Long-term effects of combined application of biochar and biogas slurry on nitrogen transformation in acidic red soil

doi:10.3969/j.issn.1004-1524.20250738

Acta Agriculturae Zhejiangensis ›› 2026, Vol. 38 ›› Issue (4): 731-744.DOI: 10.3969/j.issn.1004-1524.20250738

• Environmental Science • Previous Articles Next Articles

Long-term effects of combined application of biochar and biogas slurry on nitrogen transformation in acidic red soil

YING Mengfei¹(), GUAN Yilun², JIN Zewen²^,^*(), ZHAO Kun³, PING Lifeng², CHAI Yanjun², LI Yan⁴, SHEN Yue⁵, YAN Jun⁵

¹ Shaoxing Grain and Oil Crops Technology Promotion Center, Shaoxing 312000, China
² Key Laboratory of Recycling and Eco-Treatment of Waste Biomass of Zhejiang Province, School of Environment and Natural Resources, Zhejiang University of Science and Technology, Hangzhou 310023, China
³ College of Information Science and Technology, Zhejiang Shuren University, Hangzhou 310015, China
⁴ Institute of Environment, Resource, Soil and Fertilizer, Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China
⁵ Zhejiang Cultivated Land Quality and Fertilizer Administration Station, Hangzhou 310020, China

Received:2025-12-06 Online:2026-04-25 Published:2026-05-08
Contact: JIN Zewen

Abstract

Abstract:

Soil acidification and low nitrogen use efficiency are key constraints to sustainable agriculture in southern China. A 5-year long-term field experiment with a Chinese cabbage-sweet potato rotation was conducted to systematically explore the effects of combined biochar and biogas slurry application on nitrogen transformation in acidic red soil. Five treatments were set: no fertilizer control (CK), chemical fertilizer alone (C0B0), biogas slurry substituting chemical fertilizer (C0B1), biochar combined with chemical fertilizer (C1B0), and biochar combined with biogas slurry (C1B1). Results showed that combined biochar and biogas slurry application significantly (p<0.05) ameliorated soil acidity. Soil pH value in C1B1 increased from an initial value of 5.44 to 7.13 after 5 years, which was significantly higher than that in C0B0 by 2.05. Compared with CK, urease activity in C1B1 significantly increased by 30.0%, while nitrate reductase and nitrite reductase activities decreased significantly by 35.2% and 36.3%, indicating a shift in the nitrogen cycle from nitrification-denitrification dominance to nitrogen fixation-assimilation dominance. Microbial community analysis showed that C1B1 significantly increased the relative abundance of nitrogen-fixing bacteria but decreased the relative abundance of nitrifying bacteria compared with C0B0. The 5-year average yields of Chinese cabbage and sweet potato in C1B1 were 56.31, 46.17 t·hm^-2, respectively, and the agronomic efficiency of nitrogen (AEN) was 234.4, 220.4 kg·kg^-1, respectively, in the Chinese cabbage season and sweet potato season, which were all significantly higher than those of C0B0. Structural equation modeling identified pH as the core driver regulating the nitrogen cycle, and random forest modeling showed that the pH value of 6.5 was the critical threshold for a sharp increase in AEN. In conclusion, combined biochar and biogas slurry application optimizes nitrogen transformation in acidic red soil through pH-mediated multi-level regulation, which can reduce chemical fertilizer input while ensuring yield, providing a scientific basis for reducing chemical fertilizer application and improving efficiency.

Key words: biochar, biogas slurry, acidic red soil, nitrogen transformation, agronomic efficiency of nitrogen

CLC Number:

YING Mengfei, GUAN Yilun, JIN Zewen, ZHAO Kun, PING Lifeng, CHAI Yanjun, LI Yan, SHEN Yue, YAN Jun. Long-term effects of combined application of biochar and biogas slurry on nitrogen transformation in acidic red soil[J]. Acta Agriculturae Zhejiangensis, 2026, 38(4): 731-744.

Figures/Tables 10

Fig.1 Soil pH value and bulk density under biochar and biogas slurry treatments Bars marked without the same letters indicate significant difference at p<0.05. The same as below.

Fig.2 Contents of soil total nitrogen, ammonium nitrogen, particulate organic nitrogen (PON) and mineral-associated organic nitrogen (MAON) under biochar and biogas slurry treatments

Fig.3 Activities of soil urease, nitrate reductase and nitrite reductase under biochar and biogas slurry treatments

Fig.4 Soil functional genes abundance and microbial relative abundance under biochar and biogas slurry treatments

Table 1 Yield and agronomic efficiency of nitrogen (AEN) of sweet potato under biochar and biogas slurry treatments

处理 Treatment	历年产量r/(t·hm^-2) Yield in each year/(t·hm^-2)						AEN/(kg· kg^-1)
处理 Treatment	2020	2021	2022	2023	2024	平均值Mean	AEN/(kg· kg^-1)
CK	4.38±0.31 c	5.03±0.44 c	4.07±0.56 c	3.61±0.27 c	2.14±0.44 c	3.85±0.38 c	0
C0B0	21.67±2.42 b	22.34±1.34 b	23.09±2.65 b	19.28±1.24 b	15.71±2.39 b	20.42±2.01 b	86.3
C0B1	25.22±3.20 b	23.90±2.21 b	22.28±2.37 b	21.39±2.26 b	16.07±1.73 b	21.77±2.24 b	93.3
C1B0	47.58±3.76 a	46.92±4.32 a	47.05±6.64 a	46.39±4.28 a	42.09±4.32 a	46.00±5.35 a	219.5
C1B1	49.76±5.25 a	46.82±3.36 a	46.40±4.32 a	44.83±5.76 a	43.06±2.28 a	46.17±3.98 a	220.4

Table 2 Yield and agronomic efficiency of nitrogen (AEN) of Chinese cabbage under biochar and biogas slurry treatments

处理 Treatment	历年产量/(t·hm^-2) Yield in each year/(t·hm^-2)						AEN/(kg· kg^-1)
处理 Treatment	2020	2021	2022	2023	2024	平均值Mean	AEN/(kg· kg^-1)
CK	3.16±0.34 c	3.51±0.28 c	2.90±0.25 c	3.67±0.43 c	3.39±0.52 c	3.33±0.46 c	0
C0B0	43.65±3.35 b	36.49±3.56 b	32.86±2.28 b	27.36±2.29 b	20.31±3.34 b	32.13±2.89 b	127.4
C0B1	46.55±4.48 b	41.11±7.21 b	36.72±3.56 b	33.78±4.21 b	25.92±3.25 b	36.82±4.43 b	148.1
C1B0	64.01±5.27 a	58.24±6.25 a	51.31±4.89 a	52.44±3.56 a	45.45±5.56 a	54.29±4.76 a	225.5
C1B1	66.11±6.12 a	60.56±5.73 a	55.26±5.56 a	52.27±6.25 a	47.37±5.23 a	56.31±5.48 a	234.4

Fig.5 Structural equation model of soil pH value under biochar regulation on nitrogen transformation, soil properties and crop yield Ellipses represent observed/latent variables: exogenous driver (biochar), mediators [soil pH value, urease activity, nitrate reductase (NR) activity, (relative) abundance of nitrogen-fixing functional gene nifH, particulate organic nitrogen (PON) content, mineral-associated organic nitrogen (MAON) content], and responses [agronomic efficiency of nitrogen (AEN), crop yield]. Arrows indicate the causal paths between variables. The values on the lines are standardized path coefficients, and the absolute value reflects the strength of the effect. The direction of the arrow represents the direction of the effect [blue arrows are significantly (p<0.05) positive paths, red arrow is significantly negative path].

Fig.6 Partial least squares regression (PLS) analysis of factors influencing crop yield and agronomic efficiency of nitrogen AamoA, Relative abundance of amoA gene; ANR, Nitrate reductase activity; AUr, Urease activity; cPON, Particulate organic nitrogen content; cMAON, Mineral-associated organic nitrogen content; AnifH, Relative abundance of nifH gene. The same as below. Left panel shows PLS variable importance (VIP score), with the red dashed line indicating the VIP=1 threshold (variables with VIP>1 contribute more to model explanation). Right panel shows PLS component score plot.

Fig.7 Important variables identified by random forest model affecting agronomic efficiency of nitrogen (AEN) and their relative importance ${c}_{\mathrm{N}{\mathrm{H}}_{4}^{+}\mathrm{-}\mathrm{N}}$, Ammonium nitrogen content; AamoB, Relative abundance of amoB gene; ANiR, Nitrite reductase activity; BD, Bulk density; cTN, Total nitrogen content. The same as below.Top panel shows the random forest prediction curve illustrating the relationship between soil pH value and agronomic efficiency of nitrogen (AEN). The red dashed line in the top panel indicates the critical threshold of pH value of 6.5, with the left gray area representing the acidic region (pH value<6.5) and the right yellow area representing the neutral-alkaline region (pH value >6.5). The left part of the bottom panel shows the feature importance ranking for agronomic efficiency of nitrogen (determination coefficient of 0.916 1). The right part of the bottom panel shows the feature importance ranking for crop yield (determination coefficient of 0.765 5).

Fig.8 The correlation network diagram of the nitrogen cycling process, enzyme activity, nitrogen forms, and crop yield, agronomic efficiency of nitrogen (AEN) mediated by soil pH value Nodes represent variables related to soil nitrogen transformation. Node size indicates variable importance. Lines represent correlations between variables: blue solid lines for positive correlations (r>0.6), red dashed lines for negative correlations (r<-0.6), with values on lines indicating correlation coefficients.

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Long-term effects of combined application of biochar and biogas slurry on nitrogen transformation in acidic red soil

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