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Journal of Arid Land  2023, Vol. 15 Issue (9): 1067-1083    DOI: 10.1007/s40333-023-0028-1
Research article     
Combination of artificial zeolite and microbial fertilizer to improve mining soils in an arid area of Inner Mongolia, China
LI Wenye1, ZHANG Jianfeng2, SONG Shuangshuang3, LIANG Yao4, SUN Baoping1,*(), WU Yi5, MAO Xiao6, LIN Yachao1
1School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
2China ENFI Engineering Co., Ltd., Beijing 100038, China
3PIESAT Information Technology Co., Ltd., Beijing 100195, China
4Key Laboratory of Deep-Earth Dynamics of Ministry of Natural Resources, Institute of Geology, Chinese Academy of Geological Sciences, Beijing 100037, China
5Shanxi Dadi Minji Ecological Environment Co., Ltd., Beijing Branch, Beijing 100083, China
6Bureau of Agriculture and Rural Affairs, Wangcheng District, Changsha 410211, China
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Restoration of mining soils is important to the vegetation and environment. This study aimed to explore the variations in soil nutrient contents, microbial abundance, and biomass under different gradients of substrate amendments in mining soils to select effective measures. Soil samples were collected from the Bayan Obo mining region in Inner Mongolia Autonomous Region, China. Contents of soil organic matter (SOM), available nitrogen (AN), available phosphorus (AP), available potassium (AK), microbial biomass carbon/microbial biomass nitrogen (MBC/MBN) ratio, biomass, and bacteria, fungi, and actinomycetes abundance were assessed in Agropyron cristatum L. Gaertn., Elymus dahuricus Turcz., and Medicago sativa L. soils with artificial zeolite (AZ) and microbial fertilizer (MF) applied at T0 (0 g/kg), T1 (5 g/kg), T2 (10 g/kg), and T3 (20 g/kg). Redundancy analysis (RDA) and technique for order preference by similarity to ideal solution (TOPSIS) were used to identify the main factors controlling the variation of biomass. Results showed that chemical indices and microbial content of restored soils were far greater than those of control. The application of AZ significantly increases SOM, AN, and AP by 20.27%, 23.61%, and 40.43%, respectively. AZ significantly increased bacteria, fungi, and actinomycetes abundance by 0.63, 3.12, and 1.93 times of control, respectively. RDA indicated that AN, MBC/MBN ratio, and SOM were dominant predictors for biomass across samples with AZ application, explaining 87.6% of the biomass variance. SOM, MBC/MBN ratio, and AK were dominant predictors with MF application, explaining 82.9% of the biomass variance. TOPSIS indicated that T2 was the best dosage and the three plant species could all be used to repair mining soils. AZ and MF application at T2 concentration in the mining soils with M. sativa was found to be the most appropriate measure.

Key wordsamendment      arid area      mining soils      restoration      soil nutrition     
Received: 02 June 2023      Published: 30 September 2023
Corresponding Authors: * SUN Baoping (E-mail:
Cite this article:

LI Wenye, ZHANG Jianfeng, SONG Shuangshuang, LIANG Yao, SUN Baoping, WU Yi, MAO Xiao, LIN Yachao. Combination of artificial zeolite and microbial fertilizer to improve mining soils in an arid area of Inner Mongolia, China. Journal of Arid Land, 2023, 15(9): 1067-1083.

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Fig. 1 Soil nutrients and biomass of different plants with the application of artificial zeolite (AZ, a1-e1) and microbial fertilizer (MF, a2-e2). CK, control; AG, Agropyron cristatum L. Gaertn.; ET, Elymus dahuricus Turcz.; ML, Medicago sativa L.; SOM, soil organic matter; AN, available nitrogen; AP, available phosphorous; AK, available potassium; T0, 0 g/kg; T1, 5 g/kg; T2, 10 g/kg; T3, 20 g/kg. Different lowercase letters within the same treatment indicate significant difference among different amended concentrations of AZ and MF. The red dotted line represents nutrient classification. Bars are standard errors.
Plant Treat-ment Concen-tration
(×106 CFU/g)
(×105 CFU/g)
(×106 CFU/g)
(×106 CFU/g)
(×105 CFU/g)
(×106 CFU/g)
AG T0 0 1.07±0.38b 2.95±0.05b 3.06±0.04c 3.69±0.47a 1.02±0.05b 2.19±0.25b 3.02±0.61a 18.16±0.58a
T1 5 1.14±0.05c 2.81±0.07b 3.25±0.09d 5.50±0.91a 1.03±0.12b 2.14±0.36cd 3.80±0.32b 7.41±0.09b
T2 10 1.17±0.04c 3.23±0.08a 3.20±0.14a 7.87±5.14a 1.08±0.08a 2.16±0.86c 3.66±0.15c 6.25±0.73c
T3 20 1.44±0.03a 3.37±0.17a 3.65±030b 2.72±0.56a 1.07±0.26a 2.22±0.35a 3.71±0.02b 6.97±1.04b
ET T0 0 1.03±0.02a 0.78±0.08a 1.82±0.13a 0.67±0.14b 0.83±0.31d 2.17±1.06c 1.80±0.57c 16.46±0.47a
T1 5 1.22±0.04b 1.68±0.32b 2.18±3.91b 8.71±2.14a 1.14±0.25b 2.22±0.65b 1.93±0.26b 6.63±0.69b
T2 10 1.41±0.49b 3.12±1.49b 2.10±1.60ab 8.58±4.33a 0.93±0.17c 2.24±0.43a 1.62±0.05d 6.54±0.35b
T3 20 1.48±0.14b 2.43±0.64b 2.70±1.35ab 14.02±5.72a 1.46±0.05a 2.15±0.26d 1.45±0.41a 6.44±0.83b
ML T0 0 1.19±0.53ab 2.00±0.13b 1.05±0.05c 1.92±0.28b 1.17±1.02b 2.17±0.52d 1.03±1.05d 10.51±0.27a
T1 5 1.20±0.20b 2.05±1.29b 1.77±4.32bc 2.44±0.23ab 1.09±1.73c 2.40±1.31c 1.23±0.71c 4.31±1.08c
T2 10 1.28±0.74b 4.58±1.58a 2.07±3.74a 1.83±0.15b 0.84±1.51d 2.95±1.27a 1.27±0.32b 5.28±0.24b
T3 20 1.94±0.42a 4.35±1.43ab 2.03±5.68ab 6.68±4.68a 1.51±0.89a 2.52±0.51b 1.47±0.98a 6.00±0.71b
Table 1 Microbial content and microbial biomass carbon/microbial biomass nitrogen (MBC/MBN) ratio with the application of artificial zeolite (AZ) and microbial fertilizer (MF)
Fig. 2 Redundancy analysis (RDA) for the relationship between environmental factors (red lines) with the application of artificial zeolite (AZ; a) and microbial fertilizer (MF; b). AN, available nitrogen; AP, available phosphorous; AK, available potassium; MBC/MBN ratio, microbial biomass carbon/microbial biomass nitrogen ratio; SOM, soil organic matter; CK, control; AG, A. cristatum; ET, E. dahuricus; ML, M. sativa; T0, 0 g/kg; T1, 5 g/kg; T2, 10 g/kg; T3, 20 g/kg.
Statistic Axis 1 Axis 2 Axis 3 Axis 4
Eigenvalue 0.9678 0.0116 0.0203 0.0003
Explained variation (cumulative; %) 96.78 97.94 99.97 100.00
Pseudo-canonical correlation 0.9925 0.8115 0.0000 0.0000
Explained fitted variation (cumulative; %) 98.82 100.00
Table 2 Redundancy analysis (RDA) results between biomass and soil nutrient factors with the application of artificial zeolite
Statistic Axis 1 Axis 2 Axis 3 Axis 4
Eigenvalue 0.8498 0.0093 0.1318 0.0091
Explained variation (cumulative; %) 84.98 85.91 99.09 100.00
Pseudo-canonical correlation 0.9305 0.7083 0.0000 0.0000
Explained fitted variation (cumulative; %) 98.92 100.00
Table 3 RDA analysis results between biomass and soil nutrient factors with the application of microbial fertilizer
Fig. 3 Weight results of various evaluation indicators. MBC/MBN ratio, microbial biomass carbon/microbial biomass nitrogen ratio; SOM, soil organic matter; AN, available nitrogen; AP, available phosphorous; AK, available potassium.
Fig. 4 Euclidean distances of artificial zeolite (AZ; a) and microbial fertilizer (MF; b). AG, A. cristatum; ET, E. dahuricus; ML, M. sativa; T0, 0 g/kg; T1, 5 g/kg; T2, 10 g/kg; T3, 20 g/kg. Dmin, the minimum of distance; Dmax, the maximum of distance.
Fig. 5 Technique for order preference by similarity to ideal solution (TOPSIS) ranking result graph based on entropy weight method. AZ, artificial zeolite; MF, microbial fertilizer; AG, A. cristatum; ET, E. dahuricus; ML, M. sativa; T0, 0 g/kg; T1, 5 g/kg; T2, 10 g/kg; T3, 20 g/kg.
Fig. 6 Schematic diagram of improving mining soils with the application of artificial zeolite (AZ; a) and microbial fertilizer (MF; b). AN, available nitrogen; AP, available phosphorous; AK, available potassium; SOM, soil organic matter.
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