High concentrations of salt ions in salinized soils not only destroy soil structure, but also inhibit crop growth. Straw and straw-derived biochar have great potential in improving soil structure, reducing soil salinity, improving soil environment, and alleviating salt stress. However, the effects and mechanisms of exogenous addition of different carbon sources on the aggregate structure and microbial community of soils with different salinization degrees in cotton fields as well as the antioxidant defense system of cotton are still unclear. In this column experiment since 15 March, 2023, three soil salt contents (1.5 (S1), 5 (S2), and 10 (S3) g/kg) and five carbon treatments (straw incorporation: 6 t/hm2 (C1), 12 t/hm2 (C2); biochar incorporation: 2.25 t/hm2 (B1), 4.5 t/hm2 (B2); CK: no straw and biochar incorporation) were designed. Then, the effects of straw and biochar incorporation on the particle size distribution of soil aggregates, bacterial and fungal communities, and cotton leaf antioxidant system in S1, S2, and S3 soils were explored. The results showed that straw and biochar incorporation, especially B2, significantly reduced the salt content of S1, S2, and S3 soils, but increased the proportion of macroaggregates by 7.01%–13.12%, 5.03%–10.24%, and 4.16%–8.31%, respectively, compared with those of CK. Straw and biochar incorporation, especially C2, increased the abundances of Actinobacteria, Acidobacteria, and Enterobacteriaceae, but decreased that of Proteobacteria, compared with CK. Besides, straw and biochar incorporation significantly increased the superoxide dismutase (SOD) and catalase (CAT) activities in salt-stressed cotton leaves, and decreased the malondialdehyde (MDA) content and peroxidase (POD) activity, compared with CK. It should be noted that the alleviating effect of straw and biochar incorporation on salt stress gradually decreased with the growth of cotton and the increase of soil salinity. In summary, straw and biochar incorporation could significantly reduce the salt content of salinized soils, increase the proportion of soil macroaggregates and microbial diversity, and alleviate the salt stress in cotton. This study will provide a scientific basis for the improvement and utilization of salinized soils.

The remote sensing-based estimation of the vertical attenuation coefficient K is of great significance to increase the accuracy of the estimation of crop canopy nitrogen vertical distribution by remote sensing technology. However, the multiple-angle information is susceptible to interference from specular reflection, which greatly limits the accuracy and stability of K estimation. In this research, the cotton canopy multiple-angle spectrum and polarization were acquired. Then, the spectral reflectance in the red- and blue-edge regions were combined to construct multiple-angle vegetation indices (MAVIs) using diffuse reflection component and total reflectance separately, and the MAVIs were used to estimate K. The estimated K was used to invert the nitrogen content of different vertical layers (upper, middle, and lower layers) of cotton canopy. Finally, the inversion results were compared with the inverted nitrogen content by the constructed multi-angle vegetative indices. The results showed that removing the specular reflection component from the total reflectance significantly increased the K estimation accuracy. The K estimation accuracy of MAVIs was higher than that of single-angle vegetation indices. Among the MAVIs, MNDVIR-B (-30,45,45,45,0) had the highest K estimation accuracy, and the R2 for the different growth season was in the range of 0.816-0.871. The estimated K by the MNDVIR-B (-30,45,45,45,0) accurately inverted the nitrogen content of different vertical layers of cotton canopy, which was significantly higher than the R2 of the estimation of different-layer nitrogen directly using the MAVIs. This study will provide a new method for accurately monitoring the vertical nitrogen status of crop canopy.

•Soil TN estimation accuracy using vis-NIR spectra is higher than pXRF spectra.•Feature selection & geographical stratification improve soil TN estimation accuracy.•CARS is the optimal feature selection method for multi-sensor data fusion models.•SO-PLS fusion method increases model accuracy by fully using multiple sensor data. Soil TN estimation accuracy using vis-NIR spectra is higher than pXRF spectra. Feature selection & geographical stratification improve soil TN estimation accuracy. CARS is the optimal feature selection method for multi-sensor data fusion models. SO-PLS fusion method increases model accuracy by fully using multiple sensor data.

Timely and accurate estimation of cotton seedling emergence rate is of great significance to cotton production. This study explored the feasibility of drone-based remote sensing in monitoring cotton seedling emergence. The visible and multispectral images of cotton seedlings with 2 - 4 leaves in 30 plots were synchronously obtained by drones. The acquired images included cotton seedlings, bare soil, mulching films, and PE drip tapes. After constructing 17 visible VIs and 14 multispectral VIs, three strategies were used to separate cotton seedlings from the images: (1) Otsu’s thresholding was performed on each vegetation index (VI); (2) Key VIs were extracted based on results of (1), and the Otsu-intersection method and three machine learning methods were used to classify cotton seedlings, bare soil, mulching films, and PE drip tapes in the images; (3) Machine learning models were constructed using all VIs and validated. Finally, the models constructed based on two modeling strategies [Otsu-intersection (OI) and machine learning (Support Vector Machine (SVM), Random Forest (RF), and K-nearest neighbor (KNN)] showed a higher accuracy. Therefore, these models were selected to estimate cotton seedling emergence rate, and the estimates were compared with the manually measured emergence rate. The results showed that multispectral VIs, especially NDVI, RVI, SAVI, EVI2, OSAVI, and MCARI, had higher crop seedling extraction accuracy than visible VIs. After fusing all VIs or key VIs extracted based on Otsu’s thresholding, the binary image purity was greatly improved. Among the fusion methods, the Key VIs-OI and All VIs-KNN methods yielded less noises and small errors, with a RMSE (root mean squared error) as low as 2.69% and a MAE (mean absolute error) as low as 2.15%. Therefore, fusing multiple VIs can increase crop image segmentation accuracy. This study provides a new method for rapidly monitoring crop seedling emergence rate in the field, which is of great significance for the development of modern agriculture.

An accurate understanding of the structure of spatial correlation networks of land use carbon emissions (LUCEs) and carbon balance zoning plays a guiding role in promoting regional emission reductions and achieving high-quality coordinated development. In this study, 42 counties in the Tarim River Basin from 2002 to 2022 were chosen as samples (Corps cities were excluded due to missing statistics). The LUCE spatial correlation network characteristics and carbon balance zoning were analyzed by using the Ecological Support Coefficient (ESC), Social Network Analysis (SNA), and Spatial Clustering Data Analysis (SCDA), and a targeted optimization strategy was proposed for each zone. The results of the study indicate the following: (1) The LUCEs showed an overall upward trend, but the increase in LUCEs gradually slowed down, presenting a spatial characteristic of “high in the mid-north and low at the edges”. In addition, the ESC showed an overall decreasing trend, with a spatial characteristic opposite to that of the LUCEs. (2) With an increasingly close spatial LUCE correlation network in the Tarim River Basin, the network structure presented better accessibility and stability, but the individual network characteristics differed significantly. Aksu City, Korla City, Bachu County, Shache County, Hotan City, and Kuqa City, which were at the center of the network, displayed a remarkable ability to control and master the network correlation. (3) Based on the carbon balance analysis, the counties were subdivided into six carbon balance functional zones and targeted synergistic emission reduction strategies were proposed for each zone to promote fair and efficient low-carbon transformational development among the regions.

To clarify the effects of straw return and biochar application on the amelioration of soils with different salinity levels and cotton growth, in this soil column simulation test, straw and biochar were applied to soils with different salinity levels (1.5 (S1), 5 (S2) and 10 (S3) g/kg), with application rates equal to the same amount of carbon (two carbon levels: 6 t/hm 2 of straw (C1) = 2.25 t/hm 2 of biochar (B1); 12 t/hm 2 of straw (C2) = 4.5 t/hm 2 of biochar (B2)).Then, changes in soil physicochemical properties and cotton physiology were determined.The results showed that straw return and biochar application reduced soil salinity at S1, S2, and S3 levels.Besides, both of them increased soil water, total nitrogen, organic matter, available phosphorus, and available potassium contents, but there was no difference between S3 soil and S1 soil and between S3 soil and S2 soil (p > 0.05).Straw return and biochar application also increased chlorophyll and soluble sugar contents in cotton leaves (p < 0.05), and decreased the relative conductivity and malondialdehyde content in S1 and S2 soils (p < 0.05).However, in S3 soil, there was no difference between C1 treatments and CK and between B1 treatments and CK (p > 0.05).Thus, straw return and biochar application can improve the physicochemical properties of saline soil and regulate osmolytes in cotton, but the amelioration effect of low application rates on high-salinity soils is insignificant (p > 0.05).

研究不同施氮水平下,尿素与液态脲甲醛缓释氮肥不同比例配施对棉花生长发育、干物质积累量、棉花各器官氮素积累量、氮肥利用率以及产量的影响,为新疆滴灌棉田高产施氮管理提供理论依据.试验选用棉花品种新陆早 64 号,设置 2 种施氮方式,分别为常规全施尿素(T2)和尿素与缓释氮肥不同比例配施(US);配施处理按照施氮量设 3 个水平,分别为不减氮U0.8S0.2(T3)和U0.6S0.4(T4)、减氮 20％U0.6S0.2(T5)和U0.4S0.4(T6)、减氮 40％U0.4S0.2(T7)和U0.2S0.4(T8),不施氮肥(T1)为对照,共 8 个处理.分别在苗期、蕾期、花期、铃期、吐絮期对棉花株高、SPAD值、干物质累积量进行测定,并分析植株氮素积累量、氮肥利用率和单株产量.结果表明:尿素与缓释氮肥配施可以促进棉花的生长发育和产量,不减氮水平下T4 处理棉花的株高、SPAD值、植株干物质积累量和单株产量达到最大,T4 处理棉花单株产量较T1 和T2 处理分别显著提高了 54.09％和 26.50％(P<0.05);在减氮 20％水平下,T5 与T6 处理的棉花株高和SPAD值差异均不显著,且T5、T6 处理的棉花单株产量及其构成因素与常规全施尿素T2 处理也无显著差异,可实现减氮不减产;减氮 40％水平下,T7 与T8 处理在棉花生长发育及产量间均无显著差异.同时,尿素与缓释氮肥配施有利于提高棉花的氮素吸收利用,不减氮水平下T4 处理的氮素农学效率和氮素偏生产力在各处理间达到最大,分别为 8.73 和 24.86 kg/kg;T5、T6 处理的氮素表观利用率显著高于T2 处理(P<0.05),分别为 62.09％和 62.44％;减氮 40％水平下,配施缓释氮肥比例较高的T8 处理氮素表观利用率较T7 处理高 8.51％.综上:T4 和T5 处理均能显著增加棉花氮肥利用率,有利于棉花生长发育及单株产量的提高,是本试验中棉花高产高效的最佳配施比例.

In recent years, the improvement of soil cadmium (Cd) contamination remediation effect of biochar by modi-fication has received wide attention. However, the effect of combined modification on biochar performance in soil Cd contamination remediation and the mechanism are still unclear. In this study, cotton straw biochar and maize straw biochar were co-modified by KOH (0, 3, 5 mol L-1), K3PO4, and urea. Then, two modified biochars with high Cd adsorption capacity were selected to test the soil Cd contamination remediation effect through a pot experiment. The results showed that the combined modification by using KOH, K3PO4, and urea significantly increased the specific surface area and nitrogen (N) and phosphorus (P) contents of biochar, providing more adsorption sites for Cd. Among the modified biochar, the cotton straw biochar modified with KOH (3 mol L-1), K3PO4, and urea (m3-CSB) had the highest adsorption capacity (111.25 mg g-1), which was 7.86 times that of cotton straw biochar (CSB). The m3-CSB for adsorption isotherm and kinetics of Cd conformed to the Langmuir model and Pseudo-second-order kinetic equation, respectively. In the pot experiment, under different exogenous Cd levels (0 (Cd0), 4 (Cd4), and 8 (Cd8) mg kg-1), m3-CSB treatment decreased soil available Cd content the most (51.68%-63.4%) compared with other biochar treatments. Besides, m3-CSB treatment significantly promoted the transformation of acid-soluble Cd to reducible, oxidizable, and residual Cd, reducing the bioavailability of Cd. At the Cd4 level, the application of m3-CSB significantly reduced cotton Cd uptake compared to CK, and the maximum reduction of Cd content in cotton fibers was as high as 81.95%. Therefore, cotton straw biochar modified with KOH (3 mol L-1), K3PO4, and urea has great potential in the remediation of soil Cd contamination.

为探究减氮施肥技术和缓释氮肥在新疆滴灌棉花上的应用效果,选用当地棉花主栽品种新陆早64号,设置不施氮肥(H1)、常规全施尿素(H2,300 kg/hm2)、减氮20%缓释氮肥与尿素配施(H3,240 kg/hm2)3个处理,分别在棉花不同生育期对棉田土壤理化性质、酶活性、无机氮含量进行测定,并在棉花吐絮期测定棉花氮素含量,分析减氮配施缓释氮肥对棉花氮素利用效率的影响.结果显示:在棉花各生育时期,减氮20%配施缓释氮肥处理0～20 cm土层团聚体稳定性显著高于常规全施尿素处理(P<0.05),在0～40 cm土层H3与H2处理全氮差异不显著;不施氮肥(H1)处理土壤酶活性在棉花全生育时期均处于较低水平,常规全施尿素H2处理土壤脲酶活性显著高于减氮20%配施缓释氮肥(H3)处理,过氧化氢酶活性均低于H3处理,2个处理间蔗糖酶活性和碱性磷酸酶活性差异不显著;H3处理在40～60 cm土层铵、硝态氮含量较常规全施尿素H2处理减少了棉花生育后期氮素的淋溶损失;H3处理的氮肥利用率为45.75%,高于H2处理(P<0.05),较H2处理提高了7.87百分点;减氮配施缓释氮肥有利于提高棉花产量,减氮20%配施缓释氮肥(H3)处理下棉花皮棉产量较不施氮肥(H1)处理提高了18.26%,且铃质量、籽棉产量、皮棉产量与常规全施尿素(H2)处理差异不显著,可实现减氮不减产.结果表明,减氮20%施氮水平下缓释氮肥与尿素配施(H2)增强了表层土壤团聚体稳定性,可在棉花全生育期维持较高无机氮含量,减少了氮素淋溶损失,有利于棉花氮肥利用率及产量的提高,可在滴灌棉田中推广应用.

To screen environmentally friendly and efficient Cd pollution remediation material, the effects of BC and BF on soil Cd bio-availability and cotton Cd absorption were analyzed under Cd exposure. Besides, the differences in metabolic mechanisms by which biochar (BC) and biofertilizer (BF) affect Cd-contaminated soil and cotton were also analyzed. The results showed that the application of BC and BF increased cotton dry matter accumulation, boll number, and single boll weight, and reduced the Cd content in cotton roots, stems, leaves, and bolls. At harvest, the Cd content in cotton roots in the BC and BF groups reduced by 15.23% and 16.33%, respectively, compared with that in the control. This was attributed to the conversion of carbonate-bound Cd (carbon-Cd) and exchangeable Cd (EX-Cd) by BC and BF into residual Cd (Res-Cd). It should be noted that the soil available Cd (Ava-Cd) content in the BF group was lower than that in the BC group. The metabolomic analysis results showed that for BC vs BF, the relative abundance of differential metabolites Caffeic acid, Xanthurenic acid, and Shikimic acid in soil and cotton roots were up-regulated. Mantel test found that cotton root exudate l-Histinine was correlated with the enrichment of Cd in various organs of cotton. Therefore, the application of BC and BF can alleviate Cd stress by reducing soil Ava-Cd content and cotton's Cd uptake, and BF is superior to BC in reducing Cd content in soil and cotton organs. This study will provide a reference for the development of efficient techniques for the remediation of Cd-polluted alkaline soil, and provide a basis for subsequent metagenomics analysis.

•Vis-NIR and pXRF spectral data fusion enhances soil organic matter estimation.•1.6th-order derivative is the optimal preprocessing method for vis-NIR spectra.•Baseline correction is the optimal preprocessing method for pXRF spectra.•Feature selection lifts the single/multi sensor data fusion estimation accuracy.•CARS combined with GRA fusion provides the optimal estimation of SOM.

Amelioration of saline soil to grow crops could increase food production and improve food security. However, the long-term effects of different methods for ameliorating saline soil still need to be evaluated. In this study (2014-2021), the salinity variations of saline soils under different amelioration methods (T1: salt isolation by a stone layer + cropping; T2: subsurface drainage + cropping; T3: 5-year cropping; T4: 3-year cropping; CK: bare land) were monitored using electromagnetic induction. Besides, the long-term effects of different amelioration methods and yield reduction risk were assessed using the three-dimensional sequential Gaussian simulation (3D-SGS). The 3D-SGS results showed that soil salinity increased during abandonment (2014-2015) and then decreased during reclamation (2016-2021). Salt accumulated in the 0-40 cm soil layer in T3, T4, and CK treatments, while it accumulated in the 40-80 cm soil layer in T1 and T2 treatments. The proportion of high-risk areas in T1, T2, T3, and T4 treatments reduced after reclamation, but soil salinity only slightly reduced in T3 and T4 treatments, showing a high risk of yield reduction. Besides, the time-specific regression model had the highest prediction accuracy for soil salinity. Therefore, probabilistic evaluation based on 3D-SGS is an effective method to evaluate the effectiveness of saline soil amelioration methods, and could help decision-makers formulate scientific saline soil amelioration plans.

针对棉花规模化生产精准技术实际应用中存在的监测不精确、决策依据不充分、控制不精准及管理效率低等薄弱点,创建了棉花生产从播种到收获的关键环节精准监控技术体系.包括:研发了棉花播种质量在线监测与调控技术及装备,可明显提高播种作业质量和作业效率;创立了滴灌棉田全程养分、水分快速监测与定量诊断技术,研发了水肥决策与精量控制系统,构建了水肥一体化精准管理技术与应用云平台,可大幅度提高滴灌水肥利用效率;构建了"病虫监测→施药决策→处方图生成→精量喷药"棉花病虫害精准防控技术,可明显降低农药投入量;创新性研发了棉花产量监测,以及采棉机棉箱火情、工况参数和故障诊断检测技术及装备,构建了采棉机信息化服务云平台,可大幅提高采棉机作业效率、作业质量与管理水平.在总结上述研究进展的基础上,展望了未来棉花生产智慧管理发展的主要方向.

Soil salinization greatly restricts crop production in arid areas for salinity stress can inhibit crop photosynthesis and growth. Chlorophyll fluorescence and photosynthetic gas exchange (CFPGE) parameters are important indicators of crop photosynthesis and have been widely used to evaluate the impacts of salinity stress on crop photosynthesis and growth. Remote sensing technology can quickly and non-destructively obtain crop information under salinity stress, however, at present, the distribution of spectral features of CFPGE parameters in different regions is still unclear. In this study (2019-2020), under salinity stress conditions, the spectral data of rapeseed leaves were acquired and the CFPGE parameters were simultaneously determined. Then, continuous wavelet transformation (CWT) and standard normal variate (SNV) transformation were utilized to preprocess the raw spectral data. After that, a CFPGE parameter estimation model was constructed by using the partial least squares regression (PLSR) algorithm and the support vector machines (SVM) algorithm based on the spectral features in the red region (600-800 nm) and those in the red, blue-green (350-600 nm), and near-infrared (800-2500 nm) regions. The results showed that the spectral features of CFPGE parameters could be extracted by successive projections algorithm (SPA) based on the CWT preprocessing. The CFPGE parameter estimation model constructed based on the spectral features in the red region (675 nm, 680 nm, 688 nm, 749 nm, and 782 nm) had the highest Fv/Fm estimation accuracy on day 30, with R2c, R2p, and RPD of 0.723, 0.585, and 1.68, respectively. Based on this, the spectral features (578 nm, 976 nm, 1088 nm, 1476 nm, and 2250 nm) in the blue-green and near-infrared regions were added in the variables for modeling, which significantly improved the accuracy and stability of the model, with R2c, R2p, and RPD of 0.886, 0.815, and 2.58, respectively. Therefore, the fusion of the spectral features in the red, blue-green, and near-infrared regions could improve the estimation accuracy of rapeseed leaf CFPGE parameters. This study will provide technical reference for rapid estimation of photosynthetic performance of crops under salinity stress in arid and semi-arid areas.

为探究不同耐盐性花生品种对盐碱胁迫的响应机制,以前期试验筛选的耐盐型'益花1号'和'花育25号',盐敏感型'花育39号''豫花37号'和'汾花1号'为试验材料进行NaCl、NaHCO3和NaCl+NaHCO3不同浓度的胁迫处理,分析不同处理对花生主根长、地上部和下部干质量及鲜质量、POD、SOD和CAT活性、MDA含量和脯氨酸含量的影响.结果表明:随着胁迫浓度增加,不同品种花生主根长逐渐降低;地上部和下部干质量及鲜质量显著下降;POD和SOD活性呈先升高后降低的趋势,耐盐品种酶活性的降幅低于盐敏感品种,而CAT活性在NaCl和NaCl+NaHCO3胁迫下呈下降趋势,NaHCO3胁迫下呈小幅升高再降低的趋势;MDA含量和脯氨酸含量均显著增加,耐盐碱品种的MDA含量低于盐碱敏感品种,而脯氨酸含量高于盐碱敏感品种.综上,花生在盐碱胁迫的影响下,生长发育受到阻碍,通过抗氧化酶系统和渗透调节物质对胁迫产生响应并调节.

Soil salinization is one of the main causes of land degradation in arid and semi-arid areas. Timely and accurate monitoring of soil salinity in different areas is a prerequisite for amelioration. Hyperspectral technology has been widely used in soil salinity monitoring due to its high efficiency and rapidity. However, vegetation cover is an inevitable interference in the direct acquisition of soil spectra during crop growth period, which greatly limits the monitoring of soil salinity by remote sensing. Due to high soil salinity could lead to difficulty in plants’ water absorption, and inhibit plant dry matter accumulation, a method for monitoring root zone soil salinity by combining vegetation canopy spectral information and crop aboveground growth parameters was proposed in this study. The canopy spectral information was acquired by a spectroradiometer, and then variable importance in projection (VIP), competitive adaptive reweighted sampling (CARS), and random frog algorithm (RFA) were used to extract the salinity spectral features in cotton canopy spectrum. The extracted features were then used to estimate root zone soil salinity in cotton field by combining with cotton plant height, aboveground biomass, and shoot water content. The results showed that there was a negative correlation between plant height/aboveground biomass/shoot water content and soil salinity in 0-20, 0-40, and 0-60 cm soil layers at different growth stages of cotton. Spectral feature selection by the three methods all improved the prediction accuracy of soil salinity, especially CARS. The prediction accuracy based on the combination of spectral features and cotton growth parameters was significantly higher than that based on only spectral features, with R 2 increasing by 10.01%, 18.35%, and 29.90% for the 0-20, 0-40, and 0-60 cm soil layer, respectively. The model constructed based on the first derivative spectral preprocessing, spectral feature selection by CARS, cotton plant height, and shoot water content had the highest accuracy for each soil layer, with R 2 of 0.715,0.769, and 0.742 for the 0-20, 0-40, 0-60 cm soil layer, respectively. Therefore, the method by combining cotton canopy hyperspectral data and plant growth parameters could significantly improve the prediction accuracy of root zone soil salinity under vegetation cover conditions. This is of great significance for the amelioration of saline soil in salinized farmlands arid areas.

[目的]研究实时、快速估测冬小麦不同生育时期水分状况并构建模型,为冬小麦水分精准管理提供科学依据.[方法]以新疆典型滴灌冬小麦为研究对象,应用高光谱成像技术获取冬小麦冠层光谱信息,并对原始光谱反射率进行平滑和数据变换,利用一元线性回归(Simple linear regression,SLR)、主成分回归(Princi-pal components regression,PCR)和偏最小二乘回归(Partial least squares regression,PLSR)3种建模方法,对冬小麦冠层原始光谱及变换光谱分别构建植株水分含量估测模型.[结果]冬小麦冠层原始光谱反射率与植株水分含量相关性不高,对原始光谱反射率进行数据变换可以显著增强与水分含量的相关性和相关波段数,其中倒数一阶微分变换与冬小麦植株水分含量的相关系数最大,为-0.8930,但不同变换最优相关系数所对应的波段位置并不固定.PLSR方法的模型精度最高,对数变换的PLSR模型估测精度最高,模型R2p、RMSEp、RPD值分别为0.8808、3.2512％、2.9343;冬小麦不同生育时期估测模型精度存在差异,拔节期、抽穗期估测模型精度较低,灌浆中期最高,其估测模型R2p、RMSEp、RPD值分别为0.9048、1.3811％、3.4547.[结论]利用高光谱成像技术对估测冬小麦植株水分含量是可行的,在灌浆中期的估测效果最佳.

Abstract Background Cd seriously threatens soil environment, remedying Cd in farmland and clearing the response of soil environment to modifiers in Cd-contaminated soils is necessary. In this study, the effects of cotton straw biochar and compound Bacillus biofertilizer used as modifiers on the biochemical properties, enzyme activity, and microbial diversity in Cd-contaminated soils (1, 2, and 4 mg·kg−1) were investigated. Results The results showed that both cotton straw biochar and compound Bacillus biofertilizer could improve the soil chemical characteristics, including the increase of soil C/N ratio, electrical conductance (EC) and pH, and the most important decrease of soil available Cd content by 60.24% and 74.34%, respectively (P < 0.05). On the other hand, adding cotton straw biochar and compound Bacillus biofertilizer in Cd stressed soil also improved soil biological characteristics. Among them, cotton straw biochar mainly through increasing soil alkaline phosphatase activity and improve bacteria abundance, compound Bacillus biofertilizer by increasing soil invertase, alkaline phosphatase, catalase, and urease activity increased bacterial community diversity. On the whole, the decrease of soil available Cd was mainly caused by the increase of soil pH, C/N, urease and alkaline phosphatase activities, and the relative abundance of Acidobacteria and Proteobacteria. Conclusions In summary, the applications of cotton straw biochar and compound Bacillus biofertilizer could decrease soil available Cd concentration, increase soil bacterial community diversity and functions metabolism, and reduce the damage of Cd stress, compared with cotton straw biochar, compound Bacillus biofertilizer was more effective in immobilizing Cd and improving soil environmental quality.