Rotary Tillage and Straw Mulching Enhance Dry Matter Production, Yield, and Water productivity in a Rain-fed Wheat-Soybean Double Cropping System

Rotary Tillage and Straw Mulching Enhance Dry Matter Production, Yield, and Water productivity in a Rain-fed Wheat-Soybean Double Cropping System | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Rotary Tillage and Straw Mulching Enhance Dry Matter Production, Yield, and Water productivity in a Rain-fed Wheat-Soybean Double Cropping System Shiyan Dong, Ming Huang, Junhao Zhang, Qihui Zhou, Chuan Hu, Aohan Liu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6582786/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aims Water deficiency and low water use efficiency severely constrain wheat yield in dryland regions. This study aimed to identify suitable tillage and straw management practices to improve water use efficiency, grain yield and water use efficiency of wheat in the dryland winter wheat-summer bean double cropping system. Methods A long-term field experiment (onset in October 2009) of four treatments—plowing with no straw mulching (PTNS), plowing with straw mulching (PTSM), rotary tillage with no straw mulching (RTNS), and rotary tillage with straw mulching (RTSM), was conducted at a typical dryland in China. The wheat yield and yield component, dry matter accumulation and translocation characteristics, and water use efficiency were investigated from 2014 to 2018. Results straw mulching significantly increased spike number, grains per spike, 1000-grain weight, and harvest index, and ultimately resulting in grain yield increases of 10.5% under PT and 20.5% under RT. Tillage and straw management significantly affected dry matter accumulation and translocation characteristics except for that straw management had no significant effect on pre-anthesis dry matter translocation. Straw mulching respectively increased water consumption by 7.4% and 10.4%, and water use efficiency by 3.1% and 9.6%, compared to treatments under PT and RT without straw mulching. Straw mulching also enhanced pre-sowing water storage capacity, water-saving efficiency, and water use efficiency per unit of dry matter and grain yield. Conclusions TOPSIS confirmed RTSM's superiority through straw-induced improvements water and nutrient productivity. Rotary tillage with mulching optimizes dry matter/water yield, recommended for dryland wheat systems. straw mulching wheat-soybean double cropping water productivity grain yield Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Wheat ( Triticum aestivum L.), as a globally essential staple crop and the second-largest food crop in China [ 1 ], contributes approximately 20% of the caloric intake and protein supply for mankind [ 2 ]. However, wheat is mainly planted in dryland, which accounts for 75% and 33% of the total wheat-sown area globally and in China, respectively [ 3 , 4 ]. In Henan, where wheat constitutes over one-quarter of annual production and dryland wheat also comprises one-third of the region's wheat acreage [ 1 ]. In dryland wheat production regions, natural precipitation serves as the sole water source for wheat growth. Thus, the limited rainfall, frequent drought, and the mismatch between precipitation and the wheat-growing season severely constrain yield formation of wheat. Dry matter accumulation underpins the material basis of crop yield formation, with its accumulation, translocation, and distribution closely linked to yield and water use efficiency (WUE). Therefore, exploring agronomic techniques to improve the characteristics of dry matter in wheat plants for enhancing the yield and water use efficiency of dryland wheat is of significance in promoting wheat yield and ensuring food security in China and worldwide. Previous studies have demonstrated that both rotary tillage and plowing have been widely applied to enhance crop yield and WUE [ 5 , 6 ]. Kan et al. [ 7 ] found that rotary tillage by increasing the spatial and temporal root distribution as well as photosynthetic activity at the flowering stage, achieved higher average grain yield by 12.0% and 6.7% from 2008 to 2019 as compared with conventional tillage and no-till, respectively. Zheng et al. [ 8 ] found that the dry matter production capacity and water use efficiency under plowing were higher than those under rotary tillage. However, Wu et al. [ 9 ] demonstrated that deep vertical rotary tillage significantly enhanced grain yield and water use efficiency by 24% and 19.0% in winter wheat, compared with conventional shallow rotary tillage, particularly under drought conditions. According to Jiang et al. [ 10 ], rotary tillage and harrow tillage strengthen soil moisture preservation, consequently increasing soil water supply efficiency in the late wheat growth period compared to conventional plowing. Shi et al. [ 11 ] employed the APSIM model to demonstrate that deep plowing significantly enhanced simulated average annual soil water storage (by 8.4%), biomass (18.4%), grain yield (25.5%), and water use efficiency (22.3%) compared to shallow rotary tillage. Furthermore, plowing combined with straw mulching improved soil water storage and root growth environment, thereby promoting the translocation and distribution of dry matter and significantly increasing crop yield [ 12 , 13 ]. However, some studies indicated that rotary tillage exhibits superior soil water retention and moisture conservation capabilities, which contribute to improved soil water supply during the later wheat growth period and obtained a higher wheat yield, compared to conventional tillage [ 14 ]. Traditional tillage methods fail to meet modern agricultural demands for water retention, and nutrient cycling in soil, and even for the high yield demands. Straw mulching offers a sustainable alternative by improving soil structure, enhancing organic matter content, and promoting biological nitrogen fixation. Additionally, straw mulching can optimize soil conditions (water, nutrients, aeration, and temperature) through comprehensive effects including mitigating soil erosion, buffering temperature fluctuations, and reducing water evaporation, thereby leading to improved water use efficiency, dry matter accumulation, and ultimately higher grain yield [ 15 – 19 ]. For instance, Huang et al. [ 20 ] reported that straw mulching improved grain yield, water use efficiency for grain yield (WUE r ), and water use efficiency for aboveground biomass (WUE b ) by 6.9%, 11.3%, and 16.5%, respectively, compared to no straw mulching. Similarly, in the Loess Plateau, Zhang et al. [ 21 ] found that, straw mulching increased wheat yield by 13.3–23.0%, and WUE by 15.2–18.0% over the three years due to increasing soil water content by 0.7–22.5% and reducing the 2–10 days of soil moisture less than 60% field capacity [ 22 ] compared to no straw mulching. Ram et al. [ 23 ] also reported 14.7–34.2% higher water use efficiency in straw mulching treatments (2, 4 and 6 t ha − 1 ) than no mulching treatments across different irrigation levels. However, straw mulching effectiveness showed region-specific and can be influenced by initial soil moisture conditions. Additionally, many studies showed that the interaction between tillage practice and straw management has a certain effect on the characteristics of crop dry matter accumulation and yield formation. Liu et al. [ 24 ] demonstrated that compared to conventional tillage without straw return, the combination of rotary tillage with straw return significantly increased dry matter accumulation by 28.1%, grain yield by 17.8%, and WUE by 27.9% at the harvest stage. However, although many studies have revealed that soil tillage and straw management can improve soil moisture, dry matter accumulation, and yield, but most of these studies have been limited by their short duration. The in-depth exploration of the long-term effects of fixed-position tillage and straw mulching on dry matter production, water use efficiency, and soil water storage and yield enhancement remains limited. The winter wheat-summer soybean (hereafter refers to wheat-soybean) double cropping system is one of important planting mode in China and worldwide, which can enhance soil properties and the micro-environment for crop growth by increasing organic matter, biological nitrogen fixation, erosion prevention in soils, and reducing downward movement of soil moisture, suppressing weeds and diseases, and promoting nutrient cycling through soybean cultivation [ 25 , 26 ], thereby inevitably affecting wheat production. However, the impacts of tillage methods and straw management on soil moisture, dry matter accumulation, translocation, distribution, as well as yield and water productivity in the dryland wheat-soybean double cropping system remains scarce. Therefore, this study aims to study these gaps based on a long-term field experiment initiated in October 2009. The objectives were to: 1) assess the effects of tillage methods and straw management on soil moisture, as well as yield and water productivity of wheat; 2) comprehensively evaluate the factor-contribution of wheat yield under tillage method and straw management using PLSPM and TOPSIS methods; 3) provide a theoretical and technical insights for improving yield and water productivity of wheat in dryland wheat-soybean double cropping system. Materials and Methods Experimental Site Description This study was conducted from June 2014 to June 2018 based on a long-term experiment for wheat-soybean double cropping system initiated in October 2009. The experimental site was at the experimental station of Henan University of Science and Technology in Luoyang, Henan Province, China (112.25°E, 34.36°N). The soil at the experimental site is classified as loam with soil pH of 8.1, organic matter content of 15.9 g kg⁻¹, available nitrogen content of 36.3 mg kg⁻¹, available phosphorus content of 21.0 mg·kg⁻¹, and available potassium content of 120.0 mg kg⁻¹ in the 0–20 cm layer at the initiation of the experiment (October 2009). The monthly precipitation and temperature at the experiment site are shown in Figure. 1. Specifically, the annual precipitation in the 2014–2015 and 2017–2018 growing seasons was 604.7 mm and 565.6 mm, respectively, both of them belongs to normal rainfall year, but with relatively high precipitation during the sowing to overwintering stage and the anthesis to maturity stage, respectively. In contrast, the 2015–2016 and 2016–2017 growing seasons fall into dry year, with annual precipitation of 494.3 mm and 468.7 mm, respectively. Notably, the jointing to anthesis stage received only 0 mm and 6.8 mm of rainfall during these two growing seasons. Experimental Design and Field Managements The experiment was conducted using split-plot design with tillage method as the main plot treatment, and straw management as the subplot treatment. The two tillage methods were plowing (PT) and rotary tillage (RT). Two straw management were no straw mulching (NS) and straw mulching (SM). Thus, four treatments were laid out in the experiment: plowing with no straw mulching (PTNS), plowing with straw mulching (PTSM), rotary tillage with no straw mulching (RTNS), rotary tillage with straw mulching (RTSM). The detailed operations are shown in Table 1. There were three replications for each treatment, and the plot area was 60 m 2 (20 m × 3 m). Table 2 Experimental treatments and operation methods. Code Treatment Specific operation PTNS plowing with no straw mulching The straw of the previous crop was removed from the plot 1–3 days before tillage. The plowing (30–35 cm) was carried out immediately after evenly broadcast fertilizers by hand, using a moldboard plow. Then, the rotary tillage (12–15 cm) was carried out to smooth land using a rotavator, and the seeds according to the designed amount were sown using a wheat seeder. plowing and straw removing were employed in both wheat and maize seasons. PTSM plowing with straw mulching The straw of the previous crop was evenly mulched to the surface of the original plot before emergence of the in-season crop. The other filed management were the same with the plowing with no straw returning. RTNS Rotary tillage with no straw mulching The straw of the previous crop was removed from the plot 1–3 days before tillage. The rotary tillage (12–15 cm) was carried out twice, immediately after evenly broadcast fertilizers by hand, using a rotavator. Then, the seeds according to the designed amount were sown using a wheat seeder. Rotary tillage and straw removing were employed in both wheat and maize seasons. RTSM Rotary tillage with straw mulching The straw of the previous crop was evenly mulched to the surface of the original plot before emergence of the in-season crop. The other filed management were the same with the rotary tillage with no straw returning. Management practices in all plots were consistent across all seasons. Wheat cultivar ‘Luohan 6’ and soybean cultivar ‘Zhonghuang 13’ were used. Wheat was sown in middle or late October at a seeding rate of 180.0 kg ha − 1 and harvested in late May or early June. Soybean was sown in early or middle June at a plant density of 120,000 plants ha − 1 and harvested in late September or early October. The row spaces of wheat and soybean were 20 cm and 40 cm, respectively. There was no irrigation during the whole experimental period. Compound fertilizer (N:P 2 O 5 :K 2 O = 20:15:10) with the amount of 900 kg ha⁻¹ was applied for wheat and 300 kg ha⁻¹ for soybean as basel. Weeds, pests, and diseases were controlled with herbicides and pesticides according to local practices. Measurements and Methods Dry Matter Accumulation, Translocation, and Distribution At the jointing, anthesis, and maturity stages of wheat, 50 plants were collected from three distinct rows in each plot. After cutting off the root, samples were separated into three components in terms of stem + leaf, glume + rachis and grain. Samples were immediately oven-dried at 105°C for 30 minutes, followed by drying at 65°C to a constant weight, to determine the dry weight in each organ. The total dry matter accumulation (kg ha − 1 ) were calculated from the summed by each organ. The dry matter accumulation, translocation amount, translocation rate, and contribution rate were calculated using the method of Moradi et al. [ 27 ]. Additionally, the dry matter distribution was determined using the method of Cai et al. [ 28 ]. The calculations were as follows: Pre-anthesis dry matter translocation (kg ha ⁻1 ) = Dry matter accumulation in vegetative organs at anthesis \(\:-\) Dry matter in vegetative organs at maturity. Pre-anthesis dry matter translocation rate (%) = Pre-anthesis dry matter translocation / Total dry matter accumulation at anthesis × 100. Contribution rate of pre-anthesis translocation to grain (%) = Pre-anthesis dry matter translocation amount / Grain dry matter accumulation at maturity × 100. Post-anthesis dry matter accumulation (kg ha ⁻1 ) = Total dry matter accumulation at maturity \(\:-\) Total dry matter accumulation at anthesis. Contribution rate of post-anthesis dry matter to grain (%) = Post-anthesis dry matter accumulation/Grain dry matter accumulation at maturity × 100. Dry matter distribution = DAo / DAt; Where DAo was dry matter accumulation in organ; DAt was dry matter accumulation in total above − ground part. Grain Yield At the maturity stage, three 1 m² quadrats were randomly harvested from each plot, and air-dried for 3–5 days, then threshed. Grain samples from the three quadrats were pooled and weighted. 50 ± 5g air-dried grains were further oven-dried at a temperature of 65°C for a duration of 24 hours. Grain yield for each plot were standardized to a uniform moisture content of 12.5%, using the air − dried grain weight and its determined water content. Meanwhile, the number of spikes from two random areas (1 m × 1 m) in each plot were calculated to determined spike numbers per hectare, and 30 spikes was sampled to measure the grains per spike and thousand − grains weight. Harvest index was calculated by the grain dry weight relative to total dry matter accumulation at maturity. Soil Water Storage and Water Use Efficiency Soil water storage and water use efficiency were calculated using the formulas provided by Li et al. [ 5 ]: Soil water storage (W, mm) = h i × ρ i × ω i × 10, where h is the soil layer depth (cm), ρ is the soil bulk density (g·cm⁻³), ω is the soil water content (%), i represents the i-th soil layer, 10 is a conversion factor to convert the result from cm to mm. Water consumption (ET, mm) = P + W1 − W2, where W1 (mm) and W2 (mm) represent 0–100 cm soil water storage before sowing and after harvesting, respectively; and P (mm) is precipitation during the growth period. Water use efficiency (WUE, kg ha⁻¹ mm⁻¹) = Y / ET, where Y is the grain yield (kg ha⁻¹). Calculation on the Effectiveness of Straw Mulching The improvement of water storage, yield and dry matter of straw mulching were the difference of water storage in the 0–200 cm soil layer at sowing, grain yield and dry matter accumulation at maturity between the straw mulching and no straw mulching, respectively, under the same tillage method. The effectiveness of straw mulching on water-saving was calculated by comparing the water-saving effect of per kg yield, and that on yield increase was calculated by comparing the yield increase of per mm water consumption during the wheat growth season, according to Gao et al. [ 29 ], with a little modification. Water-saving amount (WS, mm) = ET NS / Y NS − ET SM / Y SM Water-saving rate (WSE, %) = WS × Y NS / ET NS × 100 Yield-increase amount (ΔY, kg ha⁻¹) = Y SM /ET SM − Y NS /ET NS Yield-increase rate (YIE, %) = ΔY × ET NS / Y NS ) × 100% where ET NS (mm) is water consumption under no straw mulching treatment, Y NS (kg·ha⁻¹) is the corresponding yield; ET SM (mm) and Y SM (kg·ha⁻¹) represent the values under straw mulching treatment. Calculation of Comprehensive Evaluation Value Evaluation indicators—such as yield, yield components, dry matter accumulation, and water use efficiency—vary in units and cannot be directly compared. Therefore, the data for each indicator were first normalized to eliminate dimensional differences. Subsequently, the entropy weight method was applied for objective weighting according to Zou et al. [ 30 ]. Finally, the TOPSIS method was used to calculate a comprehensive evaluation value (Ci, 0 < Ci < 1) for each treatment by measuring the distance from the ideal solution; a value closer to 1 indicates that the scheme is more conducive to achieving high maize yield. Statistical Analysis Data processing was performed using Microsoft Excel 2016. Means were presented as mean ± standard deviation (Mean ± SD). Means were analyzed by one-way ANOVA (Duncan) at p = 0.05 using a SPSS 26.0 statistical software package (version 26, IBM Corp., Chicago, IL, USA). The graphs were performed using Origin software (version 2021, Origin Lab Corporation, Northampton, USA), with further refinement of figures in Adobe Illustrator 2022 (version 2022, Adobe, Adobe Ireland, USA) to ensure clarity and visual quality. Results Yield and Yield Components The experimental years and straw management significantly affected the grain yield, yield components, and harvest index of wheat in the dryland winter wheat-soybean double cropping system, the interaction of tillage methods and straw management also significantly affected the aforementioned indicators except for spike number (Table 2 ). Compared to RTNS, PTNS increased 1000-grain weight and grain yield by 1.4% and 6.2%, respectively, over the four years. Compared to RTSM, although the difference was only significant in the 2016–2017 growing season, PTSM significantly increased the grain yield by 2.6% over the four years. Compared to no straw mulching, straw mulching significantly improved wheat yield and yield components under the same tillage method. Specifically, the grain yield, spike number, grain number per spike, 1000-grain weight, and harvest index respectively increased by 10.5%, 10.4%, 6.4%, 4.4%, and 1.8% under plowing; and by 20.5%, 14.8%, 10.1%, 7.5%, and 3.6% under rotary tillage, over the four years. Considering the interaction effects, the grain yield in all the four years followed the order RTSM > PTSM > PTNS > RTNS. RTSM also gained the highest spike number, grain number per spike, 1000-grain weight, and harvest index. Both the two treatments were significantly higher than PTNS and RTNS, however, there were no significant difference of above-mentioned indicators between RTSM and PTSM except for 1000-grain weight. Table 2 Effects of tillage methods and straw management on grain yield and harvest index of wheat in wheat-soybean double cropping system Years Treatments Spike number (×10 4 ha −1 ) Grain number per spike 1000-grain weight (g) Grain yield (kg ha −1 ) Harvest Index (%) 2014–2015 PTNS 563.3 ± 21.5 ab 33.3 ± 0.1 c 44.5 ± 0.2 c 6668.1 ± 178.4 b 48.9 ± 0.4 c PTSM 602.7 ± 34.1 ab 34.6 ± 0.4 b 46.4 ± 0.2 b 7612.9 ± 293.2 a 51.1 ± 1.5 ab RTNS 552.0 ± 14.4 b 32.8 ± 0.2 c 44.6 ± 0.1 c 6340.5 ± 161.5 b 49.6 ± 0.3 bc RTSM 609.1 ± 16.5 a 35.9 ± 0.7 a 47.0 ± 0.2 a 7937.0 ± 258.7 a 52.7 ± 0.8 a 2015–2016 PTNS 508.0 ± 19.6 b 32.3 ± 0.4 b 43.6 ± 0.2 c 6144.4 ± 209.0 b 49.6 ± 0.3 c PTSM 565.7 ± 33.1 a 34.8 ± 0.9 a 45.7 ± 0.4 b 6867.9 ± 140.0 a 50.6 ± 0.3 b RTNS 497.1 ± 14.0 b 31.8 ± 0.2 b 42.7 ± 0.1 d 5840.0 ± 90.3 b 49.8 ± 0.4 c RTSM 571.9 ± 16.0 a 35.7 ± 0.6 a 46.9 ± 0.2 a 7043.9 ± 254.5 a 52.1 ± 0.4 a 2016–2017 PTNS 427.5 ± 13.9 b 27.4 ± 0.4 b 41.1 ± 0.5 b 5137.9 ± 121.7 b 44.2 ± 0.8 a PTSM 484.5 ± 13.9 a 29.3 ± 0.6 a 42.9 ± 0.4 a 5699.2 ± 146.0 a 45.1 ± 0.4 a RTNS 419.9 ± 16.5 b 27.1 ± 0.4 b 40.3 ± 1.0 b 4437.9 ± 71.6 c 43.0 ± 0.7 b RTSM 508.8 ± 22.1 a 28.9 ± 0.6 a 42.6 ± 0.3 a 5902.5 ± 169.4 a 44.8 ± 0.3 a 2017–2018 PTNS 522.7 ± 19.0 b 32.7 ± 0.3 b 43.2 ± 0.7 b 7564.5 ± 171.0 b 56.4 ± 1.0 a PTSM 578.6 ± 32.1 a 34.8 ± 0.6 a 45.1 ± 0.8 a 8011.4 ± 149.6 a 55.8 ± 0.6 a RTNS 512.1 ± 13.5 b 32.2 ± 0.2 b 42.3 ± 0.5 b 7396.1 ± 202.3 b 56.6 ± 1.4 a RTSM 584.6 ± 15.5 a 35.2 ± 0.6 a 46.2 ± 0.8 a 8049.6 ± 179.7 a 56.5 ± 0.4 a 4- Year average PTNS 505.4 ± 11.7 b 25.1 ± 0.1 b 43.1 ± 0.2 c 6378.7 ± 69.8 b 49.8 ± 0.1 c PTSM 557.9 ± 28.2 a 26.7 ± 0.3 a 45.0 ± 0.2 b 7047.8 ± 54.7 a 50.7 ± 0.2 b RTNS 495.3 ± 10.0 b 24.7 ± 0.2 b 42.5 ± 0.3 d 6003.6 ± 82.4 c 49.7 ± 0.3 c RTSM 568.6 ± 16.0 a 27.2 ± 0.5 a 45.7 ± 0.3 a 7233.2 ± 165.1 a 51.5 ± 0.1 a ANOVA results Years (Y) ** ** * ** ** Tillage methods (T) ns ns ns ns ns Straw management (S) ** ** ** ** ** Y×T ns ns ns ns * Y×S ns * * ** ** T×S ns ** ** ** * Y×T×S ns ns ns ns ns PTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean ± SD (n = 3). Values followed by different small letters in a column indicate significant difference among treatments ( p < 0.05). *and**indicate significant differences at the p < 0.05 and p < 0.01 levels, respectively. ns means no significance. Dry matter Accumulation,Translocation, and Distribution Dry Matter Accumulation at Different Stages Figure 2 indicated that the experimental years, tillage methods (except for jointing stage) and straw management significantly influenced the dry matter accumulation in wheat under the dryland wheat-soybean double cropping system. Over the four years, RTNS increased dry matter accumulation at the anthesis stage by 5.4% but reduced it at the maturity stage by 6.2% compared to PTNS. RTSM resulted in an average increase of 7.2% in dry matter accumulation at the anthesis stage compared to PTSM but not at the maturity stage. Under the same tillage method, straw mulching significantly increased dry matter accumulation across all stages and years. Over the four years, PTSM treatments increased dry matter accumulation by 8.3% at the anthesis stage and 8.6% at maturity compared to PTNS, while RTSM treatments increased dry matter accumulation by 9.7%, 10.2%, and 16.9% at the jointing, anthesis, and maturity stages, respectively, compared to RTNS. However, there was no significant difference between PTSM and RTSM. Overall, RTSM showed a stronger ability in promoting wheat dry matter accumulation. Characteristics of Translocation of Pre-anthesis Dry Matter and Accumulation of Post-anthesis Dry Matter As shown in Table 3 , the experimental years, tillage methods (excluding pre-anthesis translocation), and straw management significantly affected the characteristics of pre-anthesis dry matter translocation and post-anthesis accumulation in wheat. Compared to RTNS, PTNS increased the accumulation and contribution to grain of post-anthesis dry matter by 64.1% and 54.1%, respectively, with significant improvements were all observed in 3 years. RTSM increased the translocation, translocation rate, and contribution to grain of pre-anthesis dry matter by, 25.0%, 16.1%, and 21.5%, respectively, compared to PTSM, with significant improvements were observed in 3 years, respectively. Conversely, PTSM increased the accumulation and contribution to grain of post-anthesis dry matter by 19.9% and 23.0%, respectively, compared to RTSM. RTNS increased the translocation amount, translocation rate, and contribution to grain of pre-anthesis dry matter by 33.0%, 26.0%, and 43.5%, respectively, compared to PTNS, with significant improvements were observed in 3 years, respectively. Over the four years, Compared to no straw mulching, the pre-anthesis dry matter translocation amount and the post-anthesis dry matter accumulation were respectively increased by 12.0% and 9.5% under plowing, and by 5.2% and 49.8% under RT. However, compared to no straw mulching, straw mulching decreased the translocation rate and contribution to grain of pre-anthesis under rotary tillage, with average reductions of 4.7% and 15.1%, respectively. Table 3 Effects of tillage methods and straw management on the characteristics of dry matter accumulation translocation and its contribution to grain of wheat in wheat-soybean double cropping system Years Treatments Pre-anthesis dry matter Post-anthesis dry matter Translocation amount (kg ha −1 ) Translocation rate (%) Contribution rate (%) Accumulation (kg ha −1 ) Contribution rate (%) 2014–2015 PTNS 2922.4 ± 190.7 c 29.5 ± 0.8 c 43.8 ± 2.2 c 3745.7 ± 140.2 ab 56.2 ± 2.2 a PTSM 3467.5 ± 114.7 b 32.3 ± 1.3 b 45.6 ± 3.3 c 4145.4 ± 401.6 a 54.4 ± 3.3 a RTNS 4347.2 ± 173.3 a 40.3 ± 1.5 a 68.6 ± 3.5 a 1993.3 ± 254.7 c 31.4 ± 3.5 c RTSM 4514.3 ± 410.5 a 38.7 ± 2.0 a 56.8 ± 3.8 b 3422.7 ± 238.2 b 43.2 ± 3.8 b 2015–2016 PTNS 2587.6 ± 505.1 c 29.1 ± 3.2 b 42.0 ± 6.8 b 3556.8 ± 306.0 a 58.0 ± 6.8 a PTSM 3267.9 ± 158.8 b 32.8 ± 1.8 b 47.6 ± 3.3 b 3600.0 ± 297.7 a 52.4 ± 3.3 a RTNS 4010.5 ± 297.9 a 40.5 ± 1.7 a 68.7 ± 5.0 a 1829.5 ± 290.6 c 31.3 ± 5.0 b RTSM 4326.0 ± 297.8 a 40.1 ± 1.4 a 61.4 ± 3.0 a 2717.9 ± 203.4 b 38.6 ± 3.0 b 2016–2017 PTNS 2547.6 ± 51.2 b 28.2 ± 0.3 c 49.6 ± 0.6 c 2590.3 ± 80.9 b 50.4 ± 0.6 a PTSM 2701.4 ± 26.0 b 28.0 ± 0.7 c 47.4 ± 1.5 c 2997.8 ± 162.9 a 52.6 ± 1.5 a RTNS 3392.9 ± 142.6 a 36.6 ± 1.6 a 76.5 ± 3.4 a 1045.0 ± 154.7 c 23.5 ± 3.4 c RTSM 3446.4 ± 191.9 a 32.2 ± 0.8 b 58.5 ± 4.7 b 2456.1 ± 347.3 b 41.5 ± 4.7 b 2017–2018 PTNS 3266.0 ± 155.3 b 32.9 ± 2.0 a 48.6 ± 3.1 a 3458.0 ± 278.5 ab 51.4 ± 3.1 a PTSM 3249.1 ± 75.8 b 31.0 ± 0.8 a 45.6 ± 1.5 a 3872.1 ± 167.2 a 54.4 ± 1.5 a RTNS 3306.3 ± 116.9 b 33.7 ± 1.4 a 50.4 ± 3.1 a 3268.1 ± 296.0 b 49.6 ± 3.1 a RTSM 3564.7 ± 66.5 a 33.4 ± 1.0 a 49.8 ± 1.6 a 3590.4 ± 182.6 ab 50.2 ± 1.6 a 4-year PTNS 2830.9 ± 150.5 c 30.0 ± 0.4 c 46.0 ± 1.3 c 3337.7 ± 28.3 b 54.1 ± 1.3 a average PTSM 3171.5 ± 74.4 b 31.1 ± 1.1 c 46.6 ± 2.1 c 3653.8 ± 237.1 a 53.5 ± 2.2 a RTNS 3764.2 ± 86.2 a 37.9 ± 1.0 a 66.0 ± 2.1 a 2034.0 ± 171.2 c 35.1 ± 2.3 c RTSM 3962.9 ± 206.9 a 36.1 ± 0.9 b 56.6 ± 2.2 b 3046.8 ± 125.0 b 43.5 ± 2.2 b ANOVA results Years (Y) ** ** ** ** ** Tillage methods (T) ** ** ** ** ** Straw management (S) ** ns ** ** ** Y×T ** ** ** ** ** Y×S ns * * * * T×S ns ** ** ** ** Y×T×S ns ns * * * PTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean ± SD (n = 3). Values followed by different small letters in a column indicate significant difference among treatments ( p < 0.05). *and**indicate significant differences at the p < 0.05 and p < 0.01 levels, respectively. ns means no significance. Dry Matter Distribution at Maturity The experimental years and straw management also significantly affected wheat dry matter distribution at maturity, while tillage methods only influenced the dry matter distribution in stem + leaves and the grain percentage (Table 4 ). Compared to RTNS, PTNS significantly increased the dry matter accumulation in stem + leaves, glumes, and grains by 7.9%, 4.0%, and 6.4%, respectively. Compared to PTSM, RTSM increased grain dry matter accumulation by 2.7%, while there were no significant differences for dry matter accumulation and distribution percentages in other organs. The effects of straw management on dry matter distribution varied with tillage methods. Compared to PTNS, PTSM increased grain dry matter distribution proportion by − 1.2–4.5%, with the significant differences were observed in 2 years. Compared to RTNS, RTSM increased grain dry matter distribution proportion by − 0.2–6.3%, with the significant differences were observed in 3 years, while significantly decreased the percentage in stem + leaves in 3 years, with an average reduction of 3.2% over the four years. Table 4 Effects of tillage methods and straw management on the distribution of dry matter in wheat at maturity in wheat-soybean double cropping system Years Tillage modes Stem + leaf Glume Grain DAA (kg ha −1 ) Percentage (%) DAA (kg ha −1 ) Percentage (%) DAA (kg ha −1 ) Percentage (%) 2014–2015 2015 PTNS 5097.7 ± 140.4 a 37.4 ± 0.3 a 1873.7 ± 64.7 ab 13.7 ± 0.4 a 6668.1 ± 178.4 b 48.9 ± 0.4 c PTSM 5298.7 ± 132.1 a 35.6 ± 1.1 ab 1986.7 ± 52.0 a 13.3 ± 0.4 a 7612.9 ± 293.2 a 51.1 ± 1.5 ab RTNS 4695.3 ± 132.2 b 36.8 ± 0.5 a 1741.6 ± 120.8 b 13.6 ± 0.8 a 6340.5 ± 161.5 b 49.6 ± 0.3 bc RTSM 5191.7 ± 89.4 a 34.5 ± 0.7 b 1941.4 ± 56.6 a 12.9 ± 0.3 a 7937.0 ± 258.7 a 52.7 ± 0.8 a 2015–2016 PTNS 4600.7 ± 216.0 a 37.1 ± 0.2 a 1649.3 ± 59.0 bc 13.3 ± 0.1 a 6144.4 ± 209.0 b 49.6 ± 0.3 c PTSM 4852.0 ± 122.4 a 35.8 ± 0.1 b 1846.4 ± 98.7 a 13.6 ± 0.4 a 6867.9 ± 140.0 a 50.6 ± 0.3 b RTNS 4293.7 ± 122.6 b 36.6 ± 0.3 a 1588.6 ± 78.2 c 13.6 ± 0.4 a 5840.0 ± 90.3 b 49.8 ± 0.4 c RTSM 4688.0 ± 160.0 a 34.7 ± 0.3 c 1773.6 ± 52.4 ab 13.2 ± 0.6 a 7043.9 ± 254.5 a 52.1 ± 0.4 a 2016–2017 PTNS 4933.7 ± 92.2 b 42.5 ± 0.3 a 1544.1 ± 96.2 b 13.3 ± 0.6 a 5137.9 ± 121.7 b 44.2 ± 0.8 a PTSM 5312.3 ± 144.3 a 42 ± 0.5 a 1630.5 ± 30.2 ab 12.9 ± 0.1 a 5699.2 ± 146.0 a 45.1 ± 0.4 a RTNS 4416.0 ± 103.7 c 42.8 ± 0.3 a 1457.3 ± 119.4 b 14.1 ± 1.2 a 4437.9 ± 71.6 c 43 ± 0.7 b RTSM 5462.0 ± 91.8 a 41.5 ± 0.7 a 1797.8 ± 172.6 a 13.7 ± 0.8 a 5902.5 ± 169.4 a 44.8 ± 0.3 a 2017–2018 PTNS 4802.1 ± 213.6 bc 35.8 ± 0.6 a 1882.6 ± 69.7 b 14.1 ± 0.8 a 6724.0 ± 152.0 b 50.2 ± 0.9 a PTSM 5140.7 ± 127.8 a 35.8 ± 0.8 a 2093.3 ± 87.2 a 14.6 ± 0.6 a 7121.2 ± 133.0 a 49.6 ± 0.6 a RTNS 4610.2 ± 158.8 c 35.2 ± 1.1 a 1891.7 ± 47.3 b 14.5 ± 0.2 a 6574.3 ± 179.8 b 50.3 ± 1.2 a RTSM 5034.8 ± 163.0 ab 35.3 ± 0.6 a 2064.1 ± 49.8 a 14.5 ± 0.3 a 7155.2 ± 159.7 a 50.2 ± 0.3 a 4-year average PTNS 4858.5 ± 115.8 b 38.0 ± 0.2 a 1737.4 ± 11.3 b 13.6 ± 0.3 a 6168.6 ± 69.5 b 48.3 ± 0.1 c PTSM 5150.9 ± 13.4 a 37.2 ± 0.1 ab 1889.2 ± 51.7 a 13.6 ± 0.3 a 6825.3 ± 55.9 a 49.2 ± 0.3 b RTNS 4503.8 ± 78.7 c 37.6 ± 0.3 a 1669.8 ± 47.2 b 13.9 ± 0.4 a 5798.2 ± 78.3 c 48.4 ± 0.3 c RTSM 5094.1 ± 87.7 a 36.4 ± 0.5 b 1894.2 ± 82.8 a 13.5 ± 0.5 a 7009.6 ± 160.4 a 50.1 ± 0.2 a ANOVA results Years (Y) ** ** ** ** ** ** Tillage modes (T) ** * ns ns ns * Straw management (S) ** ** ** ns ** ** Y×T ns ns ns ns ns ** Y×S ** * ns ns ** ** T×S ** ns ns ns ** * Y×T×S ns ns ns ns ns ns PTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean ± SD (n = 3). Values followed by different small letters in a column indicate significant difference among treatments ( p < 0.05). *and**indicate significant differences at the p < 0.05 and p < 0.01 levels, respectively. ns means no significance. Water Use Efficiency Tillage methods and straw management ca n influence soil water storage in the 0–200 cm soil profile before sowing and at harvest of wheat in the dryland wheat-soybean double cropping system, with the notable differences across soil layers (Fig. 3 ). Compared to RTSM, PTSM had an average increase of 6.8% in the 0–100 cm soil layer, whereas exhibited an average decrease of 12.1% in the 100–200 cm soil layer, indicating that rotary tillage with straw mulching (RTSM) reduced shallow soil water storage but enhanced deep soil water storage. At harvest, soil water storage varied with soil depth. In the 0–40 cm soil layer, straw mulching significantly increased soil water storage compared to no straw mulching, in which, PTSM increased by 12.7% compared to PTNS, and RTSM increased by 9.4% compared to RTNS. However, in the 40–200 cm subsoil layers, the treatments with no straw mulching had higher soil water storage, in which PTNS showed average increases of 7.8% compared to PTSM and RTNS showed average increases of 6.3% compared to RTSM. Despite these trends, there were no significant differences were observed between the two tillage methods in the middle and deeper soil layers under the same straw management. Overall, the effect of straw mulching on soil water storage was greater than that of tillage methods, particularly in the upper and middle soil layers. Figure 4 indicated that under the same straw management, tillage methods had no significant impact on water consumption during the growing season (ET). However, PTNS significantly improved water use efficiency (WUE) by 6.6% compared to RTNS over the 4 years, with significant increases were observed in 2 years. Under the same tillage method, straw mulching significantly increased ET compared to no straw mulching, with the increase of 7.4% and 10.4% under plowing and rotary tillage, respectively, over the four years. Likewise, straw mulching significantly enhanced WUE by 3.1% and 9.6%, respectively under plowing and rotary tillage. Effect of Straw Mulching on Water-saving and Yield Improvement Further analysis revealed that tillage methods significantly influenced the water-saving and yield improvement induced by straw mulching (Table 5 ). Under different years and tillage methods, straw mulching consistently resulted in positive values for pre-sowing water storage, yield and dry matter, water-saving amount and rate per kg yield, and yield-improvement amount and rate per mm water consumption. Specifically, the pre-sowing water storage, yield and dry matter improvement under rotary tillage were significantly higher than those under plowing in 2, 4, and 2 years, respectively, with 4-year average increase of 66.2%, 84.5%, and 60.7%, respectively. Similarly, the water-saving amount and rate per kg yield, as well as the yield-improvement amount and rate per mm water consumption under rotray were significantly higher than plowing in 2 years, with 4-year average increase of 231.3%, 196.8%, 216.7%, and 162.3%, respectively. These results indicated that straw mulching effectively enhances pre-sowing water storage, yield, and dry matter, as well as water-saving per kg yield and yield-improvement per mm water consumption. Moreover, the effectiveness of straw mulching on these indicators under rotary tillage were more pronounced than that under plowing. Table 5 Effects of straw mulching on water-saving and wheat productivity improvement in wheat-soybean double cropping system Years Tillage methods Water storage improvement (mm) Yield improvement (kg ha −1 ) Dry matter improvement (kg ha −1 ) Water-saving per kg yield Yield-improvement per mm water consumption Amount (mm) Rate (%) Amount (kg ha −1 ) Rate (%) 2014–2015 PT 22.0 ± 0.6 a 944.7 ± 115.3 b 2417.4 ± 679.5 a 3.5 ± 1.5 b 6.3 ± 2.8 b 1.2 ± 0.6 b 21.8 ± 9.9 b RT 34.5 ± 2.3 a 1596.6 ± 112.3 a 3348.2 ± 837.7 a 8.1 ± 2.1 a 13.7 ± 3.3 a 2.7 ± 0.7 a 45.7 ± 10.6 a 2015–2016 PT 20.9 ± 2.4 b 723.5 ± 73.1 b 2426.6 ± 1186.5 a 1.1 ± 0.1 b 2.1 ± 0.3 b 0.4 ± 0.1 b 7.2 ± 1.0 b RT 37.4 ± 1.1 a 1203.9 ± 182.2 a 3052.3 ± 742.3 a 3.1 ± 2.1 b 5.6 ± 3.7 b 1.1 ± 0.7 b 19.4 ± 13.1 b 2016–2017 PT 19.7 ± 2.1 b 561.3 ± 67.9 b 1818.6 ± 217.8 b 1.6 ± 0.7 b 2.7 ± 1.2 b 0.5 ± 0.2 b 8.6 ± 3.9 b RT 44.9 ± 5.5 a 1464.6 ± 116.1 a 4446.7 ± 551.5 a 7.5 ± 2.2 a 11.8 ± 3.2 a 2.1 ± 0.6 a 33.2 ± 8.7 a 2017–2018 PT 21.6 ± 1.0 a 397.2 ± 24.6 b 1644.9 ± 416.9 b 1.1 ± 1 b 2.9 ± 2.4 b 0.8 ± 0.6 b 19.3 ± 15.8 b RT 22.9 ± 5.3 a 580.8 ± 24.1 a 2504.8 ± 205.4 a 2.3 ± 0.5 b 5.7 ± 1.3 b 1.5 ± 0.4 b 38.2 ± 9.4 b 4-year average PT 21.0 ± 1.0 b 656.7 ± 7.1 b 2076.9 ± 488.2 b 1.6 ± 1 b 3.1 ± 2.0 b 0.6 ± 0.4 b 13.0 ± 8.7 b RT 34.9 ± 2.7 a 1211.5 ± 101.3 a 3338 ± 572.8 a 5.3 ± 1.3 a 9.2 ± 2.0 a 1.9 ± 0.4 a 34.1 ± 5.5 a ANOVA results Years (Y) ** ** ns ** ** ** * Tillage method(T) ** ** ** ** ** ** ** Y×T ** ** ns * ns ns ns PT: plowing, RT: rotary tillage. Date presented as mean ± SD (n = 3). Values followed by different small letters in a column indicate significant difference among treatments ( p < 0.05). *and** indicate significant differences at the p < 0.05 and p < 0.01 levels, respectively. ns means no significance. Correlation and Path Model Regression analysis revealed a significant linear relationship between wheat grain yield and ET (Fig. 5 ), underscoring the critical role of water consumption in improving wheat productivity. Under the four years, water consumption exhibited a significantly positive correlation with dry matter accumulation, except for the 2017–2018 growing season. However, the overall regression analysis showed a positive correlation but without statistical significance for yield. This result indicated substantial variability in water-yield relationships across different growing seasons. Conversely, the aggregated analysis demonstrated a significant positive correlation between water consumption and dry matter accumulation across years. PLS-PM analysis further indicated that straw mulching significantly influenced wheat yield through multiple pathways (Fig. 6 A and 6 B). Compared to no straw mulching treatment, straw mulching had a pronounced positive effect on yield (path coefficient, PC = 0.308, p < 0.01). Higher water use efficiency (WUE) and water consumption significantly contributed to improvements in both yield and dry matter accumulation, with path coefficients of PC = 0.323 ( p < 0.01) and PC = 0.766 ( p < 0.01), respectively. Moreover, effective water use had a greater enhancement impact on dry matter accumulation than yield enhancement. Additionally, increases in dry matter accumulation were found to directly contribute to yield improvement (PC = 0.612, p < 0.01). Table 6 shows that the comprehensive evaluation value (di) for RTSM was consistently the highest, while RTNS recorded the lowest values across four cropping seasons. In 2014–2015, the di values were 0.81 for RTSM, 0.69 for PTSM, 0.38 for PTNS, and 0.24 for RTNS. In 2015–2016, these values were 0.68 for RTSM, 0.57 for PTSM, 0.38 for PTNS, and 0.26 for RTNS. In 2016–2017, RTSM reached 0.80, PTSM 0.68, PTNS 0.47, and RTNS 0.29. Finally, in 2017–2018, the values were 0.71 for RTSM, 0.60 for PTSM, 0.41 for PTNS, and 0.29 for RTNS. Overall, RTSM di values ranged from 0.68 to 0.81, PTSM from 0.57 to 0.69, PTNS from 0.38 to 0.47, and RTNS from 0.24 to 0.29, clearly indicating that RTSM consistently outperformed the other treatments based solely on the measured evaluation values. Table 6 The degree of fit and ranking under different treatments by TOPSIS method. Treatments 2014–2015 2015–2016 2016–2017 2017–2018 di+ di- di Ranking di+ di- di Ranking di+ di- di Ranking di+ di- di Ranking PTNS 0.24 0.14 0.38c 3 0.26 0.16 0.38c 3 0.2 0.18 0.47c 3 0.23 0.16 0.41c 3 PTSM 0.11 0.25 0.69b 2 0.17 0.22 0.57b 2 0.12 0.25 0.68b 2 0.15 0.23 0.6b 2 RTNS 0.29 0.09 0.24d 4 0.29 0.1 0.26d 4 0.28 0.11 0.29d 4 0.26 0.11 0.29d 4 RTSM 0.07 0.3 0.81a 1 0.12 0.26 0.68a 1 0.07 0.28 0.8a 1 0.11 0.26 0.71a 1 di+: The distance of each evaluation scheme to the positive ideal solution; di-: The distance of each evaluation scheme to the negative ideal solution; Ci: Closeness coefficient. Different lowercase letters following the data in the same column indicate significant differences among treatments at the p < 0.05 level. Discussion Effects of Tillage Methods and Straw Management on Wheat Yield Optimizing wheat yield in dryland regions is crucial not only to meet the growing food demand but also to promote sustainable agricultural practices [ 31 ]. Research has shown that plowing is more effective than rotary tilling in breaking the plowing pan, promoting root penetration and development, ensuring water and nutrient supply during the later stages of growth, and increasing the number of ears, number of grains per ear, and thousand-grain weight, thereby enhancing yield [ 5 , 32 , 33 ]. This study demonstrated that the effect of tillage methods on wheat yield varies with straw management. Under no straw mulching, plowing increased yield by 2.6% and thousand-grain weight by 1.5% compared to rotary tilling. Conversely, under straw mulching, rotary tillage has an average yield increase of 6.2% over the four years compared to plowing, with average increases in thousand-grain weight and harvest index both at 1.6%. The observed yield enhancement can be attributed to rotary tillage-induced acceleration of straw decomposition through stimulation of extracellular lignocellulose hydrolase activities and enrichment of copiotroph taxa, which facilitate synchronized nutrient mineralization (particularly ammonium-N and labile carbon pools) and promoting root proliferation and photosynthetic assimilation efficiency [ 12 , 34 ]. The comparison between straw mulching and no straw mulching treatments underscores the critical role of straw in enhancing wheat yield. Under both plowing and rotary tillage regimes, straw mulching consistently enhanced yield, with average increases of 10.5% under plowing and 20.5% under rotary tillage (Table 2 ). These yield improvement may be ascribed to straw mulching-induced improvement in organic matter decomposition, which enhanced soil moisture retention and nutrient availability, and directly benefited grain filling and 1000-grain weight [ 16 – 18 , 35 ]. The substantial yield gain under RTSM was mainly due to the synergistic effects of improved water management and nutrient cycling [ 36 ]. This demonstrated that straw mulching is essential for maintaining soil moisture, particularly in rain-fed cropping system where water stress is a prominent limiting factor for yield formation. Under no straw mulching, rapid soil moisture loss and greater temperature fluctuations further stress the crop, while reduced organic matter content limits nutrient cycling and microbial activity, thereby constraining yield formation. Over the four years, RTSM increased the spike number, grain number per spike, 1000-grain weight, and harvest index increasing by 14.8%, 10.1%, 7.5%, and 3.6%, respectively, compared to RTNS. These gains may be attributed to the synergistic effects of enhancing soil penetration resistance and root penetration, facilitating nutrient and water uptake by rotary tillage [ 37 ], and improving moisture retention, reducing evaporation, stabilizing soil temperature fluctuations by straw mulching [ 38 , 39 ]. The increase in 1000-grain weight and spike number under RTSM was especially notable, as these yield components are highly sensitive to water availability and nutrient supply during grain filling stage [ 40 , 41 ]. In contrast, PTSM also increased wheat yield, but the yield increase was slightly lower than that of RTSM relative to their respective non-mulched treatments. The smaller yield improvements observed under PTNS may be due to the limited soil loosening and root penetration compared to RTNS, which restricts water and nutrient uptake efficiency. This study highlights the significant impact of tillage methods and straw management on wheat yield and its components, with a particularly strong interaction between the two factors. The rotary tillage combined with straw mulching gain the highest yield and should be applied in the wheat-soybean double cropping system. Effects of Tillage Methods and Straw Management on Dry Matter Accumulation, Translocation, and Distribution Efficient dry matter accumulation, translocation, and distribution are pivotal for wheat yield in rain-fed cropping systems, driven by tillage-straw interactions [ 5 ]. Previous study indicated the significant influence of tillage methods and straw management on dry matter dynamics, and demonstrated that the combination of rotary tillage with straw mulching optimizes soil conditions, enhances nutrient availability, and improves moisture retention, thereby promoting dry matter accumulation and its efficient translocation to grains [ 5 , 11 , 41 ]. Our results showed that rotary tillage with straw mulching significantly increased dry matter accumulation at anthesis and maturity by 6.1% and 3.7%, respectively, compared to plowing with straw mulching. This was in accordance to Zhai et al. [ 42 ], who reported that dry matter accumulation and, yield, and harvest index of deep rotary tillage were significantly higher than those of no tillage with strip subsoiling, primarily due to a significant increase in post-anthesis dry matter accumulation. Furthermore, our trial showed rotary tillage with straw mulching enhanced pre-anthesis dry matter translocation, translocation rate, and contribution to grain yield by 105%, 88.4%, and 98%, respectively. The elevated pre-anthesis dry matter translocation, translocation rate, and the contribution of translocation to grain under straw-mulched rotary tillage are mechanistically associated with two synergistic drivers: (1) prolonged soil moisture sustaining nitrate reductase activity to enhance nitrogen assimilation efficiency [ 43 , 44 ], and (2) ethylene-auxin signaling coordination mediated by improved soil aeration for optimized source-sink allocation dynamics [ 45 , 46 ]. These improvements suggest that rotary tillage with straw mulching facilitates a more efficient source-sink relationship, ensuring that assimilates produced before anthesis are effectively re-mobilized to grains. In contrast, under no straw mulching, rotary tillage did not enhance dry matter translocation and even reduced its translocation rate compared to plowing, underscoring the importance of straw retention in sustaining soil nutrients and moisture availability [ 47 ]. Yue et al. [ 48 ] similarly reported that straw mulching improves dry matter accumulation and translocation at all growth stages. In our trails, rotary tillage with straw mulching increased post-anthesis dry matter accumulation by 23.9% compared to no straw mulching, further reinforcing its role in optimizing yield formation. In addition to total dry matter accumulation, this study also examined dry matter distribution in distinct organs and found there were significant interactions between tillage and straw management. Rotary tillage with straw mulching leading to greater dry matter allocation to grains. These results align with previous research indicating that tillage and straw mulching improve soil structure and microbial activity, which facilitate carbon and nitrogen cycling [ 49 ]. For example, Zheng et al. [ 8 ] found that plowing improved dry matter translocation efficiency by increasing soil organic matter, while Li et al. [ 32 ] reported that rotary tillage with straw mulching enhanced root growth and nutrient uptake, leading to higher dry matter accumulation and increased grain yield. Additionally, plowing with straw mulching encouraged deeper root penetration and improved soil nutrient availability, supporting grain filling [ 50 ]. These findings emphasize the potential of sustainable tillage and straw management practices in mitigating water limitations, improving dry matter efficiency, and ensuring stable wheat yields in rain-fed systems. Effects of Tillage Methods and Straw Management on Water Use Efficiency of Wheat Tillage methods modify soil physical and chemical properties, thereby increasing soil water storage capacity and enhancing crop yield and WUE [ 5 , 51 ]. Our study showed that the interaction between tillage methods and straw mulching plays a critical role in optimizing water storage in a rain-fed wheat–soybean double cropping system. Specifically, RTNS increased water storage in the upper soil layers (0–40 cm) at sowing and harvest of wheat, likely due to its ability to loosen the soil surface and facilitate water infiltration [ 52 ]. In contrast, PTNS helped to enhance water storage in deeper soil layers (40–200 cm), particularly at harvest. These findings corroborate [ 53 ], who demonstrated that straw mulching effectively improves water retention across diverse soil types, suggesting that its benefits are broadly applicable regardless of soil texture. Our trial demonstrated that straw mulching significantly improved soil water retention. This enhancement could be attributed to organic matter incorporation and reduced evaporation, consistent with previous studies reporting that surface residue coverage enhances soil aggregation while suppressing vapor flux through physical barrier effects [ 38 , 54 ]. For instance, under straw mulching, RTSM increased water storage by 5.0% compared to RTNS [ 55 ]. The integration of effective straw management with appropriate tillage practices also substantially improves WUE and crop productivity [ 24 ]. In the present study, although straw mulching increased water consumption during the growing season, PTSM and RTSM treatments increased water use by 7.4% and 10.4%, respectively, compared to no straw mulching treatments. For example, RTSM achieved a 9.6% higher WUE than RTNS. Regression analysis revealed a significant positive correlation between water consumption and dry mater accumulation ( p < 0.05), emphasizing that adequate moisture is critical for biomass production [ 56 ]. The improved WUE under RTSM was mainly attributed to enhanced dry matter accumulation (Fig. 2 ) and dry matter translocation to grains (Table 4 ), ultimately leading to a higher grain yield (Table 2 ). These results, consistent with previous studies [ 53 ], demonstrated that integrating rotary tillage and straw mulching optimizes soil moisture conditions, offering a promising strategy for achieving sustainable, high-yield wheat production in a rain-fed wheat–soybean double cropping system. Despite slightly higher water consumption under straw-mulched treatments, these increases were offset by greater WUE, and enhanced translocation of dry matter to grains. The additional water stored in mulched systems was effectively utilized to support higher spike numbers, grain numbers per spike, and 1000-grain weight. These findings align with previous research [ 19 , 55 ] and emphasize that straw mulching is a crucial strategy for improving soil moisture availability, maximizing WUE, and achieving sustainable yield increases in water-limited environments. Thus, integrating straw mulching with appropriate tillage practices presents a viable long-term solution for enhancing resource use efficiency and stabilizing wheat production in rain-fed agricultural systems. Our results also indicated that the effectiveness of straw mulching on the improvement of pre-sowing water storage, yield, dry matter accumulation, and the water-saving amounts and rates of per kg yield, and yield improvement per mm water consummation varied with tillage methods. the water-saving amount and rate per kg yield, as well as the yield-improvement amount and rate per mm water consumption under rotary were 223.7%, 195.5%, 187.5%, and 163.3% higher than plowing, which may be due to the pre-sowing water storage, yield and dry matter improvement under rotary tillage were significantly higher than those under plowing in 2, 4, and 2 years, respectively, with 4-year average increase of 66.0%, 84.5%, and 60.7%. Pathway Analysis Using PLSPM and Comprehensive Evaluation Regression analysis further underscored the critical role of water consumption in wheat yield formation. A significant positive correlation was observed between water consumption and dry matter accumulation ( p < 0.05), indicating that adequate moisture is essential for biomass production. The aggregated data did not reveal a statistically significant relationship between water consumption and yield—likely due to interannual variability—the strong association with dry matter accumulation confirms the importance of water availability for crop growth [ 56 ]. In the present study, the partial least squares path modeling (PLS-PM) analysis revealed that straw mulching had a pronounced positive effect on yield (path coefficient, PC = 0.308, p < 0.01). Higher water use efficiency (PC = 0.323, p < 0.01) and water consumption (PC = 0.766, p < 0.01) were significantly associated with improvements in both yield and DM accumulation, while increased DM accumulation directly contributed to yield enhancement (PC = 0.612, p < 0.01). Our study also found that the interaction between tillage and straw management optimizes soil water retention. RT improved water storage in the upper soil layers before sowing and at harvest, whereas PTNS enhanced water retention in deeper soil layers. Regression analysis also confirmed a significant positive correlation between water consumption and dry matter accumulation ( p < 0.05), underscoring the essential role of soil moisture in biomass production. Although there was no significant relationship between total water consumption and yield across all years—likely due to interannual variability—the strong association with dry matter accumulation highlights the importance of stable soil moisture availability for crop growth [ 56 ]. PLS-PM analysis further demonstrated that straw mulching directly contributed to higher yields through multiple pathways. Straw mulching had a strong positive effect on yield (PC = 0.308, p < 0.01), with increased WUE (PC = 0.323, p < 0.01) and water consumption (PC = 0.766, p < 0.01) significantly improving both dry matter accumulation and grain yield. Furthermore, increased dry matter accumulation directly enhanced yield formation (PC = 0.612, p < 0.01), reinforcing the critical role of optimized soil moisture conditions in supporting grain development. The TOPSIS model revealed that RTSM treatment consistently achieved the highest comprehensive evaluation values over the four-year period, while RTNS recorded the lowest. This outcome is likely due to the superior integration of straw residues in RTSM, which promotes a more uniform distribution of organic matter, enhancing soil structure, moisture retention, and nutrient recycling [ 6 ]. In contrast, RTNS may lead to uneven residue incorporation and greater disruption of soil aggregates, resulting in lower organic matter retention and reduced nutrient availability [ 57 ]. The intermediate performance of other study further supports the notion that optimal tillage and residue management practices can significantly influence soil fertility and crop productivity [ 40 , 50 ]. These mechanistic insights not only validate the TOPSIS results but also emphasize the critical role of conservation tillage in sustaining long-term agricultural productivity. Conclusions The results of the present study indicated that the effects of tillage methods on dry matter production, yield, and water use efficiency of wheat in rain-fed wheat-soybean double cropping system varied with straw management. Specifically, PTNS was superior to RTNS, while RTSM significantly outperformed PTSM. Straw mulching was beneficial for increasing soil water storage and promoting water absorption from deep soil by wheat plants, thereby enhancing dry matter accumulation and its translocation to grains, optimizing yield components, ultimately increasing wheat yield and water use efficiency by 10.5–20.5% and 7.4–10.4%, respectively. RTSM helped to promote the pre-sowing water storage, dry matter accumulation and translocation, and offering superior water-saving and yield-improvement effects compared to PTSM, making it is suitable for widespread for high yield wheat production in dryland wheat-soybean double-cropping system. Declarations Author Contributions: S. D. Conceptualization; Data curation; Investigation; Writing—Original draft; Writing—Review & editing. M. H. Data curation; Writing—Original draft. J. Z., Q. Z., C. H., A. L. Investigation; Data curation. H W. Software; Visualization; Writing—Review & editing. G. F. Conceptualization, Writing—Review & editing. J. W., Y. L. Conceptualization; Funding acquisition; Writing—Review & editing. Funding: This study was financially supported by the National Key Research and Development Program (under Grant No.: 2022YFD2300800; 2018YFD0300700) and the Science and Technology Research Project of Henan, China (under Grant No.:232102111009). Data Availability Statement: This study includes all supporting data, which can be obtained from the corresponding authors upon request. Acknowledgments: The author would like to thank the reviewers for their valuable comments and suggestions for this work. 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2018.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/918befa253171abd22a7818d.png"},{"id":82597649,"identity":"714cb0b2-346a-4a84-9f9c-b183dfdb5088","added_by":"auto","created_at":"2025-05-13 09:07:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":206922,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of tillage methods and straw management on dry matter accumulation at different growth stages of wheat in wheat-soybean double cropping system\u003c/p\u003e\n\u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching, Y: years, T: tillage methods, S: straw management. Different lowercase letters within the same year or 4-year average in figures indicate significant difference among treatments (p\u0026lt;0.05). *and**indicate significant differences at the p\u0026lt;0.05 and p\u0026lt;0.01 levels, respectively. ns means no significance.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/17ee58a7f93917cb19c189b5.png"},{"id":82597650,"identity":"11e4d28f-3ca8-457f-970c-2b969ade38d0","added_by":"auto","created_at":"2025-05-13 09:07:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":218418,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of tillage methods and straw management on soil water storage across different soil layers (0–200 cm) before wheat sowing in wheat-soybean double cropping system\u003c/p\u003e\n\u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/8d6d84b27755046aa4d0931b.png"},{"id":82598581,"identity":"d118183b-50b3-4c7d-96d1-c89fae2bbd58","added_by":"auto","created_at":"2025-05-13 09:15:36","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":254418,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of tillage methods and straw management on water consumption during the wheat growing season (A) and water use efficiency (B) in wheat-soybean double cropping system\u003c/p\u003e\n\u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching, Y: year, T: tillage methods, S: straw management. Different lowercase letters within the same year or 4-year average in figures indicate significant difference among treatments (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). *and**indicate significant differences at the \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01 levels, respectively. ns means no significance.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/4fd7557c140a02bc474e24bb.png"},{"id":82597264,"identity":"2ca228f4-ae4c-414f-9a4f-d6cc64082fa4","added_by":"auto","created_at":"2025-05-13 08:59:36","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":218322,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships among grain yield, dry matter accumulation, and water consumption in wheat in wheat-soybean double cropping system\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/d9fcabfd6d3a585516963581.png"},{"id":82597655,"identity":"39e9f836-4420-415a-b525-8b59610c2b0c","added_by":"auto","created_at":"2025-05-13 09:07:36","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":142420,"visible":true,"origin":"","legend":"\u003cp\u003ePath diagram of the direct and indirect effects of straw mulching, dry matter translocation, water management, and dry matter accumulation on wheat yield.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/1f68f7e284c4e5d7283efb50.png"},{"id":84917090,"identity":"1937075b-82a0-4ff6-977c-496d8c3164ae","added_by":"auto","created_at":"2025-06-18 18:50:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2803910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6582786/v1/1b4b2b60-a33e-46c8-a5eb-d6df7868fa7f.pdf"}],"financialInterests":"","formattedTitle":"Rotary Tillage and Straw Mulching Enhance Dry Matter Production, Yield, and Water productivity in a Rain-fed Wheat-Soybean Double Cropping System","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWheat (\u003cem\u003eTriticum aestivum\u003c/em\u003e L.), as a globally essential staple crop and the second-largest food crop in China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], contributes approximately 20% of the caloric intake and protein supply for mankind [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, wheat is mainly planted in dryland, which accounts for 75% and 33% of the total wheat-sown area globally and in China, respectively [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Henan, where wheat constitutes over one-quarter of annual production and dryland wheat also comprises one-third of the region's wheat acreage [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In dryland wheat production regions, natural precipitation serves as the sole water source for wheat growth. Thus, the limited rainfall, frequent drought, and the mismatch between precipitation and the wheat-growing season severely constrain yield formation of wheat. Dry matter accumulation underpins the material basis of crop yield formation, with its accumulation, translocation, and distribution closely linked to yield and water use efficiency (WUE). Therefore, exploring agronomic techniques to improve the characteristics of dry matter in wheat plants for enhancing the yield and water use efficiency of dryland wheat is of significance in promoting wheat yield and ensuring food security in China and worldwide.\u003c/p\u003e \u003cp\u003ePrevious studies have demonstrated that both rotary tillage and plowing have been widely applied to enhance crop yield and WUE [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Kan et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] found that rotary tillage by increasing the spatial and temporal root distribution as well as photosynthetic activity at the flowering stage, achieved higher average grain yield by 12.0% and 6.7% from 2008 to 2019 as compared with conventional tillage and no-till, respectively. Zheng et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] found that the dry matter production capacity and water use efficiency under plowing were higher than those under rotary tillage. However, Wu et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] demonstrated that deep vertical rotary tillage significantly enhanced grain yield and water use efficiency by 24% and 19.0% in winter wheat, compared with conventional shallow rotary tillage, particularly under drought conditions. According to Jiang et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], rotary tillage and harrow tillage strengthen soil moisture preservation, consequently increasing soil water supply efficiency in the late wheat growth period compared to conventional plowing. Shi et al. [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] employed the APSIM model to demonstrate that deep plowing significantly enhanced simulated average annual soil water storage (by 8.4%), biomass (18.4%), grain yield (25.5%), and water use efficiency (22.3%) compared to shallow rotary tillage. Furthermore, plowing combined with straw mulching improved soil water storage and root growth environment, thereby promoting the translocation and distribution of dry matter and significantly increasing crop yield [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, some studies indicated that rotary tillage exhibits superior soil water retention and moisture conservation capabilities, which contribute to improved soil water supply during the later wheat growth period and obtained a higher wheat yield, compared to conventional tillage [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTraditional tillage methods fail to meet modern agricultural demands for water retention, and nutrient cycling in soil, and even for the high yield demands. Straw mulching offers a sustainable alternative by improving soil structure, enhancing organic matter content, and promoting biological nitrogen fixation. Additionally, straw mulching can optimize soil conditions (water, nutrients, aeration, and temperature) through comprehensive effects including mitigating soil erosion, buffering temperature fluctuations, and reducing water evaporation, thereby leading to improved water use efficiency, dry matter accumulation, and ultimately higher grain yield [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For instance, Huang et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] reported that straw mulching improved grain yield, water use efficiency for grain yield (WUE\u003csub\u003er\u003c/sub\u003e), and water use efficiency for aboveground biomass (WUE\u003csub\u003eb\u003c/sub\u003e) by 6.9%, 11.3%, and 16.5%, respectively, compared to no straw mulching. Similarly, in the Loess Plateau, Zhang et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] found that, straw mulching increased wheat yield by 13.3\u0026ndash;23.0%, and WUE by 15.2\u0026ndash;18.0% over the three years due to increasing soil water content by 0.7\u0026ndash;22.5% and reducing the 2\u0026ndash;10 days of soil moisture less than 60% field capacity [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] compared to no straw mulching. Ram et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] also reported 14.7\u0026ndash;34.2% higher water use efficiency in straw mulching treatments (2, 4 and 6 t ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than no mulching treatments across different irrigation levels. However, straw mulching effectiveness showed region-specific and can be influenced by initial soil moisture conditions. Additionally, many studies showed that the interaction between tillage practice and straw management has a certain effect on the characteristics of crop dry matter accumulation and yield formation. Liu et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] demonstrated that compared to conventional tillage without straw return, the combination of rotary tillage with straw return significantly increased dry matter accumulation by 28.1%, grain yield by 17.8%, and WUE by 27.9% at the harvest stage. However, although many studies have revealed that soil tillage and straw management can improve soil moisture, dry matter accumulation, and yield, but most of these studies have been limited by their short duration. The in-depth exploration of the long-term effects of fixed-position tillage and straw mulching on dry matter production, water use efficiency, and soil water storage and yield enhancement remains limited.\u003c/p\u003e \u003cp\u003eThe winter wheat-summer soybean (hereafter refers to wheat-soybean) double cropping system is one of important planting mode in China and worldwide, which can enhance soil properties and the micro-environment for crop growth by increasing organic matter, biological nitrogen fixation, erosion prevention in soils, and reducing downward movement of soil moisture, suppressing weeds and diseases, and promoting nutrient cycling through soybean cultivation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], thereby inevitably affecting wheat production. However, the impacts of tillage methods and straw management on soil moisture, dry matter accumulation, translocation, distribution, as well as yield and water productivity in the dryland wheat-soybean double cropping system remains scarce. Therefore, this study aims to study these gaps based on a long-term field experiment initiated in October 2009. The objectives were to: 1) assess the effects of tillage methods and straw management on soil moisture, as well as yield and water productivity of wheat; 2) comprehensively evaluate the factor-contribution of wheat yield under tillage method and straw management using PLSPM and TOPSIS methods; 3) provide a theoretical and technical insights for improving yield and water productivity of wheat in dryland wheat-soybean double cropping system.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Site Description\u003c/h2\u003e \u003cp\u003eThis study was conducted from June 2014 to June 2018 based on a long-term experiment for wheat-soybean double cropping system initiated in October 2009. The experimental site was at the experimental station of Henan University of Science and Technology in Luoyang, Henan Province, China (112.25\u0026deg;E, 34.36\u0026deg;N). The soil at the experimental site is classified as loam with soil pH of 8.1, organic matter content of 15.9 g kg⁻\u0026sup1;, available nitrogen content of 36.3 mg kg⁻\u0026sup1;, available phosphorus content of 21.0 mg\u0026middot;kg⁻\u0026sup1;, and available potassium content of 120.0 mg kg⁻\u0026sup1; in the 0\u0026ndash;20 cm layer at the initiation of the experiment (October 2009). The monthly precipitation and temperature at the experiment site are shown in Figure. 1. Specifically, the annual precipitation in the 2014\u0026ndash;2015 and 2017\u0026ndash;2018 growing seasons was 604.7 mm and 565.6 mm, respectively, both of them belongs to normal rainfall year, but with relatively high precipitation during the sowing to overwintering stage and the anthesis to maturity stage, respectively. In contrast, the 2015\u0026ndash;2016 and 2016\u0026ndash;2017 growing seasons fall into dry year, with annual precipitation of 494.3 mm and 468.7 mm, respectively. Notably, the jointing to anthesis stage received only 0 mm and 6.8 mm of rainfall during these two growing seasons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental Design and Field Managements\u003c/h3\u003e\n\u003cp\u003eThe experiment was conducted using split-plot design with tillage method as the main plot treatment, and straw management as the subplot treatment. The two tillage methods were plowing (PT) and rotary tillage (RT). Two straw management were no straw mulching (NS) and straw mulching (SM). Thus, four treatments were laid out in the experiment: plowing with no straw mulching (PTNS), plowing with straw mulching (PTSM), rotary tillage with no straw mulching (RTNS), rotary tillage with straw mulching (RTSM). The detailed operations are shown in Table\u0026nbsp;1. There were three replications for each treatment, and the plot area was 60 m\u003csup\u003e2\u003c/sup\u003e (20 m \u0026times; 3 m).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eExperimental treatments and operation methods.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCode\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTreatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSpecific operation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eplowing with no straw mulching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe straw of the previous crop was removed from the plot 1\u0026ndash;3 days before tillage. The plowing (30\u0026ndash;35 cm) was carried out immediately after evenly broadcast fertilizers by hand, using a moldboard plow. Then, the rotary tillage (12\u0026ndash;15 cm) was carried out to smooth land using a rotavator, and the seeds according to the designed amount were sown using a wheat seeder. plowing and straw removing were employed in both wheat and maize seasons.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePTSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eplowing with straw mulching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe straw of the previous crop was evenly mulched to the surface of the original plot before emergence of the in-season crop. The other filed management were the same with the plowing with no straw returning.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRTNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRotary tillage with no straw mulching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe straw of the previous crop was removed from the plot 1\u0026ndash;3 days before tillage. The rotary tillage (12\u0026ndash;15 cm) was carried out twice, immediately after evenly broadcast fertilizers by hand, using a rotavator. Then, the seeds according to the designed amount were sown using a wheat seeder. Rotary tillage and straw removing were employed in both wheat and maize seasons.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRTSM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRotary tillage with straw mulching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe straw of the previous crop was evenly mulched to the surface of the original plot before emergence of the in-season crop. The other filed management were the same with the rotary tillage with no straw returning.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eManagement practices in all plots were consistent across all seasons. Wheat cultivar \u0026lsquo;Luohan 6\u0026rsquo; and soybean cultivar \u0026lsquo;Zhonghuang 13\u0026rsquo; were used. Wheat was sown in middle or late October at a seeding rate of 180.0 kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and harvested in late May or early June. Soybean was sown in early or middle June at a plant density of 120,000 plants ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and harvested in late September or early October. The row spaces of wheat and soybean were 20 cm and 40 cm, respectively. There was no irrigation during the whole experimental period. Compound fertilizer (N:P\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e:K\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;=\u0026thinsp;20:15:10) with the amount of 900 kg ha⁻\u0026sup1; was applied for wheat and 300 kg ha⁻\u0026sup1; for soybean as basel. Weeds, pests, and diseases were controlled with herbicides and pesticides according to local practices.\u003c/p\u003e\n\u003ch3\u003eMeasurements and Methods\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDry Matter Accumulation, Translocation, and Distribution\u003c/h2\u003e \u003cp\u003eAt the jointing, anthesis, and maturity stages of wheat, 50 plants were collected from three distinct rows in each plot. After cutting off the root, samples were separated into three components in terms of stem\u0026thinsp;+\u0026thinsp;leaf, glume\u0026thinsp;+\u0026thinsp;rachis and grain. Samples were immediately oven-dried at 105\u0026deg;C for 30 minutes, followed by drying at 65\u0026deg;C to a constant weight, to determine the dry weight in each organ. The total dry matter accumulation (kg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) were calculated from the summed by each organ. The dry matter accumulation, translocation amount, translocation rate, and contribution rate were calculated using the method of Moradi et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Additionally, the dry matter distribution was determined using the method of Cai et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The calculations were as follows:\u003c/p\u003e \u003cp\u003e \u003cem\u003ePre-anthesis dry matter translocation (kg ha\u003c/em\u003e \u003csup\u003e \u003cem\u003e⁻1\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e)\u0026thinsp;=\u0026thinsp;Dry matter accumulation in vegetative organs at anthesis\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:-\\)\u003c/span\u003e \u003c/span\u003e \u003cem\u003eDry matter in vegetative organs at maturity.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ePre-anthesis dry matter translocation rate (%)\u0026thinsp;=\u0026thinsp;Pre-anthesis dry matter translocation / Total dry matter accumulation at anthesis \u0026times; 100.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eContribution rate of pre-anthesis translocation to grain (%)\u0026thinsp;=\u0026thinsp;Pre-anthesis dry matter translocation amount / Grain dry matter accumulation at maturity \u0026times; 100.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ePost-anthesis dry matter accumulation (kg ha\u003c/em\u003e \u003csup\u003e \u003cem\u003e⁻1\u003c/em\u003e \u003c/sup\u003e \u003cem\u003e)\u0026thinsp;=\u0026thinsp;Total dry matter accumulation at maturity\u003c/em\u003e \u003cspan class=\"InlineEquation\"\u003e \u003cspan class=\"mathinline\"\u003e\\(\\:-\\)\u003c/span\u003e \u003c/span\u003e \u003cem\u003eTotal dry matter accumulation at anthesis.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eContribution rate of post-anthesis dry matter to grain (%)\u0026thinsp;=\u0026thinsp;Post-anthesis dry matter accumulation/Grain dry matter accumulation at maturity \u0026times; 100.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eDry matter distribution\u0026thinsp;=\u0026thinsp;DAo / DAt;\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eWhere DAo was dry matter accumulation in organ; DAt was dry matter accumulation in total above \u0026minus;\u0026thinsp;ground part.\u003c/em\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGrain Yield\u003c/h3\u003e\n\u003cp\u003eAt the maturity stage, three 1 m\u0026sup2; quadrats were randomly harvested from each plot, and air-dried for 3\u0026ndash;5 days, then threshed. Grain samples from the three quadrats were pooled and weighted. 50\u0026thinsp;\u0026plusmn;\u0026thinsp;5g air-dried grains were further oven-dried at a temperature of 65\u0026deg;C for a duration of 24 hours. Grain yield for each plot were standardized to a uniform moisture content of 12.5%, using the air\u0026thinsp;\u0026minus;\u0026thinsp;dried grain weight and its determined water content. Meanwhile, the number of spikes from two random areas (1 m \u0026times; 1 m) in each plot were calculated to determined spike numbers per hectare, and 30 spikes was sampled to measure the grains per spike and thousand\u0026thinsp;\u0026minus;\u0026thinsp;grains weight. Harvest index was calculated by the grain dry weight relative to total dry matter accumulation at maturity.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSoil Water Storage and Water Use Efficiency\u003c/h2\u003e \u003cp\u003eSoil water storage and water use efficiency were calculated using the formulas provided by Li et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003eSoil water storage (W, mm)\u0026thinsp;=\u0026thinsp;h\u003csub\u003ei\u003c/sub\u003e\u0026thinsp;\u0026times;\u0026thinsp;ρ\u003csub\u003ei\u003c/sub\u003e\u0026thinsp;\u0026times;\u0026thinsp;ω\u003csub\u003ei\u003c/sub\u003e\u0026thinsp;\u0026times;\u0026thinsp;10, where h is the soil layer depth (cm), ρ is the soil bulk density (g\u0026middot;cm⁻\u0026sup3;), ω is the soil water content (%), i represents the i-th soil layer, 10 is a conversion factor to convert the result from cm to mm.\u003c/p\u003e \u003cp\u003eWater consumption (ET, mm)\u0026thinsp;=\u0026thinsp;P\u0026thinsp;+\u0026thinsp;W1\u0026thinsp;\u0026minus;\u0026thinsp;W2, where W1 (mm) and W2 (mm) represent 0\u0026ndash;100 cm soil water storage before sowing and after harvesting, respectively; and P (mm) is precipitation during the growth period.\u003c/p\u003e \u003cp\u003eWater use efficiency (WUE, kg ha⁻\u0026sup1; mm⁻\u0026sup1;)\u0026thinsp;=\u0026thinsp;Y / ET, where Y is the grain yield (kg ha⁻\u0026sup1;).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCalculation on the Effectiveness of Straw Mulching\u003c/h3\u003e\n\u003cp\u003eThe improvement of water storage, yield and dry matter of straw mulching were the difference of water storage in the 0\u0026ndash;200 cm soil layer at sowing, grain yield and dry matter accumulation at maturity between the straw mulching and no straw mulching, respectively, under the same tillage method.\u003c/p\u003e \u003cp\u003eThe effectiveness of straw mulching on water-saving was calculated by comparing the water-saving effect of per kg yield, and that on yield increase was calculated by comparing the yield increase of per mm water consumption during the wheat growth season, according to Gao et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], with a little modification.\u003c/p\u003e \u003cp\u003eWater-saving amount (WS, mm)\u0026thinsp;=\u0026thinsp;ET\u003csub\u003eNS\u003c/sub\u003e / Y\u003csub\u003eNS\u003c/sub\u003e \u0026minus; ET\u003csub\u003eSM\u003c/sub\u003e/ Y\u003csub\u003eSM\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eWater-saving rate (WSE, %)\u0026thinsp;=\u0026thinsp;WS \u0026times; Y\u003csub\u003eNS\u003c/sub\u003e / ET\u003csub\u003eNS\u003c/sub\u003e \u0026times; 100\u003c/p\u003e \u003cp\u003eYield-increase amount (ΔY, kg ha⁻\u0026sup1;)\u0026thinsp;=\u0026thinsp;Y\u003csub\u003eSM\u003c/sub\u003e/ET\u003csub\u003eSM\u003c/sub\u003e \u0026minus; Y\u003csub\u003eNS\u003c/sub\u003e/ET\u003csub\u003eNS\u003c/sub\u003e\u003c/p\u003e \u003cp\u003eYield-increase rate (YIE, %) = ΔY \u0026times; ET\u003csub\u003eNS\u003c/sub\u003e / Y\u003csub\u003eNS\u003c/sub\u003e) \u0026times; 100%\u003c/p\u003e \u003cp\u003ewhere ET\u003csub\u003eNS\u003c/sub\u003e (mm) is water consumption under no straw mulching treatment, Y\u003csub\u003eNS\u003c/sub\u003e (kg\u0026middot;ha⁻\u0026sup1;) is the corresponding yield; ET\u003csub\u003eSM\u003c/sub\u003e (mm) and Y\u003csub\u003eSM\u003c/sub\u003e (kg\u0026middot;ha⁻\u0026sup1;) represent the values under straw mulching treatment.\u003c/p\u003e\n\u003ch3\u003eCalculation of Comprehensive Evaluation Value\u003c/h3\u003e\n\u003cp\u003eEvaluation indicators\u0026mdash;such as yield, yield components, dry matter accumulation, and water use efficiency\u0026mdash;vary in units and cannot be directly compared. Therefore, the data for each indicator were first normalized to eliminate dimensional differences. Subsequently, the entropy weight method was applied for objective weighting according to Zou et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Finally, the TOPSIS method was used to calculate a comprehensive evaluation value (Ci, 0\u0026thinsp;\u0026lt;\u0026thinsp;Ci\u0026thinsp;\u0026lt;\u0026thinsp;1) for each treatment by measuring the distance from the ideal solution; a value closer to 1 indicates that the scheme is more conducive to achieving high maize yield.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData processing was performed using Microsoft Excel 2016. Means were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD). Means were analyzed by one-way ANOVA (Duncan) at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05 using a SPSS 26.0 statistical software package (version 26, IBM Corp., Chicago, IL, USA). The graphs were performed using Origin software (version 2021, Origin Lab Corporation, Northampton, USA), with further refinement of figures in Adobe Illustrator 2022 (version 2022, Adobe, Adobe Ireland, USA) to ensure clarity and visual quality.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eYield and Yield Components\u003c/h2\u003e\n \u003cp\u003eThe experimental years and straw management significantly affected the grain yield, yield components, and harvest index of wheat in the dryland winter wheat-soybean double cropping system, the interaction of tillage methods and straw management also significantly affected the aforementioned indicators except for spike number (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Compared to RTNS, PTNS increased 1000-grain weight and grain yield by 1.4% and 6.2%, respectively, over the four years. Compared to RTSM, although the difference was only significant in the 2016\u0026ndash;2017 growing season, PTSM significantly increased the grain yield by 2.6% over the four years. Compared to no straw mulching, straw mulching significantly improved wheat yield and yield components under the same tillage method. Specifically, the grain yield, spike number, grain number per spike, 1000-grain weight, and harvest index respectively increased by 10.5%, 10.4%, 6.4%, 4.4%, and 1.8% under plowing; and by 20.5%, 14.8%, 10.1%, 7.5%, and 3.6% under rotary tillage, over the four years. Considering the interaction effects, the grain yield in all the four years followed the order RTSM\u0026thinsp;\u0026gt;\u0026thinsp;PTSM\u0026thinsp;\u0026gt;\u0026thinsp;PTNS\u0026thinsp;\u0026gt;\u0026thinsp;RTNS. RTSM also gained the highest spike number, grain number per spike, 1000-grain weight, and harvest index. Both the two treatments were significantly higher than PTNS and RTNS, however, there were no significant difference of above-mentioned indicators between RTSM and PTSM except for 1000-grain weight.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of tillage methods and straw management on grain yield and harvest index of wheat in wheat-soybean double cropping system\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpike number\u003c/p\u003e\n \u003cp\u003e(\u0026times;10\u003csup\u003e4\u003c/sup\u003e ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrain\u003c/p\u003e\n \u003cp\u003enumber per spike\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1000-grain\u003c/p\u003e\n \u003cp\u003eweight (g)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGrain yield\u003c/p\u003e\n \u003cp\u003e(kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHarvest\u003c/p\u003e\n \u003cp\u003eIndex (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e563.3\u0026thinsp;\u0026plusmn;\u0026thinsp;21.5 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6668.1\u0026thinsp;\u0026plusmn;\u0026thinsp;178.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e602.7\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7612.9\u0026thinsp;\u0026plusmn;\u0026thinsp;293.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e552.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6340.5\u0026thinsp;\u0026plusmn;\u0026thinsp;161.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e609.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7937.0\u0026thinsp;\u0026plusmn;\u0026thinsp;258.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e508.0\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6144.4\u0026thinsp;\u0026plusmn;\u0026thinsp;209.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e565.7\u0026thinsp;\u0026plusmn;\u0026thinsp;33.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6867.9\u0026thinsp;\u0026plusmn;\u0026thinsp;140.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e497.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5840.0\u0026thinsp;\u0026plusmn;\u0026thinsp;90.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e571.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7043.9\u0026thinsp;\u0026plusmn;\u0026thinsp;254.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e427.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5137.9\u0026thinsp;\u0026plusmn;\u0026thinsp;121.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e484.5\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5699.2\u0026thinsp;\u0026plusmn;\u0026thinsp;146.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e419.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4437.9\u0026thinsp;\u0026plusmn;\u0026thinsp;71.6 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e508.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5902.5\u0026thinsp;\u0026plusmn;\u0026thinsp;169.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e522.7\u0026thinsp;\u0026plusmn;\u0026thinsp;19.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7564.5\u0026thinsp;\u0026plusmn;\u0026thinsp;171.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e578.6\u0026thinsp;\u0026plusmn;\u0026thinsp;32.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8011.4\u0026thinsp;\u0026plusmn;\u0026thinsp;149.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e512.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7396.1\u0026thinsp;\u0026plusmn;\u0026thinsp;202.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e584.6\u0026thinsp;\u0026plusmn;\u0026thinsp;15.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8049.6\u0026thinsp;\u0026plusmn;\u0026thinsp;179.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e4- Year\u003c/p\u003e\n \u003cp\u003eaverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e505.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6378.7\u0026thinsp;\u0026plusmn;\u0026thinsp;69.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e557.9\u0026thinsp;\u0026plusmn;\u0026thinsp;28.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7047.8\u0026thinsp;\u0026plusmn;\u0026thinsp;54.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e495.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6003.6\u0026thinsp;\u0026plusmn;\u0026thinsp;82.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e568.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7233.2\u0026thinsp;\u0026plusmn;\u0026thinsp;165.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003eANOVA results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears (Y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTillage methods (T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStraw management (S)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3). Values followed by different small letters in a column indicate significant difference among treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). *and**indicate significant differences at the \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 levels, respectively. ns means no significance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eDry matter Accumulation,Translocation, and Distribution\u003c/h2\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003eDry Matter Accumulation at Different Stages\u003c/h2\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e indicated that the experimental years, tillage methods (except for jointing stage) and straw management significantly influenced the dry matter accumulation in wheat under the dryland wheat-soybean double cropping system. Over the four years, RTNS increased dry matter accumulation at the anthesis stage by 5.4% but reduced it at the maturity stage by 6.2% compared to PTNS. RTSM resulted in an average increase of 7.2% in dry matter accumulation at the anthesis stage compared to PTSM but not at the maturity stage. Under the same tillage method, straw mulching significantly increased dry matter accumulation across all stages and years. Over the four years, PTSM treatments increased dry matter accumulation by 8.3% at the anthesis stage and 8.6% at maturity compared to PTNS, while RTSM treatments increased dry matter accumulation by 9.7%, 10.2%, and 16.9% at the jointing, anthesis, and maturity stages, respectively, compared to RTNS. However, there was no significant difference between PTSM and RTSM. Overall, RTSM showed a stronger ability in promoting wheat dry matter accumulation.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eCharacteristics of Translocation of Pre-anthesis Dry Matter and Accumulation of Post-anthesis Dry Matter\u003c/h2\u003e\n \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, the experimental years, tillage methods (excluding pre-anthesis translocation), and straw management significantly affected the characteristics of pre-anthesis dry matter translocation and post-anthesis accumulation in wheat. Compared to RTNS, PTNS increased the accumulation and contribution to grain of post-anthesis dry matter by 64.1% and 54.1%, respectively, with significant improvements were all observed in 3 years. RTSM increased the translocation, translocation rate, and contribution to grain of pre-anthesis dry matter by, 25.0%, 16.1%, and 21.5%, respectively, compared to PTSM, with significant improvements were observed in 3 years, respectively. Conversely, PTSM increased the accumulation and contribution to grain of post-anthesis dry matter by 19.9% and 23.0%, respectively, compared to RTSM. RTNS increased the translocation amount, translocation rate, and contribution to grain of pre-anthesis dry matter by 33.0%, 26.0%, and 43.5%, respectively, compared to PTNS, with significant improvements were observed in 3 years, respectively. Over the four years, Compared to no straw mulching, the pre-anthesis dry matter translocation amount and the post-anthesis dry matter accumulation were respectively increased by 12.0% and 9.5% under plowing, and by 5.2% and 49.8% under RT. However, compared to no straw mulching, straw mulching decreased the translocation rate and contribution to grain of pre-anthesis under rotary tillage, with average reductions of 4.7% and 15.1%, respectively.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of tillage methods and straw management on the characteristics of dry matter accumulation translocation and its contribution to grain of wheat in wheat-soybean double cropping system\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePre-anthesis dry matter\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePost-anthesis dry matter\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTranslocation amount (kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTranslocation rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eContribution rate (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAccumulation\u003c/p\u003e\n \u003cp\u003e(kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eContribution rate\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2922.4\u0026thinsp;\u0026plusmn;\u0026thinsp;190.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3745.7\u0026thinsp;\u0026plusmn;\u0026thinsp;140.2 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3467.5\u0026thinsp;\u0026plusmn;\u0026thinsp;114.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4145.4\u0026thinsp;\u0026plusmn;\u0026thinsp;401.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4347.2\u0026thinsp;\u0026plusmn;\u0026thinsp;173.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1993.3\u0026thinsp;\u0026plusmn;\u0026thinsp;254.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4514.3\u0026thinsp;\u0026plusmn;\u0026thinsp;410.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3422.7\u0026thinsp;\u0026plusmn;\u0026thinsp;238.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2587.6\u0026thinsp;\u0026plusmn;\u0026thinsp;505.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.1\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3556.8\u0026thinsp;\u0026plusmn;\u0026thinsp;306.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3267.9\u0026thinsp;\u0026plusmn;\u0026thinsp;158.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3600.0\u0026thinsp;\u0026plusmn;\u0026thinsp;297.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4010.5\u0026thinsp;\u0026plusmn;\u0026thinsp;297.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1829.5\u0026thinsp;\u0026plusmn;\u0026thinsp;290.6 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4326.0\u0026thinsp;\u0026plusmn;\u0026thinsp;297.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2717.9\u0026thinsp;\u0026plusmn;\u0026thinsp;203.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2016\u0026ndash;2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2547.6\u0026thinsp;\u0026plusmn;\u0026thinsp;51.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2590.3\u0026thinsp;\u0026plusmn;\u0026thinsp;80.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2701.4\u0026thinsp;\u0026plusmn;\u0026thinsp;26.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2997.8\u0026thinsp;\u0026plusmn;\u0026thinsp;162.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3392.9\u0026thinsp;\u0026plusmn;\u0026thinsp;142.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1045.0\u0026thinsp;\u0026plusmn;\u0026thinsp;154.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3446.4\u0026thinsp;\u0026plusmn;\u0026thinsp;191.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2456.1\u0026thinsp;\u0026plusmn;\u0026thinsp;347.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u0026thinsp;\u0026plusmn;\u0026thinsp;4.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3266.0\u0026thinsp;\u0026plusmn;\u0026thinsp;155.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3458.0\u0026thinsp;\u0026plusmn;\u0026thinsp;278.5 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3249.1\u0026thinsp;\u0026plusmn;\u0026thinsp;75.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3872.1\u0026thinsp;\u0026plusmn;\u0026thinsp;167.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3306.3\u0026thinsp;\u0026plusmn;\u0026thinsp;116.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3268.1\u0026thinsp;\u0026plusmn;\u0026thinsp;296.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3564.7\u0026thinsp;\u0026plusmn;\u0026thinsp;66.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3590.4\u0026thinsp;\u0026plusmn;\u0026thinsp;182.6 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4-year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2830.9\u0026thinsp;\u0026plusmn;\u0026thinsp;150.5 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3337.7\u0026thinsp;\u0026plusmn;\u0026thinsp;28.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eaverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3171.5\u0026thinsp;\u0026plusmn;\u0026thinsp;74.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3653.8\u0026thinsp;\u0026plusmn;\u0026thinsp;237.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3764.2\u0026thinsp;\u0026plusmn;\u0026thinsp;86.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2034.0\u0026thinsp;\u0026plusmn;\u0026thinsp;171.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3962.9\u0026thinsp;\u0026plusmn;\u0026thinsp;206.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3046.8\u0026thinsp;\u0026plusmn;\u0026thinsp;125.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003eANOVA results\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears (Y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTillage methods (T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStraw management (S)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3). Values followed by different small letters in a column indicate significant difference among treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). *and**indicate significant differences at the \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 levels, respectively. ns means no significance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eDry Matter Distribution at Maturity\u003c/h2\u003e\n \u003cp\u003eThe experimental years and straw management also significantly affected wheat dry matter distribution at maturity, while tillage methods only influenced the dry matter distribution in stem\u0026thinsp;+\u0026thinsp;leaves and the grain percentage (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Compared to RTNS, PTNS significantly increased the dry matter accumulation in stem\u0026thinsp;+\u0026thinsp;leaves, glumes, and grains by 7.9%, 4.0%, and 6.4%, respectively. Compared to PTSM, RTSM increased grain dry matter accumulation by 2.7%, while there were no significant differences for dry matter accumulation and distribution percentages in other organs. The effects of straw management on dry matter distribution varied with tillage methods. Compared to PTNS, PTSM increased grain dry matter distribution proportion by \u0026minus;\u0026thinsp;1.2\u0026ndash;4.5%, with the significant differences were observed in 2 years. Compared to RTNS, RTSM increased grain dry matter distribution proportion by \u0026minus;\u0026thinsp;0.2\u0026ndash;6.3%, with the significant differences were observed in 3 years, while significantly decreased the percentage in stem\u0026thinsp;+\u0026thinsp;leaves in 3 years, with an average reduction of 3.2% over the four years.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of tillage methods and straw management on the distribution of dry matter in wheat at maturity in wheat-soybean double cropping system\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTillage modes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eStem\u0026thinsp;+\u0026thinsp;leaf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGlume\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGrain\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDAA (kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDAA (kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDAA (kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5097.7\u0026thinsp;\u0026plusmn;\u0026thinsp;140.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1873.7\u0026thinsp;\u0026plusmn;\u0026thinsp;64.7 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6668.1\u0026thinsp;\u0026plusmn;\u0026thinsp;178.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5298.7\u0026thinsp;\u0026plusmn;\u0026thinsp;132.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1986.7\u0026thinsp;\u0026plusmn;\u0026thinsp;52.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7612.9\u0026thinsp;\u0026plusmn;\u0026thinsp;293.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4695.3\u0026thinsp;\u0026plusmn;\u0026thinsp;132.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1741.6\u0026thinsp;\u0026plusmn;\u0026thinsp;120.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6340.5\u0026thinsp;\u0026plusmn;\u0026thinsp;161.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5191.7\u0026thinsp;\u0026plusmn;\u0026thinsp;89.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1941.4\u0026thinsp;\u0026plusmn;\u0026thinsp;56.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7937.0\u0026thinsp;\u0026plusmn;\u0026thinsp;258.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4600.7\u0026thinsp;\u0026plusmn;\u0026thinsp;216.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1649.3\u0026thinsp;\u0026plusmn;\u0026thinsp;59.0 bc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6144.4\u0026thinsp;\u0026plusmn;\u0026thinsp;209.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4852.0\u0026thinsp;\u0026plusmn;\u0026thinsp;122.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1846.4\u0026thinsp;\u0026plusmn;\u0026thinsp;98.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6867.9\u0026thinsp;\u0026plusmn;\u0026thinsp;140.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4293.7\u0026thinsp;\u0026plusmn;\u0026thinsp;122.6 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1588.6\u0026thinsp;\u0026plusmn;\u0026thinsp;78.2 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5840.0\u0026thinsp;\u0026plusmn;\u0026thinsp;90.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4688.0\u0026thinsp;\u0026plusmn;\u0026thinsp;160.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1773.6\u0026thinsp;\u0026plusmn;\u0026thinsp;52.4 ab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n 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\u003cp\u003e6825.3\u0026thinsp;\u0026plusmn;\u0026thinsp;55.9 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4503.8\u0026thinsp;\u0026plusmn;\u0026thinsp;78.7 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1669.8\u0026thinsp;\u0026plusmn;\u0026thinsp;47.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5798.2\u0026thinsp;\u0026plusmn;\u0026thinsp;78.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5094.1\u0026thinsp;\u0026plusmn;\u0026thinsp;87.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1894.2\u0026thinsp;\u0026plusmn;\u0026thinsp;82.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7009.6\u0026thinsp;\u0026plusmn;\u0026thinsp;160.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"7\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003cp\u003eresults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears (Y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTillage modes (T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStraw management (S)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eT\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u0026times;S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ePTNS: plowing with no straw mulching, PTSM: plowing with straw mulching, RTNS: rotary tillage with no straw mulching, RTSM: rotary tillage with straw mulching Date presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3). Values followed by different small letters in a column indicate significant difference among treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). *and**indicate significant differences at the \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 levels, respectively. ns means no significance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eWater Use Efficiency\u003c/h2\u003e\n \u003cp\u003eTillage methods and straw management ca\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003en\u003c/span\u003e influence soil water storage in the 0\u0026ndash;200 cm soil profile before sowing and at harvest of wheat in the dryland wheat-soybean double cropping system, with the notable differences across soil layers (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Compared to RTSM, PTSM had an average increase of 6.8% in the 0\u0026ndash;100 cm soil layer, whereas exhibited an average decrease of 12.1% in the 100\u0026ndash;200 cm soil layer, indicating that rotary tillage with straw mulching (RTSM) reduced shallow soil water storage but enhanced deep soil water storage. At harvest, soil water storage varied with soil depth. In the 0\u0026ndash;40 cm soil layer, straw mulching significantly increased soil water storage compared to no straw mulching, in which, PTSM increased by 12.7% compared to PTNS, and RTSM increased by 9.4% compared to RTNS. However, in the 40\u0026ndash;200 cm subsoil layers, the treatments with no straw mulching had higher soil water storage, in which PTNS showed average increases of 7.8% compared to PTSM and RTNS showed average increases of 6.3% compared to RTSM. Despite these trends, there were no significant differences were observed between the two tillage methods in the middle and deeper soil layers under the same straw management. Overall, the effect of straw mulching on soil water storage was greater than that of tillage methods, particularly in the upper and middle soil layers.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e indicated that under the same straw management, tillage methods had no significant impact on water consumption during the growing season (ET). However, PTNS significantly improved water use efficiency (WUE) by 6.6% compared to RTNS over the 4 years, with significant increases were observed in 2 years. Under the same tillage method, straw mulching significantly increased ET compared to no straw mulching, with the increase of 7.4% and 10.4% under plowing and rotary tillage, respectively, over the four years. Likewise, straw mulching significantly enhanced WUE by 3.1% and 9.6%, respectively under plowing and rotary tillage.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eEffect of Straw Mulching on Water-saving and Yield Improvement\u003c/h2\u003e\n \u003cp\u003eFurther analysis revealed that tillage methods significantly influenced the water-saving and yield improvement induced by straw mulching (Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). Under different years and tillage methods, straw mulching consistently resulted in positive values for pre-sowing water storage, yield and dry matter, water-saving amount and rate per kg yield, and yield-improvement amount and rate per mm water consumption. Specifically, the pre-sowing water storage, yield and dry matter improvement under rotary tillage were significantly higher than those under plowing in 2, 4, and 2 years, respectively, with 4-year average increase of 66.2%, 84.5%, and 60.7%, respectively. Similarly, the water-saving amount and rate per kg yield, as well as the yield-improvement amount and rate per mm water consumption under rotray were significantly higher than plowing in 2 years, with 4-year average increase of 231.3%, 196.8%, 216.7%, and 162.3%, respectively. These results indicated that straw mulching effectively enhances pre-sowing water storage, yield, and dry matter, as well as water-saving per kg yield and yield-improvement per mm water consumption. Moreover, the effectiveness of straw mulching on these indicators under rotary tillage were more pronounced than that under plowing.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eEffects of straw mulching on water-saving and wheat productivity improvement in wheat-soybean double cropping system\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003eYears\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTillage methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eWater storage improvement\u003c/p\u003e\n \u003cp\u003e(mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eYield improvement\u003c/p\u003e\n \u003cp\u003e(kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDry matter improvement\u003c/p\u003e\n \u003cp\u003e(kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eWater-saving per kg yield\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eYield-improvement per mm water consumption\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmount (mm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmount (kg ha\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRate (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e944.7\u0026thinsp;\u0026plusmn;\u0026thinsp;115.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2417.4\u0026thinsp;\u0026plusmn;\u0026thinsp;679.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1596.6\u0026thinsp;\u0026plusmn;\u0026thinsp;112.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3348.2\u0026thinsp;\u0026plusmn;\u0026thinsp;837.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45.7\u0026thinsp;\u0026plusmn;\u0026thinsp;10.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e723.5\u0026thinsp;\u0026plusmn;\u0026thinsp;73.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2426.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1186.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1203.9\u0026thinsp;\u0026plusmn;\u0026thinsp;182.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3052.3\u0026thinsp;\u0026plusmn;\u0026thinsp;742.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e2016\u0026ndash;2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.7\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e561.3\u0026thinsp;\u0026plusmn;\u0026thinsp;67.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1818.6\u0026thinsp;\u0026plusmn;\u0026thinsp;217.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1464.6\u0026thinsp;\u0026plusmn;\u0026thinsp;116.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4446.7\u0026thinsp;\u0026plusmn;\u0026thinsp;551.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e397.2\u0026thinsp;\u0026plusmn;\u0026thinsp;24.6 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1644.9\u0026thinsp;\u0026plusmn;\u0026thinsp;416.9 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e580.8\u0026thinsp;\u0026plusmn;\u0026thinsp;24.1 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2504.8\u0026thinsp;\u0026plusmn;\u0026thinsp;205.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e4-year\u003c/p\u003e\n \u003cp\u003eaverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e656.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2076.9\u0026thinsp;\u0026plusmn;\u0026thinsp;488.2 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7 b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1211.5\u0026thinsp;\u0026plusmn;\u0026thinsp;101.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3338\u0026thinsp;\u0026plusmn;\u0026thinsp;572.8 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.3 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5 a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"3\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003cp\u003eresults\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears (Y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTillage method(T)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eY\u0026times;T\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003ePT: plowing, RT: rotary tillage. Date presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (n\u0026thinsp;=\u0026thinsp;3). Values followed by different small letters in a column indicate significant difference among treatments (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). *and** indicate significant differences at the \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 levels, respectively. ns means no significance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003eCorrelation and Path Model\u003c/h2\u003e\n \u003cp\u003eRegression analysis revealed a significant linear relationship between wheat grain yield and ET (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e), underscoring the critical role of water consumption in improving wheat productivity. Under the four years, water consumption exhibited a significantly positive correlation with dry matter accumulation, except for the 2017\u0026ndash;2018 growing season. However, the overall regression analysis showed a positive correlation but without statistical significance for yield. This result indicated substantial variability in water-yield relationships across different growing seasons. Conversely, the aggregated analysis demonstrated a significant positive correlation between water consumption and dry matter accumulation across years.\u003c/p\u003e\n \u003cp\u003ePLS-PM analysis further indicated that straw mulching significantly influenced wheat yield through multiple pathways (Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB). Compared to no straw mulching treatment, straw mulching had a pronounced positive effect on yield (path coefficient, PC\u0026thinsp;=\u0026thinsp;0.308, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Higher water use efficiency (WUE) and water consumption significantly contributed to improvements in both yield and dry matter accumulation, with path coefficients of PC\u0026thinsp;=\u0026thinsp;0.323 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and PC\u0026thinsp;=\u0026thinsp;0.766 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), respectively. Moreover, effective water use had a greater enhancement impact on dry matter accumulation than yield enhancement. Additionally, increases in dry matter accumulation were found to directly contribute to yield improvement (PC\u0026thinsp;=\u0026thinsp;0.612, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\n \u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e shows that the comprehensive evaluation value (di) for RTSM was consistently the highest, while RTNS recorded the lowest values across four cropping seasons. In 2014\u0026ndash;2015, the di values were 0.81 for RTSM, 0.69 for PTSM, 0.38 for PTNS, and 0.24 for RTNS. In 2015\u0026ndash;2016, these values were 0.68 for RTSM, 0.57 for PTSM, 0.38 for PTNS, and 0.26 for RTNS. In 2016\u0026ndash;2017, RTSM reached 0.80, PTSM 0.68, PTNS 0.47, and RTNS 0.29. Finally, in 2017\u0026ndash;2018, the values were 0.71 for RTSM, 0.60 for PTSM, 0.41 for PTNS, and 0.29 for RTNS. Overall, RTSM di values ranged from 0.68 to 0.81, PTSM from 0.57 to 0.69, PTNS from 0.38 to 0.47, and RTNS from 0.24 to 0.29, clearly indicating that RTSM consistently outperformed the other treatments based solely on the measured evaluation values.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe degree of fit and ranking under different treatments by TOPSIS method.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"17\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTreatments\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e2014\u0026ndash;2015\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e2015\u0026ndash;2016\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e2016\u0026ndash;2017\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e2017\u0026ndash;2018\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi+\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi-\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi+\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi-\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi+\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi-\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi+\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi-\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003edi\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRanking\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.41c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.69b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.57b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.68b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6b\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTNS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.24d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.29d\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRTSM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.81a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.68a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.71a\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003edi+: The distance of each evaluation scheme to the positive ideal solution; di-: The distance of each evaluation scheme to the negative ideal solution; Ci: Closeness coefficient. Different lowercase letters following the data in the same column indicate significant differences among treatments at the p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Tillage Methods and Straw Management on Wheat Yield\u003c/h2\u003e \u003cp\u003eOptimizing wheat yield in dryland regions is crucial not only to meet the growing food demand but also to promote sustainable agricultural practices [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Research has shown that plowing is more effective than rotary tilling in breaking the plowing pan, promoting root penetration and development, ensuring water and nutrient supply during the later stages of growth, and increasing the number of ears, number of grains per ear, and thousand-grain weight, thereby enhancing yield [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. This study demonstrated that the effect of tillage methods on wheat yield varies with straw management. Under no straw mulching, plowing increased yield by 2.6% and thousand-grain weight by 1.5% compared to rotary tilling. Conversely, under straw mulching, rotary tillage has an average yield increase of 6.2% over the four years compared to plowing, with average increases in thousand-grain weight and harvest index both at 1.6%. The observed yield enhancement can be attributed to rotary tillage-induced acceleration of straw decomposition through stimulation of extracellular lignocellulose hydrolase activities and enrichment of copiotroph taxa, which facilitate synchronized nutrient mineralization (particularly ammonium-N and labile carbon pools) and promoting root proliferation and photosynthetic assimilation efficiency [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe comparison between straw mulching and no straw mulching treatments underscores the critical role of straw in enhancing wheat yield. Under both plowing and rotary tillage regimes, straw mulching consistently enhanced yield, with average increases of 10.5% under plowing and 20.5% under rotary tillage (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These yield improvement may be ascribed to straw mulching-induced improvement in organic matter decomposition, which enhanced soil moisture retention and nutrient availability, and directly benefited grain filling and 1000-grain weight [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The substantial yield gain under RTSM was mainly due to the synergistic effects of improved water management and nutrient cycling [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This demonstrated that straw mulching is essential for maintaining soil moisture, particularly in rain-fed cropping system where water stress is a prominent limiting factor for yield formation. Under no straw mulching, rapid soil moisture loss and greater temperature fluctuations further stress the crop, while reduced organic matter content limits nutrient cycling and microbial activity, thereby constraining yield formation. Over the four years, RTSM increased the spike number, grain number per spike, 1000-grain weight, and harvest index increasing by 14.8%, 10.1%, 7.5%, and 3.6%, respectively, compared to RTNS. These gains may be attributed to the synergistic effects of enhancing soil penetration resistance and root penetration, facilitating nutrient and water uptake by rotary tillage [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], and improving moisture retention, reducing evaporation, stabilizing soil temperature fluctuations by straw mulching [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The increase in 1000-grain weight and spike number under RTSM was especially notable, as these yield components are highly sensitive to water availability and nutrient supply during grain filling stage [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. In contrast, PTSM also increased wheat yield, but the yield increase was slightly lower than that of RTSM relative to their respective non-mulched treatments. The smaller yield improvements observed under PTNS may be due to the limited soil loosening and root penetration compared to RTNS, which restricts water and nutrient uptake efficiency. This study highlights the significant impact of tillage methods and straw management on wheat yield and its components, with a particularly strong interaction between the two factors. The rotary tillage combined with straw mulching gain the highest yield and should be applied in the wheat-soybean double cropping system.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eEffects of Tillage Methods and Straw Management on Dry Matter Accumulation, Translocation, and Distribution\u003c/h2\u003e \u003cp\u003eEfficient dry matter accumulation, translocation, and distribution are pivotal for wheat yield in rain-fed cropping systems, driven by tillage-straw interactions [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Previous study indicated the significant influence of tillage methods and straw management on dry matter dynamics, and demonstrated that the combination of rotary tillage with straw mulching optimizes soil conditions, enhances nutrient availability, and improves moisture retention, thereby promoting dry matter accumulation and its efficient translocation to grains [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Our results showed that rotary tillage with straw mulching significantly increased dry matter accumulation at anthesis and maturity by 6.1% and 3.7%, respectively, compared to plowing with straw mulching. This was in accordance to Zhai et al. [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], who reported that dry matter accumulation and, yield, and harvest index of deep rotary tillage were significantly higher than those of no tillage with strip subsoiling, primarily due to a significant increase in post-anthesis dry matter accumulation. Furthermore, our trial showed rotary tillage with straw mulching enhanced pre-anthesis dry matter translocation, translocation rate, and contribution to grain yield by 105%, 88.4%, and 98%, respectively. The elevated pre-anthesis dry matter translocation, translocation rate, and the contribution of translocation to grain under straw-mulched rotary tillage are mechanistically associated with two synergistic drivers: (1) prolonged soil moisture sustaining nitrate reductase activity to enhance nitrogen assimilation efficiency [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and (2) ethylene-auxin signaling coordination mediated by improved soil aeration for optimized source-sink allocation dynamics [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. These improvements suggest that rotary tillage with straw mulching facilitates a more efficient source-sink relationship, ensuring that assimilates produced before anthesis are effectively re-mobilized to grains. In contrast, under no straw mulching, rotary tillage did not enhance dry matter translocation and even reduced its translocation rate compared to plowing, underscoring the importance of straw retention in sustaining soil nutrients and moisture availability [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Yue et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] similarly reported that straw mulching improves dry matter accumulation and translocation at all growth stages. In our trails, rotary tillage with straw mulching increased post-anthesis dry matter accumulation by 23.9% compared to no straw mulching, further reinforcing its role in optimizing yield formation.\u003c/p\u003e \u003cp\u003eIn addition to total dry matter accumulation, this study also examined dry matter distribution in distinct organs and found there were significant interactions between tillage and straw management. Rotary tillage with straw mulching leading to greater dry matter allocation to grains. These results align with previous research indicating that tillage and straw mulching improve soil structure and microbial activity, which facilitate carbon and nitrogen cycling [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. For example, Zheng et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] found that plowing improved dry matter translocation efficiency by increasing soil organic matter, while Li et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] reported that rotary tillage with straw mulching enhanced root growth and nutrient uptake, leading to higher dry matter accumulation and increased grain yield. Additionally, plowing with straw mulching encouraged deeper root penetration and improved soil nutrient availability, supporting grain filling [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These findings emphasize the potential of sustainable tillage and straw management practices in mitigating water limitations, improving dry matter efficiency, and ensuring stable wheat yields in rain-fed systems.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eEffects of Tillage Methods and Straw Management on Water Use Efficiency of Wheat\u003c/h2\u003e \u003cp\u003eTillage methods modify soil physical and chemical properties, thereby increasing soil water storage capacity and enhancing crop yield and WUE [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Our study showed that the interaction between tillage methods and straw mulching plays a critical role in optimizing water storage in a rain-fed wheat\u0026ndash;soybean double cropping system. Specifically, RTNS increased water storage in the upper soil layers (0\u0026ndash;40 cm) at sowing and harvest of wheat, likely due to its ability to loosen the soil surface and facilitate water infiltration [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In contrast, PTNS helped to enhance water storage in deeper soil layers (40\u0026ndash;200 cm), particularly at harvest. These findings corroborate [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], who demonstrated that straw mulching effectively improves water retention across diverse soil types, suggesting that its benefits are broadly applicable regardless of soil texture. Our trial demonstrated that straw mulching significantly improved soil water retention. This enhancement could be attributed to organic matter incorporation and reduced evaporation, consistent with previous studies reporting that surface residue coverage enhances soil aggregation while suppressing vapor flux through physical barrier effects [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. For instance, under straw mulching, RTSM increased water storage by 5.0% compared to RTNS [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe integration of effective straw management with appropriate tillage practices also substantially improves WUE and crop productivity [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In the present study, although straw mulching increased water consumption during the growing season, PTSM and RTSM treatments increased water use by 7.4% and 10.4%, respectively, compared to no straw mulching treatments. For example, RTSM achieved a 9.6% higher WUE than RTNS. Regression analysis revealed a significant positive correlation between water consumption and dry mater accumulation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), emphasizing that adequate moisture is critical for biomass production [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The improved WUE under RTSM was mainly attributed to enhanced dry matter accumulation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and dry matter translocation to grains (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), ultimately leading to a higher grain yield (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These results, consistent with previous studies [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], demonstrated that integrating rotary tillage and straw mulching optimizes soil moisture conditions, offering a promising strategy for achieving sustainable, high-yield wheat production in a rain-fed wheat\u0026ndash;soybean double cropping system. Despite slightly higher water consumption under straw-mulched treatments, these increases were offset by greater WUE, and enhanced translocation of dry matter to grains. The additional water stored in mulched systems was effectively utilized to support higher spike numbers, grain numbers per spike, and 1000-grain weight. These findings align with previous research [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] and emphasize that straw mulching is a crucial strategy for improving soil moisture availability, maximizing WUE, and achieving sustainable yield increases in water-limited environments. Thus, integrating straw mulching with appropriate tillage practices presents a viable long-term solution for enhancing resource use efficiency and stabilizing wheat production in rain-fed agricultural systems.\u003c/p\u003e \u003cp\u003eOur results also indicated that the effectiveness of straw mulching on the improvement of pre-sowing water storage, yield, dry matter accumulation, and the water-saving amounts and rates of per kg yield, and yield improvement per mm water consummation varied with tillage methods. the water-saving amount and rate per kg yield, as well as the yield-improvement amount and rate per mm water consumption under rotary were 223.7%, 195.5%, 187.5%, and 163.3% higher than plowing, which may be due to the pre-sowing water storage, yield and dry matter improvement under rotary tillage were significantly higher than those under plowing in 2, 4, and 2 years, respectively, with 4-year average increase of 66.0%, 84.5%, and 60.7%.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003ePathway Analysis Using PLSPM and Comprehensive Evaluation\u003c/h2\u003e \u003cp\u003eRegression analysis further underscored the critical role of water consumption in wheat yield formation. A significant positive correlation was observed between water consumption and dry matter accumulation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating that adequate moisture is essential for biomass production. The aggregated data did not reveal a statistically significant relationship between water consumption and yield\u0026mdash;likely due to interannual variability\u0026mdash;the strong association with dry matter accumulation confirms the importance of water availability for crop growth [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In the present study, the partial least squares path modeling (PLS-PM) analysis revealed that straw mulching had a pronounced positive effect on yield (path coefficient, PC\u0026thinsp;=\u0026thinsp;0.308, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Higher water use efficiency (PC\u0026thinsp;=\u0026thinsp;0.323, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and water consumption (PC\u0026thinsp;=\u0026thinsp;0.766, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were significantly associated with improvements in both yield and DM accumulation, while increased DM accumulation directly contributed to yield enhancement (PC\u0026thinsp;=\u0026thinsp;0.612, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Our study also found that the interaction between tillage and straw management optimizes soil water retention. RT improved water storage in the upper soil layers before sowing and at harvest, whereas PTNS enhanced water retention in deeper soil layers.\u003c/p\u003e \u003cp\u003eRegression analysis also confirmed a significant positive correlation between water consumption and dry matter accumulation (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), underscoring the essential role of soil moisture in biomass production. Although there was no significant relationship between total water consumption and yield across all years\u0026mdash;likely due to interannual variability\u0026mdash;the strong association with dry matter accumulation highlights the importance of stable soil moisture availability for crop growth [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. PLS-PM analysis further demonstrated that straw mulching directly contributed to higher yields through multiple pathways. Straw mulching had a strong positive effect on yield (PC\u0026thinsp;=\u0026thinsp;0.308, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), with increased WUE (PC\u0026thinsp;=\u0026thinsp;0.323, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and water consumption (PC\u0026thinsp;=\u0026thinsp;0.766, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) significantly improving both dry matter accumulation and grain yield. Furthermore, increased dry matter accumulation directly enhanced yield formation (PC\u0026thinsp;=\u0026thinsp;0.612, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), reinforcing the critical role of optimized soil moisture conditions in supporting grain development.\u003c/p\u003e \u003cp\u003eThe TOPSIS model revealed that RTSM treatment consistently achieved the highest comprehensive evaluation values over the four-year period, while RTNS recorded the lowest. This outcome is likely due to the superior integration of straw residues in RTSM, which promotes a more uniform distribution of organic matter, enhancing soil structure, moisture retention, and nutrient recycling [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In contrast, RTNS may lead to uneven residue incorporation and greater disruption of soil aggregates, resulting in lower organic matter retention and reduced nutrient availability [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The intermediate performance of other study further supports the notion that optimal tillage and residue management practices can significantly influence soil fertility and crop productivity [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These mechanistic insights not only validate the TOPSIS results but also emphasize the critical role of conservation tillage in sustaining long-term agricultural productivity.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe results of the present study indicated that the effects of tillage methods on dry matter production, yield, and water use efficiency of wheat in rain-fed wheat-soybean double cropping system varied with straw management. Specifically, PTNS was superior to RTNS, while RTSM significantly outperformed PTSM. Straw mulching was beneficial for increasing soil water storage and promoting water absorption from deep soil by wheat plants, thereby enhancing dry matter accumulation and its translocation to grains, optimizing yield components, ultimately increasing wheat yield and water use efficiency by 10.5\u0026ndash;20.5% and 7.4\u0026ndash;10.4%, respectively. RTSM helped to promote the pre-sowing water storage, dry matter accumulation and translocation, and offering superior water-saving and yield-improvement effects compared to PTSM, making it is suitable for widespread for high yield wheat production in dryland wheat-soybean double-cropping system.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eS. D. Conceptualization; Data curation; Investigation; Writing—Original draft; Writing—Review \u0026amp; editing. M. H. Data curation; Writing—Original draft. J. Z., Q. Z., C. H., A. L. Investigation; Data curation. H W. Software; Visualization; Writing—Review \u0026amp; editing. G. F. Conceptualization, Writing—Review \u0026amp; editing. J. W., Y. L. Conceptualization; Funding acquisition; Writing—Review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis study was financially supported by the National Key Research and Development Program (under Grant No.:\u0026nbsp;2022YFD2300800; 2018YFD0300700) and the Science and Technology Research Project of Henan, China (under Grant No.:232102111009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003eThis study includes all supporting data, which can be obtained from the corresponding authors upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThe author would like to thank the reviewers for their valuable comments and suggestions for this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNational Bureau of Statistics (NBS). 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Cleaner Prod\u003c/em\u003e. \u003cstrong\u003e2022\u003c/strong\u003e, 381: 135181. https://doi.org/10.1016/j.jclepro.2022.135181.\u003c/li\u003e\n\u003cli\u003eSingh, P.K.; Naresh, R.K.; Singh, N.K.; Bhatt, R.; Sahoo, P.; Gupta, S.; Kaur, A.; Tiwari, H. Effect of Conservation Tillage on Changes in Soil Aggregate-associated Organic Carbon and Biological Pools to Nitrogen and Straw Alters in RWCS in North-Western India: A Review. Int. \u003cem\u003eJ. Environ. Clim. Change.\u003c/em\u003e\u003cstrong\u003e2023\u003c/strong\u003e, 13: 452-470. https://doi.org/10.9734/IJECC/2023/v13i71898.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"straw mulching, wheat-soybean double cropping, water productivity, grain yield","lastPublishedDoi":"10.21203/rs.3.rs-6582786/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6582786/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e Water deficiency and low water use efficiency severely constrain wheat yield in dryland regions. This study aimed to identify suitable tillage and straw management practices to improve water use efficiency, grain yield and water use efficiency of wheat in the dryland winter wheat-summer bean double cropping system.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e A long-term field experiment (onset in October 2009) of four treatments—plowing with no straw mulching (PTNS), plowing with straw mulching (PTSM), rotary tillage with no straw mulching (RTNS), and rotary tillage with straw mulching (RTSM), was conducted at a typical dryland in China. The wheat yield and yield component, dry matter accumulation and translocation characteristics, and water use efficiency were investigated from 2014 to 2018.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e straw mulching significantly increased spike number, grains per spike, 1000-grain weight, and harvest index, and ultimately resulting in grain yield increases of 10.5% under PT and 20.5% under RT. Tillage and straw management significantly affected dry matter accumulation and translocation characteristics except for that straw management had no significant effect on pre-anthesis dry matter translocation. Straw mulching respectively increased water consumption by 7.4% and 10.4%, and water use efficiency by 3.1% and 9.6%, compared to treatments under PT and RT without straw mulching. Straw mulching also enhanced pre-sowing water storage capacity, water-saving efficiency, and water use efficiency per unit of dry matter and grain yield.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e TOPSIS confirmed RTSM's superiority through straw-induced improvements water and nutrient productivity. Rotary tillage with mulching optimizes dry matter/water yield, recommended for dryland wheat systems.\u003c/p\u003e","manuscriptTitle":"Rotary Tillage and Straw Mulching Enhance Dry Matter Production, Yield, and Water productivity in a Rain-fed Wheat-Soybean Double Cropping System","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 08:59:31","doi":"10.21203/rs.3.rs-6582786/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff2abbad-909c-4823-a7cb-4596f4efa420","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-18T18:42:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 08:59:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6582786","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6582786","identity":"rs-6582786","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}