quality, health, and fertility (Yang et al., 2023). Land cultivation methods and cropland management practices affect the soil microbial community. Conservation tillage has the potential to improve the soil microbial community and the activities of soil enzymes (Rakesh et al., 2021). This study depicts that NTS, CTS, and NT raised the microbial community and activities of urease, alkaline phosphatase, catalase, invertase, and cellulase in the soil system to a greater extent than the CT system. This shows that conservative tillage mechanically makes the soil more porous (Yang et al., 2018) and increases the SOM distribution while facilitating the activity of enzymes (Balota et al., 2004). Hence, stubbles coupled with no-tillage (NTS) improved the soil microbial count, urease, alkaline phosphatase, invertase, cellulase, and catalase, which improved crop germination, growth, and yield. Optimal soil physicochemical properties could increase enzyme activity (Wei et al., 2013). In this context, NTS, CTS, and NT treatments were more effective than CT control treatment. Measurements of soil characteristics and variations are crucial for evaluating the influence of soil management techniques (Jat et al., 2021). The improved enzyme activities may be because of augmented carbon sequestration and immobilization of carbon as well as nitrogen during the decomposition of residues, as numerous studies have revealed that the activities of soil enzymes can be influenced by SOC sequestration (He et al., 2020; Pu et al., 2020). Our results are in accordance with Bhattacharya et al. (2020).

Furthermore, the principal component analysis (PCA) in accordance with the Jolliffe cutoff value permits isolating five principal components. In PCA analysis, the observation point made by contact between PC1 and PC2 illustrates the general variance defined by the five chief components. The PCA analysis of 39 variables (namely SWC, WFPS, SWS, ST, BD, P, soil aggregates, Ks, SOC, LFOC, CS, MBC, TN, AN, NS, MBN, TP, AP, TK, AK, ECe, pH, C:N ratio, C:P ratio, N:P ratio, MC, urease, alkaline phosphatase, invertase, cellulase, catalase, plant height, root yield, number of spikes per plant, number of seeds per meter square, grain yield, aboveground biomass yield, dry matter yield, harvest index), PC1 and PC2 were extracted with eigenvalues >1 and explained 65.7% of the total variance. Nevertheless, PC3, PC4, and PC5 do not allow the addition of additional information; that is why they are not involved. The highest PC1 loadings encompassed 50.4% of the total variance, and in PC2, the maximum loadings of 15.3% of the total variance were detected (Figure 4). According to our expectations, the correlation between wheat seed productivity and yield-attributing traits was significantly positive. Moreover, a significant positive correlation was noted between soil hydraulic properties, soil nutrients, and enzymatic activities and the seed yield of spring wheat (Figure 5). This concurs with the results reported by Yuan et al. (2023a).

Significant variation in GHG (CO₂, CH₄, and N₂O) was observed under different tillage regimes (Figure 6). The efflux rates of CO₂ (representing ecosystem respiration) under conservation tillage depicted apparent seasonal variations (Figure 6A). The maximum emissions arising during the summer months peak in the CT system in July, at the grouting spring wheat crop growth stage. The CT and CTS treatments showed the highest ecosystem respiration rates, including all investigated crop growth stages, while the NTS and NT treatments had the lowest CO₂ emission rates, but a significant difference between the different treatments was observed in bloom, grouting, maturity, and harvest stages. The highest CO₂ efflux rates during the summer months correspond with the maximum ST and dry matter accumulation, hence augmented soil respiration (Ussiri et al., 2009). Wu et al. (2011) clarified that an increase in soil temperature from 5°C to 15°C led to a noteworthy increase in the emission of carbon dioxide because of high soil organic matter mineralization and improved soil microbial activity. Lowering of soil CO₂ efflux rates during the growing seasons under conservation tillage was previously reported by many researchers (Alhassan et al., 2021; Li et al., 2023). Al-Kaisi and Yin (2005) stated a huge 80% reduction in CO₂ efflux rates under the NT compared to the CT system. Average CO₂ efflux rates were higher in tilled soils compared with non-tilled soils. The average CO₂ efflux rates were 180 ± 14.2, 171 ± 25.8, 245 ± 8.8 and 260 ± 15.3 mg Cm⁻² h⁻¹ in NTS, NT, CTS and CT respectively (Figure 4B). A significant positive correlation of CO₂ emission among soil moisture and soil temperature and a negative correlation of CO₂ emission with nitrogen and carbon contents and hydraulic conductivity were observed during the current study (Table 6). The CO₂ efflux rates are habitually controlled by plenty of factors, including carbon dioxide concentration gradient in the environment and the wind speed, soil water, soil temperature, soil medium, and soil physicochemical properties (Raich and Schlesinger, 1992). The tillage effect on these parameters would affect carbon dioxide emissions as well. The CT causes soil disturbance, which increases rates of decomposition because of improved soil microbe activities (Al-Kaisi and Yin, 2005), leading to maximum emissions of CO₂. Quite the reverse, under NTS and NT treatments, decomposition is slower because of no soil disturbance (Curtin et al., 2000). Conservation tillage practices (CTS, NT, and NTS) might correspondingly improve soil properties, which in turn can decrease soil CO₂ emissions. Maximum SWC under CTS treatment, combined with maximum ST, produced higher cumulative soil CO₂ emissions compared with NT and NTS. The SWC and ST habitually exert a collaborative effect on CO₂ emissions (Bond-Lamberty et al., 2016).

All the tested tillage systems acted as CH₄ sinks during the study period (Figure 6C). Peak absorption arose during the summer months at booting and bloom crop growth stages under the NT system. Seasonal changes were recorded in the sink capacities of different tillage systems. The CT had minimum CH₄ absorption rates during the investigated crop growth stages. A significant difference between different treatments was observed except for emergence and jointing of spring wheat crop growth stages. The maximum CH₄ emissions during the summer months were because of the high SWC status and ST, which may perhaps have boosted the activity of CH₄-oxidizing bacteria. The analysis of variance showed that all the investigated tillage techniques, namely CT, CTS, NT, and NTS, had a significant influence on average methane emission. In general, our results showed the average absorption rate of CH₄ followed the trend of CT < CTS < NT < NTS (Figure 4D). Another study done by Yeboah et al. (2016) had comparable consequences. Shen et al. (2018) showed that semi-arid agroecosystems habitually act as sinks of CH₄ as a result of soil aerobic conditions (Schaufler et al., 2010). Similar to the emission of CO₂, the absorption has a significant positive correlation with ST and SWC and a negative correlation with Ks and carbon and nitrogen elements (Table 6). The results of the current study are consistent with the results recorded by Yeboah et al. (2016) and Wang et al. (2022), who stated that improved SWC status can lead to high CH₄ uptake owing to the anaerobiosis occurrence and methanogenesis increment. Singh et al. (2010) observed maximum CH₄ emission rates under 13% soil water content in sandy loamy soils, and a parallel situation was detected in this study. Our study depicted that the methane flux was constantly negative, signifying CH₄ uptake by all the tillage systems. The NTS had the highest CH₄ uptake in this study. Under NTS treatment, minor ST might have played a substantial role in high CH₄ uptake. During high ST, the dominant methanogen (Methanosarcinaceae) employs H₂/CO₂ and acetate as precursors of CH₄ producing and produces far maximum CH₄ over the methanogen at lesser temperatures (Methanosaetaceae), which uses solitary acetate as a precursor of CH₄ producing (Ding et al., 2003). Our results are consistent with other appraisals in the Loess Plateau of China, where NT with straw-return was found to be a net sink for atmospheric CH₄ (Alhassan et al., 2021). The greater methane uptake under the NTS system might be because of good soil aeration and less degradation of the soil, which improved the activity of methanotrophs. McLain and Martens (2006) recorded that the activity of methanotrophs was heightened under tolerable gas diffusion and from the microbial activity sites. The NTS system inclines to increase soil organic carbon and decrease the bulk density of soil, which might lead to lesser CH₄ emissions risk. Yeboah et al. (2016) stated that the degradation of soil can diminish the soil’s ability to oxidize or consume atmospheric methane by as much as 30–90%. However, we proved that the most noteworthy CH₄ uptake control was SWC at the surface soil depth, with ST and Ks brought about by enhanced soil condition or quality and improved SOC. Soil carbon and nitrogen contents are also negatively correlated with CH₄ emission. This obscures the fact that improved soil carbon and nitrogen levels condensed the emission of CH₄.

Our study data showed that peak N₂O emission occurred in August at the final crop maturity growth stage, while the lowest N₂O flux was observed in the spring months. This trend is consistent with the findings stated by Cai et al. (2013) at the identical research site. During most tested crop growth stages, the CT and CTS emit more N₂O compared with the NT and NTS treatments, while at the harvest crop growth stage, NT served as a slight emitter and dominated the CTS system. A significant difference between different treatments was observed only at tillering, maturity, and harvest crop growth stages (Figure 6E). The N₂O flux pattern depicted that when SWC and ST appeared higher during the summer season, the N₂O emissions were higher. These consequences are similar to earlier studies (Bhattacharyya et al., 2023; Bozal-Leorri et al., 2023; Li et al., 2023). The ST is a significant factor influencing seasonal variations of N₂O flux. Taghizadeh-Toosi et al. (2022) observed that the variation in N₂O flux rate is almost harmonized with the surface temperature of the soil. Zhang et al. (2022) noted that ST increasement can diminish the nitrification contribution to N₂O and increase the N₂O amount produced during the denitrification process. The highest N₂O emissions noted during the rainiest months under all tested tillage systems might be credited to the fact that the spell’s rainfall levels might be higher than normal on that date, making all tillage systems very wet, so that denitrification situations were not dissimilar among them.

Significantly higher N₂O fluxes were observed under CT treatment compared with NTS, NT, and CTS treatments. The N₂O flux rates followed the trend of NTS < NT < CTS < CT (Figure 4F). On average, all investigated tillage systems served as slight N₂O emitters. These results are in accordance with those described by Pokharel and Chang (2021). Quite the reverse, Alhassan et al. (2021) observed maximum N₂O fluxes under the NT system over the CT technique. In this study, different conservation tillage practices, for instance, CTS, NT, and NTS, decreased the emission of N₂O by increasing soil structure, as revealed by bulk density of soil, pore space, soil aggregates, and soil hydraulic conductivity. Higher N₂O emissions under the CT system have been credited to the condensed diffusivity of gas and air-filled pore space (Rabot et al., 2015). Additionally, N₂O flux rates recorded in this experimental research were in the range of N₂O flux rates noted by Yeboah et al. (2016).

A significant positive correlation was noted between ST and N₂O emissions, which is attributed to the microbial respiration augmentation after heating origins oxygen dearth in the soil profile, which generates anaerobic conditions for denitrifying microbes’ activity (Castaldi, 2000; Mehnaz et al., 2018), and all together, warming also rises soil denitrification activity (Braker et al., 2010), which led to a rise in N₂O emissions. Additionally, our results also showed positive correlations among SWC and N₂O emissions. This is due to the improvement in SWC that limits the soil oxygen concentration, chiefly the anaerobic soil environment formation, pointedly falling nitrification and increasing denitrification, which in turn led to dominant denitrification to produce N₂O emissions (Pokharel and Chang, 2021). Our results are identical with other scientific reports by Taghizadeh-Toosi et al. (2022), demonstrating the influence of ST and SWC on the emission of soil N₂O.

The correlation study in Table 6 showed a significant negative relationship between N₂O emission and carbon and nitrogen contents, supporting the (He et al., 2023) that enhancing carbon stocks and nitrogen soil status can decrease the emission of soil N₂O. Consequently, these findings are consistent with earlier results reported by Zhao et al. (2020). High soil bulk density related to the degradation of soil by tillage application can have consequences for soil aeration reduction. Soil degradation reduction, whereas surface soil preservation covered by crop straws, might lead to minor denitrification as well as N₂O emissions risk. Quite the reverse, Li et al. (2005) reported a positive correlation between soil N₂O emissions and soil carbon contents. This is due to the increase in soil carbon contents delivering sufficient sources of nitrogen and a suggestive rise in the heterotrophic microorganism’s respiration. All at once, carbon availability in the soil offers electron donors for denitrifying microbes, which endorses the denitrification incidence, in that way increasing emissions of N₂O. Soil nitrogen contents were positively correlated with N₂O emission. Su et al. (2021) stated that improved N₂O production might be a consequence of augmented nitrogen contents and bacterial activities; meanwhile, the activities of microbes are controlled by soil carbon contents. This obscures that soil carbon contents improve the N₂O-producing microbe’s activities. This also verifies the results of Guenet et al. (2021), who showed that high carbon contents mostly raise the emission of N₂O. Changes in CO₂, N₂O, and CH₄ emission seemed to be described by variations in soil temperature, moisture content, and saturated hydraulic conductivity in the surface soil layer of 0–10 cm soil depth, with 95% of the data variance described by these environmental variables.

The GWP of CO₂, CH₄ and N₂O and net global warming potential (GWP) under all investigated tillage practices are shown in (Figure 7). The highest cumulative CO₂ flux was recorded under CT, whereas conservation tillage measures NTS, NT, and CTS pointedly reduced the cumulative CO₂ flux, as the least cumulative CO₂ flux was noted under NT, which was followed by NTS. The global warming potential due to the emissions of CH₄ was significantly lower under NTS, which was followed by NT over CT during the study period. The global warming potential due to the emissions of N₂O was significantly less under NT, which was followed by NTS over CT. The net global warming potential followed the trend of CT > CTS > NT > NTS (Figure 7D). The NTS, NT, and CTS decreased net-GWP by 23.44, 19.57, and 16.54%, respectively, over the CT system. The effect of different tillage practices on the atmospheric radiative forcing and henceforth changing climate can be evaluated by global warming potential determination from the biosphere–atmosphere exchange of numerous greenhouse gases. The noted global warming potential for the current study ranged between 1000 and 1400 kg CO₂-e ha⁻¹ which is in the range of those stated by Ma et al. (2013) but superior to those stated by Yeboah et al. (2016). The net-GWP was positively correlated with ST and SWC and negatively correlated with carbon and nitrogen elements and Ks (Table 6). In PCA analysis, we found that soil moisture, soil temperature, bulk density, hydraulic conductivity, carbon, and nitrogen elements explained 96.2, 69.6, 67.8, and 77% of the variations in soil CO₂, CH₄, and N₂O fluxes and GWP, respectively (Figures 8A–D). Compared with CH₄ and N₂O fluxes and GWP, soil CO₂ had a strong relationship with environmental variables, as shown in Figure 8A. Conservation agriculture has the potential to contribute to environmental conservation, though its influence differs depending on management strategies. The higher greenhouse gas intensity (GHGI) was associated with the CT system, while the minimum GHGI value was observed with the NT system, which was followed by the NTS system. The GHGI followed the trend of CT > CTS > NTS > NT. The conservation tillage systems NT, NTS, and CTS decreased GHGI by 29.96, 23.20, and 18.72%, respectively, compared with CT practice (Figure 7E). The current noted global warming intensity values were higher compared with other studies (Qin et al., 2010; Ma et al., 2013), which is attributable to the overall lower grain yield in this experimental research. Global warming intensity is a crop yield function, and it is directly affected by low grain yield. A significant reduction was observed under NTS and NT practices over CTS and CT systems in case of global warming potential and global warming intensity values. These findings are in line with Alhassan et al. (2021) and Li et al. (2023), who stated that different conservation tillage systems decreased the global warming potential and global warming intensity compared with the CT technique.