Preamble

Effects of a Combination of Biochar and Cow Manure on Soil Nutrients and Cotton Yield in Salinized Fields

HUANG Cheng¹,², HOU Shengtong¹,², WANG Bao¹,², SONG Yuchuan¹,², Aikeremu ABULATIJIANG¹,², MIN Jiuzhou¹,², SHENG Jiandong¹,², JIANG Ping'an¹,², WANG Ze¹,², CHENG Junhui¹,²*

¹ College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
² Xinjiang Key Laboratory of Soil and Plant Ecological Processes, Xinjiang Agricultural University, Urumqi 830052, China

Abstract: Biochar and animal manure application can improve crop yields in salt-affected soil. Previous studies have primarily applied biochar and animal manure either alone or at fixed ratios, while their combined effects with varying combination proportions remain unclear. To address this knowledge gap, we performed a two-year experiment (2023–2024) in a salinized cotton field in Wensu County, Xinjiang Uygur Autonomous Region, China, with six treatments: control; biochar application alone (10 t/hm²) (BC100%); cow manure application alone (10 t/hm²) (CM100%); 70% biochar (7 t/hm²) combined with 30% cow manure (3 t/hm²) (BC70%+CM30%); 50% biochar (5 t/hm²) combined with 50% cow manure (5 t/hm²) (BC50%+CM50%); and 30% biochar (3 t/hm²) combined with 70% cow manure (7 t/hm²) (BC30%+CM70%). By measuring soil pH, electrical conductivity, soil organic matter, available phosphorus, available potassium, and available nitrogen at 0–20 and 20–40 cm depths, as well as yield components and cotton yield in 2023 and 2024, this study revealed that soil nutrients in the 0–20 cm depth were more sensitive to treatment effects. Among all treatments, BC50%+CM50% produced the highest soil pH (9.63±0.07) but the lowest values of electrical conductivity (161.9±31.8 μS/cm), soil organic matter (1.88±0.27 g/kg), and available potassium (42.72±8.25 mg/kg) in 2024. Moreover, the highest cotton yield (5336.63±467.72 kg/hm²) was also observed under BC50%+CM50% treatment in 2024, which was 1.9 times greater than that under the control. In addition, cotton yield in 2023 was jointly determined by yield components (density and number of cotton bolls) and soil nutrients (available phosphorus and available potassium), but in 2024, cotton yield was only positively related to yield components (density, number of cotton bolls, and single boll weight). Overall, this study highlights that in salt-affected soil, combining biochar and cow manure at a 1:1 ratio is recommended for increasing cotton yield and reducing soil salinity stress.

Keywords: biochar; animal manure; yield components; crop yield; soil nutrients; soil salinity stress; salt-affected soil

Citation: HUANG Cheng, HOU Shengtong, WANG Bao, SONG Yuchuan, Aikeremu ABULATIJIANG, MIN Jiuzhou, SHENG Jiandong, JIANG Ping'an, WANG Ze, CHENG Junhui. 2025. Effects of a combination of biochar and cow manure on soil nutrients and cotton yield in salinized fields. Journal of Arid Land, 17(7): 1014–1026. https://doi.org/10.1007/s40333-025-0054-2; https://cstr.cn/32276.14.JAL.02500542

Introduction

Cotton is one of the most broadly cultivated crops worldwide due to its economic importance (Jans et al., 2021). As the largest cotton-producing country globally, China produces 1.0×10⁷ t of cotton annually (FAO, 2022). In China, more than 80% of the cultivated area and over 90% of cotton yield are contributed by Xinjiang Uygur Autonomous Region (National Bureau of Statistics, 2023a, b). However, cotton yield in Xinjiang is subjected to stress from soil salinity, as more than 30% of farmland is threatened by soil salinization (Luo et al., 2001). With increasing soil salinity stress, cotton is estimated to lose 15%–55% of yield annually (Satir and Berberoglu, 2016). Given that the area of salt-affected soil will increase under future climate change conditions (Eswar et al., 2021), increasing cotton yield in salt-affected soil is vital for maintaining sustainable development of the cotton industry and increasing farmer income.

The adverse effects of soil salinity on cotton yield can be explained through several pathways (Cabot et al., 2014; Zhang et al., 2023). For example, cotton cannot absorb sufficient water from soil when salt content exceeds its tolerance threshold, leading to reduced growth and development (Munns, 2002; Munns et al., 2006). Moreover, high soil salinity decreases the bioavailability of nitrogen, phosphorus, and potassium—three essential elements for cotton growth and yield formation—through ion competition and reduced enzyme activity (Fageria et al., 2011). In addition, soil salinity stress negatively affects cotton yield components, such as reducing density by lowering germination rate (Sharif et al., 2019). Density, in turn, affects boll weight and total boll number through changes in photosynthate allocation (Zhang et al., 2004; Wang et al., 2011).

In salt-affected soil, biochar and animal manure application can increase soil nutrients and crop yields via multiple mechanisms (Biederman and Harpole, 2013; Liu et al., 2023; Su et al., 2024). First, biochar is a carbon-rich product associated with labile organic compounds (Schmidt et al., 2021), whereas manure contains high macronutrient content (Garbowski et al., 2023). Combined application of biochar and animal manure can increase soil fertility by enhancing nutrient supply (Hu et al., 2024). Second, biochar and animal manure decrease soil bulk density and increase soil porosity (Liu et al., 2023; Su et al., 2024). High soil porosity facilitates salt leaching and reduces salt stress (Zong et al., 2023). Finally, the dark color of biochar alters soil thermal dynamics, positively affecting seed germination (Genesio et al., 2012), suggesting that biochar application could increase crop density. In salt-affected soil, biochar and animal manure application can increase yield for many crops, such as wheat (Fouladidorhani et al., 2020), maize (Lashari et al., 2014), and soybean (Zhang et al., 2020). However, it remains unclear whether biochar and animal manure application improves cotton yield, especially in salt-affected soil. In addition, previous studies applied biochar and animal manure either alone or in fixed ratios (Ali et al., 2017; Lebrun et al., 2024), and their combined effects with varying proportions on soil nutrients and cotton yield remain unknown.

To address these knowledge gaps, this study conducted a two-year experiment in a salinized cotton field. Biochar and animal manure were applied alone and in combination at different proportions. By surveying soil salt and nutrients at 0–20 and 20–40 cm depths, as well as yield components in 2023 and 2024, this study aimed to explore three scientific questions. First, how do soil salt and nutrients change when biochar and animal manure are applied alone and mixed in different proportions? Second, are biochar and animal manure applied in different combination proportions superior to those applied alone in terms of cotton yield? Third, among soil salt, nutrients, and cotton yield components, which factors are most sensitive to cotton yield? These questions involve soil–crop interactions in salt-affected soil, and the findings can provide scientific guidance for improving crop yield in salinized fields.

2.1 Study Area

This study was performed in a cotton field (41°09′59′′N, 80°40′43′′E; 1056.3 m a.s.l.) in Wensu County, Xinjiang Uygur Autonomous Region, China, in 2023 and 2024. The study area is characterized by a warm temperate continental arid climate, with abundant solar and thermal resources but low precipitation. The average annual temperature is 13.3°C and average annual precipitation is 139.0 mm (Li et al., 2021). The soil suffers from several limiting factors. First, the soil has high salt stress, as total salinity contents at 0–20 and 20–40 cm depths are both above 6.00 g/kg (Table 1 [TABLE:1]). Second, soil organic matter, available phosphorus, available potassium, and available nitrogen contents are below average values reported for farmland in Xinjiang Uygur Autonomous Region (Jiang et al., 2004; Ma et al., 2022). Third, a compacted clay layer existed at 50–70 cm depth because the soil was reclaimed by adding sand to salinized tidal flat soil in 2020 by local farmers.

Table 1 Background values of soil properties

Note: EC, electrical conductivity; SOM, soil organic matter; AP, available phosphorus; AK, available potassium; AN, available nitrogen; BD, bulk density.

2.2 Experimental Design

Cow manure and biochar can be applied to fields to increase soil fertility and alleviate soil salinity stress and nutrient limitations (Lashari et al., 2014; Gao et al., 2019). Six treatments were applied: control; biochar application alone (10 t/hm²) (BC100%); cow manure application alone (10 t/hm²) (CM100%); 70% biochar (7 t/hm²) combined with 30% cow manure (3 t/hm²) (BC70%+CM30%); 50% biochar (5 t/hm²) combined with 50% cow manure (5 t/hm²) (BC50%+CM50%); and 30% biochar (3 t/hm²) combined with 70% cow manure (7 t/hm²) (BC30%+CM70%). Cow manure and biochar were surface-applied and incorporated into the soil to 35 cm depth by tillage at the end of April, prior to sowing. Each treatment was replicated four times, with 24 experimental plots total. Each plot measured 11.0 m × 9.0 m (99.00 m²).

Biochar was obtained from Xinjiang Henhuijunyang Biotechnology Company in Korla City, Xinjiang Uygur Autonomous Region. The biochar had pH 8.20, and contained 700.00 g/kg organic matter, 8.15 g/kg total nitrogen, 0.60 g/kg total phosphorus, and 13.00 g/kg total potassium. Cow manure was composted and provided by local farmers, containing 446.03 g/kg organic matter, 26.04 g/kg total nitrogen, 2.41 g/kg total phosphorus, and 1.63 g/kg total potassium.

To address low soil permeability caused by the compacted clay layer at 50–70 cm depth, we evenly collected five soil cores (5 cm diameter) per plot to extract 0–80 cm soil, thereby breaking the compacted layer and increasing soil permeability. Other management and fertilization methods were consistent with local farmer practices. The cotton variety was 'Xinluzhong 54'. The planting mode consisted of a single plastic film covering three drip irrigation tubes and six planting rows, with a planting density of 225,000 individuals/hm². Irrigation water was slightly saline (3.5 g/L salinity), with total irrigation amount of 4570 m³/hm² during the cotton growing season.

2.3 Soil Sampling and Analysis

Soil samples from 0–20 and 20–40 cm depths were collected at the end of September when cotton reached the boll opening period, using soil augers with 5 cm diameter (Li et al., 2024b). To avoid effects of soil heterogeneity on nutrient availability, we randomly collected five subsamples from each soil layer in each plot, which were then mixed into a composite sample. A total of 48 composite samples were included (6 treatments × 4 replications/treatment × 2 soil layers/replication). Composite samples were air-dried naturally and sieved through a 2-mm mesh in October before measuring soil nutrients. Soil pH and electrical conductivity were measured in a 1:5 soil-water suspension using a pH meter and conductivity meter. Soil organic matter content was determined via potassium dichromate oxidation with external heating, available phosphorus by molybdenum-antimony anti-colorimetric method, available potassium by flame photometry, and available nitrogen by alkaline hydrolysis diffusion (Bao, 2000).

2.4 Measurement of Cotton Yield

Cotton yield was measured at the end of September when cotton reached the boll opening period. First, a 6.70 m² subplot was designated within each plot as the yield measurement area. To minimize edge effects, the subplot was positioned at least 2.0 m inward from plot boundaries. Cotton density was measured in each subplot, and 10 individuals were randomly selected to measure boll number per plant and single boll weight (Wang et al., 2011; Li et al., 2024b). A total of 240 individuals were selected for cotton yield measurement. Cotton yield was calculated by multiplying density, boll number per plant, and single boll weight (Wang et al., 2011; Li et al., 2024b).

2.5 Statistical Analysis

Two-way analysis of variance (ANOVA) tested main and interaction effects of year and treatment on soil nutrient contents in each soil layer and yield components. When significant main or interaction effects were detected (P<0.050), Fisher's least significant difference (LSD) method was applied for multiple comparisons (Tian et al., 2018). Spearman correlation analysis explored relationships between soil nutrients and cotton yield. Since each treatment had four replications, Spearman correlation was not performed for individual treatments due to limited sample size. Therefore, soil nutrients and cotton yield from all treatments were pooled and analyzed separately by year. Based on Spearman correlation results, random forest modeling distinguished the relative importance of soil nutrients to cotton yield. All analyses were performed in R software (v.4.2.1) (R Development Core Team, 2012). Two-way ANOVA and LSD were conducted with the 'agricolae' package (v.1.3-5.0), while Spearman correlation and random forest modeling used the 'linkET' (v.0.0-7.4) and 'randomForest' (v.4.7-1.1) packages, respectively.

3.1 Effects of Biochar Combined with Cow Manure on Soil pH and Electrical Conductivity

At 0–20 cm depth, year had significant but contrasting effects on soil pH and electrical conductivity (P<0.010). Compared with 2023 treatments, BC70%+CM30% and BC50%+CM50% in 2024 increased soil pH but decreased electrical conductivity (Table 2 [TABLE:2]). Soil pH was significantly affected by year × treatment interaction (P<0.050). All treatments had no significant effects on soil pH in 2023 (P>0.050) but significantly increased soil pH in 2024 (P<0.050). Generally, the highest soil pH (9.63±0.07) and lowest electrical conductivity (161.9±31.8 μS/cm) were both detected under BC50%+CM50% treatment in 2024 (Table 2).

At 20–40 cm depth, soil pH and electrical conductivity were strongly affected only by year (P<0.050; Table 2). On average, soil pH increased from 9.07 (±0.20) in 2023 to 9.39 (±0.24) in 2024, while electrical conductivity decreased from 560.2 (±280.1) μS/cm in 2023 to 319.4 (±159.7) μS/cm in 2024.

Table 2 Effects of biochar combined with cow manure on soil pH and electrical conductivity (EC)

Note: CK, BC100%, CM100%, BC70%+CM30%, BC50%+CM50%, and BC30%+CM70% represent control, biochar application alone (10 t/hm²), cow manure application alone (10 t/hm²), 70% biochar (7 t/hm²) combined with 30% cow manure (3 t/hm²), 50% biochar (5 t/hm²) combined with 50% cow manure (5 t/hm²), and 30% biochar (3 t/hm²) combined with 70% cow manure (7 t/hm²), respectively. Mean±SE. Different lowercase letters indicate significant differences in soil pH and EC among treatments and between years at P<0.050 level.

3.2 Effects of Biochar Combined with Cow Manure on Soil Nutrients

Biochar combined with cow manure had different effects on soil organic matter, available nitrogen, available phosphorus, and available potassium (Fig. 1 [FIGURE:1]). At 0–20 cm depth, soil organic matter and available potassium were strongly affected by treatment (P<0.050). Among all treatments, CM100% produced the greatest soil organic matter (5.50±1.14 g/kg) in 2024 (Fig. 1a) and highest available potassium (67.48±5.18 mg/kg) in 2023 (Fig. 1d). The lowest values of soil organic matter (1.88±0.27 g/kg) and available potassium (42.72±8.25 mg/kg) were detected under BC50%+CM50% treatment in 2024. Available nitrogen was only significantly affected by year (P<0.001). Compared with 2023, all treatments significantly decreased available nitrogen except CM100% and BC30%+CM70% (Fig. 1b). All treatments had no significant effect on available phosphorus in 2023, whereas available phosphorus increased 96% under CM100% treatment in 2024 compared with control (Fig. 1c).

At 20–40 cm depth, soil organic matter and available nitrogen were significantly affected by treatment (P<0.010) and year (P<0.010), respectively. The highest values of soil organic matter and available nitrogen were found under BC70%+CM30% treatment in 2024 and 2023, respectively, which were 2.1 and 1.1 times greater than those under control (Fig. 1e and f). Treatment and year had no significant effects on available phosphorus and available potassium (P>0.050; Fig. 1g and h).

3.3 Effects of Biochar Combined with Cow Manure on Yield Components and Cotton Yield

The number of cotton bolls, single boll weight, density, and cotton yield were strongly affected by year (P<0.001). Compared with 2023, all treatments in 2024 significantly decreased the number of cotton bolls (except BC70%+CM30%) but increased single boll weight, density, and cotton yield (except control and BC70%+CM30% treatments) (Fig. 2 [FIGURE:2]). The number of cotton bolls, single boll weight, and cotton yield were also significantly affected by treatment (P<0.050). The highest cotton yield (5336.63±467.72 kg/hm²) was observed under BC50%+CM50% treatment in 2024, which was 1.9 times greater than that under control (Fig. 2d). Additionally, BC50%+CM50% treatment significantly increased cotton yield, number of cotton bolls, and single boll weight in 2023 (Fig. 2).

3.4 Relationships of Cotton Yield with Soil Nutrients and Yield Components

Spearman correlation analysis revealed that cotton yield was affected by different factors in 2023 and 2024 (Fig. 3 [FIGURE:3]). Cotton yield in 2023 was positively associated with yield components (density and number of cotton bolls) and available soil nutrients (available phosphorus and available potassium) at 0–20 and 20–40 cm depths (Fig. 3a and b). However, cotton yield in 2024 was positively related only to yield components (density, number of cotton bolls, and single boll weight) (Fig. 3c and d). These findings demonstrate that cotton yield in 2023 was controlled by both yield components and soil nutrients, whereas in 2024 it was affected only by yield components.

Random forest modeling further revealed that among yield components, the number of cotton bolls was the most important factor regulating cotton yield in both 2023 and 2024, as it produced the largest increase in mean square error when its true value was used instead of random data (Fig. 4 [FIGURE:4]). Among soil nutrients, available phosphorus at 0–20 cm depth was more important than available potassium at 0–20 and 20–40 cm depths for modifying cotton yield in 2023 (Fig. 4a).

4.1 Contrasting Variations of Soil pH and Electrical Conductivity

Previous studies propose that biochar application can increase or have no significant effect on soil pH depending on soil texture, salinization level, or application amount (Su et al., 2024; Wang et al., 2024), while animal manure decreases soil pH as humic acids buffer alkaline substances (Liu et al., 2023). This study revealed that BC70%+CM30% and BC50%+CM50% treatments significantly increased soil pH at 0–20 cm depth in 2024 (Table 2), consistent with previous pot and field studies (Liu et al., 2022; Iqbal et al., 2024). The highest soil pH under BC50%+CM50% treatment (Table 2) can be explained by two reasons. First, irrigation water used in this study was saline water (3.5 g/L), which can increase soil pH by promoting salt ion accumulation (Baath et al., 2020). Second, both biochar and cow manure contain large amounts of salt ions such as Ca²⁺ and Mg²⁺, leading to relatively high soil pH (Chan et al., 2008; Lashari et al., 2014). High soil pH promotes combination of OH⁻ and cations to form insoluble substances, decreasing electrical conductivity (Sparks et al., 2024), which aligns with our findings that BC50%+CM50% treatment had the highest soil pH but lowest electrical conductivity (Table 2).

4.2 Diversified Responses of Soil Nutrients

Many studies suggest that biochar and animal manure applications increase soil nutrient availability in saline soils (Liu et al., 2020; Schmidt et al., 2021; Li et al., 2024a). This two-year experiment revealed that at 0–20 cm depth, the greatest values of soil organic matter, available phosphorus, and available potassium were observed under CM100% treatment in 2023 and 2024 (Fig. 1a, c, and d), consistent with previous studies (Shakoor et al., 2021; Lebrun et al., 2024). Increased soil organic matter, available phosphorus, and available potassium under CM100% treatment partly resulted from nutrients contained in cow manure (Liu et al., 2020). Additionally, cow manure application can lower soil bulk density and increase soil porosity (Eden et al., 2017), increasing nutrient inputs by promoting microbiome activity and root growth (Liu et al., 2017). Unlike early research by Meki et al. (2022), this study demonstrated that BC50%+CM50% treatment lowered soil organic matter and available potassium contents at 0–20 cm depth in 2024 (Fig. 1a and d). The decrease in soil organic matter and available potassium may have resulted from cotton acquisition, as BC50%+CM50% treatment produced the highest cotton yield in 2024 (Fig. 2d). A recent meta-analysis proposed that in arid areas, animal manure addition has no significant effect on nitrogen availability due to limitations in soil enzyme activity (Liu et al., 2022). This phenomenon was also observed, as all treatments had no apparent effect on available nitrogen in either 2023 or 2024 (Fig. 1c).

BC70%+CM30% treatment also increased soil organic matter and available nitrogen contents at 20–40 cm depth in 2024 (Fig. 2e and f). This can be explained by biochar's ability to increase soil organic matter stability due to its highly porous structure and sorption capacity (Weng et al., 2017; Bai et al., 2019). Increased soil organic matter positively affects soil inorganic nitrogen through ammonium nitrogen adsorption and changes in soil biochemical properties (Gao et al., 2019; Luo et al., 2020), which was confirmed in this study (Fig. 2f). In contrast with soil organic matter and available nitrogen, available phosphorus and available potassium at 20–40 cm depth did not significantly vary among treatments each year (Fig. 2g and h), as available potassium is easily dissolved and leached due to low adsorption affinity (Farrar et al., 2021), whereas phosphorus dynamics are limited in alkaline soil due to low initial content (Khadem et al., 2021).

4.3 Variations of Yield Components and Cotton Yield

Cotton yield is simultaneously affected by the number of cotton bolls, single boll weight, and density (Coyle and Smith, 1997). The number of cotton bolls and single boll weight are constrained by density (Bednarz et al., 2000). In this study, yield components varied conversely between 2023 and 2024, as all treatments in 2024 decreased the number of cotton bolls but increased single boll weight and density relative to 2023 (Fig. 2a–c). In 2023, lower density resulted from greater electrical conductivity (Table 2) because high salinity stress reduces density by lowering germination rate (Sharif et al., 2019). Under lower-density conditions, a greater number of cotton bolls appears due to increased mainstem nodes and monopodial branches (Bednarz et al., 2000). In 2024, higher density can be explained by lower electrical conductivity (Table 2). Under high-density conditions, relatively high single boll weight compensates for relatively low boll number (Bednarz et al., 2000).

It is widely demonstrated that biochar and animal manure application can increase crop yields (Lashari et al., 2014; Palansooriya et al., 2019). This study also revealed that BC50%+CM50% treatment produced the highest cotton yield in 2024 (Fig. 2d), suggesting that in salt-affected soil, biochar and cow manure combined at a 1:1 ratio has the greatest potential to increase cotton yield. The increased yield under BC50%+CM50% treatment can be partly explained by alleviation of soil salinity stress, as biochar application increases soil porosity and decreases bulk density, promoting salt leaching (Wu et al., 2023). Additionally, cow manure application increases soil fertility and promotes cotton growth (Wei et al., 2022).

4.4 Contributions of Soil Nutrients to Cotton Yield

Previous studies demonstrate that moderate density can increase cotton yield and single boll weight (Wang et al., 2011; Zhou et al., 2017) because cotton canopy photosynthetic product is positively related to planting density (Zhang et al., 2004). This phenomenon was observed, as cotton yield was positively associated with density and number of cotton bolls in both 2023 and 2024 (Fig. 3a and b). It is widely proposed that cotton yield linearly increases with available phosphorus when content is below agricultural threshold (Li et al., 2024b). Additionally, cotton yield is constrained by available potassium because cotton has high potassium demand (Lv et al., 2024). These findings were confirmed, as cotton yield was positively associated with available phosphorus and available potassium at 0–20 and 20–40 cm depths in 2023 (Fig. 3a and b), indicating that in salt-affected soil, cotton yield is concurrently constrained by yield components and soil nutrients.

5 Conclusions

This study clearly revealed that in salt-affected soil, biochar and cow manure combination significantly affected soil nutrient availability and cotton yield. Among all treatments and years, BC50%+CM50% treatment had the greatest effect on modifying soil nutrient availability and increasing cotton yield in 2024. Compared with 2023, BC50%+CM50% treatment in 2024 significantly increased soil pH and cotton yield but decreased electrical conductivity, soil organic matter, and available potassium. Short-term field experiments indicated that in salt-affected soil, biochar and cow manure combined at a 1:1 ratio was the best combination for improving cotton yield. Long-term experiments are still needed to explore whether the positive effect of BC50%+CM50% treatment on cotton yield is time-dependent.

Conflict of Interest: The authors declare no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

Acknowledgements: This research was funded by the Key Research and Development Project of Xinjiang Uygur Autonomous Region (2023A02002-2), the National Key Research and Development Program of China (2023YFD1901503), and the Central Guidance Fund for Local Science and Technology Development of Xinjiang Uygur Autonomous Region (ZYYD2024CG03).

Author Contributions: Conceptualization: SHENG Jiandong, JIANG Ping'an; Investigation: HUANG Cheng, HOU Shengtong, WANG Bao; Formal analysis: HUANG Cheng, SONG Yuchuan, Aikeremu ABULATIJIANG, CHENG Junhui; Writing – original draft: HUANG Cheng, MIN Jiuzhou, WANG Ze, CHENG Junhui; Writing – review & editing: HUANG Cheng, CHENG Junhui; Funding acquisition: JIANG Ping'an; Supervision: CHENG Junhui. All authors approved the manuscript.

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