Co-incorporating green manure and crop straw increases crop productivity and improves soil quality with low greenhouse-gas emissions in a crop rotation

In a nine-year field experiment in a wheat-maize-sunflower cropping system in Hetao Irrigation Area,Inner Mongolia,China,organic amendments applied as straw,manure,green manure,and the combination of green manure and straw increased wheat and maize yield,soil aggregate stability,and soil microbial activity in comparison with chemical fertilizer,without changing greenhouse gas emission intensity.

Multivariate Approach to Characterizing Soil Quality of Gabonese’s Ferralitic Soils

Assessing soil quality is essential for crop management and soil temporal changes. The present study aims to evaluate soil quality in the Ferralitic soils context countrywide. This assessment was done using multivariate soil quality indice (SQI) models, such as additive quality index (AQI), weighted quality indexes (WQIadd and WQIcom) and Nemoro quality index (NQI), applied to two approaches of indicator selection: total data set (TDS) and minimum data set (MDS). Physical and chemical soil indicators were extracted from the ORSTOM’s reports resulting from a sampling campaign in different provinces of Gabon. The TDS approach shows soil quality status according to eleven soil indicators extracted from the analysis of 1,059 samples from arable soil layer (0 - 30 cm depth). The results indicated that 87% of all provinces presented a very low soil quality (Q5) whatever the model. Among soil indicators, exchangeable K+ and Mg2+, bulk density and C/N ratio were retained in MDS, using principal component analysis (PCA). In the MDS approach, 50 to 63% of provinces had low soil quality grades with AQI, WQIadd and NQI, whereas the total was observed with WQIcom. Only 25% of provinces had medium soil quality grades with AQI and NQI models, while 12.5% (NQI) and 25% (AQI) presented high quality grades. Robust statistical analyses confirmed the accuracy and validation (0.80 r P ≤ 0.016) of AQI, WQIadd and NQI into the TDS and MDS approaches. The same sensitivity index value (1.53) was obtained with AQI and WQIadd. However, WQIadd was chosen as the best SQI model, according to its high linear regression value (R2 = 0.82) between TDS and MDS. This study has important implications in decision-making on monitoring, evaluation and sustainable management of Gabonese soils in a pedoclimatic context unfavorable to plant growth.

Assessment of Agricultural Soil Quality Indices Using Mechanistic Models

Assessing soil quality is a critical strategy for diagnosing soil status and anticipating concerns in land use systems for agricultural sustainability. In this study, two soil quality assessment indices, the Integrated Quality Index (IQI) and Nemoro Quality Index (NQI), were employed using two indicator selection methods: Total Data Set (TDS) and Minimum Data Set (MDS), focusing on agricultural fields in Golestan province, Iran. A total of 89 soil samples were collected and analyzed for particle size distribution, organic carbon, calcium carbonate equivalent (CCE), electrical conductivity (EC), pH, and plant-essential nutrients, including nitrogen, phosphorus, potassium, zinc, copper, manganese, and iron. Principal component analysis (PCA) was used to extract MDS from TDS, and geostatistical adaptation and correlation analyses were performed to determine the optimal soil quality evaluation index. Our results show that the exponential model better suits the spatial structure of soil quality indicators (IQIMDS: 0.955). Conformity and correlation analyses indicate that the IQI index outperformed the NQI index in estimating soil quality. The superiority of the TDS technique over the MDS technique in terms of accuracy (IQITDSs kappa: 0.155). Linear relationships between different methods showed a higher correlation coefficient (R2 = 0.43) through the application of IQI. This study suggests the use of IQIMDS to provide a reliable measurement that is particularly useful in assessing the quality of agricultural soil.

Soil quality assessment for desertification based on multi-indicators with the best-worst method in a semi-arid ecosystem

Since there are some signs of land degradation and desertification showing how soil sustainability is threatened, it is crucial to create a soil quality index(SQI) model in the semi-arid ?orum Basin, situated between the Black Sea and Anatolia Region, Central Turkey. The primary aims of the study are:(1) to determine SQI values of the micro-basin in terms of land degradation and desertification.Moreover, the best-worst method(BWM) was used to determine the weighting score for each parameter;(2) to produce the soils' spatial distribution by utilizing different geostatistical models and GIS(geographic information system) techniques;and(3) to validate the obtained SQI values with biomass reflectance values. Therefore, the relationship of RE-OSAVI(red-edge optimized soil-adjusted vegetation index) and NDVI(normalized difference vegetation index) generated from Sentinel-2A satellite images at different time series with soil quality was examined. Results showed that SQI values were high in the areas that had almost a flat and slight slope. Moreover, the areas with high clay content and thick soil depth did not have salinity problems, and were generally distributed in the middle parts of the basin. However, the areas with a high slope, poor vegetation, high sand content, and low water holding capacity had low SQI values.Furthermore, a statistically high positive correlation of RE-OSAVI and NDVI indices with soil quality was found, and NDVI had the highest correlative value for June(R~2=0.802) compared with RE-OSAVI.

A new hybrid approach to assessing soil quality using neutrosophic fuzzy-AHP and support vector machine algorithm in sub-humid ecosystem

Soil quality determination and estimation is an important issue not only for terrestrial ecosystems but also for sustainable management of soils.In this study,soil quality was determined by linear and nonlinear standard scoring function methods integrated with a neutrosophic fuzzy analytic hierarchy process in the micro catchment.In addition,soil quality values were estimated using a support vector machine(SVM)in machine learning algorithms.In order to generate spatial distribution maps of soil quality indice values,different interpolation methods were evaluated to detect the most suitable semivariogram model.While the soil quality index values obtained by the linear method were determined between 0.458-0.717,the soil quality index with the nonlinear method showed variability at the levels of 0.433-0.651.There was no statistical difference between the two methods,and they were determined to be similar.In the estimation of soil quality with SVM,the normalized root means square error(NRMSE)values obtained in the linear and nonlinear method estimation were determined as 0.057 and 0.047,respectively.The spherical model of simple kriging was determined as the interpolation method with the lowest RMSE value in the actual and predicted values of the linear method while,in the nonlinear method,the lowest error in the distribution maps was determined with exponential of the simple kriging.

Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around.Hence,the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield.In present decade,the application of deep learning models in many fields of research has created greater impact.The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model,leads to the incorporation of deep learning method to predict the soil quality.With that concern,this paper proposes a novel model called Improved Soil Quality Prediction Model using Deep Learning(ISQP-DL).The work considers the chemical,physical and biological factors of soil in particular area to estimate the soil quality.Firstly,pH rating of soil samples has been collected from the soil testing laboratory from which the acidic range has been categorized through soil test and the same data has been taken as input to the Deep Neural Network Regression(DNNR)model.Secondly,soil nutrient data has been given as second input to the DNNR model.By utilizing this data set,the DNNR method is used to evaluate the fertility rate by which the soil quality has been estimated.For training and testing,the model uses Deep Neural Network Regression(DNNR),by utilizing the dataset.The results show that the proposed model is effective for SQP(Soil Quality Prediction Model)with efficient good fitting and generality is enhanced with input features with higher rate of classification accuracy.The results show that the proposed model achieves 96.7%of accuracy rate compared with existing models.

Soil Organic Carbon Stock and Soil Quality under Four Major Agroecosystems in the Eastern Flank of Mount Bambouto (West-Cameroon)

Assessing soil organic carbon stock (SOCS) and soil quality (SQ) helps design better agricultural practices to improve environmental sustainability and productivity. The purpose of the study is to assess SOCS and soil quality SQ in the main agroecosystems (AES) of the eastern flank of Mount Bambouto (West, Cameroon). Using multiple statistics tests and principal component analysis (PCA), SOCS and Soil Quality Index (SQI) were computed for each AES. SOCS and SQI were computed based on soil chemical properties and analysis of variance. Topsoil samples (0 - 30 cm) were collected in a different AES and analyzed in the laboratory. The four AES identified and selected are cultivated land (CL), forest areas (FA), mixed areas (MA), and bush areas (BA). Further, multiple comparison tests were used to compare soils from different AES. PCA was used to select the most appropriate indicators that control SOCS and SQ. Several soil properties showed high to very high coefficient of variation within the AES. Organic matter (OM) was significantly high in FA. SOCS and SQ differ significantly (p = 0.000) between the AES. The study further indicates that the main variables controlling SQ within the eastern flank of Mount Bambouto are OM, pHw, N, C/N, and CEC. While the main soil parameters controlling SOCS are OM, OC, BD, C/N, S, and pHKCl.

Effects of Different Cropping Systems on Soil Quality

[Objective] The aim was to explore the soil properties change in the process of field crops into greenhouse vegetables and their possible adverse effects on the environment.[Method] Fertilization,irrigation,crop growth conditions and soil quality changes in the major cropping systems（greenhouse monoculture,greenhouse rotation and open field rotation）in Chongming Island,Shanghai were investigated from 2007 to 2009.[Result] Different cropping systems significantly affected soil quality.Soil organic carbon,mineral nitrogen,available phosphorus and exchangeable potassium content increased in greenhouse cultivation compared to open field rotation due to excessive application of irrigation and fertilizers.Soil pH values decreased by 0.6 and 0.4 in the greenhouse monoculture and greenhouse rotation,respectively,while did not significantly change in open field rotation.Meanwhile,greenhouse cultivation significantly increased soil EC,and NO-3 and Cl-contents,which showed an increasing trend with the planting years increase.However,the salt content changes were not significant in open field rotation.[Conclusion] High cropping index,excessive fertilizer input and inappropriate fertilization and irrigation resulted in greenhouse soil quality degradation due to weak farmer＇s skill and local extension services.

Soil Quality Assessment of Acid Sulfate Paddy Soils with Different Productivities in Guangdong Province,China

Land conversion is considered an effective measure to ensure national food security in China, but little information is available on the quality of low productivity soils, in particular those in acid sulfate soil regions. In our study, acid sulfate paddy soils were divided into soils with high, medium and low levels based on local rice productivity, and 60 soil samples were collected for analysis. Twenty soil variables including physical, chemical and biochemical properties were determined. Those variables that were significantly different between the high, medium and low productivity soils were selected for principal component analysis, and microbial biomass carbon （MBC）, total nitrogen （TN）, available silicon （ASi）, pH and available zinc （AZn） were retained in the minimum data set （MDS）. After scoring the MDS variables, they were integrated to calculate a soil quality index （SQI）, and the high, medium and low productivity paddy soils received mean SQI scores of 0.95, 0.83 and 0.60, respectively. Low productivity paddy soils showed worse soil quality, and a large discrepancy was observed between the low and high productivity paddy soils. Lower MBC, TN, ASi, pH and available K （AK） were considered as the primary limiting factors. Additionally, all the soil samples collected were rich in available P and AZn, but deficient in AK and ASi. The results suggest that soil AK and ASi deficiencies were the main limiting factors for all the studied acid sulfate paddy soil regions. The application of K and Si on a national basis and other sustainable management approaches are suggested to improve rice productivity, especially for low productivity paddy soils. Our results indicated that there is a large potential for increasing productivity and producing more cereals in acid sulfate paddy soil regions.

Effects of Different Tillage and Mulching Modes on Tobacco Output Value and Soil Quality

Based on three years of long-term fixed-site field trial, the effects of differ- ent tillage and mulching modes on the yield and output value of tobacco and soil quality were investigated. The results showed that the yield and output value of to- bacco in tillage treatment were improved by 22.72 % and 37.23 % compared with non-tillage treatment, respectively; the yield and output value of tobacco in rotation treatment were improved by 1.83% and 19.41% compared with continuous cropping treatment, respectively; the yield and output value of tobacco in straw mulching treatment were improved by 3.55% and 2.4% compared with non-straw mulching treatment, respectively, which indicated that tillage, rotation and straw mulching could improve the yield and output value of tobacco to a certain extent; especially, the yield and output value of tobacco increased significantly after plowing under rotation conditions. The contents of available phosphorus （AP）, alkali-hydrolyzable nitrogen （AN）, organic matter （OM）, total nitrogen （TN） and total phosphorus （TP） in non- tillage treatment were 35.14%, 9.92%, 9.57%, 4.40% and 34.16% higher compared with tillage treatment; especially, under non-tillage conditions, soil pH and contents of available potassium （AK）, AP, AN,OM,TN,TP and total potassium （TK） in continu- ous cropping field were 2.01%, 48.68%, 73.09%, 11.45%, 7.71%, 7.31%, 47.68% and 11.78% higher compared with rotation field, indicating that non-tillage treatment and continuous cropping could improve the total content and available content of organic matter, nitrogen and phosphorus. Therefore, from the perspective of soil fer- tility improvement and sustainable tobacco production, continuous cropping under non-tillage conditions might be the most appropriate cropping pattern for local soil fertility improvement; aiming at improving the yield and output value of tobacco, green manure-tobacco→, green manure/wheat/maize→green manure-tobacco ro- tation might be the most appropriate cropping pattern.

Characterization of Soil Quality Under Vegetable Production Along an Urban-Rural Gradient

Human activity and urbanization result in urban-rural environmental gradients. Understanding effect of the gradients on soil properties is necessary for management of the soils around urban areas. In this study, soil quality of some vegetable fields was characterized along an urban-rural gradient in Shaoxing County, Zhejiang Province. Fifteen soil physical and chemical properties were evaluated by using principal component analysis.Results showed that there was a great variation in the soil quality along the gradient. From rural to urban zones, soil organic matter, water-stable aggregates, cation exchangeable capacity (CEC), total N and P, and available K increased, whereas soil pH value decreased. In addition, Pb, Cu, Ni, Co, Zn and Cr in the soils tended to be accumulated toward the urban zone. Sequential chemical extraction showed that mobility of all the heavy metals in the soils tended to increase from the rural to the urban zones. The variation of soil properties accounted for by the first principal component was significantly explained by the difference in application rates of municipal wastes.

Application of Projection Pursuit Evaluation Model Based on Real-Coded Accelerating Genetic Algorithm in Evaluating Wetland Soil Quality Variations in the Sanjiang Plain, China

A new technique of dimension reduction named projection pursuit is applied to model and evaluatewetland soil quality variations in the Sanjiang Plain, Helongjiang Province, China. By adopting the im-proved real-coded accelerating genetic algorithm (RAGA), the projection direction is optimized and multi-dimensional indexes are converted into low-dimensional space. Classification of wetland soils and evaluationof wetland soil quality variations are realized by pursuing optimum projection direction and projection func-tion value. Therefore, by adopting this new method, any possible human interference can be avoided andsound results can be achieved in researching quality changes and classification of wetland soils.

Comparing the soil quality changes of different land uses determined by two quantitative methods

Soil quality is one of the most important environmental factors in sustaining the global biosphere and developing sustainable agricultural practices. A study was initiated in Wolong Nature Reserve, Sichuan Province, China to elucidate the soil quality changes of natural secondary succession, forest planting and agricultural practices after deforestation in the humid mountainous region. The soil qualities of six land use types (natural forestland, grassland, shrub land, secondary forestland, cultivated land and reforested land) were compared using two quantitative methods: the integrated soil quality index(QI) and soil deterioration index(DI). The QI values of natural forestland, grassland, shrub land, secondary forestland, cultivated land, reforested land were 0.8039, 0.3277, 0.9127, 0.6881, 0.0285 and 0.3183, respectively. The DI values were 0%, -14%, 12%, 1%, -26% and -18% respectively. Both indexes suggested that shrub land can restore soil properties. To compare the two methods more directly, a deduced index QI′ based on QI value was developed. The results showed that DI and QI′had a very high linear correlation coefficient (r=0.9775) despite the values were different. Both methods were efficient in evaluating the soil quality levels and DI was a more simple way in soil quality assessment, while QI could show more ecological meanings.

Chemical and Microbiological Parameters of Paddy Soil Quality as Affected by Different Nutrient and Water Regimes

A field experiment was conducted from 1999 to 2002 to compare and evaluate the effects of nutrient and water regimes on paddy soil quality by investigating soil chemical and microbiological parameters. Four nutrient regimes, a control, chemical fertilizers only (CF), chemical fertilizers with swine manure (SM), and chemical fertilizers with wheat straw (WS), and two soil moisture regimes, continuous waterlogging (CWL) and alternate wetting and drying (AWD), were investigated. With SM and WS total organic carbon and total nitrogen in the paddy soil were significantly higher (P < 0.05) than those with CF. A similar effect for organic amendments was observed in the soil light fraction organic C (LFOC), water-soluble carbohydrates (WSC), and water-soluble organic C (WSOC). CWL, in particular when swine manure was incorporated into the paddy soil, markedly decreased soil redox potential (Eh) and increased total active reducing substances (ARS). Meanwhile, as compared to CF, SM and WS significantly (P < 0.05) increased soil microbial biomass C (MBC) and mineralizable carbon, with differences in AWD being higher than CWL. In addition, SM and WS treatments significantly (P < 0.05) improved rice above-ground biomass and grain yield, with AWD being greater than CWL. Thus, for ecologically sustainable agricultural management of paddy soils, long-term waterlogging should be avoided when organic manure was incorporated into paddy soil.

A practical soil management to improve soil quality by applying mineral organic fertilizer

Heavy use of chemical fertilizer causes increasing soil and environmental crisis, and the use of organic fertilizer increases obvious in recent years. In this study,mineral organic fertilizer(MOF) and compound fertilizer(CF) were applied in amaranth culture to explore the effects of these two kinds of fertilizers on soil quality and the potential function for CO_2 fixation. Some soil parameters were tested, e.g. p H value, organic carbon content, microbial biomass, urease activity, and available potassium content. In addition, some parameters of soil infiltration water were also determined, such as p H and HCO_3^- concentration. Experimental results showed that MOF improved soil quality and amaranth biomass and increased possible soil carbon sink.On the contrary, the utilization of CF worsened soil quality and made the soil acidize. These results suggested that MOF can partially replace CF to improve plant growth, soil quality and possible CO_2 sink.

Changes in and evaluation of surface soil quality in Populus×xiaohei shelterbelts in midwestern Heilongjiang province,China

To examine changes in surface soil quality over time in Populus×xiaohei shelterbelts,we collected soil samples from five shelterbelts of different ages and also from former cropland left fallow for 25 years.Twenty-one surface soil(0–20 cm)properties were measured,and variation in soil quality was assessed using one-way ANOVAs and multiple comparison tests.Based on this analysis,16 soil indexes were used in a model evaluating soil quality,with each index given weight as determined by the correlation coefficient.Compared with the control,the postmature forest had greater soil moisture content but lower bulk density(P<0.05).The mature forest also had higher soil pH,total organic carbon,alkali-hydrolyzed nitrogen,available phosphorus,and biomass nitrogen content,but reduced nitrate-nitrogen and total phosphorus content than the control(P<0.05).Total porosity was highly positively correlated with aeration,nitrate-nitrogen,alkali-hydrolyzed nitrogen,available phosphorus,microbial biomass carbon and microbial biomass nitrogen.Soil total organic carbon,ammonium nitrogen,nitrate-nitrogen,alkali-hydrolyzed nitrogen,total nitrogen,available phosphorus,microbial biomass carbon and microbial biomass nitrogen were all strongly correlated.In the soil quality evaluation model,total organic carbon was assigned the highest weight and total potassium content the lowest.The soil quality index was lowest in the near-mature forest and greatest in the postmature forest.Generally,soil quality in P opulus×xiaohei shelterbelts varied with age and was higher in the 10–20 cm versus 0–10 cm soil layer.After a single forest generation,surface soil quality was significantly improved.

The effects of crop rotation combinations on the soil quality of old apple orchard

This study investigated the effects of six crop rotation combinations on the soil quality of old apple orchard and seedling growth of Malus hupehensis Rehd.(apple rootstock) under pot conditions. The inhibitory effects of crops such as Allium fistulosum, Brassica juncea, and Triticum aestivum on four species of Fusarium were observed and compared in six treatments. These were continuous cropping(CK), fumigation with the methyl bromide(FM), rotating A. fistulosum only(R1), rotating A. fistulosum and T. aestivum(R2), rotating A. fistulosum, B. juncea, and T. aestivum(R3), and fallow(FC) in a year. The results showed that the biomass of Malus hupehensis Rehd. seedlings increased significantly. The root length increased and the root architecture was optimized. The respiration rate of the root system was increased by about 1 time after rotation. The treatments of R1, R2, R3, and FC increased bacterial count by 232.17%, 96.04%, 316.21%, and 60.02%, respectively. However, the fungi were reduced in varying degrees and bacteria/fungi ratio was increased by 5–10 times. The enzyme activities, p H, and organic matter were increased, but soil bulk density was decreased. Phenolic acids such as phloridzin was decreased significantly. The copy number of four Fusarium species declined by 85.59%, 74.94%, 69.68%, and 54.41% after rotating three different crops(R3 treatment). The root volatiles of three plants inhibited mycelial growth and spore germination of four Fusarium species.

Co-application of compost or inorganic NPK fertilizer with biochar influences soil quality,grain yield and net income of rice

Most agricultural soils in sub-Saharan Africa are degraded,compromising the grain yield of rice and farmers return on investment.A 3-year field study was undertaken to explore the effect of the application of compost or inorganic NPK fertilizer applied alone or in combination with biochar on soil quality,grain yield of rice and net income.The five treatments were laid out using a randomized complete block design with four replications.The treatments were applied to supply approximately 75 kg N ha–1.The best fertilizer input was compost+biochar which resulted in the greatest improvement in soil physico-chemical properties by reducing bulk density and increasing porosity and moisture retention,organic matter content,percent nitrogen,available phosphorus and cation exchange capacity.Apart from treatment with inorganic fertilizer alone,treated soils showed a decrease in pH.Bacterial and fungal counts and basal respiration decreased in soils in the following order:compost+biochar>compost only>inorganic NPK fertilizer+biochar>inorganic NPK fertilizer>control.The increase in pooled grain yield and net income in response to treatment followed the order:compost+biochar>NPK+biochar>NPK>compost>control.The findings suggest that the use of compost or NPK alone might improve soil quality and increase grain yield and net income,but it is greatly recommended to co-apply these fertilisers with biochar.

Impact of sand burial on maize(Zea mays L.)productivity and soil quality in Horqin sandy cropland,Inner Mongolia,China

Croplands are often suffering from sand burial in dry regions of northern China. For studying this phenomenon, we carried out a case study of field experiment including four sand burial levels, i.e. shallow （1-3 cm）, moderate （8-12 cm） and deep （15-20 cm） sand burials, and no sand burial （control, CK）, in a typical agro-pastoral transitional zone in Naiman Banner of eastern Inner Mongolia. The aim of this study was to assess the impacts of sand burial on maize （Zea rnays L.） productivity and the soil quality along a gradient of burial depths. Results showed that there was a strong negative effect of sand burial on maize productivity and soil quality, which significantly declined （P〈0.05） under moderate and deep sand burial treatments. In comparison with the CK, the maize yield and above-ground biomass reduced by 47.41% and 39.47%, respectively. The soil silt and clay, soil water, soil organic carbon and total nitrogen contents under deep sand burial decreased by 67.85%, 40.32%, 86.52% and 82.11%, respectively, while microbial biomass carbon, microbial abundance and enzyme activity decreased by 89.78%, 42.28%-79.66% and 69.51%-97.71%, respectively. There was no significant effect on crop productivity and soil quality with shallow sand burial treatment. The correlations analysis showed that there was significant positive correlations of both maize yield and above-ground biomass with soil silt and clay, soil organic carbon and total nitrogen contents, pH, electrical conductivity, soil water content, microbial abundance and biomass and all tested soil enzyme activities. Stepwise regression analysis indicated that soil water and total nitrogen contents, urease, cellobiohydrolase and peroxidase activities were key determining factors for maize productivity. This combination of factors explains reason of the decreased maize productivity with deep sand burial. We found that degradation of cropland as a result of sand burial changed soil physical-chemical properties and soil enzyme activities in the plow layer, and decreased overall maize productivity. Furthermore, decreased soil enzyme activity was a better indicator to predict sandy cropland degradation.

Effects of mushroom waste on improvement of reclaimed soil qualityin coal mining areas

Restoring soil quality is the main evaluation norm of the reclamation. In order to reveal the effects of mushroom waste on the quality improvement of reclaimed soil in coal mining areas, the physical, chemical and microbial characteristics of soil are studied. The results show clear improvement in the soil after using mushroom waste. Because of human cultivation and fertilization, cultivated soil after reclamation exhibits high comprehensive quality and the index of quality of surface soil reaches 0.64 and 0.73. The average index of surface soil quality is as high as 0.52 and 0.54. In comparison, the quality of reclaimed soil of forest land is low, with average index of 0.40. The effects of mushroom waste are mainly on the surface soil in the first 2 years after the application. After that period, with the decomposition of mushroom waste, soil quality index tends to be the same as the original soil. The quality of surface soil is higher than that of subsoil, especially after the application of mushroom waste, at which point the soil quality reaches a peak at about 15 cm. Cultivated soil after reclamation has great variance in quality, after the coefficient of 24.74%. Mushroom waste can reduce such variation, particularly with long-term use. The variance efficient falls to 3.59% after 3-year application.