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
) were investigated.
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.
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.
In recent years, the improvement of soil cadmium (Cd) contamination remediation effect of biochar by modification 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.
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•Combined modification enhanced the adsorption capacity of straw-derived biochar.•Nitrogen and phosphorus were successfully loaded on MSB through KOH.•Combined modified biochar reduced soil cadmium bioavailability more than biochar.•Combined modified biochar reduced Cd uptake and transport in cotton more than biochar.
Nitrogen application could alleviate salt stress on crops, but the specific physiological mechanism is still unclear. Therefore, in this study, a pot experiment was conducted to explore the effects ...of different application rates of nitrogen (0, 0.15, 0.30, and 0.45 g·kg
−1
) on the growth parameters, osmotic adjustment, reactive oxygen species scavenging, and photosynthesis of rapeseed seedlings planted in the soils with different concentrations of sodium chloride (1.5, 3.5, 5.5, and 7.5 g·kg
−1
). The results showed that nitrogen could alleviate the inhibition of salt on rapeseed growth, and improve the antioxidant enzyme activities and the contents of non-enzymatic substances, K
+
, soluble protein (SP), soluble sugar (SS), and proline. Besides, there was a significant correlation between the indexes of active oxygen scavenging system, osmoregulation system, and photosynthesis. Therefore, applying appropriate amount of nitrogen can promote the growth and development of rapeseed seedlings under salt stress, accelerate the scavenging of reactive oxygen species, maintain osmotic balance, and promote photosynthesis. This study will improve our understanding on the mechanism by which nitrogen application alleviates salt stress to crops.
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 R
c, R
p, 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 R
c, R
p, 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.
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
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
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.
The functional lipid components found in breast milk, vernix caseosa, and meconium are Branched‐chain Fatty Acids (BCFA). The goal of this study was to establish the existence of BCFA in vernix and ...meconium in infants born at different gestational ages. TLC plates and GC‐MS were examined for the lipids in vernix caseosa and meconium. The results indicated that there were nine BCFA in vernix caseosa, including iso‐12:0, anteiso‐13:0, iso‐14:0, iso‐15:0, anteiso‐15:0, iso‐16:0, anteiso‐17:0, iso‐18:0, and iso‐20:0. Five BCFA (iso‐12:0, anteiso‐13:0, iso‐14:0, iso‐15:0, and anteiso‐15:0) were not contained in the meconium, suggesting that some of the BCFA may be digested and consumed by infants. In the vernix caseosa, the content of BCFA in triacylglycerol (TAG) and free fatty acid (FFA) was 15.59% and 11.82%, respectively. The vernix caseosa's wax ester fraction contained the highest content of BCFA, reaching up to 16.81%. The carbon chain length of fatty acids (FA) ranged from 12 to 24 in the vernix caseosa and 14 to 22 in meconium samples. The gestational age was likely to affect BCFA concentrations, with the vernix caseosa and meconium BCFA content being significantly higher in full‐term infants than in preterm infants (p < .001). Further research is required into the relationship between BCFA and gut microbiotas.
The content of BCFA in the vernix and meconium was significantly higher in full‐term infants than in preterm infants. BCFA may be digested and absorbed in the infants’ gastrointestinal tract.
Inhibitory activities of ethanol extracts from seven fermented soybean products, including douchi, sufu, stinky tofu, to acetylcholinesterase were determined, and crude extract from Yongchuan douchi, ...which showed the strongest inhibitory effect, was further extracted systematically. Highly active anticholinesterase ingredients were mainly found in petroleum ether extracts; after multistep column chromatography, three compounds were purified finally with high-speed countercurrent chromatography. By their spectral data of MS,
1
H-NMR, and
13
C-NMR, three compounds were identified as genistein, daidzein, and kaempferol, whose further research could lay foundation for research and development of new drugs and foods against Alzheimer's disease.
•EMI data over 7 consecutive years was used to monitor the dynamic changes of SSC.•Improvement measures can inhibit the salt moving upward after tillage abandonment.•Combination engineering ...improvement and conventional planting can decrease SSC.
Understanding the impacts of desalination treatments on salt migration in saline soil during the farmland abandonment-reclamation process has significance for saline soil development and utilization. In this study, the soil salt content of severely salinized land in Xinjiang, China, was monitored over seven consecutive years using electromagnetic induction (EMI) rapid measurement technology. The experiment involved three different soil desalination engineering treatments and one control in the newly reclaimed, highly saline land (T1: salt isolation treatment at root area with conventional planting; T2: underground tube salt drainage with conventional planting; T3: conventional planting; CK: a natural control). A profile salinity prediction model was built based on the EMI to simulate the three-dimensional spatial distribution characteristics of soil salinity in the test area. The effects of the different saline soil improvement treatments on the distribution of salt content in the soil profile and the effect of desalination were analysed. The results demonstrated the following: (1) the soil salt content in the test area showed an obvious trend of surface salt accumulation. The salt content in the 0−100 cm layers under the different treatments showed decreasing, increasing and decreasing trends with the process of cotton planting, abandonment and reclamation, respectively, with a greater decrease in salt content associated with a longer planting period. (2) The soil salt content obviously decreased under the T1 treatment in the 0−40 cm and 80−100 cm soil layers and in the 20−60 cm soil layers under the T2 and T3 treatments. After the implementation of salinized soil improvement measures and tillage abandonment, a trend of increased salt content was evident in the plough layer under the different treatments; however, engineering improvement measures were able to inhibit salt migration to a certain degree. Under engineered drainage and salt isolation at the root area in combination with agricultural cultivation, irrigation could effectively reduce the soil salt content in the plough layer. These results provide a theoretical basis for soil improvement and utilization in arid areas.
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•A new means for multi-source spectral fusion based on deep learning was proposed.•Soil quality index developed from 21 physical, chemical, environmental properties.•Continuous ...wavelet transform highlighted the spectra related to soil quality index.•The proposed method was superior to the commonly used data fusion methods.
Soil quality assessment, as a means to assess the impact of human activities on soil, is of great significance to achieve sustainable development. Proximal sensing offers a rapid and cost-effective means for soil spectral acquisition, which resolves the shortcomings of traditional laboratory analysis and provides a new way for soil quality assessment. However, using a singular spectroscopic technique may not encompass adequate information needed for soil quality assessment. Therefore, in this research, the visible-near-infrared (vis-NIR) and portable X-ray fluorescence (pXRF) spectral data were fused, and the continuous wavelet transform (CWT) was combined with the parallel input 2D convolutional neural network (PI-2D-CNN) algorithm, to enhance the prediction accuracy of soil quality index (SQI). A total of 287 soil samples were collected from the Yarkand-Kashgar River Basin in Xinjiang, China for proximal sensing in the laboratory, and 21 soil physicochemical properties were measured for SQI calculation simultaneously. After preprocessing the vis-NIR and pXRF spectral data with the CWT, partial least squares regression (PLSR) and CNN models were constructed to predict SQI. The results showed that the SQI prediction accuracy based on vis-NIR spectra (coefficient of determination for validation set (R2) = 0.32–0.54) was higher than that based on pXRF spectra (R2 = 0.17–0.36). The prediction accuracy of both vis-NIR and pXRF spectra were improved by CWT combined with CNN. Compared with the traditional spectral data fusion methods (concatenation, sequential and orthogonalised-partial least squares (SO-PLS)), the PI-CNN algorithm demonstrated superior SQI prediction accuracy, and the constructed PI-2D-CNN model obtained the highest prediction accuracy (R2 = 0.67). Overall, this study proved that the combination of CWT and PI-CNN could increase the SQI prediction accuracy. This research will provide a rapid and low-cost approach for large-scale soil quality assessment.
Nitrated polycyclic aromatic hydrocarbons (NPAHs) are widespread organic pollutants that possess carcinogenic and mutagenic properties, so they may pose a risk to the environment and human health. In ...this study, the concentrations of 15 NPAHs and 16 polycyclic aromatic hydrocarbons (PAHs) in 30 surface water samples and 26 sediment samples were measured in 2018 from the Taige Canal, one of the main rivers flowing into Taihu Lake, China. The total NPAH concentrations in water and sediment ranged from 14.7 to 235 ng/L and 22.9 to 96.5 ng/g dw, respectively. 9-nitrophenanthrene (nd–76.3 ng/L) was the dominant compound in surface water, while 2+3-nitrofluoranthene (1.73–18.1 ng/g dw) dominated in sediment. Among PAHs, concentration ranging from 1,097 to 2,981 ng/L and 1,089 to 4,489 ng/g dw in surface water and sediment, respectively. There was a strong positive correlation between the log octanol-water partition coefficient (Kow) and log sediment-water partition coefficient due to hydrophobic interaction. The fugacity fraction value increased with the decrease of log Kow, and chrysene was transferred from water into sediment. The residual NPAHs in surface water and sediment of the Taige Canal have partial correlation. Diesel engine and coal combustion emissions were probably the principal sources of NPAHs in surface water and sediment. The results of ecological risk assessment showed that some NPAHs in water (e.g, 1-nitropyrene and 6-nitrochrysene) and sediment (e.g., 2-nitrobiphenyl, 5-nitroacenaphthene, 9-nitrophenanthrene and 2+3-nitrofluoranthene) had moderate ecological risks, which should be of concern.
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