Double-channel sensors for high precision measurement of methane based on a dual-path Herriott cell.

A double-channel methane (CH4) sensor was developed using a dual-pass multipass cell (DP-MPC) and a novel method that combines averaging dual-channel concentration signals with optimized detector gain configuration. This DP-MPC features two input/output coupling holes, resulting in absorption path lengths of approximately 95.8 m and 35.8 m, respectively. By optimizing the photodetector gain configuration and averaging the dual-channel concentration signals, the detection performance of the sensor was further enhanced. Allan deviation analysis indicated that after optimizing the detector gain, the measurement precision after dual-channel averaging reaches 21 ppb with an integration time of 1 s at a concentration of 2 ppm CH4, which is approximately 1.4 times higher than the measurement precision of the long-path channel (31 ppb) and short-path channel (30 ppb). The time required to achieve a measurement precision of 21 ppb is 2.4 s for the long-path channel and 2.1 s for the short-path channel. The response speed of the dual-channel averaging is approximately 2 times that of any single channel. Meanwhile, the sensor demonstrated its stability and reliability through continuous outdoor atmospheric CH4 measurements.

Humidity Sensing Properties of Different Atomic Layers of Graphene on the SiO2/Si Substrate.

Graphene has great potential to be used for humidity sensing due to its ultrahigh surface area and conductivity. However, the impact of different atomic layers of graphene on the SiO2/Si substrate on humidity sensing has not been studied yet. In this paper, we fabricated three types of humidity sensors on the SiO2/Si substrate based on one to three atomic layers of graphene, in which the sensing areas of graphene are 75 µm × 72 µm and 45 µm × 72 µm, respectively. We studied the impact of both the number of atomic layers of graphene and the sensing areas of graphene on the responsivity and response/recovery time of the prepared graphene-based humidity sensors. We found that the relative resistance change of the prepared devices decreased with the increase of number of atomic layers of graphene under the same change of relative humidity. Further, devices based on tri-layer graphene showed the fastest response/recovery time, while devices based on double-layer graphene showed the slowest response/recovery time. Finally, we chose devices based on double-layer graphene that have relatively good responsivity and stability for application in respiration monitoring and contact-free finger monitoring.

A fast response and highly sensitive flexible humidity sensor based on a nanocomposite film of MoS2 and graphene oxide.

Graphene oxide (GO)-based humidity sensors are attracting widespread attention due to their high responsivity and low cost. However, GO-based humidity sensors generally suffer from slow response and recovery as well as poor stability. Here, we report a flexible resistive humidity sensor based on a MoS2/GO composite film that was fabricated by mixing different volumes of MoS2 and GO dispersions with adjustable volume ratios. The MoS2/GO composite film has been used as a sensing layer on screen-printed interdigital electrodes. The results show that the best device performance was achieved at a dispersion volume of 0.05 mL with a MoS2/GO volume ratio of 5 : 1, featuring a high responsivity (∼98%), a fast response/recovery time (1.3/12.1 s), excellent stability and low cost. Furthermore, the humidity sensor exhibits good linearity over a wide humidity range (33%RH-98%RH) at room temperature (25 °C) and can be fabricated easily and feasibly. The application of the humidity sensors we prepared in human respiration detection and human fingertip proximity detection has been demonstrated. These findings indicate the great potential of the MoS2/GO composite in developing next generation high-performance humidity sensors.

Global critical soil moisture thresholds of plant water stress.

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.

Metacognition and Mathematical Modeling Skills: The Mediating Roles of Computational Thinking in High School Students.

This study was to investigate the relationship between metacognition and the mathematical modeling skills of high school students, as well as the mediating role of computational thinking. A cluster sampling method was adopted to investigate 661 high school students, using the metacognition scale, computational thinking scale, and mathematical modeling skill test questions. The results showed that metacognitive knowledge and metacognitive monitoring had a direct and positive correlation with high school students' mathematical modeling skills. Additionally, the critical thinking dimension of computational thinking mediated the relationship between metacognitive knowledge, experience, monitoring, and mathematical modeling skills. These findings indicated that sufficient metacognition could improve the critical thinking of high school students' computational thinking and enhance their mathematical modeling skills.

[Effects of reductive soil disinfestation and organic fertilizer application on microbial community stability in a facility vegetable soil]. / 强还原处理和施用有机肥对设施蔬菜地土壤微生物群落稳定性的影响.

Reductive soil disinfestation (RSD) is an effective method for remediating degraded facility vegetable soils. However, the effectiveness of RSD using green manure as a carbon source in the field has not yet been clarified. We investigated the effects of RSD and organic fertilizer application on soil microbial community composition, diversity, and stability in a degraded facility vegetable soil. There were six treatments, including no fertilization (CK), no fertilization and soil flooded and mulched with plastic film (FF), soil amended with chicken manure (OM), soil amended with chicken manure and flooded and mulched with plastic film (OMR), soil amended with Sesbania cannabina (TF), and soil amended with S. cannabina and flooded and mulched with plastic film (TR). The results showed that the OMR and TR treatments significantly decreased bacterial Chao1 index, altered bacterial and fungal community structure, and increased the relative abundances of Bacillus, Rhodococcus, Clostridium, and Penicillium. The TR treatment significantly reduced the relative abundance of Fusarium. Results of redundancy analysis and Mantel test analysis suggested that soil ammonium nitrogen and dissolved organic carbon contents were the key factors influencing bacterial community composition, and soil pH was the key factor affecting fungal community composition. Results of cohesion analysis showed that the OMR and TR treatments significantly improved bacterial community stability, and that there was no difference between OMR and TR treatments. The TR treatment enhanced fungal community stability, which was significantly higher than the OMR treatment. Therefore, the RSD with green manure as carbon source could be effective remediation practice to improve soil health.

The regional disparities in liver disease comorbidity among elderly Chinese based on a health ecological model: the China Health and Retirement Longitudinal Study.

PURPOSE: This study aimed to investigate the risk factors for liver disease comorbidity among older adults in eastern, central, and western China, and explored binary, ternary and quaternary co-morbid co-causal patterns of liver disease within a health ecological model. METHOD: Basic information from 9,763 older adults was analyzed using data from the China Health and Retirement Longitudinal Study (CHARLS). LASSO regression was employed to identify significant predictors in eastern, central, and western China. Patterns of liver disease comorbidity were studied using association rules, and spatial distribution was analyzed using a geographic information system. Furthermore, binary, ternary, and quaternary network diagrams were constructed to illustrate the relationships between liver disease comorbidity and co-causes. RESULTS: Among the 9,763 elderly adults studied, 536 were found to have liver disease comorbidity, with binary or ternary comorbidity being the most prevalent. Provinces with a high prevalence of liver disease comorbidity were primarily concentrated in Inner Mongolia, Sichuan, and Henan. The most common comorbidity patterns identified were "liver-heart-metabolic", "liver-kidney", "liver-lung", and "liver-stomach-arthritic". In the eastern region, important combination patterns included "liver disease-metabolic disease", "liver disease-stomach disease", and "liver disease-arthritis", with the main influencing factors being sleep duration of less than 6 h, frequent drinking, female, and daily activity capability. In the central region, common combination patterns included "liver disease-heart disease", "liver disease-metabolic disease", and "liver disease-kidney disease", with the main influencing factors being an education level of primary school or below, marriage, having medical insurance, exercise, and no disabilities. In the western region, the main comorbidity patterns were "liver disease-chronic lung disease", "liver disease-stomach disease", "liver disease-heart disease", and "liver disease-arthritis", with the main influencing factors being general or poor health satisfaction, general or poor health condition, severe pain, and no disabilities. CONCLUSION: The comorbidities associated with liver disease exhibit specific clustering patterns at both the overall and local levels. By analyzing the comorbidity patterns of liver diseases in different regions and establishing co-morbid co-causal patterns, this study offers a new perspective and scientific basis for the prevention and treatment of liver diseases.

Quantitative analysis of three ingredients in Salvia miltiorrhiza by near infrared spectroscopy combined with hybrid variable selection strategy.

Rosmarinic acid (RA), Tanshinone IIA (Tan IIA), and Salvianolic acid B (Sal B) are crucial compounds found in Salvia miltiorrhiza. Quickly predicting these components can aid in ensuring the quality of S. miltiorrhiza. Spectral preprocessing and variable selection are essential processes in quantitative analysis using near infrared spectroscopy (NIR). A novel hybrid variable selection approach utilizing iVISSA was employed in this study to enhance the quantitative measurement of RA, Tan IIA, and Sal B contents in S. miltiorrhiza. The spectra underwent 108 preprocessing approaches, with the optimal method being determined as orthogonal signal correction (OSC). iVISSA was utilized to identify the intervals (feature bands) that were most pertinent to the target chemical. Various methods such as bootstrapping soft shrinkage (BOSS), competitive adaptive reweighted sampling (CARS), genetic algorithm (GA), variable combination population analysis (VCPA), successive projections algorithm (SPA), iteratively variable subset optimization (IVSO), and iteratively retained informative variables (IRIV) were used to identify significant feature variables. PLSR models were created for comparison using the given variables. The results fully demonstrated that iVISSA-SPA calibration model had the best comprehensive performance for Tan IIA, and iVISSA-BOSS had the best comprehensive performance for RA and Sal B, and correlation coefficients of cross-validation (R2cv), root mean square errors of cross-validation (RMSECV), correlation coefficients of prediction (R2p), and root mean square errors of prediction (RMSEP) were 0.9970, 0.0054, 0.9990 and 0.0033, 0.9992, 0.0016, 0.9961 and 0.0034, 0.9998, 0.0138, 0.9875 and 0.1090, respectively. The results suggest that NIR spectroscopy, along with PLSR and a hybrid variable selection method using iVISSA, can be a valuable tool for quickly quantifying RA, Sal B, and Tan IIA in S. miltiorrhiza.

Changes in free amino acid and protein polymerization in wheat caryopsis and endosperm during filling after shading.

Over the past several decades, a decreasing trend in solar radiation has been observed during the wheat growing season. The effects of shade stress on grain yield formation have been extensively studied. However, little information on shade stress's effects on protein formation warrants further investigation. Two wheat cultivars were grown under three treatments, no shade as the control group (CK), shading from the joint to the anthesis stage (S1), and shading from the joint to the mature stage (S2), to investigate the effects of shade stress on the free amino acids of the caryopsis and endosperm and protein accumulation during grain filling. The dry mass of caryopsis and endosperm was significantly decreased under shade stress, whereas Glu, Ser, Ala, and Asp and protein relative content increased during grain filling. The observed increases in total protein in S1 and S2 were attributed to the increases in the SDS-isoluble and SDS-soluble protein extracts, respectively. S1 improved polymer protein formation, but S2 delayed the conversion of albumins and globulins into monomeric and polymeric proteins. Moreover, shade stress increased the proportion of SDS-unextractable polymeric protein, which represented an increase in the degree of protein polymerization. The polymerization of protein interrelations between protein components and accumulation in caryopsis and endosperm provided novel insights into wheat quality formation under shade stress.

The 60 nm gold nanoparticles improve qPCR amplification efficiency through specific palindromic sequences (GGATCC or ACCGGT) in primers.

BACKGROUND: Polymerase chain reaction (PCR) technology and quantitative real-time PCR (qPCR) technology are widely used in clinical diagnosis and research, but amplification efficiency and sensitivity are still key problems for researchers. An increasing number of reports show that gold nanoparticles (AuNPs) can be used to improve the sensitivity and amplification efficiency of PCR. Here, we found that 60 nm gold nanoparticles with a positive charge (60 nm- Au+) can enhance the amplification efficiency of qPCR. METHODS: Mouse DNA was extracted by the alkaline lysis method. Primer 5.0 software was used to design primers and mutation primers, and the DNA fragments were obtained by the method of synthesizing plasmids. The qPCR was applied to amplify target gene fragments. RESULTS: The amplification efficiency of qPCR was improved by about 1.828 times in the experimental group with 60 nm- Au+ compared with the control group without 60 nm- Au+. The primer pair contains a specific palindromic sequence (GGATCC or ACCGGT). And 60 nm Au+ did not enhance the amplification efficiency of qPCR when the above primer was mutated. CONCLUSIONS: The primers contain special palindrome sequences (GGATCC or ACCGGT) with 60 nm- Au+ can enhance the amplification efficiency of qPCR. Therefore, it suggests a more in-depth understanding of the mechanism and function of gold nanoparticles and primer sequences. This study has presented some implications for gold nanoparticles application in the development of qPCR technology.

Relationship between the baking quality of wheat (Triticum aestivum L.) and the protein composition and structure after shading.

Although wheat (Triticum aestivum L.) grain protein content is increased by shade stress, the relationship between the baking quality of wheat flour and protein composition and structure remains unclear. Here, we investigated the effects of shade stress on wheat flour protein composition and structure. The contents of the flour protein, α/ß-gliadins and disulfide and hydrogen bonds were significantly increased by shade stress. Glutenins, UPP%, and ß-sheet contents also increased, whereas that of α-helices decreased. Spearman correlations revealed that the flour protein content, Glu:Gli ratio, and disulfide, hydrogen, and ionic bonds can predict the specific volume and number of crumb cells in bread, whereas α/ß-gliadins content can predict the crumb cell wall thickness and diameter of bread. Under shade stress, variations in protein composition and structure help increase the specific volume and crumb cells number and decrease crumb cell wall thickness and diameter of bread, ultimately leading to improved baking quality.

Denitrification process of Casuarina root nodule endophyte Frankia.

To examine the characteristic of denitrification in Frankia, a symbiotic nitrogen-fixing microbe associated with non-leguminous plants, and its role as a N2O source or sink, Casuarina root nodule endophyte Frankia was isolated using sectioning method, which was then purely cultured to investigate the denitrification process under NO3- addition. The results showed that after addition of NO3- to the medium under anaerobic condition, the concentration of NO3- decreased with time, while the concentrations of NO2- and N2O initially increased and then decreased over time. Key denitrification genes and nitrogenase gene were detected at 26 h, 54 h and 98 h during incubation. Abundances of these genes significantly differed among each other, and their dynamics were asynchronous. Redundancy analysis of the effect of NO3-, NO2-, N2O concentrations on abundances of denitrification genes and nitrogenase gene indicated that 81.9% of the total variation in gene abundances could be explained by the first two axes. Frankia had a denitrifying activity under anaerobic condition, with denitrification genes, including nitrous oxide reductase gene (nosZ), being identified. Our results suggested that Frankia possessed a complete denitrification pathway and the ability of N2O reduction under anaerobic condition.

Shading affects the starch structure and digestibility of wheat by regulating the photosynthetic light response of flag leaves.

Heavy haze-induced decreases in solar radiation represent an important factor that affects the structural properties of starch macromolecules. However, the relationship between the photosynthetic light response of flag leaves and the structural properties of starch remains unclear. In this study, we investigated the impact of light deprivation (60 %) during the vegetative-growth or grain-filling stage on the leaf light response, starch structure, and biscuit-baking quality of four wheat cultivars with contrasting shade tolerance. Shading decreased the apparent quantum yield and maximum net photosynthetic rate of flag leaves, resulting in a lower grain-filling rate and starch content and higher protein content. Shading decreased the starch, amylose, and small starch granule amount and swelling power but increased the larger starch granule amount. Under shade stress, the lower amylose content decreased the resistant starch content while increasing the starch digestibility and estimated glycemic index. Shading during the vegetative-growth stage increased starch crystallinity, 1045/1022 cm-1 ratio, starch viscosity, and the biscuit spread ratio, while shading during the grain-filling stage decreased these values. Overall, this study indicated that low light affects the starch structure and biscuit spread ratio by regulating the photosynthetic light response of flag leaves.

Ruminococcaceae_UCG-013 Promotes Obesity Resistance in Mice.

Alterations in the gut microbiome have been linked to obesity and type 2 diabetes, in epidemiologic studies and studies of fecal transfer effects in germ-free mice. Here, we aimed to identify the effects of specific gut microbes on the phenotype of mice fed a high-fat diet (HFD). After eight weeks of HFD feeding, male C57BL/6J mice in the HFD group ranking in the upper and lower quartiles for body weight gain were considered obese prone and obese resistant, respectively. 16S rRNA gene sequencing was used to determine the composition of the intestinal microbiota, and fecal transplantation (FMT) was conducted to determine whether the microbiota plays a causal role in phenotypic variation. Ruminococcaceae_UCG-013 was more abundant in the gut microbes of mice with a lean phenotype than in those with an obese phenotype. Ruminococcaceae_UCG-013 was identified as the most significant biomarker for alleviating obesity by random forest analysis. In a correlation analysis of serum parameters and body weight, Ruminococcaceae_UCG-013 was positively associated with serum HDL-C levels and negatively associated with serum TC, TG, and LDL-C levels. To conclude, Ruminococcaceae_UCG-013 was identified as a novel microbiome biomarker for obesity resistance, which may serve as a basis for understanding the critical gut microbes responsible for obesity resistance. Ruminococcaceae_UCG-013 may serve as a target for microbiome-based diagnoses and treatments in the future.

Response of soil bacterial communities in wheat rhizosphere to straw mulching and N fertilization.

Straw mulching and N fertilization are effective in augmenting crop yields. Since their combined effects on wheat rhizosphere bacterial communities remain largely unknown, our aim was to assess how the bacterial communities respond to these agricultural measures. We studied wheat rhizosphere microbiomes in a split-plot design experiment with maize straw mulching (0 and 8,000 kg straw ha-1) as the main-plot treatment and N fertilization (0, 120 and 180 kg N ha-1) as the sub-plot treatment. Bacterial communities in the rhizosphere were analyzed using 16S rRNA gene amplicon sequencing and quantitative PCR. Most of the differences in soil physicochemical properties and rhizosphere bacterial communities were detected between the straw mulching (SM) and no straw mulching (NSM) treatments. The contents of soil organic C (SOC), total N (TN), NH4 +-N, available N (AN), available P (AP) and available K (AK) were higher with than without mulching. Straw mulching led to greater abundance, diversity and richness of the rhizosphere bacterial communities. The differences in bacterial community composition were related to differences in soil temperature and SOC, AP and AK contents. Straw mulching altered the soil physiochemical properties, leading to greater bacterial diversity and richness of the rhizosphere bacterial communities, likely mostly due to the increase in SOC content that provided an effective C source for the bacteria. The relative abundance of Proteobacteria was high in all treatments and most of the differentially abundant OTUs were proteobacterial. Multiple OTUs assigned to Acidobacteria, Chloroflexi and Actinobacteria were enriched in the SM treatment. Putative plant growth promoters were enriched both in the SM and NSM treatments. These findings indicate potential strategies for the agricultural management of soil microbiomes.

Parameter-tuning stochastic resonance as a tool to enhance wavelength modulation spectroscopy using a dense overlapped spot pattern multi-pass cell.

The parameter-tuning stochastic resonance (SR) method can convert part of the noise energy into the signal energy to suppress the noise and amplify the signal, comparing with traditional weak periodic signal detection methods (e.g., time average method, filtering method, and correlation analysis method). In this work, the numerical calculation is conducted to find the optimal resonance parameters for applying the SR method to the wavelength modulation spectroscopy (WMS). Under the stochastic resonance state, the peak value of 2f signal (a constant concentration of CH4∼20 ppm) is effectively amplified to ∼0.0863 V, which is 3.8 times as much as the peak value of 4000-time average signal (∼0.0231 V). Although the standard deviation also increases from ∼0.0015 V(1σ) to ∼0.003 V(1σ), the SNR can be improved by 1.83 times (from ∼25.9 to ∼15.8) correspondingly. A linear spectral response of SR 2f signal peak value to raw 2f signal peak value is obtained. It suggests that the SR method is effective for enhancing photoelectric signal under strong noise background.

Exploring complex water stress-gross primary production relationships: Impact of climatic drivers, main effects, and interactive effects.

The dominance of vapor pressure deficit (VPD) and soil water content (SWC) for plant water stress is still under debate. These two variables are strongly coupled and influenced by climatic drivers. The impacts of climatic drivers on the relationships between gross primary production (GPP) and water stress from VPD/SWC and the interaction between VPD and SWC are not fully understood. Here, applying statistical methods and extreme gradient boosting models-Shapley additive explanations framework to eddy-covariance observations from the global FLUXNET2015 data set, we found that the VPD-GPP relationship was strongly influenced by climatic interactions and that VPD was more important for plant water stress than SWC across most plant functional types when we removed the effect of main climatic drivers, e.g. air temperature, incoming shortwave radiation and wind speed. However, we found no evidence for a significant influence of elevated CO2 on stress alleviation, possibly because of the short duration of the records (approximately one decade). Additionally, the interactive effect between VPD and SWC differed from their individual effect. When SWC was high, the SHAP interaction value of SWC and VPD on GPP was decreased with increasing VPD, but when SWC was low, the trend was the opposite. Additionally, we revealed a threshold effect for VPD stress on GPP loss; above the threshold value, the stress on GPP was flattened off. Our results have important implications for independently identifying VPD and SWC limitations on plant productivity, which is meaningful for capturing the magnitude of ecosystem responses to water stress in dynamic global vegetation models.

Strong Bacterial Cellulose-Based Films with Natural Laminar Alignment for Highly Sensitive Humidity Sensors.

Humidity sensors have been widely used for humidity monitoring in industry and agriculture fields. However, the rigid structure, nondegradability, and large dimension of traditional humidity sensors significantly restrict their applications in wearable fields. In this study, a flexible, strong, and eco-friendly bacterial cellulose-based humidity sensor (BPS) was fabricated using a two-step method, involving solvent evaporation-induced self-assembly and electrolyte permeation. Rapid evaporation of organic solvent induces the formation of nanopores of the bacterial cellulose (BC) surface and promotes structural densification. Furthermore, the successful embedding of potassium hydroxide into the sophisticated network of BC effectively enhanced the sensing performance of BPS. The BPS exhibits an excellent humidity sensing response of more than 103 within the relative humidity ranging from 36.4 to 93% and strong (66.4 MPa) and high flexibility properties owing to the ultrafine fiber network and abundant hydrophilic functional groups of BC. Besides being strong and thin, BPS is also highly flexible, biodegradable, and humidity-sensitive, making it a potential candidate in wearable electronics, human health monitoring, and noncontact switching.

[Effects of Feedstock Material and Pyrolysis Temperature on Dissolved Organic Matter in Biochars].

The aim of this study was to investigate the effects of feedstock material and pyrolysis temperature on the content and spectral properties of dissolved organic matter(DOM) in biochars. Biochars were produced from the pyrolysis of rice straw and Cunninghamia lanceolata litter at three temperatures(350, 500, and 650℃). The results showed that the pH values of the two biochars with pyrolysis temperature increases were improved from 8.10 and 6.56 to 10.53 and 8.23, respectively. The pyrolysis temperature had no significant effect on the total C content of biochar, but the feedstock material and their interaction had significant effects on the total C content of the biochar(P<0.05). The dissolved organic carbon(DOC) content of the two types of biochar first decreased and then increased with increasing pyrolysis temperature, and the content of DOC of the biochar derived from rice straw was significantly higher than that from Cunninghamia lanceolata litter under the same temperature(P<0.05). The feedstock material had no significant effect on the SUVA254 value of DOM, but temperature and its interactive effect with the feedstock material had a significant effect on the SUVA254 values(P<0.05). Maximum DOC SUVA254 values occurred at 500℃ in the two types of biochar, indicating the highest degree of aromatization. Three-dimensional fluorescence spectra showed that the DOM components of the two types of biochar were dominated by fulvic acid-like and humic acid-like material, which had different responses to pyrolysis temperature. FTIR spectra suggested that the DOM of the biochars had absorption peaks at similar positions, in five regions, and the stretching vibration of aliphatic C-H gradually weakened with an increase in pyrolysis temperature. Therefore, the biochars produced at higher pyrolysis temperatures(500℃ and 650℃) had lower DOC contents but a higher aromatization degree and humification degree, and were more stable, compared to the biochars produced at a lower pyrolysis temperature(350℃).

Straw Mulching and Nitrogen Fertilization Affect Diazotroph Communities in Wheat Rhizosphere.

Diazotrophs that carry out the biological fixation of atmospheric dinitrogen (N2) replenish biologically available nitrogen (N) in soil and are influenced by the input of inorganic and organic substrates. To date, little is known about the effects of combined organic substrate addition and N fertilization on the diazotroph community composition and structure in purple soils. We investigated the effects of N fertilization and straw mulching on diazotroph communities by quantifying and sequencing the nifH gene in wheat rhizosphere. The abundance and richness of diazotrophs were greater the higher the fertilization level in the mulched treatments, whereas in the nonmulched treatments (NSMs), richness was lowest with the highest N fertilization level. The abundance and α-diversity of diazotrophs correlated with most of the soil properties but not with pH. At the genus level, the relative abundances of Azospirillum, Bacillus, and Geobacter were higher in the NSMs and those of Pseudacidovorax, Skermanella, Azospira, Paraburkholderia, Azotobacter, Desulfovibrio, Klebsiella, and Pelomonas in the mulched treatments. The differences in community composition between the mulched and the NSMs were associated with differences in soil temperature and soil organic carbon and available potassium contents and C:N ratio. Overall, straw mulching and N fertilization were associated with changes in diazotroph community composition and higher abundance of nifH gene in alkaline purple soils.