Micro-sprinkling irrigation improves grain yield, dry matter accumulation and nitrogen use efficiency of purple wheat in the North China Plain

Micro-sprinkling irrigation improves grain yield, dry matter accumulation and nitrogen use efficiency of purple wheat in the North China Plain | 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 Micro-sprinkling irrigation improves grain yield, dry matter accumulation and nitrogen use efficiency of purple wheat in the North China Plain xinyu zhao, rugang wu, juan liu, dong wang, xiang lin, yuangang zhu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7038231/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 Background and Aims Micro-sprinkling irrigation (MSI) has been instrumental in enhancing crop yield and water utilization efficiency. Nevertheless, there is a paucity of research on the impact of MSI on purple wheat. Methods A field experiment was carried out to examine the influence of conventional irrigation practice (CI) and MSI on grain yield, dry matter accumulation, and nitrogen (N) use efficiency of purple wheat. Results The findings indicate that grain yield, protein yield, spikes per square meter and grains per spike increased by an average of 12.0%, 9.7%, 8.3%, and 8.7%, respectively, under MSI relative to CI. Additionally, the dry matter accumulation of MSI at various growth stages surpassed that of CI. MSI also led to an increase in leaf area index, specific leaf nitrogen and leaf area duration, while simultaneously decreasing specific leaf area. The net assimilation rate,N accumulation and productivity demonstrated similar patterns to leaf area duration during the stages from sowing to jointing and from anthesis to maturity. The improvement of N use efficiency resulting from MSI was primarily attributed to the increase in N uptake efficiency. Conversely, the lack of variation in N utilization efficiency was primarily due to the unchanged nitrogen harvest index and grain nitrogen concentration. MSI has increased the contribution of dry matter and nitrogen after anthesis to grains, while the reverse was true before anthesis. Conclusions As a result, MSI has been shown to enhance the growth and yield of purple wheat through improved dry matter accumulation and N use efficiency. Micro-sprinkling irrigation Grain yield Nitrogen use efficiency Dry matter accumulation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 INTRODUCTION Given the escalating consumption rates among a substantial population and the constrained and diminishing availability of arable land resulting from urbanization and socioeconomic progress, the matter of food security has consistently held significant policy importance in China (Lu and Fan 2013). Enhancing the productivity of existing arable land is imperative to guarantee a stable food supply. The North China Plain, which serves as the central hub for grain production in contemporary China, is identified as the region with the most severe water scarcity within the country (Guo et al. 2019). Insufficient water supply continues to pose a major hindrance and persistent peril to achieving enhanced crop productivity in this area. In order to safeguard the attainment of national food security, the utilization of surface irrigation is extensively employed to supplement the water requirements for crop cultivation (Ma et al. 2012). Nevertheless, the excessive exploitation of groundwater as the predominant source for extensive irrigation has led to significant depletion of groundwater resources (He et al. 2017), thereby exacerbating the prevailing water crisis in this particular region (Du et al. 2014). Furthermore, the substantial expansion of irrigated agriculture, although it has contributed to the reduction of surface temperatures and alleviation of soil drought, has concurrently facilitated the integration of temperature and humidity measurements, consequently intensifying the occurrence of heat waves (Kang and Eltahir 2018). With the evident contradiction between the growing scarcity of water resources and the imperative of national food security, it is crucial to enhance water productivity (WP, the ratio of grain yield to evapotranspiration) by exploring novel irrigation strategies that promote water conservation. This approach aims to address the pressing issues of groundwater depletion while ensuring food self-sufficiency. Consequently, the pursuit of more effective utilization of water resources has emerged as a prominent research focus in the region. The effective water-saving strategies to seek to match crop water requirements with supplementary irrigation have been widely developed. Nowadays, advanced irrigation techniques have been verified to be played a pivotal role in decreasing the irrigation water requirements, and achieving higher WP and efficient agricultural production, particularly under conditions of water scarcity (AI-Ghobari and Dewidar 2018). For example, drip irrigation and sprinkler irrigation are useful in decreasing the required irrigation water, and offers the advantages of regulating root distribution and promoting the growth and boosting the WP and the economic benefit (Dar et al. 2017; Li et al. 2021; Zhang et al. 2019). Micro-sprinkling irrigation (MSI) has been in favour of improving the uniformity of the soil wetting body and the water amount per unit area of tillage layer and achieving good results in crop production (Baram et al. 2018; Li et al. 2019; Man et al. 2014, 2017). Optimizing supplemental irrigation regimes by adopting agronomic management practices and adjusting the supplemental irrigation schedule plays a significant role in maintaining high yields and improving WP (Devkota et al. 2023; Yan et al. 2022). The timing and volume of irrigation have a significant impact on the growth and yield of winter wheat, thus influencing WP (Ech-chatir et al. 2025; Liu et al. 2024). Deficit irrigation as a limited irrigation strategy would be effective in improving efficiency and maximize profits through a reduction in the amount of water applied (Geerts and Raes 2009; Saitta et al. 2021; Tejero et al. 2011; Zhang et al. 2018), which includes three main strategies: sustained deficit irrigation, regulated deficit irrigation and partial root drying (Du et al. 2010; Fereres and Sorian 2007; Ginestar and Castel 1996; Kang et al. 2017; Marsal et al. 2008; Shellie 2014). Some research reported that limited irrigation can improve the growth and absorptive area of roots in both deep and surface soil layers and thus uptake more soil-stored water from the subsurface layers (Wang et al. 2014), and ultimately achieve higher grain yield (GY) and WP (Wang et al. 2016; Xu et al. 2016). Combining deficit irrigation with subsurface drip irrigation can achieve water savings in winter wheat production in water-scarce areas by not only improving deep soil water the extraction, but also maintaining yields by stimulating plant growth (Yang et al. 2020). Moreover, optimizing the MSI schedule has significantly improved the GY, WP and nitrogen use efficiency (NUE) of winter wheat (Li et al. 2019; Zhai et al. 2021), and also effectively reduced greenhouse gas emissions (Zhang et al. 2023). Besides, drip and MSI under plastic film can have stronger water saving capacity and improve WP, yield and crop quality, and directly regulate soil bacterial community and root system and reduce the soil water evaporation in the vertical direction (He et al. 2013; Zhang et al. 2020). The development of an optimized irrigation and fertilizer application regime is conducive to achieving sustainable agricultural development of and further improving crop yield, WP, and NUE. Optimized split nitrogen fertilizer has improved flag leaf photosynthetic performance and grain storage capacity of wheat, and achieved a high yield and high water and nitrogen (N) efficiency under water‑saving irrigation (Zhang et al. 2020). GY and photosynthetic capacity of drip-irrigated winter wheat were improved by appropriate split nitrogen application under different water regimes in the North China Plain (Hamani et al. 2023). GY, WP and NUE of winter wheat were improved by optimizing MSI and N application (Li et al. 2021). In addition, studies have reported that integrated water and fertilizer application has many advantages, such as reducing amounts of irrigation water and fertilizer, promoting crop growth and fertilizer absorption, enhanced WP and NUE and grain yield (Yan et al. 2019; Yan et al. 2021; Zou et al. 2020). And late sown wheat with supplemental irrigation at the jointing stage could improve production and WUE (Wang et al. 2023). Purple wheat, as one of the colored wheats, has been received widely concerned for its potential health-enhancing properties (Gamel et al. 2023; Szőke-Trenyik et al. 2023). Purple wheat contains relatively rich anthocyanin and phenolic acid compounds, which have been proved to play multiple and beneficial physiological roles in the human health (Liu et al. 2018; Shipp and Abdel-Aal 2020). Although many studies have investigated the effect of MSI on grain yield and WP of field crops, information on whether MSI can increases grain yield and NUE of purple wheat is limited. Based on this, the aim of this study is to explore whether MSI can improve the yield and NUE of purple wheat by growth, water allocation and nutrient contents. Field experiment was carried out to (1) determine the effects of MSI on the GY and yield formation; (2) identify how MSI affects the accumulation and remobilization of dry matter (DM) and N, and N use. The results of this study provided theoretical basis and practical experience for water-saving, yield increases, and high-efficiency of purple wheat production in NCP. MATERIALS AND METHODS Experimental site and growth conditions Field experiments were conducted during the 2020–2021 and 2021–2022 growing seasons at the experimental field of the Qianhua Village (37° 32′N, 116° 57′E), Bianlin Town, Lingcheng District, Dezhou City, Shandong Province. The primary substrate in this area was sandy loam (Typic Cambisols) with a pH of 8.13. The nutrients in the top 0–0.2 m soil profile comprised organic carbon 8.84 g kg –1 , total nitrogen 0.90 g kg –1 , available phosphorus 20.68 mg kg –1 , and exchangeable potassium 248.00 mg kg –1 . Treatments and experimental design A purple wheat cultivar ( Triticum aestivum ) Nongda 3753 with high selenium and strong gluten as the experimental material, bred by the College of Agronomy and Biotechnology of China Agricultural University, was sown at a density of 330 plants m −2 on October 12, 2020 and October 11, 2021. For both conventional irrigation (CI) and micro-sprinkling irrigation (MSI), irrigation was implemented at four key growth stages: after sowing, before wintering, at jointing, and at anthesis in both growing seasons. Each irrigation event delivered approximately 60 mm of water, verified by water meters installed at the discharge end of the hoses. This approach was chosen to ensure consistency in the irrigation schedule and to align with local agricultural practices in the North China Plain. CI was carried out via a mobile plastic hose connected to a tap. The micro-sprinkling hose with 40 cm diameter was 25 m long and had a flow rate of 6.0 m 3 h -1 , and the sprinkling angle of the hose was 80°. Each experimental plot consisted of 20 rows of wheats paced 20 cm apart. Two micro-sprinkler hoses were laid between the fifth and sixth rows from the plot borders, so that the sprinkling range on each side of the hose was 1 m. The water meter installed at the discharge end of the hose was used to control the irrigation volume. Before sowing, compound fertilizers comprising N, P, and K at rates of 22% N, 9.6% P (equivalent to 22% P₂O₅), and 5.0% K (equivalent to 6% K₂O), respectively were applied as basal fertilizer with an amount of 600 kg ha –1 . An extra 120 kg ha –1 N as urea was topdressed at jointing. Each individual subplot was 25 m long and 4m wide, and a completely randomized block design has been arranged with three replicates. Diseases, pests, and weeds were well-controlled by applied prophylactic fungicides, insecticides and herbicides in all treatments following local field management protocols. All subplots were harvested on June 8, 2021 and June 6, 2022. Sampling and measurement All shoots per unit area at jointing, booting and anthesis and spikes per unit area at maturity were counted in the 1.0 m × 6 lines quadrats with three repeats. At the same time, two rows of whole plants within 0.5 m were taken, including root systems 15 cm below the surface. After the roots were washed and dried with absorbent paper, the total number of roots including primary roots and nodal roots was counted, and then converted into the number of roots per unit area and per stem. Aboveground plants were separated into leaves, stems (including sheath), spikes (including spike rachis and glumes) and grains. Later on, green leaf area was measured to determine the leaf area index (LAI), which was then used to calculate the leaf area duration (LAD). All samples were dried to a constant weight at 80°C for 72 h to determine the quantity of aboveground DM. Specific leaf area (SLA) was calculated by dividing leaf area (cm 2 ) by leaf dry mass. Net assimilation rate (NAR) was calculated as the rate of aboveground DM production expressed per unit of leaf area. The DM wasted in sterile tillers from jointing to booting and booting to anthesis was calculated as the product of DM per plant at jointing and at booting and the number of unproductive tillers at corresponding stage. Aboveground N uptake was determined by analyzing N content of dried plant components using the semi-micro-Kjeldahl method. Specific leaf N content (SLN) was calculated as leaf N content per unit leaf area (Vos et al. 2005). The calculation of N wasted in non-viable tillers from jointing to booting and booting to anthesis was similar to that of DM. The GY per unit of N supply (soil N+ fertilizer N) is defined as N use efficiency (NUE) (López-Bellido and López-Bellido 2001), which is the product of two primary components: (i) the N uptake efficiency (NUpE) as total plant N uptake divided by N supply, and (ii) the N utilization efficiency (NUtE) as the ratio of grain yield to total plant N uptake (Moll et al. 1982). Furthermore, the NUtE can be obtained by dividing the nitrogen harvest index (NHI) as the fraction of aboveground N uptake present as grain N by the grain nitrogen concentration (GNC). Grain protein concentration (GPC) was calculated as GNC× 5.7 (Nehe et al, 2020). In addition, plant N productivity was calculated as the ratio of increase in both plant DM and N content per unit time (Ingestad 1979). In order to estimate the accumulation of DM and N contributed to GY before and after anthesis, we calculated the various parameters involved in the movement of DM and N from the plant components into the grains according to Papakosta and Gagianas (1991). DM and N remobilization after anthesis was given as the amount of DM and N stored in the crop non-grain organs of the plant (leaves, stems, and spikes) at anthesis that was not present in the above straw at maturity. The accumulated quantity of DM and N after anthesis was calculated as the difference between grain DM and N yield at harvest and the quantity of DM and N remobilized from the vegetative organs, respectively. The remobilization and accumulation of DM and N after anthesis contributed to final grain DM and N yields were then calculated as the percentage of each in the final grain DM and N yields respectively. Soil samples were collected at 20 cm intervals to a depth of 100 cm by artificial spiral drills before wintering, at jointing, anthesis and maturity in 2020-2021. The soil water content was measured by oven-drying method at 80 °C to a constant weight (Li et al. 2018). At maturity, 30 stems randomly selected from each subplot were threshed separately by hand to measure and record the grain numbers and weights, and then the average grains per spike and grain weight were calculated. GY was measured by harvesting all spikes in a quadrat of 3.0 m long and 1.0 m wide in each plot, and defined as the grain weight with a standard 12% moisture content. Grain protein yield (PY) was calculated as GY×GPC at maturity. Statistical analysis Statistical analysis employed standard analysis of variance (ANOVA) using DPS (Data Processing System). The least significant difference (LSD) method was used to determine whether there were differences between treatments at the probability level of 5%. Microsoft Excel 2010 and SigmaPlot 10.0 software were used for data analyses and post-processing. Use the “linkET” package in R·4.3.1 to perform a mantel test analysis. RESULTS Grain yield and protein yield Irrigation methods had significant effects on spikes per unit area, grains per spike, GY and PY of purple wheat, but had no effect on grain weight and GNC (Table 1). Year significantly affected grain weight, GPC, GY and PY but had no effect on spikes per square meter and grains per spike (Table 1). The effect of their interaction was only significant for GPC (Table 1). Compared with CI, GY, spikes per square meter and grains per spike of MSI significantly increased by 12.0%, 8.3%, and 8.7%, respectively. Patterns of change in PY were consistent with those in GY (Table 1). Table 1 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on grain Treatment Spikes per square meter (no. m -2 ) Grains per spike (no.) Grain weight (mg) GY (kg hm -2 ) GPC (%) PY (kg hm -2 ) 2020-2021 MSI 714.4±3.1a 31.14±0.38a 37.16±0.13a 6417.7±116.3a 11.65±0.09a 738.68±11.07a CI 658.8±12.5b 28.76±0.15b 36.77±0.30a 5644.2±154.6b 11.91±0.04a 672.79±17.72b 2021-2022 MSI 715.8±11.3a 31.82±0.66a 40.40±0.18a 6897.53±124.9a 12.27±0.10a 846.33±15.40a CI 662.1±9.4b 29.15±0.37b 39.85±0.44a 6253.78±88.9b 12.35±0.11a 772.34±10.85b ANOVA Irrigation method *** *** ns *** ns *** Year ns ns *** ** *** *** Irrigation method×Year ns ns ns ns ** ns yield (GY) and its constituent factors, grain protein concentration (GPC) and protein yield (PY) of purple wheat Different letters indicate significant difference between CI and MSI at P < 0.05 level. *, ** and *** indicate significant effects at P < 0.05, P < 0.01 and P < 0.001, respectively; ns indicates no significant effect. Values are means ± standard error (n = 3). Dry matter accumulation and remobilization Irrigation methods significantly influenced DM accumulation and biomass per individual plant (Table 2). MSI led to significantly increase the accumulated DM by 47.5% at jointing, 21.5% at booting, 9.9% at anthesis and 14.9% at maturity compared with CI (Fig. 1). No uniform trends in the DM accumulations were observed at different growth stages, MSI significantly increased DM accumulations from sowing to jointing by 47.5% and from anthesis to maturity by 27.3% compared to CI. But lack of significant difference in DM accumulation was found from jointing to booting and from booting to anthesis. Similar trends were observed in biomass per individual plant except for anthesis in 2022 (Fig. 1). Table 2 Analysis of variance of dry matter (DM) accumulation, biomass per individual plant (BIP), leaf area index (LAI), specific leaf area (SLA), specific leaf N content (SLN), leaf area duration (LAD), net assimilation rate (NAR), DM wasted in non-surviving tillers, nitrogen (N) accumulation, N wasted in non-surviving tillers, N productivity, total roots per unit area, average roots number per stem as affected by irrigation method (I), year (Y) and their interaction (I × Y) for purple wheat Factor DM accumulation BIP LAI SLA SLN LAD NAR DM wasted in non-surviving tillers N accumulation N wasted in non-surviving tillers N productivity Total roots per unit area Average roots number per stem I *** *** *** *** *** *** ** *** *** *** ** *** *** Y ns ns *** *** *** *** *** * ns ns ns * * I×Y ns ns ns ns *** ns ns * ns ** ** ns ns *, ** and *** indicate significant effects at P < 0.05, P < 0.01 and P < 0.001, respectively; ns indicates no significant effect. Irrigation methods had significant effects on dry matter accumulation at anthesis and maturity, pre-anthesis translocation and post-anthesis accumulation and their contribution to grain yield of each organ (Table 2). Year had only significantly influenced dry matter accumulation of stem at anthesis and its contribution of remobilized dry matter before anthesis to grain yield (Table 2). The interaction of irrigation methods× year had significant effect on spikes (excluding grains) at maturity and the contribution rate of total dry matter remobilization before anthesis and DM accumulation post anthesis to GY (Table 2). Higher DM accumulation was dramatically observed in stems than that in leaves and spikes (excluding grains) at anthesis and maturity under two irrigation methods, DM accumulation in spikes was significantly lowest (Table 3). MSI exerted a significantly higher DM accumulation in stems and spikes than that in CI, between which, increased by 10.0% and 15.2% at anthesis, 14.5% and 25.3% at maturity, respectively. No uniform trends in the DM accumulation in leaves at anthesis and at maturity were observed. No significant difference was observed in DM accumulation of leaves between MSI and CI at anthesis, but the former was significantly higher by 14.2% than the latter at maturity. The DM remobilization (DMR) of stems and leaves before anthesis was significantly higher than that in spikes under both MSI and CI, but there were no significant differences in the DMR between stems and leaves except for MSI in 2022. The contribution of DMR of various plant components to GY (DMRC) was consistent with DMR. MSI significantly decreased the DMR and DMRC of each organ and the total contribution rate of DMR to GY (DMRCT) of relative to CI, whereas DM accumulation post anthesis (DMPA) and the DMPA contributed to GY (DMPAC) showed the opposite trends. Compared with CI, the DMR of leaves, stems and spikes and the DMRCT of MSI have significantly decreased by 28.0%, 42.9%, 39.5% and 36.1%. However, MSI have significantly increased DMPA by 27.3% and DMPAC by 12.4% than those in CI. On the whole, MSI significantly increased DM accumulation after anthesis and its contribution to grain while decreased the DM remobilization and contribution before anthesis compared to CI. Table 3 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on dry matter accumulation at anthesis (DMA), dry matter accumulation at maturity (excluding grains) (DMM), dry matter remobilization before anthesis (DMR), contribution of dry matter remobilization of organs before anthesis to grain yield (DMRC), the total contribution rate of dry matter remobilization before anthesis to grain yield (DMRCT), dry matter accumulation post anthesis (DMPA), the contribution of dry matter accumulation after anthesis to grain yield (DMPAC) of purple wheat Treatment Organ DMA (kg hm -2 ) DMM (kg hm -2 ) DMR (kg hm -2 ) DMRC (%) DMRCT (%) DMPA (kg hm -2 ) DMPAC (%) 2020-2021 MSI Leaf 2339.59±60.93c 1939.89±72.98c 399.70±30.45b 6.09±0.51b 14.59±0.92b 5613.54±147.30a 85.41±1.59a Stem 7756.37±61.89a 7318.65±143.16a 437.72±48.89b 6.67±0.60b Spike 1837.74±89.46d 1717.82±17.96d 119.92±41.28d 1.84±0.58d CI Leaf 2246.35±73.36c 1652.59±65.00d 593.76±7.77a 10.23±0.24a 26.42±0.55a 4274.21±82.24b 73.58±0.95b Stem 6992.67±69.40b 6326.23±62.61b 666.44±4.39a 11.48±0.13a Spike 1553.01±29.69e 1279.19±26.20e 273.82±17.94c 4.71±0.29c 2021-2022 MSI Leaf 2371.81±77.79c 1843.28±64.72c 528.53±75.77a 7.97±1.23b 17.18±1.15b 5510.75±208.80a 82.82±1.15a Stem 7554.47±107.75a 7198.93±17.66a 355.53±61.32b 5.34±0.92c Spike 1752.61±55.49d 1496.10±84.17e 256.51±28.95b 3.87±0.49e CI Leaf 2210.27±119.56c 1660.95±65.33d 549.31±41.91a 9.29±0.80a 23.53±1.33a 4473.50±68.19b 76.47±0.77b Stem 6923.22±115.83b 6358.24±62.93b 564.98±48.52a 9.52±0.69a Spike 1563.63±36.46e 1285.66±26.33f 277.97±32.91b 4.71±0.61d ANOVA Irrigation method / / / / *** *** *** Leaf * *** * ** Stem *** *** ** *** Spike *** *** * ** Year / / / / ns ns ns Leaf ns ns ns ns Stem * ns ns * Spike ns ** ns ns Irrigation method×Year / / / / * ns * Leaf ns ns ns ns Stem ns ns ns ns Spike ns ** ns ns Different letters indicate significant difference between CI and MSI at P < 0.05 level. *, ** and *** indicate significant effects at P < 0.05, P < 0.01 and P < 0.001, respectively; ns indicates no significant effect. Values are means ± standard error (n = 3). The characteristics of photosynthetic production Irrigation methods and year significantly influenced LAI, SLA, SLN, LAD, NAR and DM losses in sterile tillers, but the effect of their interaction was only significant for SLN and DM losses in sterile tillers (Table 2). LAI of MSI at different growth periods was significantly higher than CI, between which, increased by 18.4% at jointing, 11.2% at booting, 8.6% at anthesis (Fig. 2). While the reverse was true in SLA, the reduction was 8.5% at jointing, 8.5% at booting and 7.1% at anthesis (Fig. 2). Trends similar to those in LAI were observed in SLN at the same growth period (Fig. 2). As shown in Fig. 3, the LAD of MSI at different growth stages was significantly higher than that of CI treatment. The LAD of MSI increased by 18.4% from sowing to jointing, 13.1% from jointing to booting, 10.2% from booting to anthesis, and 10.2% from anthesis to maturity compared to that of CI. NAR at different stages of growth showed a trend consistent with DM accumulation (Fig. 3). NAR of MSI from sowing to jointing and from anthesis to maturity significantly increased by 39.6% and 22.4% compared to CI, respectively. Lack of significant difference in NAR was observed from jointing to booting and from booting to anthesis. Different irrigation methods had significant influence on DM losses in sterile tillers during the stem elongation (Fig. 3). Compared with CI, MSI resulted in a 118.5% increase in the quantity of DM wasted in unproductive tillers from jointing to booting and a 20.4% increase from booting to anthesis, respectively. Nitrogen accumulation and remobilization Irrigation methods had significantly affected N accumulation, N wasted in non-surviving tillers and N productivity, and the interaction of irrigation methods× year had influenced the latter two (Table 2). Year has no significant effect on the above indexes (Table 2). As shown in Fig. 4, irrigation methods had a significant effect on aboveground N uptake from sowing to jointing and from anthesis to maturity, while had no influence on aboveground N uptake from jointing to booting and from booting to anthesis. Compared with CI, MSI resulted in a 41.5% increase in aboveground N uptake from sowing to jointing and a 33.6% increase from anthesis to maturity. The patterns of changes in N lose in non-viable tillers were similar to DM wasted in unproductive tillers. The amount of N wasted in sterile tillers during the jointing to booting and booting to anthesis stages under MSI was found to be 71.3% and 11.4% higher, respectively, compared to that observed under control irrigation. No differences in N productivity from sowing to jointing and from jointing to booting were observed between irrigation methods. Nevertheless, significant increments in N productivity from booting to anthesis and from anthesis to maturity were obtained for under MSI exhibiting 14.0% and 12.1% higher values than those under CI. In addition to N accumulation of leaf and spike (excluding grains) at maturity and the contribution of remobilizated N of leaf before anthesis to grain N, irrigation methods had significant effects on N accumulation at anthesis and maturity, pre-anthesis translocation and post-anthesis accumulation and their contribution to grain N of each organ (Table 2). Year had significantly influenced N accumulation at anthesis and maturity, pre-anthesis translocation and their contribution to grain N of each organ except N accumulation of leaf at both anthesis and maturity and spike (excluding grains) at maturity and N translocation of leaf before anthesis (Table 2). The interaction of irrigation methods× year had significant effect on N accumulation of stem and spike (excluding grains) at maturity and pre-anthesis translocation of spike (excluding grains) and their contribution to grain N (Table 2). N accumulation in stems was significantly greater than that in leaves and spikes at anthesis and maturity under both CI and MSI. The N accumulation in stems exhibited a significantly higher level in MSI compared to CI, with an increase of 6.5% at anthesis, and 23.4% at maturity, respectively. The N accumulation in spike (excluding grains) was found to be similar between MSI and CI at anthesis during the two growth stages, and the former exhibited a significantly higher level by 13.7% compared to the latter. However, the patterns of changes in N accumulation in spike (excluding grains) at maturity were opposite during the two growth stages (Table 4). The N remobilization (NR) and the pre-anthesis contribution of NR to grain N (NRC) was significantly higher in leaves than that in stems and spikes under both MSI and CI, with spike exhibiting the lowest NR and NRC. The NRC of stems as well as the total contribution rate of NR to grain N (NRCT) were significantly lower in MSI relative to those in CI. Conversely, N accumulation after anthesis (NAA) and its contribution of NAA to grain yield (NAAC) exhibited opposite trends between MSI and CI. The NRC of stems as well as the NRCT of MSI showed a significant decrease by 17.7% and 8.7% when compared to CI. However, MSI demonstrated a significant increase in NAA by 33.6% and NAAC by 20.2% compared to CI. The overall results suggest that MSI significantly enhanced post-anthesis N accumulation and its contribution to grain N, while decreasing the contribution of pre-anthesis N remobilization decreased compared to CI. Table 4 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on N accumulation at anthesis (NA), N accumulation at maturity (besides grain) (NM), N remobilization pre-anthesis of different organs (NR), the contribution rate of N remobilization pre-anthesis of different organs to grain N (NRC), total contribution of N remobilization preanthesis to grain N (NRCT), N accumulation after anthesis (NAA), the contribution of N accumulation after anthesis to grain N (NAAC) of purple wheat Treatment Organ NA (kg hm -2 ) NM (kg hm -2 ) NR (kg hm -2 ) NRC (%) NRCT (%) NAA (kg hm -2 ) NAAC (%) 2020-2021 MSI Leaf 55.72±1.45c 11.28±0.42c 44.44±1.19a 33.49±1.70a 62.78±2.16b 49.40±4.04a 37.22±2.16a Stem 76.23±0.61a 48.63±0.95a 27.60±0.39b 20.80±0.22c Spike 22.83±1.11d 11.55±0.12c 11.28±0.99c 8.50±0.76d CI Leaf 53.84±1.76c 10.27±0.40c 43.57±1.36a 35.91±1.17a 69.28±2.02a 37.28±3.10b 30.72±2.02b Stem 72.01±0.71b 42.03±0.42b 29.98±0.30b 24.71±0.57b Spike 19.64±0.36e 9.14±0.19e 10.51±0.35c 8.66±0.37d 2021-2022 MSI Leaf 54.22±1.78c 10.41±0.37c 43.81±1.43a 30.41±0.24b 65.28±1.28b 50.05±1.62a 34.72±1.28a Stem 78.39±1.12a 39.02±0.10a 39.37±1.11b 27.33±0.87c Spike 19.73±0.62e 8.88±0.50d 10.85±0.36c 7.54±0.41d CI Leaf 50.35±2.72d 10.38±0.36c 39.97±2.44b 31.37±2.39b 70.90±2.45a 37.14±2.18b 29.10±2.45b Stem 73.10±1.22b 29.75±0.34b 43.35±0.98a 34.00±0.58a Spike 17.75±0.41f 10.68±1.08c 7.07±0.72d 5.54±0.45e ANOVA Irrigation method / / / / *** *** *** Leaf * ns * ns Stem *** *** *** *** Spike *** ns *** * Year / / / / ns ns ns Leaf ns ns ns ** Stem * *** *** *** Spike *** ns *** *** Irrigation method×Year / / / / ns ns ns Leaf ns ns ns ns Stem ns ** ns ns Spike ns *** ** ** Different letters indicate significant difference between CI and MSI at P < 0.05 level. *, ** and *** indicate significant effects at P < 0.05, P < 0.01 and P < 0.001, respectively; ns indicates no significant effect. Values are means ± standard error (n = 3). Nitrogen use efficiency and its associated parameters Irrigation methods had significant effect on NUE and its associated parameters except GNC (Table 5). Year had significantly influenced NUE and GNC, and their interaction had only significant effect on GNC (Table 5). The NUE of MSI was 10.4% higher than that of CI due to a higher GY. NUpE showed a similar pattern to NUE. NUpE significantly raised under MSI relative to CI, because of a higher aboveground N uptake. No differences in NUtE were observed between CI and MSI attribute to similar NHI and GNC. Table 5 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on nitrogen use efficiency (NUE), nitrogen uptake efficiency (NUpE), nitrogen utilization efficiency (NUtE), nitrogen harvest index (NHI), and grain nitrogen concentration (GNC) of purple wheat Treatment NUE (kg kg −1 ) NUpE (%) NUtE (kg kg −1 ) NHI (%) GNC (%) 2020-2021 MSI 15.67±0.49a 49.86±0.51a 31.44±0.99a 65.00±0.90a 2.02±0.01a CI 14.05±0.75b 44.63±0.79b 31.48±0.45a 66.38±0.57a 2.09±0.02a 2021-2022 MSI 17.35±0.54a 50.92±1.17a 34.10±1.70a 71.18±0.33a 2.17±0.02a CI 15.87±0.20b 44.87±0.54b 35.39±0.85a 71.50±0.76a 2.15±0.02a ANOVA Irrigation method *** *** ** *** ns Year *** ns ns ns *** Irrigation method×Year ns ns ns ns * Different letters indicate significant difference between CI and MSI at P < 0.05 level. *, ** and *** indicate significant effects at P < 0.05, P < 0.01 and P < 0.001, respectively; ns indicates no significant effect. Values are means ± standard error (n = 3). Roots number Irrigation methods and year had significant impact on the total roots per unit area and average roots number per stem, and the interaction had no effect (Fig. 5). MSI exhibited a significant increase in the total roots per unit area and average roots number per stem of 66.6% and 67.4%, respectively, at jointing, while at booting and anthesis stages, these increases were observed to be 22.0% and 14.0%, as well as 25.6% and 16.9%, compared to those of CI (Fig. 5). Soil water content As shown in Fig. 6, the soil moisture content under the two irrigation methods varies dynamically at each growth stage. Although MSI maintained a relatively high soil moisture level in different soil layers during the three key stages of pre-wintering (BW), jointing (J), and flowering (A), no significant difference was achieved compared with CI. Correlation analyses Correlation analysis showed that the total root number per unit area was significantly and positively correlated with the aboveground N uptake (Fig. 7). A significant and positive correlation was also observed between the average roots number per stem and biomass per individual plant (Fig. 7). We found that GY was strongly and positively related to spikes per square meter and grains per spike, but no significant correlation with grain weight at harvest (Fig. 8). Moreover, GY showed statistically positive and significant relationship to NAR, total dry matter accumulation at maturity, dry matter accumulation post anthesis and the contribution of dry matter accumulation after anthesis to grain yield, but negative to SLA (Fig. 8). Additionally, similar correlations were also found between GY and above-ground N accumulation at maturity, N accumulation after anthesis; NAC, the contribution of N accumulation after anthesis to grain N (Fig. 8). PY presented significant positive correlations with NAR, NR before anthesis, spikes per square meter, grains per spike, grain weight and GY, but was negatively correlated with SLA (Fig. 8). DISCUSSION Water is an essential factor that influences the conversion of soil nutrient and absorption of crop nutrient, and exerts important impact on crop growth and yield formation (Guo et al. 2019).Excessive irrigation has a limited impact on yield growth, but can exacerbate groundwater consumption and nitrogen loss (He et al. 2017; Xin and Tao 2019). Hence, agricultural irrigation should be managed according to local resource reserves, climatic characteristics and actual crop needs (Dalin et al. 2011), and adoption of advanced irrigation techniques is a crucial means for enhancing irrigation WP and for realizing efficient agricultural production. In this study, we found that MSI has significantly elevated GY, spikes per square meter and grains per spike of purple wheat, but no significant differences in grain weight. The increase in harvestable spikes of MSI was attributed to the increment in tiller survival rate. It has previously been established that the number of grains per spike at maturity has a significant positive correlation with the number of fertile florets per spike at anthesis (González et al. 2011). Further research is essential to understand the response mechanisms of floret development to the increase in the number of grains per spike by MSI. Our findings tend to indicate that the increment in grain yield of purple wheat by MSI was mainly due to the increase in grain number per unit area. Increasing DM is the prerequisite for obtaining high yield (Yan et al. 2022), and DM accumulation is largely dependent on environmental conditions, especially soil water content (Yan et al. 2019; Zhiipao et al. 2023). Our results indicated that MSI increased the accumulation of dry matter in different growth stages of purple wheat. Dry matter production is affected by the ability of canopy to intercept photosynthetically active radiation and use it to produce biomass referred to as radiation-use efficiency (RUE) (Muurinen and Peltonen-Sainio 2006). Radiation captured by the crop can be represented as a function of LAI. SLA and SLN have been confirmed as two key characters that determine the photosynthetic capacity (Lemaire et al. 2008; Sieling et al. 2016), which were related to RUE. Therefore, enhanced investment into leaf which achieves a higher leaf area or lower SLA is crucial to increase the assimilation capacity per plant. In the current study, we demonstrated that MSI has significantly improved LAI, which proved beneficial in terms of increasing LAD. Moreover, MSI has decreased SLA and enhanced the SLN, indicating that MSI may allow the investment of more N into the leaf which could therefore contribute to improve the photosynthetic rate. This further explains that MSI had coordinated the growth and development of purple wheat to optimize light capture and energy conversion. However, the no significant difference in the NAR from jointing to booting and from booting to anthesis was found between MSI and CI. The reason may be mainly due to the fact that MSI produces more dry matter waste of ineffective tillers than CI. The DM required for developing grain in cereals mainly originates from the remobilization of reserves stored in the vegetative organs and the current assimilation by photosynthates after anthesis (Gorooei et al. 2023; Zhang et al. 2019), the characteristics of which are significantly affected by soil water status (Cui et al. 2015). Previous studies suggested that water deficit had decreased the accumulation of DM after anthesis and was conducive to promote the translocation of stored DM before anthesis to grain (Ercoli et al. 2008; Liu et al. 2016). Limited irrigation before anthesis enhances photosynthesis and DM remobilization after anthesis (Xue et al. 2006). Supplemental irrigation or mild deficit irrigation boosted DM accumulation at anthesis and post anthesis and DM remobilization, but decreased DM remobilization efficiency (Moradi et al. 2022; Yan et al. 2022). MSI produced greater DM in various organs at anthesis and maturity than CI in the present study, but the amount and contribution of pre-anthesis DM translocated to grain of MSI was lower than CI. However, the opposite trend was observed in the DM accumulation and the share of DM accumulation after anthesis to GY. Since the DMA has a significant positive correlation with the yield, maintaining a relatively high LAI and photosynthetic capacity after anthesis is conducive to improve the biomass and increase GY (Ba et al. 2020). It was previously shown that MSI had observed the higher chlorophyll content of leaves during the mid–late grain filling period and increased the contribution of DM accumulation after anthesis to GY of winter wheat with consequent boosted GY compared to CI (Li et al. 2021). This research assumed that lower SLA and higher the SLN under MSI helps to maintain the ability of photosynthetic carbon assimilation of leaves after anthesis, which in turn, contributes to an increment in DM and GY of purple wheat. It further indicated that purple wheat under MSI would depend more on current photosynthesis for grain filling than on translocation of their pre-anthesis stored reserves. N accumulation and remobilization are vital processes that determine grain quality and yield (Gaju et al. 2011), and the uptake, remobilization, and assimilation of N have been influenced by irrigation schemes (Li et al. 2009). Studies have shown that water deficient can decrease N absorption and NUE (Plaut et al. 2004), and increasing irrigation rates cause an increment in aboveground N uptake (AGN) and NUE (Zhang et al. 2006). However, other studies have revealed that mild water deficits promote N availability and uptake (Széles et al. 2012; Yan et al. 2020). In the present study, MSI significantly increased N accumulation from sowing to jointing and from anthesis to maturity compared with CI. However, there was no difference in N accumulation from jointing to booting and from booting to anthesis, which may be due to the higher N wasted in non-surviving tillers caused by MSI than CI. N utilization is a comprehensive process involving the absorption and utilization of N by plants (Moradi et al. 2022). MSI obtained high NUE mainly through increased NUpE resulting from increases N uptake, however remained lack of difference in GY per unit of N consumed (NUtE) owing to no change in NHI and GNC compared to CI. Root morphology and physiology has a close association with above–ground growth and development (Ju et al. 2015). Previous research demonstrated a well-developed root system could boost the capacity of uptake nutrients which is more conducive to for the increment in yield and NUE (Palta et al. 2007; Wang et al. 2014), and a shallow root system is imperative to absorb nutrients that are mainly concentrated in the upper soil (Becker et al. 2016). In this study, more root number obtained by MSI could be associated with enhanced the extraction capacity of N, which couple with higher N productivity, resulting in a greater N accumulation and biomass production. It has also been reported that N remobilization efficiency in wheat had been enhanced by water deficit (Li et al. 2021). Although the N accumulated in stems and spikes at the anthesis and maturity of MSI were significantly more than CI, there was no difference in the remobilization of N before flowering between treatments. Similar to DM accumulation, MSI increased post-anthesis N accumulation and thus increased its contribution to grain N, and greatly increased total N accumulation at maturity. This further indicates that although the remobilization of the stored N in vegetative organs at anthesis provides a major drive to developing grain (Gaju et al. 2014),post-flower N accumulation is also a key factor in determining grain N. Further studies are needed to investigate the mechanism that capacity of root absorption and N accumulation and remobilization, which could also allow for a better understanding of MSI and its effects on purple wheat yield. Optimizing irrigation management can regulate the soil moisture status, which is closely has a great influence on temporal and spatial distribution of root in soil (Feng et al., 2017; Li et al., 2018; Ma et al. 2013; Wang et al., 2014). A reasonable root distribution significantly increases N use efficiency and reduces the loss of nitrogen fertilizer and the negative effects on the environment (Rasmussen et al., 2015). Although our soil water content measurements (0–100 cm soil depth) did not show statistically significant differences between MSI and CI treatments at key growth stages, the inherent characteristics of MSI likely modified soil moisture distribution in ways not fully captured by bulk measurements. Studies have demonstrated that MSI delivers water more uniformly and frequently at lower volumes compared to CI, creating a shallower and more homogeneous wetting front that favors root proliferation in the upper soil layers (Li et al., 2021; Man et al., 2014). This is corroborated by our data showing significantly higher root numbers per unit area and per stem under MS, particularly in surface layers. Such a root distribution enhances access to water and nutrients concentrated near the soil surface, thereby supporting greater early-season dry matter accumulation and nitrogen uptake. Moreover, we speculate that MSI optimizes soil moisture availability in the root zone, promoting vigorous early growth and delaying water stress during critical reproductive stages. This is reflected in the extended leaf area duration (LAD) and higher net assimilation rates (NAR) during post-anthesis periods, which facilitated greater reliance on current photosynthates for grain filling rather than remobilization of pre-anthesis reserves. In addition, the stable soil water status may also affect the remobilization and distribution of nitrogen. MSI increased the post-anthesis nitrogen accumulation and its contribution to grain nitrogen, while decreasing the pre-anthesis nitrogen remobilization. This change in nitrogen distribution pattern may be related to the stable soil water status maintaining the physiological functions of plants after anthesis, promoting the absorption and utilization of nitrogen. This study provides valuable insights into the mechanisms underlying the improved performance of purple wheat under MSI. And the findings also underscore the potential for the application of MSI technology in the production of purple wheat. Future research should focus on exploring the physiological and biochemical mechanisms through which MSI improves yield and nutrient uptake of purple wheat, as well as characterizing root system architecture and spatial distribution under MSI, linking root traits to water-nitrogen uptake efficiency in different soil layers. Additionally, exploring different irrigation schedules and volumes as well as the water-nitrogen interaction effects tailored to the specific needs of purple wheat at each growth stage could provide further insights into optimizing use efficiency of water and N. Declarations Funding This work was supported by Shandong Province Natural Science Foundation (ZR2019MC032), Dezhou University School-level Scientific Research Project (2019xjrc316), Dezhou University College Students' Innovation and Entrepreneurship Training Program (X202410448059), and the Open Project Program of State Key Laboratory for Crop Stress Resistance and High-Efficiency Production NWAFU (SKLCSRHPKF14), Yangling, Shaanxi, 712100, China Competing Interests The authors have no competing interests to declare that are relevant to the content of this article. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Xinyu Zhao, Rugang Wu, Juan Liu and Xiang Lin. The first draft of the manuscript was written and reviewed by Yuangang Zhu, Zhongmin Dai and Dong Wang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. ACKNOWLEDGEMENTS This work was supported by Shandong Province Natural Science Foundation (ZR2019MC032), Dezhou University School-level Scientific Research Project (2019xjrc316), Dezhou University College Students' Innovation and Entrepreneurship Training Program (X202410448059), and the Open Project Program of State Key Laboratory for Crop Stress Resistance and High-Efficiency Production NWAFU (SKLCSRHPKF14), Yangling, Shaanxi, 712100, China. 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Agric Water Manage 230:105986. https://doi.org/10.1016/j.agwat.2019.105986 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7038231","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482078934,"identity":"b4416583-0e26-4611-97b8-86860061fcac","order_by":0,"name":"xinyu zhao","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"xinyu","middleName":"","lastName":"zhao","suffix":""},{"id":482078935,"identity":"d6252d0b-2cdf-4b15-9273-6d573bf616c6","order_by":1,"name":"rugang wu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"rugang","middleName":"","lastName":"wu","suffix":""},{"id":482078936,"identity":"6291d7c3-caa4-4242-b1f5-87f898a42bed","order_by":2,"name":"juan liu","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"juan","middleName":"","lastName":"liu","suffix":""},{"id":482078937,"identity":"cd1d4cd2-fda0-428a-abfd-8db69bc43285","order_by":3,"name":"dong wang","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"dong","middleName":"","lastName":"wang","suffix":""},{"id":482078938,"identity":"2f785964-2a72-4ee8-8dee-5c8573bfabd4","order_by":4,"name":"xiang lin","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"xiang","middleName":"","lastName":"lin","suffix":""},{"id":482078939,"identity":"cbea9d2e-e8c8-4765-b362-8453963e3d15","order_by":5,"name":"yuangang zhu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIiWNgGAWjYDACCQST8UGCgY0cG3v7AaK1MBt8qEgz5uM5k0C0FjbJGWcOJ86TcDDAq0N+do+ZNE/NHbv+2e0XpHnbmNPbJBgSGH5UbMOphXHOGaCWY8+SZ9w5U2DM28aW2ybdeICx58xtnFqYJXKAWtgOJzPcyElI5m3jyW2TOZDAzNiGWwsbWMu/w8nyQC2Hedsk0tkkEgzwauEBaeFtO2xncCP9YOOMMwYJBLVISKQVW87tO5xgeCOHmeFDRYJhGzCQD+Lzi/yM5I033nw7bC93I/35jwSD//Ly7e0HH/yowK0FCFhAUZPYwMCDiI4D+NQDAfMHIGHPwMD+gIDCUTAKRsEoGKkAAKEGWfU3kFxmAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-8611-9912","institution":"Dezhou University","correspondingAuthor":true,"prefix":"","firstName":"yuangang","middleName":"","lastName":"zhu","suffix":""},{"id":482078940,"identity":"6ca8ac50-d9cf-44cc-a5b0-38d3067e1d2d","order_by":6,"name":"zhongmin dai","email":"","orcid":"https://orcid.org/0009-0003-5863-5586","institution":"","correspondingAuthor":false,"prefix":"","firstName":"zhongmin","middleName":"","lastName":"dai","suffix":""}],"badges":[],"createdAt":"2025-07-03 12:32:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7038231/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7038231/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86450977,"identity":"422e5d2c-a2dc-4fe9-95eb-c34693ea24ed","added_by":"auto","created_at":"2025-07-10 19:19:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":17535,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on dry matter accumulation in 2021 (A) and in 2022 (B) and biomass per individual plant in 2021 (C) and in 2022 (D) of purple wheat at different growth periods. Different letters indicate significant difference between CI and MSI at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/9fdd9ac95d22fa8e46cd1260.png"},{"id":86450974,"identity":"227e551f-ee93-4e9a-b8ea-a0f0abb4c4c5","added_by":"auto","created_at":"2025-07-10 19:19:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":20204,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on leaf area index (LAI) in 2021 (A) and in 2022 (B), specific leaf area (SLA) in 2021 (C) and in 2022 (D), and specific leaf N content (SLN) in 2021 (E) and in 2022 (F) of purple wheat at different growth stages. Different letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/b315758eb34d10e5c025a0ee.png"},{"id":86451296,"identity":"549e678e-092d-4fda-bce7-524f4da9a023","added_by":"auto","created_at":"2025-07-10 19:27:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":25330,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on leaf area duration (LAD) in 2021 (A) and in 2022 (B), net assimilation rate (NAR) in 2021 (C) and in 2022 (D), and dry matter (DM) wasted in non-surviving tillers in 2021 (E) and in 2022 (F) of purple wheat at different growth stages. S-J, from sowing to jointing; J-B, from jointing to booting; B-A, from booting to anthesis; A-M, from anthesis to maturity. Different letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/3ec2e061935bc7c407168122.png"},{"id":86451297,"identity":"78db702b-5e39-4aa3-9f17-11c9703605e7","added_by":"auto","created_at":"2025-07-10 19:27:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":28851,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on aboveground N uptake in 2021 (A) and in 2022 (B), N wasted in non-surviving tillers in 2021 (C) and in 2022 (D) and N productivity in 2021 (E) and in 2022 (F) of purple wheat at different growth stages. S-J, from sowing to jointing; J-B, from jointing to booting; B-A, from booting to anthesis; A-M, from anthesis to maturity. Different letters indicate significant difference between CI and MSI at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/0926002b2127ea9b737fbb2e.png"},{"id":86450976,"identity":"eba75622-ebf4-43bf-9d86-bf6ab9f1a8c3","added_by":"auto","created_at":"2025-07-10 19:19:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":14421,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on total roots per unit area in 2021 (A) and in 2022 (B) and average roots number per stem in 2021 (C) and in 2022 (D) of purple wheat at different growth stages. Different letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/f6e7a04f09e35a466c093bf5.png"},{"id":86451478,"identity":"40f42b71-61e6-45c7-88bf-b6634c131af3","added_by":"auto","created_at":"2025-07-10 19:35:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":219935,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on soil water content in the 100 cm soil profile at critical growth stages of purple wheat in 2020-2021. BW, before wintering; J, jointing stage; A, anthesis stage; M, maturity stage.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/07745637733dc55bcf83ede7.png"},{"id":86450979,"identity":"441788c6-fb03-4f34-a2a4-01794f165f04","added_by":"auto","created_at":"2025-07-10 19:19:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":11899,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships between total roots per unit area and aboveground N uptake (A), and relationships between average roots number per stem and biomass per individual plant (B) under flood irrigation (CI,) and micro-sprinkling irrigation (MSI). * and ** indicate significant effects at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, respectively.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/bcd80754d78aee7b750bdb3b.png"},{"id":86450983,"identity":"064c27a4-bdd0-442e-86c4-79ecaf358d3d","added_by":"auto","created_at":"2025-07-10 19:19:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":121617,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between main agronomic traits of purple wheat in this study. DMM, total dry matter accumulation at maturity; DMR, dry matter remobilization before anthesis; DMRC, contribution of dry matter remobilization of organs before anthesis to grain yield; DMPA, dry matter accumulation post anthesis; DMPAC, the contribution of dry matter accumulation after anthesis to grain yield; LAI, leaf area index ; LAD, leaf area duration; NAR, net assimilation rate ; SLA, specific leaf area; NM, total N accumulation at maturity; NR, N remobilization pre-anthesis of different organs; NRC, the contribution rate of N remobilization pre-anthesis of different organs to grain N; NAA, N accumulation after anthesis; NAAC, the contribution of N accumulation after anthesis to grain N; SLN, specific leaf N content; SSM, spikes per square meter; GW, Grain weight; GS, Grains per spike; GY, Grain yield, PY, protein yield. *, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP\u003c/em\u003e\u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/2fa209cf37e697e8ab91340b.png"},{"id":90699570,"identity":"f91955ee-db4b-463d-8f7b-22511e421ba3","added_by":"auto","created_at":"2025-09-05 22:12:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1402334,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7038231/v1/c8669991-7b03-4509-907f-325ffe1891ad.pdf"}],"financialInterests":"","formattedTitle":"Micro-sprinkling irrigation improves grain yield, dry matter accumulation and nitrogen use efficiency of purple wheat in the North China Plain","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eGiven the escalating consumption rates among a substantial population and the constrained and diminishing availability of arable land resulting from urbanization and socioeconomic progress, the matter of food security has consistently held significant policy importance in China (Lu and Fan 2013). Enhancing the productivity of existing arable land is imperative to guarantee a stable food supply. The North China Plain, which serves as the central hub for grain production in contemporary China, is identified as the region with the most severe water scarcity within the country (Guo et al. 2019). Insufficient water supply continues to pose a major hindrance and persistent peril to achieving enhanced crop productivity in this area. In order to safeguard the attainment of national food security, the utilization of surface irrigation is extensively employed to supplement the water requirements for crop cultivation\u0026nbsp;(Ma et al. 2012). Nevertheless, the excessive exploitation of groundwater as the predominant source for extensive irrigation has led to significant depletion of groundwater resources (He et al. 2017), thereby exacerbating the prevailing water crisis in this particular region (Du et al. 2014). Furthermore, the substantial expansion of irrigated agriculture, although it has contributed to the reduction of surface temperatures and alleviation of soil drought, has concurrently facilitated the integration of temperature and humidity measurements, consequently intensifying the occurrence of heat waves (Kang and Eltahir 2018). With the evident contradiction between the growing scarcity of water resources and the imperative of national food security, it is crucial to enhance water productivity (WP, the ratio of grain yield to evapotranspiration) by exploring novel irrigation strategies that promote water conservation.\u0026nbsp;This approach aims to address the pressing issues of groundwater depletion while ensuring food self-sufficiency. Consequently, the pursuit of more effective utilization of water resources has emerged as a prominent research focus in the region.\u003c/p\u003e\n\u003cp\u003eThe effective water-saving strategies to seek to match crop water requirements with supplementary irrigation have been widely developed. Nowadays, advanced irrigation techniques have been verified to be played a pivotal role in decreasing the irrigation water requirements, and achieving higher WP and efficient agricultural production, particularly under conditions of water scarcity (AI-Ghobari and Dewidar 2018). For example, drip irrigation and sprinkler irrigation are useful in decreasing the required irrigation water, and offers the advantages of regulating root distribution and promoting the growth and boosting the WP and the economic benefit (Dar et al. 2017; Li et al. 2021; Zhang et al. 2019). Micro-sprinkling irrigation (MSI) has been in favour of improving the uniformity of the soil wetting body and the water amount per unit area of tillage layer and achieving good results in crop production (Baram et al. 2018; Li et al. 2019; Man et al. 2014, 2017).\u003c/p\u003e\n\u003cp\u003eOptimizing supplemental irrigation regimes by adopting agronomic management practices and adjusting the supplemental irrigation schedule plays a significant role in maintaining high yields and improving WP (Devkota et al. 2023; Yan et al. 2022). The timing and volume of irrigation have a significant impact on the growth and yield of winter wheat, thus influencing WP (Ech-chatir et al. 2025; Liu et al. 2024). Deficit irrigation as a limited irrigation strategy would be effective in improving efficiency and maximize profits through a reduction in the amount of water applied (Geerts and Raes 2009; Saitta et al. 2021; Tejero et al. 2011; Zhang et al. 2018), which includes three main strategies: sustained deficit irrigation, regulated deficit irrigation and partial root drying (Du et al. 2010; Fereres and Sorian 2007; Ginestar and Castel 1996; Kang et al. 2017; Marsal et al. 2008; Shellie 2014). Some research reported that limited irrigation can improve the growth and absorptive area of roots in both deep and surface soil layers and thus uptake more soil-stored water from the subsurface layers (Wang et al. 2014), and ultimately achieve higher grain yield (GY) and WP (Wang et al. 2016; Xu et al. 2016). Combining deficit irrigation with subsurface drip irrigation can achieve water savings in winter wheat production in water-scarce areas by not only improving deep soil water the extraction, but also maintaining yields by stimulating plant growth (Yang et al. 2020). Moreover, optimizing the MSI schedule has significantly improved the GY, WP and nitrogen use efficiency (NUE) of winter wheat (Li et al. 2019; Zhai et al. 2021), and also effectively reduced greenhouse gas emissions (Zhang et al. 2023). Besides, drip and MSI under plastic film can have stronger water saving capacity and improve WP, yield and crop quality, and directly regulate soil bacterial community and root system and reduce the soil water evaporation in the vertical direction (He et al. 2013; Zhang et al. 2020). The development of an optimized irrigation and fertilizer application regime is conducive to achieving sustainable agricultural development of and further improving crop yield, WP, and NUE. Optimized split nitrogen fertilizer has improved flag leaf photosynthetic performance and grain storage capacity of wheat, and achieved a high yield and high water and nitrogen (N) efficiency under water‑saving irrigation (Zhang et al. 2020). GY and photosynthetic capacity of drip-irrigated winter wheat were improved by appropriate split nitrogen application under different water regimes in the North China Plain (Hamani et al. 2023). GY, WP and NUE of winter wheat were improved by optimizing MSI and N application (Li et al. 2021). In addition, studies have reported that integrated water and fertilizer application has many advantages, such as reducing amounts of irrigation water and fertilizer, promoting crop growth and fertilizer absorption, enhanced WP and NUE and grain yield (Yan et al. 2019; Yan et al. 2021; Zou et al. 2020). And late sown wheat with supplemental irrigation at the jointing stage could improve production and WUE (Wang et al. 2023).\u003c/p\u003e\n\u003cp\u003ePurple wheat, as one of the colored wheats, has been received widely concerned for its potential health-enhancing properties (Gamel et al. 2023; Szőke-Trenyik et al. 2023). Purple wheat contains relatively rich anthocyanin and phenolic acid compounds, which have been proved to play multiple and beneficial physiological roles in the human health (Liu et al. 2018; Shipp and Abdel-Aal 2020). Although many studies have investigated the effect of MSI on grain yield and WP of field crops, information on whether MSI can increases grain yield and NUE of purple wheat is limited. Based on this, the aim of this study is to explore whether MSI can improve the yield and NUE of purple wheat by growth, water allocation and nutrient contents. Field experiment was carried out to (1) determine the effects of MSI on the GY and yield formation; (2) identify how MSI affects the accumulation and remobilization of dry matter (DM) and N, and N use. The results of this study provided theoretical basis and practical experience for water-saving, yield increases, and high-efficiency of purple wheat production in NCP.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eExperimental site and growth conditions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eField experiments were conducted during the 2020–2021 and 2021–2022 growing seasons at the experimental field of the Qianhua Village (37° 32′N, 116° 57′E), Bianlin Town, Lingcheng District, Dezhou City, Shandong Province. The primary substrate in this area was sandy loam (Typic Cambisols) with a pH of 8.13. The nutrients in the top 0–0.2 m soil profile comprised organic carbon 8.84 g kg\u003csup\u003e–1\u003c/sup\u003e, total nitrogen 0.90 g kg\u003csup\u003e–1\u003c/sup\u003e, available phosphorus 20.68 mg kg\u003csup\u003e–1\u003c/sup\u003e, and exchangeable potassium 248.00 mg kg\u003csup\u003e–1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTreatments and experimental design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA purple wheat cultivar (\u003cem\u003eTriticum aestivum\u003c/em\u003e) Nongda 3753 with high selenium and strong gluten as the experimental material, bred by the College of Agronomy and Biotechnology of China Agricultural University, was sown at a density of 330 plants m\u003csup\u003e−2\u003c/sup\u003e on October 12, 2020\u0026nbsp;and October 11, 2021. For both conventional irrigation (CI) and micro-sprinkling irrigation (MSI), irrigation was implemented at four key growth stages: after sowing, before wintering, at jointing, and at anthesis in both growing seasons. Each irrigation event delivered approximately 60 mm of water, verified by water meters installed at the discharge end of the hoses. This approach was chosen to ensure consistency in the irrigation schedule and to align with local agricultural practices in the North China Plain. CI was carried out via a mobile plastic hose connected to a tap. The micro-sprinkling hose with 40 cm diameter was 25 m long and had a flow rate of 6.0 m\u003csup\u003e3\u003c/sup\u003e h\u003csup\u003e-1\u003c/sup\u003e, and the sprinkling angle of the hose was 80°. Each experimental plot consisted of 20 rows of wheats paced 20 cm apart. Two micro-sprinkler hoses were laid between the fifth and sixth rows from the plot borders, so that the sprinkling range on each side of the hose was 1 m. The water meter installed at the discharge end of the hose was used to control the irrigation volume. Before sowing, compound fertilizers comprising N, P, and K at rates of 22% N, 9.6% P (equivalent to 22% P₂O₅), and 5.0% K (equivalent to 6% K₂O), respectively were applied as basal fertilizer with an amount of 600 kg ha\u003csup\u003e–1\u003c/sup\u003e. An extra 120 kg ha\u003csup\u003e–1\u003c/sup\u003e N as urea was topdressed at jointing. Each individual subplot was 25 m long and 4m wide, and a completely randomized block design has been arranged with three replicates. Diseases, pests, and weeds were well-controlled by applied prophylactic fungicides, insecticides and herbicides in all treatments following local field management protocols. All subplots were harvested on June 8, 2021 and June 6, 2022.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling and measurement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll shoots per unit area at jointing, booting and anthesis and spikes per unit area at maturity were counted in the 1.0 m × 6 lines quadrats with three repeats. At the same time, two rows of whole plants within 0.5 m were taken, including root systems 15 cm below the surface. After the roots were washed and dried with absorbent paper, the total number of roots including primary roots and nodal roots was counted, and then converted into the number of roots per unit area and per stem. Aboveground plants were separated into leaves, stems (including sheath), spikes (including spike rachis and glumes) and grains. Later on, green leaf area was measured to determine the leaf area index (LAI), which was then used to calculate the leaf area duration (LAD). All samples were dried to a constant weight at 80°C for 72 h to determine the quantity of aboveground DM. Specific leaf area (SLA) was calculated by dividing leaf area (cm\u003csup\u003e2\u003c/sup\u003e) by leaf dry mass. Net assimilation rate (NAR) was calculated as the rate of aboveground DM production expressed per unit of leaf area. The DM wasted in sterile tillers from jointing to booting and booting to anthesis was calculated as the product of DM per plant at jointing and at booting and the number of unproductive tillers at corresponding stage.\u003c/p\u003e\n\u003cp\u003eAboveground N uptake was determined by analyzing N content of dried plant components using the semi-micro-Kjeldahl method. Specific leaf N content (SLN) was calculated as leaf N content per unit leaf area (Vos et al. 2005). The calculation of N wasted in non-viable tillers from jointing to booting and booting to anthesis was similar to that of DM. The GY per unit of N supply (soil N+ fertilizer N) is defined as N use efficiency (NUE) (López-Bellido and López-Bellido 2001), which is the product of two primary components: (i) the N uptake efficiency (NUpE) as total plant N uptake divided by N supply, and (ii) the N utilization efficiency (NUtE) as the ratio of grain yield to total plant N uptake (Moll et al. 1982). Furthermore, the NUtE can be obtained by dividing the nitrogen harvest index (NHI) as the fraction of aboveground N uptake present as grain N by the grain nitrogen concentration (GNC). Grain protein concentration (GPC) was calculated as GNC× 5.7 (Nehe et al, 2020). In addition, plant N productivity was calculated as the ratio of increase in both plant DM and N content per unit time (Ingestad 1979).\u003c/p\u003e\n\u003cp\u003eIn order to estimate the accumulation of DM and N contributed to GY before and after anthesis, we calculated the various parameters involved in the movement of DM and N from the plant components into the grains according to Papakosta and Gagianas (1991). DM and N remobilization after anthesis was given as the amount of DM and N stored in the crop non-grain organs of the plant (leaves, stems, and spikes) at anthesis that was not present in the above straw at maturity. The accumulated quantity of DM and N after anthesis was calculated as the difference between grain DM and N yield at harvest and the quantity of DM and N remobilized from the vegetative organs, respectively. The remobilization and accumulation of DM and N after anthesis contributed to final grain DM and N yields were then calculated as the percentage of each in the final grain DM and N yields respectively.\u003c/p\u003e\n\u003cp\u003eSoil samples were collected at 20 cm intervals to a depth of 100 cm by artificial spiral drills before wintering, at jointing, anthesis and maturity in 2020-2021. The soil water content was measured by oven-drying method at 80\u0026nbsp;°C\u0026nbsp;to a constant weight (Li et al. 2018).\u003c/p\u003e\n\u003cp\u003eAt maturity, 30 stems randomly selected from each subplot were threshed separately by hand to measure and record the grain numbers and weights, and then the average grains per spike and grain weight were calculated. GY was measured by harvesting all spikes in a quadrat of 3.0 m long and 1.0 m wide in each plot, and defined as the grain weight with a standard 12% moisture content. Grain protein yield (PY) was calculated as GY×GPC at maturity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis employed standard analysis of variance (ANOVA) using DPS (Data Processing System). The least significant difference (LSD) method was used to determine whether there were differences between treatments at the probability level of 5%. Microsoft Excel 2010 and SigmaPlot 10.0 software were used for data analyses and post-processing. Use the “linkET” package in R·4.3.1 to perform a mantel test analysis.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003eGrain yield and protein yield \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods had significant effects on spikes per unit area, grains per spike, GY and PY of purple wheat, but had no effect on grain weight and GNC (Table 1). Year significantly affected grain weight, GPC, GY and PY but had no effect on spikes per square meter and grains per spike (Table 1). The effect of their interaction was only significant for GPC (Table 1). Compared with CI, GY, spikes per square meter and grains per spike of MSI significantly increased by 12.0%, 8.3%, and 8.7%, respectively. Patterns of change in PY were consistent with those in GY (Table 1).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on grain\u003c/p\u003e\n\u003ctable width=\"126%\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eTreatment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003eSpikes per square\u003c/p\u003e\n\u003cp\u003emeter (no. m\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003eGrains per spike\u003c/p\u003e\n\u003cp\u003e(no.)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003eGrain weight (mg)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003eGY\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003eGPC\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003ePY\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003e2020-2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eMSI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e714.4\u0026plusmn;3.1a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e31.14\u0026plusmn;0.38a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e37.16\u0026plusmn;0.13a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e6417.7\u0026plusmn;116.3a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e11.65\u0026plusmn;0.09a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e738.68\u0026plusmn;11.07a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e658.8\u0026plusmn;12.5b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e28.76\u0026plusmn;0.15b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e36.77\u0026plusmn;0.30a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e5644.2\u0026plusmn;154.6b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e11.91\u0026plusmn;0.04a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e672.79\u0026plusmn;17.72b\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003e2021-2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eMSI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e715.8\u0026plusmn;11.3a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e31.82\u0026plusmn;0.66a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e40.40\u0026plusmn;0.18a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e6897.53\u0026plusmn;124.9a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e12.27\u0026plusmn;0.10a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e846.33\u0026plusmn;15.40a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e662.1\u0026plusmn;9.4b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e29.15\u0026plusmn;0.37b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e39.85\u0026plusmn;0.44a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e6253.78\u0026plusmn;88.9b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e12.35\u0026plusmn;0.11a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e772.34\u0026plusmn;10.85b\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eANOVA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eIrrigation method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eYear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"20%\"\u003e\n\u003cp\u003eIrrigation method\u0026times;Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"15%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"14%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"13%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eyield (GY) and its constituent factors, grain protein concentration (GPC) and protein yield (PY) of purple wheat\u003c/p\u003e\n\u003cp\u003eDifferent letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level. *, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively; ns indicates no significant effect. Values are means \u0026plusmn; standard error (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDry matter accumulation and remobilization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods significantly influenced DM accumulation and biomass per individual plant (Table 2). MSI led to significantly increase the accumulated DM by 47.5% at jointing, 21.5% at booting, 9.9% at anthesis and 14.9% at maturity compared with CI (Fig. 1). No uniform trends in the DM accumulations were observed at different growth stages, MSI significantly increased DM accumulations from sowing to jointing by 47.5% and from anthesis to maturity by 27.3% compared to CI. But lack of significant difference in DM accumulation was found from jointing to booting and from booting to anthesis. Similar trends were observed in biomass per individual plant except for anthesis in 2022 (Fig. 1).\u003c/p\u003e\n\u003cp\u003eTable 2 Analysis of variance of dry matter (DM) accumulation, biomass per individual plant (BIP), leaf area index (LAI), specific leaf area (SLA), specific leaf N content (SLN), leaf area duration (LAD), net assimilation rate (NAR), DM wasted in non-surviving tillers, nitrogen (N) accumulation, N wasted in non-surviving tillers, N productivity, total roots per unit area, average roots number per stem as affected by irrigation method (I), year (Y) and their interaction (I \u0026times; Y) for purple wheat\u003c/p\u003e\n\u003ctable width=\"115%\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eFactor\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003eDM accumulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003eBIP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003eLAI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eSLA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eSLN\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eLAD\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eNAR\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"12%\"\u003e\n\u003cp\u003eDM wasted in non-surviving tillers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003eN accumulation\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003eN wasted in non-surviving tillers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7%\"\u003e\n\u003cp\u003eN productivity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"8%\"\u003e\n\u003cp\u003eTotal roots per unit area\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003eAverage roots number per stem\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"12%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"8%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eY\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"12%\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"8%\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003eI\u0026times;Y\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"3%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"4%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"12%\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"9%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"11%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"7%\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"8%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"10%\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively; ns indicates no significant effect.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIrrigation methods had significant effects on dry matter accumulation at anthesis and maturity, pre-anthesis translocation and post-anthesis accumulation and their contribution to grain yield of each organ (Table 2). Year had only significantly influenced dry matter accumulation of stem at anthesis and its contribution of remobilized dry matter before anthesis to grain yield (Table 2). The interaction of irrigation methods\u0026times; year had significant effect on spikes (excluding grains) at maturity and the contribution rate of total dry matter remobilization before anthesis and DM accumulation post anthesis to GY (Table 2). Higher DM accumulation was dramatically observed in stems than that in leaves and spikes (excluding grains) at anthesis and maturity under two irrigation methods, DM accumulation in spikes was significantly lowest (Table 3). MSI exerted a significantly higher DM accumulation in stems and spikes than that in CI, between which, increased by 10.0% and 15.2% at anthesis, 14.5% and 25.3% at maturity, respectively. No uniform trends in the DM accumulation in leaves at anthesis and at maturity were observed. No significant difference was observed in DM accumulation of leaves between MSI and CI at anthesis, but the former was significantly higher by 14.2% than the latter at maturity. The DM remobilization (DMR) of stems and leaves before anthesis was significantly higher than that in spikes under both MSI and CI, but there were no significant differences in the DMR between stems and leaves except for MSI in 2022. The contribution of DMR of various plant components to GY (DMRC) was consistent with DMR. MSI significantly decreased the DMR and DMRC of each organ and the total contribution rate of DMR to GY (DMRCT) of relative to CI, whereas DM accumulation post anthesis (DMPA) and the DMPA contributed to GY (DMPAC) showed the opposite trends. Compared with CI, the DMR of leaves, stems and spikes and the DMRCT of MSI have significantly decreased by 28.0%, 42.9%, 39.5% and 36.1%. However, MSI have significantly increased DMPA by 27.3% and DMPAC by 12.4% than those in CI. On the whole, MSI significantly increased DM accumulation after anthesis and its contribution to grain while decreased the DM remobilization and contribution before anthesis compared to CI.\u003c/p\u003e\n\u003cp\u003eTable 3 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on dry matter accumulation at anthesis (DMA), dry matter accumulation at maturity (excluding grains) (DMM), dry matter remobilization before anthesis (DMR), contribution of dry matter remobilization of organs before anthesis to grain yield (DMRC), the total contribution rate of dry matter remobilization before anthesis to grain yield (DMRCT), dry matter accumulation post anthesis (DMPA), the contribution of dry matter accumulation after anthesis to grain yield (DMPAC) of purple wheat\u003c/p\u003e\n\u003ctable width=\"718\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eTreatment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eOrgan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003eDMA\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eDMM\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003eDMR\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003eDMRC\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003eDMRCT\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003eDMPA\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003eDMPAC\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e2020-2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eMSI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e2339.59\u0026plusmn;60.93c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e1939.89\u0026plusmn;72.98c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e399.70\u0026plusmn;30.45b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e6.09\u0026plusmn;0.51b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e14.59\u0026plusmn;0.92b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e5613.54\u0026plusmn;147.30a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e85.41\u0026plusmn;1.59a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e7756.37\u0026plusmn;61.89a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e7318.65\u0026plusmn;143.16a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e437.72\u0026plusmn;48.89b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e6.67\u0026plusmn;0.60b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e1837.74\u0026plusmn;89.46d\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd 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width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eIrrigation method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eYear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003eIrrigation method\u0026times;Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"80\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"46\"\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"99\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"95\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"73\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"98\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDifferent letters indicate significant difference between CI and MSI at \u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05 level. *, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively; ns indicates no significant effect. Values are means \u0026plusmn; standard error (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe characteristics of photosynthetic production\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods and year significantly influenced LAI, SLA, SLN, LAD, NAR and DM losses in sterile tillers, but the effect of their interaction was only significant for SLN and DM losses in sterile tillers (Table 2). LAI of MSI at different growth periods was significantly higher than CI, between which, increased by 18.4% at jointing, 11.2% at booting, 8.6% at anthesis (Fig. 2). While the reverse was true in SLA, the reduction was 8.5% at jointing, 8.5% at booting and 7.1% at anthesis (Fig. 2). Trends similar to those in LAI were observed in SLN at the same growth period (Fig. 2).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 3, the LAD of MSI at different growth stages was significantly higher than that of CI treatment. The LAD of MSI increased by 18.4% from sowing to jointing, 13.1% from jointing to booting, 10.2% from booting to anthesis, and 10.2% from anthesis to maturity compared to that of CI. NAR at different stages of growth showed a trend consistent with DM accumulation (Fig. 3). NAR of MSI from sowing to jointing and from anthesis to maturity significantly increased by 39.6% and 22.4% compared to CI, respectively. Lack of significant difference in NAR was observed from jointing to booting and from booting to anthesis.\u003c/p\u003e\n\u003cp\u003eDifferent irrigation methods had significant influence on DM losses in sterile tillers during the stem elongation (Fig. 3). Compared with CI, MSI resulted in a 118.5% increase in the quantity of DM wasted in unproductive tillers from jointing to booting and a 20.4% increase from booting to anthesis, respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNitrogen accumulation and remobilization\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods had significantly affected N accumulation, N wasted in non-surviving tillers and N productivity, and the interaction of irrigation methods\u0026times; year had influenced the latter two (Table 2). Year has no significant effect on the above indexes (Table 2). As shown in Fig. 4, irrigation methods had a significant effect on aboveground N uptake from sowing to jointing and from anthesis to maturity, while had no influence on aboveground N uptake from jointing to booting and from booting to anthesis. Compared with CI, MSI resulted in a 41.5% increase in aboveground N uptake from sowing to jointing and a 33.6% increase from anthesis to maturity. The patterns of changes in N lose in non-viable tillers were similar to DM wasted in unproductive tillers. The amount of N wasted in sterile tillers during the jointing to booting and booting to anthesis stages under MSI was found to be 71.3% and 11.4% higher, respectively, compared to that observed under control irrigation. No differences in N productivity from sowing to jointing and from jointing to booting were observed between irrigation methods. Nevertheless, significant increments in N productivity from booting to anthesis and from anthesis to maturity were obtained for under MSI exhibiting 14.0% and 12.1% higher values than those under CI.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to N accumulation of leaf and spike (excluding grains) at maturity and the contribution of remobilizated N of leaf before anthesis to grain N, irrigation methods had significant effects on N accumulation at anthesis and maturity, pre-anthesis translocation and post-anthesis accumulation and their contribution to grain N of each organ (Table 2). Year had significantly influenced N accumulation at anthesis and maturity, pre-anthesis translocation and their contribution to grain N of each organ except N accumulation of leaf at both anthesis and maturity and spike (excluding grains) at maturity and N translocation of leaf before anthesis (Table 2). The interaction of irrigation methods\u0026times; year had significant effect on N accumulation of stem and spike (excluding grains) at maturity and pre-anthesis translocation of spike (excluding grains) and their contribution to grain N (Table 2). N accumulation in stems was significantly greater than that in leaves and spikes at anthesis and maturity under both CI and MSI. The N accumulation in stems exhibited a significantly higher level in MSI compared to CI, with an increase of 6.5% at anthesis, and 23.4% at maturity, respectively. The N accumulation in spike (excluding grains) was found to be similar between MSI and CI at anthesis during the two growth stages, and the former exhibited a significantly higher level by 13.7% compared to the latter. However, the patterns of changes in N accumulation in spike (excluding grains) at maturity were opposite during the two growth stages (Table 4). The N remobilization (NR) and the pre-anthesis contribution of NR to grain N (NRC) was significantly higher in leaves than that in stems and spikes under both MSI and CI, with spike exhibiting the lowest NR and NRC. The NRC of stems as well as the total contribution rate of NR to grain N (NRCT) were significantly lower in MSI relative to those in CI. Conversely, N accumulation after anthesis (NAA) and its contribution of NAA to grain yield (NAAC) exhibited opposite trends between MSI and CI. The NRC of stems as well as the NRCT of MSI showed a significant decrease by 17.7% and 8.7% when compared to CI. However, MSI demonstrated a significant increase in NAA by 33.6% and NAAC by 20.2% compared to CI. The overall results suggest that MSI significantly enhanced post-anthesis N accumulation and its contribution to grain N, while decreasing the contribution of pre-anthesis N remobilization decreased compared to CI.\u003c/p\u003e\n\u003cp\u003eTable 4 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on N accumulation at anthesis (NA), N accumulation at maturity (besides grain) (NM), N remobilization pre-anthesis of different organs (NR), the contribution rate of N remobilization pre-anthesis of different organs to grain N (NRC), total contribution of N remobilization preanthesis to grain N (NRCT), N accumulation after anthesis (NAA), the contribution of N accumulation after anthesis to grain N (NAAC) of purple wheat\u003c/p\u003e\n\u003ctable width=\"643\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eTreatment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eOrgan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003eNM\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003eNR\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003eNRC\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eNRCT\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003eNAA\u003c/p\u003e\n\u003cp\u003e(kg hm\u003csup\u003e-2\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003eNAAC\u003c/p\u003e\n\u003cp\u003e(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e2020-2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd 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width=\"75\"\u003e\n\u003cp\u003e27.33\u0026plusmn;0.87c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e19.73\u0026plusmn;0.62e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e8.88\u0026plusmn;0.50d\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e10.85\u0026plusmn;0.36c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e7.54\u0026plusmn;0.41d\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e50.35\u0026plusmn;2.72d\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e10.38\u0026plusmn;0.36c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e39.97\u0026plusmn;2.44b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e31.37\u0026plusmn;2.39b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e70.90\u0026plusmn;2.45a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e37.14\u0026plusmn;2.18b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e29.10\u0026plusmn;2.45b\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e73.10\u0026plusmn;1.22b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e29.75\u0026plusmn;0.34b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e43.35\u0026plusmn;0.98a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e34.00\u0026plusmn;0.58a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e17.75\u0026plusmn;0.41f\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e10.68\u0026plusmn;1.08c\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e7.07\u0026plusmn;0.72d\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e5.54\u0026plusmn;0.45e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eANOVA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eIrrigation method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eYear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003eIrrigation method\u0026times;Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e/\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eLeaf\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eStem\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"100\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cp\u003eSpike\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"78\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"72\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"75\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"70\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"71\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDifferent letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level. *, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively; ns indicates no significant effect. Values are means \u0026plusmn; standard error (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNitrogen use efficiency and its associated parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods had significant effect on NUE and its associated parameters except GNC (Table 5). Year had significantly influenced NUE and GNC, and their interaction had only significant effect on GNC (Table 5). The NUE of MSI was 10.4% higher than that of CI due to a higher GY. NUpE showed a similar pattern to NUE. NUpE significantly raised under MSI relative to CI, because of a higher aboveground N uptake. No differences in NUtE were observed between CI and MSI attribute to similar NHI and GNC.\u003c/p\u003e\n\u003cp\u003eTable 5 Effects of conventional flood irrigation (CI) and micro-sprinkling irrigation (MSI) on nitrogen use efficiency (NUE), nitrogen uptake efficiency (NUpE), nitrogen utilization efficiency (NUtE), nitrogen harvest index (NHI), and grain nitrogen concentration (GNC) of purple wheat\u003c/p\u003e\n\u003ctable width=\"576\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eTreatment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003eNUE\u003c/p\u003e\n\u003cp\u003e(kg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eNUpE\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eNUtE\u003c/p\u003e\n\u003cp\u003e(kg kg\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003eNHI\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eGNC\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;(%)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e2020-2021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMSI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e15.67\u0026plusmn;0.49a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e49.86\u0026plusmn;0.51a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e31.44\u0026plusmn;0.99a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e65.00\u0026plusmn;0.90a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2.02\u0026plusmn;0.01a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e14.05\u0026plusmn;0.75b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e44.63\u0026plusmn;0.79b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e31.48\u0026plusmn;0.45a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e66.38\u0026plusmn;0.57a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2.09\u0026plusmn;0.02a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003e2021-2022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eMSI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e17.35\u0026plusmn;0.54a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e50.92\u0026plusmn;1.17a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e34.10\u0026plusmn;1.70a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e71.18\u0026plusmn;0.33a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2.17\u0026plusmn;0.02a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eCI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e15.87\u0026plusmn;0.20b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e44.87\u0026plusmn;0.54b\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e35.39\u0026plusmn;0.85a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e71.50\u0026plusmn;0.76a\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2.15\u0026plusmn;0.02a\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eANOVA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eIrrigation method\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e**\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eYear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e***\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"159\"\u003e\n\u003cp\u003eIrrigation method\u0026times;Year\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"86\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ens\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e*\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDifferent letters indicate significant difference between CI and MSI at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 level. *, ** and *** indicate significant effects at \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01 and \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001, respectively; ns indicates no significant effect. Values are means \u0026plusmn; standard error (n = 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRoots number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIrrigation methods and year had significant impact on the total roots per unit area and average roots number per stem, and the interaction had no effect (Fig. 5). MSI exhibited a significant increase in the total roots per unit area and average roots number per stem of 66.6% and 67.4%, respectively, at jointing, while at booting and anthesis stages, these increases were observed to be 22.0% and 14.0%, as well as 25.6% and 16.9%, compared to those of CI (Fig. 5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSoil water content\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 6, the soil moisture content under the two irrigation methods varies dynamically at each growth stage. Although MSI maintained a relatively high soil moisture level in different soil layers during the three key stages of pre-wintering (BW), jointing (J), and flowering (A), no significant difference was achieved compared with CI.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrelation analysis showed that the total root number per unit area was significantly and positively correlated with the aboveground N uptake (Fig. 7). A significant and positive correlation was also observed between the average roots number per stem and biomass per individual plant (Fig. 7).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found that GY was strongly and positively related to spikes per square meter and grains per spike, but no significant correlation with grain weight at harvest (Fig. 8). Moreover, GY showed statistically positive and significant relationship to NAR, total dry matter accumulation at maturity, dry matter accumulation post anthesis and the contribution of dry matter accumulation after anthesis to grain yield, but negative to SLA (Fig. 8). Additionally, similar correlations were also found between GY and above-ground N accumulation at maturity, N accumulation after anthesis; NAC, the contribution of N accumulation after anthesis to grain N (Fig. 8). PY presented significant positive correlations with NAR, NR before anthesis, spikes per square meter, grains per spike, grain weight and GY, but was negatively correlated with SLA (Fig. 8).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWater is an essential factor that influences the conversion of soil nutrient and absorption of crop nutrient, and exerts important impact on crop growth and yield formation (Guo et al. 2019).Excessive irrigation has a limited impact on yield growth, but can exacerbate groundwater consumption and nitrogen loss (He et al. 2017; Xin and Tao 2019). Hence, agricultural irrigation should be managed according to local resource reserves, climatic characteristics and actual crop needs (Dalin et al. 2011), and adoption of advanced irrigation techniques is a crucial means for enhancing irrigation WP and for realizing efficient agricultural production. In this study, we found that MSI has significantly elevated GY, spikes per square meter and grains per spike of purple wheat, but no significant differences in grain weight. The increase in harvestable spikes of MSI was attributed to the increment in tiller survival rate. It has previously been established that the number of grains per spike at maturity has a significant positive correlation with the number of fertile florets per spike at anthesis (González et al. 2011). Further research is essential to understand the response mechanisms of floret development to the increase in the number of grains per spike by MSI. Our findings tend to indicate that the increment in grain yield of purple wheat by MSI was mainly due to the increase in grain number per unit area.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIncreasing DM is the prerequisite for obtaining high yield (Yan et al. 2022), and DM accumulation is largely dependent on environmental conditions, especially soil water content (Yan et al. 2019; Zhiipao et al. 2023). Our results indicated that MSI increased the accumulation of dry matter in different growth stages of purple wheat. Dry matter production is affected by the ability of canopy to intercept photosynthetically active radiation and use it to produce biomass referred to as radiation-use efficiency (RUE) (Muurinen and Peltonen-Sainio 2006). Radiation captured by the crop can be represented as a function of LAI. SLA and SLN have been confirmed as two key characters that determine the photosynthetic capacity (Lemaire et al. 2008; Sieling et al. 2016), which were related to RUE. Therefore, enhanced investment into leaf which achieves a higher leaf area or lower SLA is crucial to increase the assimilation capacity per plant. In the current study, we demonstrated that MSI has significantly improved LAI, which proved beneficial in terms of increasing LAD. Moreover, MSI has decreased SLA and enhanced the SLN, indicating that MSI may allow the investment of more N into the leaf which could therefore contribute to improve the photosynthetic rate. This further explains that MSI had coordinated the growth and development of purple wheat to optimize light capture and energy conversion. However, the no significant difference in the NAR from jointing to booting and from booting to anthesis was found between MSI and CI. The reason may be mainly due to the fact that MSI produces more dry matter waste of ineffective tillers than CI.\u003c/p\u003e\n\u003cp\u003eThe DM required for developing grain in cereals mainly originates from the remobilization of reserves stored in the vegetative organs and the current assimilation by photosynthates after anthesis (Gorooei et al. 2023; Zhang et al. 2019), the characteristics of which are significantly affected by soil water status (Cui et al. 2015). Previous studies suggested that water deficit had decreased the accumulation of DM after anthesis and was conducive to promote the translocation of stored DM before anthesis to grain (Ercoli et al. 2008; Liu et al. 2016). Limited irrigation before anthesis enhances photosynthesis and DM remobilization after anthesis (Xue et al. 2006). Supplemental irrigation or mild deficit irrigation boosted DM accumulation at anthesis and post anthesis and DM remobilization, but decreased DM remobilization efficiency (Moradi et al. 2022; Yan et al. 2022). MSI produced greater DM in various organs at anthesis and maturity than CI in the present study, but the amount and contribution of pre-anthesis DM translocated to grain of MSI was lower than CI. However, the opposite trend was observed in the DM accumulation and the share of DM accumulation after anthesis to GY. Since the DMA has a significant positive correlation with the yield, maintaining a relatively high LAI and photosynthetic capacity after anthesis is conducive to improve the biomass and increase GY (Ba et al. 2020). It was previously shown that MSI had observed the higher chlorophyll content of leaves during the mid–late grain filling period and increased the contribution of DM accumulation after anthesis to GY of winter wheat with consequent boosted GY compared to CI (Li et al. 2021). This research assumed that lower SLA and higher the SLN under MSI helps to maintain the ability of photosynthetic carbon assimilation of leaves after anthesis, which in turn, contributes to an increment in DM and GY of purple wheat. It further indicated that purple wheat under MSI would depend more on current photosynthesis for grain filling than on translocation of their pre-anthesis stored reserves.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eN accumulation and remobilization are vital processes that determine grain quality and yield (Gaju et al. 2011), and the uptake, remobilization, and assimilation of N have been influenced by irrigation schemes (Li et al. 2009). Studies have shown that water deficient can decrease N absorption and NUE (Plaut et al. 2004), and increasing irrigation rates cause an increment in aboveground N uptake (AGN) and NUE (Zhang et al. 2006). However, other studies have revealed that mild water deficits promote N availability and uptake (Széles et al. 2012; Yan et al. 2020). In the present study, MSI significantly increased N accumulation from sowing to jointing and from anthesis to maturity compared with CI. However, there was no difference in N accumulation from jointing to booting and from booting to anthesis, which may be due to the higher N wasted in non-surviving tillers caused by MSI than CI. N utilization is a comprehensive process involving the absorption and utilization of N by plants (Moradi et al. 2022). MSI obtained high NUE mainly through increased NUpE resulting from increases N uptake, however remained lack of difference in GY per unit of N consumed (NUtE) owing to no change in NHI and GNC compared to CI. Root morphology and physiology has a close association with above–ground growth and development (Ju et al. 2015). Previous research demonstrated a well-developed root system could boost the capacity of uptake nutrients which is more conducive to for the increment in yield and NUE (Palta et al. 2007; Wang et al. 2014), and a shallow root system is imperative to absorb nutrients that are mainly concentrated in the upper soil (Becker et al. 2016). In this study, more root number obtained by MSI could be associated with enhanced the extraction capacity of N, which couple with higher N productivity, resulting in a greater N accumulation and biomass production.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt has also been reported that N remobilization efficiency in wheat had been enhanced by water deficit (Li et al. 2021). Although the N accumulated in stems and spikes at the anthesis and maturity of MSI were significantly more than CI, there was no difference in the remobilization of N before flowering between treatments. Similar to DM accumulation, MSI increased post-anthesis N accumulation and thus increased its contribution to grain N, and greatly increased total N accumulation at maturity. This further indicates that although the remobilization of the stored N in vegetative organs at anthesis provides a major drive to developing grain (Gaju et al. 2014),post-flower N accumulation is also a key factor in determining grain N. Further studies are needed to investigate the mechanism that capacity of root absorption and N accumulation and remobilization, which could also allow for a better understanding of MSI and its effects on purple wheat yield.\u003c/p\u003e\n\u003cp\u003eOptimizing irrigation management can regulate the soil moisture status, which is closely has a great influence on temporal and spatial distribution of root in soil (Feng et al., 2017; Li et al., 2018; Ma et al. 2013; Wang et al., 2014). A reasonable root distribution significantly increases N use efficiency and reduces the loss of nitrogen fertilizer and the negative effects on the environment (Rasmussen et al., 2015). Although our soil water content measurements (0–100 cm soil depth) did not show statistically significant differences between MSI and CI treatments at key growth stages, the inherent characteristics of MSI likely modified soil moisture distribution in ways not fully captured by bulk measurements. Studies have demonstrated that MSI delivers water more uniformly and frequently at lower volumes compared to CI, creating a shallower and more homogeneous wetting front that favors root proliferation in the upper soil layers (Li et al., 2021; Man et al., 2014). This is corroborated by our data showing significantly higher root numbers per unit area and per stem under MS, particularly in surface layers. Such a root distribution enhances access to water and nutrients concentrated near the soil surface, thereby supporting greater early-season dry matter accumulation and nitrogen uptake. Moreover, we speculate that MSI optimizes soil moisture availability in the root zone, promoting vigorous early growth and delaying water stress during critical reproductive stages. This is reflected in the extended leaf area duration (LAD) and higher net assimilation rates (NAR) during post-anthesis periods, which facilitated greater reliance on current photosynthates for grain filling rather than remobilization of pre-anthesis reserves. In addition, the stable soil water status may also affect the remobilization and distribution of nitrogen. MSI increased the post-anthesis nitrogen accumulation and its contribution to grain nitrogen, while decreasing the pre-anthesis nitrogen remobilization. This change in nitrogen distribution pattern may be related to the stable soil water status maintaining the physiological functions of plants after anthesis, promoting the absorption and utilization of nitrogen. This study provides valuable insights into the mechanisms underlying the improved performance of purple wheat under MSI. And the findings also underscore the potential for the application of MSI technology in the production of purple wheat. Future research should focus on exploring the physiological and biochemical mechanisms through which MSI improves yield and nutrient uptake of purple wheat, as well as characterizing root system architecture and spatial distribution under MSI, linking root traits to water-nitrogen uptake efficiency in different soil layers. Additionally, exploring different irrigation schedules and volumes as well as the water-nitrogen interaction effects tailored to the specific needs of purple wheat at each growth stage could provide further insights into optimizing use efficiency of water and N.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by Shandong Province Natural Science Foundation (ZR2019MC032), Dezhou University School-level Scientific Research Project (2019xjrc316), Dezhou University College Students' Innovation and Entrepreneurship Training Program (X202410448059), and the Open Project Program of State Key Laboratory for Crop Stress Resistance and High-Efficiency Production NWAFU (SKLCSRHPKF14), Yangling, Shaanxi, 712100, China\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003eAuthor Contributions\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Xinyu Zhao, Rugang Wu, Juan Liu and Xiang Lin. The first draft of the manuscript was written and reviewed by Yuangang Zhu, Zhongmin Dai and Dong Wang, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by Shandong Province Natural Science Foundation (ZR2019MC032), Dezhou University School-level Scientific Research Project (2019xjrc316), Dezhou University College Students' Innovation and Entrepreneurship Training Program (X202410448059), and the Open Project Program of State Key Laboratory for Crop Stress Resistance and High-Efficiency Production\u0026nbsp;NWAFU (SKLCSRHPKF14), Yangling, Shaanxi, 712100, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAI-Ghobari HM, Dewidar AZ (2018) Integrating deficit irrigation into surface and subsurface drip irrigation as a strategy to save water in arid regions. Agric Water Manag 209:55\u0026ndash;61. https://doi.org/10.1016/j.agwat.2018.07.010\u003c/li\u003e\n\u003cli\u003eBa QS, Zhang LL, Chen SX, et al (2020) Effects of foliar application of magnesium sulfate on photosynthetic characteristics, dry matter accumulation and its translocation, and carbohydrate metabolism in grain during wheat grain filling. 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Agric Water Manage 230:105986. https://doi.org/10.1016/j.agwat.2019.105986\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":"Micro-sprinkling irrigation, Grain yield, Nitrogen use efficiency, Dry matter accumulation","lastPublishedDoi":"10.21203/rs.3.rs-7038231/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7038231/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Aims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMicro-sprinkling irrigation (MSI) has been instrumental in enhancing crop yield and water utilization efficiency. Nevertheless, there is a paucity of research on the impact of MSI on purple wheat.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA field experiment was carried out to examine the influence of conventional irrigation practice (CI) and MSI on grain yield, dry matter accumulation, and nitrogen (N) use efficiency of purple wheat.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings indicate that grain yield, protein yield, spikes per square meter and grains per spike increased by an average of 12.0%, 9.7%, 8.3%, and 8.7%, respectively, under MSI relative to CI. Additionally, the dry matter accumulation of MSI at various growth stages surpassed that of CI. MSI also led to an increase in leaf area index, specific leaf nitrogen and leaf area duration, while simultaneously decreasing specific leaf area. The net assimilation rate,N accumulation and productivity demonstrated similar patterns to leaf area duration during the stages from sowing to jointing and from anthesis to maturity. The improvement of N use efficiency resulting from MSI was primarily attributed to the increase in N uptake efficiency. Conversely, the lack of variation in N utilization efficiency was primarily due to the unchanged nitrogen harvest index and grain nitrogen concentration. MSI has increased the contribution of dry matter and nitrogen after anthesis to grains, while the reverse was true before anthesis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs a result, MSI has been shown to enhance the growth and yield of purple wheat through improved dry matter accumulation and N use efficiency.\u003c/p\u003e","manuscriptTitle":"Micro-sprinkling irrigation improves grain yield, dry matter accumulation and nitrogen use efficiency of purple wheat in the North China Plain","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-10 19:19:23","doi":"10.21203/rs.3.rs-7038231/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":"890046ba-388b-43e0-8f41-a7545371d777","owner":[],"postedDate":"July 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-05T22:03:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-10 19:19:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7038231","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7038231","identity":"rs-7038231","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}