Polycyclic Aromatic Hydrocarbons Concentration in Straw Biochar with different Particle Size

AbstractBiochar, a carbon-rich material formed by a biomass pyrolyzed at relatively low temperatures (≤700°C), showed attractive sorption capacity on both organic pollutants and heavy metals and wildly used in various areas of environmental engineering. However, polycyclic aromatic hydrocarbons (PAHs) may also be assumed to be produced for the oxygen-limited pyrolysis condition in biochar production process. It is not well known about the affect of particle size in concentration and distributing characteristic of PAHs of biochar. In the current study, twenty-seven PAHs concentration in maize straw biochar produced with different powder particle size (9.31, 20.26, 60.77, 71.07, 101.9μm) were quantified, and the ∑27PAHs, total LMW PAHs, total MMW PAHs and total HMW PAHs concentration were analyzed. As the particle size increase, the ∑27PAHs concentrations show a trend of firstly increase and then decrease, and the maximum appears at 60.77μm (166.52 ng/g) and the minimum appears at 101.90μm (14.63 ng/g). LMW total PAHs and total MMW PAHs concentrations firstly increase and then decrease, with the particle size increasing from 9.31μm to 101.9μm. Meanwhile, the total HMW PAH concentrations decrease gradually when biochar particle size increasing. Compared to US, UK background soil concentrations and Canada standards, it is appropriate to conclude that PAHs in straw biochar have minimal effects after application to soil especially at 101.9μm

On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies

Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772–0.942, 0.774–0.970, 0754–0.960, and 0.800–0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index

Calibration of capacitive soil moisture sensor based on random forest

Objective Soil moisture information crucial for various applications, such as natural ecological restoration, farmland irrigation management, and soil engineering construction. One of the main sensors used to obtain this information is the capacitive soil moisture sensor. Methods To accurately calibrate the soil water content observation data of the 5TE capacitive soil water sensor, soil dielectric permittivity, electric conductivity and temperature observation experiments were carried out under different temperature, salt content and soil water content conditions. A soil water content estimation model based on the random forest machine learning method was established. Results The results showed that: ① The soil dielectric permittivity was significantly affected by varying salinity and temperature with constant soil water content. The traditional soil water content estimation model based only on soil dielectric permittivity became invalid, ② The soil water content estimation model based on the random forest method could effectively improve the soil water content estimation with the soil dielectric permittivity, electric conductivity and temperature data as input. Random forest method obtained soil moisture estimation with RMSE=0.05 m3/m3 and R2=0.77, while RMSE=0.07 m3/m3 and R2=0.54 were obtained by the modified Topp equation, and ③ The soil electric conductivity was the most important factor for soil water content estimation, followed by the dielectric permittivity and temperature. Nevertheless, the importance of the dielectric permittivity and temperature did not reach a negligible level. Conclusion This study provides a way to support the successful application of capacitive soil moisture sensors in areas with variable temperature and salinity

The Effect of Water Transfer during Non-growing Season on the Wetland Ecosystem via Surface and Groundwater Interactions in Arid Northwestern China

The use of ecological water transfer to maintain the ecological environment in arid or semiarid regions has become an important means of human intervention to alleviate vegetation ecosystem degradation in arid and semiarid areas. The water transfer to downstream in a catchment is often carried out during the non-growing season, due to the competitive water use between the upper and middle reaches and lower reaches of rivers. However, the impacts and mechanism of artificial water transfer on vegetation and wetland ecosystem restoration have not been thoroughly investigated, especially in northwest China. Taking the Qingtu Lake wetland system in the lower reaches of the Shiyang River Catchment as the study area, this study analyzed the spatial and temporal distribution surface area of Qingtu Lake and the surrounding vegetation coverage before and after water transfer, by interpreting remote sensing data, the variation of water content in the vadose zone, and the groundwater level by obtaining field monitoring data, as well as the correlation between the water body area of Qingtu Lake and the highest vegetation coverage area in the following year. The conclusion is that there is a positive correlation between the water body area of Qingtu Lake in autumn and the vegetation coverage in each fractional vegetation coverage (FVC) interval in the next summer, especially in terms of the FVC of 30–50%. The groundwater level and soil water content increase after water transfer and remain relatively high for the following months, which suggests that transferred water from upstream can be stored as groundwater or soil water in the subsurface through surface water and subsurface water interaction. These water sources can provide water for the vegetation growth the next spring, or support plants in the summer

Construction of 9<i>H</i>‑Pyrrolo[1,2‑<i>a</i>]indoles by a Copper-Catalyzed Friedel–Crafts Alkylation/Annulation Cascade Reaction

An efficient and concise Cu­(OTf)₂-catalyzed Friedel–Crafts alkylation/annulation cascade reaction of substituted indoles with 1,2-dicarbonyl-3-enes has been established. This reaction uses readily available starting materials and is operationally simple, thus representing a practical method for the construction of diverse 9<i>H</i>-pyrrolo­[1,2-<i>a</i>]­indoles bearing a carbonyl group

Transcriptome analysis of barley (Hordeum vulgare L.) under waterlogging stress, and overexpression of the HvADH4 gene confers waterlogging tolerance in transgenic Arabidopsis

Abstract Background Waterlogging is one of the major abiotic stresses in barley and greatly reduces grain yield and quality. To explore the mechanism controlling waterlogging tolerance in barley, physiological, anatomical and transcriptional analyses were performed in two contrasting barley varieties, viz. Franklin (susceptible) and TX9425 (tolerant). Results Compared to Franklin, TX9425 had more adventitious roots and aerenchymas and higher antioxidant enzyme activities. A total of 3064 and 5693 differentially expressed genes (DEGs) were identified in TX9425 after 24 h and 72 h of waterlogging treatment, respectively, while 2297 and 8462 DEGs were identified in Franklin. The results suggested that TX9425 was less affected by waterlogging stress after 72 h of treatment. The DEGs were enriched mainly in energy metabolism, hormone regulation, reactive oxygen species (ROS) scavenging, and cell wall-modifying enzymes. Alcohol dehydrogenase (ADH) plays an important role in response to waterlogging stress. We found that HvADH4 was significantly upregulated under waterlogging stress in TX9425. Transgenic Arabidopsis overexpressing HvADH4 displayed higher activity of antioxidant enzymes and was more tolerant to waterlogging than the wild type (WT). Conclusions The current results provide valuable information that will be of great value for the exploration of new candidate genes for molecular breeding of waterlogging tolerance in barley

Table_2_Genome-wide association scan and transcriptome analysis reveal candidate genes for waterlogging tolerance in cultivated barley.xlsx

Waterlogging is the primary abiotic factor that destabilizes the yield and quality of barley (Hordeum vulgare L.). However, the genetic basis of waterlogging tolerance remains poorly understood. In this study, we conducted a genome-wide association study (GWAS) by involving 106,131 single-nucleotide polymorphisms (SNPs) with a waterlogging score (WLS) of 250 barley accessions in two years. Out of 72 SNPs that were found to be associated with WLS, 34 were detected in at least two environments. We further performed the transcriptome analysis in root samples from TX9425 (waterlogging tolerant) and Franklin (waterlogging sensitive), resulting in the identification of 5,693 and 8,462 differentially expressed genes (DEGs) in these genotypes, respectively. The identified DEGs included various transcription factor (TF) genes, primarily including AP2/ERF, bZIP and MYB. By combining GWAS and RNA-seq, we identified 27 candidate genes associated with waterlogging, of which three TFs (HvDnaJ, HvMADS and HvERF1) were detected in multiple treatments. Moreover, by overexpressing barley HvERF1 in Arabidopsis, the transgenic lines were detected with enhanced waterlogging tolerance. Altogether, our results provide new insights into the genetic mechanisms of waterlogging, which have implications in the molecular breeding of waterlogging-tolerant barley varieties.</p

Table_1_Genome-wide association scan and transcriptome analysis reveal candidate genes for waterlogging tolerance in cultivated barley.xlsx

Waterlogging is the primary abiotic factor that destabilizes the yield and quality of barley (Hordeum vulgare L.). However, the genetic basis of waterlogging tolerance remains poorly understood. In this study, we conducted a genome-wide association study (GWAS) by involving 106,131 single-nucleotide polymorphisms (SNPs) with a waterlogging score (WLS) of 250 barley accessions in two years. Out of 72 SNPs that were found to be associated with WLS, 34 were detected in at least two environments. We further performed the transcriptome analysis in root samples from TX9425 (waterlogging tolerant) and Franklin (waterlogging sensitive), resulting in the identification of 5,693 and 8,462 differentially expressed genes (DEGs) in these genotypes, respectively. The identified DEGs included various transcription factor (TF) genes, primarily including AP2/ERF, bZIP and MYB. By combining GWAS and RNA-seq, we identified 27 candidate genes associated with waterlogging, of which three TFs (HvDnaJ, HvMADS and HvERF1) were detected in multiple treatments. Moreover, by overexpressing barley HvERF1 in Arabidopsis, the transgenic lines were detected with enhanced waterlogging tolerance. Altogether, our results provide new insights into the genetic mechanisms of waterlogging, which have implications in the molecular breeding of waterlogging-tolerant barley varieties.</p

DataSheet_1_Genome-wide association scan and transcriptome analysis reveal candidate genes for waterlogging tolerance in cultivated barley.docx

Waterlogging is the primary abiotic factor that destabilizes the yield and quality of barley (Hordeum vulgare L.). However, the genetic basis of waterlogging tolerance remains poorly understood. In this study, we conducted a genome-wide association study (GWAS) by involving 106,131 single-nucleotide polymorphisms (SNPs) with a waterlogging score (WLS) of 250 barley accessions in two years. Out of 72 SNPs that were found to be associated with WLS, 34 were detected in at least two environments. We further performed the transcriptome analysis in root samples from TX9425 (waterlogging tolerant) and Franklin (waterlogging sensitive), resulting in the identification of 5,693 and 8,462 differentially expressed genes (DEGs) in these genotypes, respectively. The identified DEGs included various transcription factor (TF) genes, primarily including AP2/ERF, bZIP and MYB. By combining GWAS and RNA-seq, we identified 27 candidate genes associated with waterlogging, of which three TFs (HvDnaJ, HvMADS and HvERF1) were detected in multiple treatments. Moreover, by overexpressing barley HvERF1 in Arabidopsis, the transgenic lines were detected with enhanced waterlogging tolerance. Altogether, our results provide new insights into the genetic mechanisms of waterlogging, which have implications in the molecular breeding of waterlogging-tolerant barley varieties.</p