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View from specialist: It is creative, and of certain scientific and educational value. Objective: To investigate the therapeutic effect and mechanism of Maimendong decoction on idiopathic pulmonary fibrosis by utilizing network pharmacology methods and combining experimental research.Methods: TCMSP, ETCM and Swiss ADME were used to screen the active ingredients of Maimendong decoction. Through PubChem, SwissTargetPrediction and Uniport databases, the action targets of various components of traditional Chinese medicine were screened. The GeneCards database and OMIN database were applied to obtain target genes of idiopathic pulmonary fibrosis. Venn diagrams drawing tool was used to screen the intersection targets of traditional Chinese medicine and diseases. The "traditional Chinese medicine active ingredient disease target" network diagram was constructed by using the Cytoscape 3.9.1 software, and the protein interaction network (PPI) was constructed by using the CytoNCA plug-in to screen the core target proteins. DAVID was used for enrichment analysis of GO and KEGG pathways. Finally, we used bleomycin to establish a pulmonary fibrosis model in SD rats, observed the macroscopic specimens and pathological sections of rat lung tissue, and conducted real-time fluorescence quantitative PCR analysis to compare the mRNA expression levels of TGF-β1, α-SMA, IL-4, IFN-γ, LC3-II, and beclin1 between the treatment group and the control group. Results:A total of 402 therapeutic targets of Maimendong decoction for IPF were screened, including 50 core targets, corresponding to 159 active ingredients of 5 traditional Chinese medicines. GO enrichment analysis and KEGG enrichment analysis involved the PI3K-AKT signal pathway, MAPK signal pathway and other signal pathways to treat idiopathic pulmonary fibrosis. The animal experiment results showed that compared with the model group, the Maimendong decoction group could significantly reduce the relative expression level of TGF-β1, α-SMA and IL-4 mRNA (P<0.05), significantly upregulated the relative expression level of mRNA LC3-II, beclin1, IFN-γ (P<0.05) .Conclusion: This study suggests that the key active components of Maimendong decoction may play a role in biological processes such as autophagy, inflammatory reaction, macrophage polarization, and improve pulmonary fibrosis. [ABSTRACT FROM AUTHOR]

Soil surface topography affects fundamental hydrologic processes, such as infiltration and soil water percolation. Topographic variations potentially alter both the magnitude and directions of unsaturated flow The objective of this study is to evaluate the effects of surface topography on wetting front moving patterns under different rainfall and soil conditions through combined experimental and numerical modelling studies. Specifically, laboratory-scale infiltration and unsaturated flow experiments and HYDRUS-2D modelling were conducted for different topographic surfaces, rainfall intensities, and soil types. The simulated and observed wetting front distributions were compared and evaluated. Two different stages were observed: topography-dominated two-dimensional flow and uniform one-dimensional flow. A uniformly distributed wetting front was eventually achieved although soil surfaces had dissimilar topographic characteristics. However, the timing or duration to reach such a uniform flat wetting front varied, mainly depending on surface topography, rainfall characteristics, and soil hydraulic properties. The findings from this study are important to better understand the mechanism of topography-controlled unsaturated flow, wetting front movement, and overland flow generation, and to further improve modelling of soil water flow and transport processes under such complex conditions across different scales. Additional keywords: HYDRUS, surface roughness, unsaturated flow, vadose zone., Introduction Many experimental studies have quantified wetting front movement in unsaturated soils under different conditions. For example, Bernadiner (1998) investigated the capillary microscale structure of wetting fronts, and the mechanism [...]

A study was conducted at three sites in North Dakota to strengthen understanding of the usefulness of different proximal geophysical data types in agricultural contexts of varying pedology. This study hypothesizes that electromagnetic induction (EMI), gamma‐ray sensor (GRS), cosmic‐ray neutron sensor (CRNS), and elevation data layers are all useful in multiple linear regression (MLR) predictions of soil properties that meet expert criteria at three agricultural sites. In addition to geophysical data collection with vehicle‐mounted sensors, 15 soil samples were collected at each site and analyzed for nine soil properties of interest. A set of model training data was compiled by pairing the sampled soil property measurements with the nearest geophysical data. Eleven models passed expert‐defined uncertainty criteria at Site 1, 16 passed at Site 2, and 14 passed at Site 3. Electrical conductivity (EC), organic matter (OM), available water holding capacity, silt, and clay were predicted at Site 1 with an R‐squared of prediction (Rpred2)$(R_{pred}^2)$ >.50 and acceptable root mean square error of prediction (RMSEP). Bulk density (BD), OM, available water capacity, silt, and clay were predicted with Rpred2$R_{pred}^2$ >.50 and acceptable RMSEP at Site 2. At Site 3, no soil properties were predicted with acceptable RMSEP and an Rpred2$R_{pred}^2$ >.50. These results confirm feasibility of our method, and the authors recommend the prioritization of EMI data collection if geophysical data collection is limited to a single mapping effort and calibration soil samples are few. Core Ideas: Framework given to assess relationships between proximal sensing and soil properties.Correlations between sensing data and soil properties varied among three study sites.Electromagnetic induction was most consistently useful in soil property prediction. [ABSTRACT FROM AUTHOR]

Drainage water recycling (DWR) involves capture, storage, and reuse of surface and subsurface drainage water as irrigation to enhance crop production during critical times of the growing season. Our objectives were to synthesize 53 site-years of data from 1996 to 2017 in the midwestern United States to determine the effect of DWR using primarily subirrigation on corn (Zea mays L.) grain yield and yield variability and to identify precipitation factors at key stages of corn development (V1-V8, V9-VT, R1-R2, R3-R4, and R5-R6) that correlated to an increase in yield with DWR. A generalized additive model was used to quantify and characterize the relationship between precipitation and corn grain yield during corn development stages and to determine if that relationship differed between DWR and free drainage (FD). Corn yield response to precipitation was generally similar between DWR and FD, except during the critical period of V9-R2, in which DWR was more resilient to precipitation extremes than FD. Drainage water recycling was generally more responsive than FD in years with low and normal precipitation (<181 mm). When precipitation was low (27-85 mm) from V9 to R2, DWR had higher yields (77% of the site-years evaluated), with an average yield increase of 3.6 Mg ha-1 (1.2-7.5 Mg ha-1). Overall, FD had 28% greater yield variability than DWR. Additional research is needed on DWR impacts on different soils and locations throughout this region to improve the stability of corn yields and to develop automated DWR systems for enhancing efficiency of water management with increasing climate variability. [ABSTRACT FROM AUTHOR]

The potential impact of controlled drainage (CD), which limits drainage outflow, and subirrigation (SI), which provides supplemental water through drain tile, on surface water quality are not well known in the Red River Valley (RRV). In this study, water samples were collected and analyzed for chemical concentrations from a tile-drained field that also has controlled drainage and subirrigation modes in the RRV of southeastern North Dakota from 2012–2018. A decreasing trend in overall nutrient load loss was observed because of reduced drainage outflow, though some chemical concentrations were found to be above the recommended surface water quality standards in this region. For example, sulfate was recommended to be below 750 mg/L but was reported at a mean value of 1971 mg/L during spring free drainage. The chemical composition of the subirrigation water was shown to have an impact on drainage water and the soil, specifically on salinity-related parameters, and the impact varied between years. This variation largely depended on the amount of subirrigation applied, soil moisture, and soil properties. Overall, the results of this study show the benefits of controlled drainage on nutrient loss reduction from agricultural fields. [ABSTRACT FROM AUTHOR]

Pulmonary fibrosis is a kind of interstitial lung disease with architectural remodeling of tissues and excessive matrix deposition. Apart from messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA), and circular RNA (circRNA) could also play important roles in the regulatory processes of occurrence and progression of pulmonary fibrosis. In the present study, the pulmonary fibrosis model was administered with bleomycin. Whole transcriptome sequencing analysis was applied to investigate the expression profiles of mRNAs, lncRNAs, circRNAs, and miRNAs. After comparing bleomycin-induced pulmonary fibrosis model lung samples and controls, 286 lncRNAs, 192 mRNAs, 605 circRNAs, and 32 miRNAs were found to be differentially expressed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to investigate the potential functions of these differentially expressed (DE) mRNAs and non-coding RNAs (ncRNAs). The terms related to inflammatory response and tumor necrosis factor (TNF) signaling pathway were enriched, implying potential roles in regulatory process. In addition, two co-expression networks were also constructed to understand the internal regulating relationships of these mRNAs and ncRNAs. Our study provides a systematic perspective on the potential functions of these DE mRNAs and ncRNAs during PF process and could help pave the way for effective therapeutics for this devastating and complex disease. [ABSTRACT FROM AUTHOR]

Human‐induced landscape changes affect hydrologic responses (e.g., floods) that can be detected from a suite of satellite and model data sets. Tapping these vast data sets using machine learning algorithms can produce critically important and accurate insights. In the Red River of the North Basin in the United States, agricultural subsurface drainage (SD; so‐called tile drainage) systems have greatly increased since the late 1990s. Over this period, river flow in the Red River has markedly increased and 6 of 13 major floods during the past century have occurred in the past two decades. The impact of SD systems on river flow is elusive because there are surprisingly few SD records in the United States. In this study, Random Forest machine learning (RFML) classification method running on Google Earth Engine's cloud computing platform was able to capture SD within a field (30 m) and its expansion over time for a large watershed (>100,000 km2). The resulting RFML classifier drew from operational multiple satellites and model data sets (total 14 variables with 36 layers including vegetation, land cover, soil properties, and climate variables). The classifier identified soil properties and land surface temperature to be the strongest predictors of SD. The maps agreed well with SD permit records (overall accuracies of 76.9–87.0%) and corresponded with subwatershed‐level statistics (r = 0.77–0.96). It is expected that the maps produced with this data‐intensive machine learning approach will help water resource managers to assess the hydrological impact from SD expansion and improve flood predictions in SD‐dominated regions. Plain Language Summary: Farmers install subsurface drainage pipes (so‐called tile drainage) to improve crop yields on poorly drained soils, which impacts hydrological response (e.g., floods). Consistent records of subsurface drainage expansion are needed to understand its impacts on water resources. In the Red River of the North Basin in the United States, subsurface drainage systems have increased since the late 1990s. Over this period, river flow in the Red River has markedly increased and 6 of 13 major floods during the past century have occurred in the past two decades. Because the current National Oceanic and Atmospheric Administration's National Weather Service flood forecasting model does not include subsurface drainage information, they sometimes overpredict or underpredict flood flows. We developed high‐resolution (30 m) subsurface drainage maps by combining multiple satellite "big" data and model products using a Random Forest machine learning classification via Google Earth Engine's cloud computing platform. The maps showed good agreement with available subsurface permit records. It is expected that the machine learning‐based subsurface drainage maps will help water resource managers and flood forecasters to improve flood prediction in agricultural dominated regions. Key Points: High‐resolution subsurface drainage maps were developed using satellite big data and random forest machine learning via Google Earth EngineReliable subsurface drainage records are needed for sustainable water resource management, but such records are very limited in the United StatesWhile soil variables are important to identify potential drainage areas, land surface temperature distinguishes where drainage has occurred [ABSTRACT FROM AUTHOR]

The Red River of the North basin (RRB) is vulnerable to spring snowmelt flooding because of its flat terrain, low permeability soils, and the presence of river ice jams resulting from the river's northward flow direction. The onset and magnitude of major flood events in the RRB have been very difficult to forecast, in part due to limited field observations of snow water equivalent (SWE). Coarse-resolution (25-km) passive microwave observations from satellite instruments are well suited for the monitoring of SWE. Despite routine use in the Earth sciences community to document the impacts of climate change, the use of passive microwave observations in operational flood forecasting is rare. This paper compares daily satellite passive microwave SWE observations from special sensor microwave/imager (SSM/I) and special sensor microwave imager/sounder (SSMIS), advanced microwave scanning radiometer for earth observing system (AMSR-E), and advanced microwave scanning radiometer 2 (AMSR2) from 2003 to 2016 to modeled output from the SNOw Data Assimilation System (SNODAS) and Global Snow Monitoring for Climate Research -2 (GlobSnow-2) in the RRB to determine the differences between the remotely sensed SWE estimates and the model products currently used in flood forecasting. Results show statistically significant differences between the satellite observations and SNODAS in the northern region of the basin that were not evident in the southern region. Satellite estimates of peak SWE in the forecast subbasins in the northern region were 40–125% higher than the model results which points to the lack of ground observations used to constrain the model simulations. This paper recommends that satellite SWE observations should be considered for improving operational snowmelt forecasting in the RRB. [ABSTRACT FROM AUTHOR]

Core Ideas: Soil moisture is needed in defining well‐watered turfgrass condition in evapotranspiration measurement.Deep soil moisture supports turfgrass growth when surface soil moisture is not sufficient.The ETa can be estimated from 0.96 ETo using the ASCE‐EWRI standardized method for well‐watered turfgrass.The ASCE‐EWRI standardized reference ET equation can be used for water management of turfgrass in northern cool climates and during drought periods. Turfgrass actual evapotranspiration (ETa) measurements are critical for water management and irrigation scheduling. With no historical ETa measurements in eastern North Dakota, turfgrass ETa rates were measured with the residual method using eddy covariance instrumentation and two arrays of soil moisture sensors on unirrigated turfgrass under natural conditions in the 2011, 2012, and 2013 growing seasons. An on‐site weather station provided weather data to calculate the standardized grass‐based reference evapotranspiration (ETo) (Allen et al., 2005). The daily ETa/ETo ratios were screened using the criteria of soil moisture ≥50% of available water for the top 30 cm of the root zone, rain amounts ≤10 mm, and a recovering period after drought. The screened monthly average ETa/ETo ratios for the unirrigated turfgrass were 1.03, 0.98, 0.94, 0.90, 0.82, and 1.18 from May to October. The mean ETa/ETo ratio for the entire growing seasons was 0.96, implying that the American Society of Civil Engineering–Environmental and Water Resource Institute ETo method was valid for guiding the turfgrass ETa calculation even in unirrigated and cold climate conditions. Because this is the first reported study on ETa measurement of a turfgrass site, the limited data can provide a baseline on water management for turfgrass under various weather conditions in this region. The results indicated that a monthly refinement of ETa/ETo values might be required to maintain the landscape turfgrass quality more precisely in terms of water management. [ABSTRACT FROM AUTHOR]

Emodin is the main pharmacodynamic components of rhubarb, with significant pharmacological effects and clinical efficacy.Emodin has a variety of therapy effects, such as anti-cancer, anti-fibrosis effects, and is widely used to treat encephalitis, diabetic cataract and organ fibrosis. Several studies have shown that emodin has a good treatment effect on organ fibrosis, but the mechanism is complex. Moreover, the evidence of some studies is conflicting and confusing. This paper reviewed the mechanism, pharmacokinetics and toxicology of emodin in fibrosis treatment, and briefly discussed relevant cutting-edge new formulations to improve the efficacy, the result can provide some reference for future study. [Display omitted] [ABSTRACT FROM AUTHOR]

Transient receptor potential vanilloid type 1 (TRPV1), involved in multiple pathophysiological processes including inflammation, is a thermally activated, non-selective cation channel. It has been identified that TRPV1 is highly involved in some common respiratory diseases including allergic rhinitis, asthma, chronic obstructive pulmonary disease, and pulmonary infection by participating in neurogenic and immunogenic inflammation, sensitization, and oxidative stress. In recent years, the hypothesis of transient receptor potential (TRP) has been introduced in studies on the theory of five flavors and four properties of Chinese medicinal. However, the hypothesis is undetermined due to the multi-component and multi-target characteristics of Chinese medicinal. This study describes the relations between TRPV1 and four types of respiratory diseases based on the literature in recent five years. In the meantime, the therapeutic effect of Chinese medicinal by intervening TRPV1 was reviewed, in an attempt to provide certain evidence for future studies on the medicinal property-effect relationship, mechanism of drug action, the syndrome differentiation in traditional Chinese medicine (TCM) for respiratory diseases and to help for new drug development. [Display omitted] • Discussion of TRPV1-mediated respiratory disease pathology. • Discussion of potential mechanisms for commonly used Chinese herbs for treating respiratory diseases. • Discussion of potential mechanisms for commonly used Chinese medicinal compounds for treating respiratory diseases. • Discussion of TRPV1-mediated theory of five flavors and four properties of Chinese medicinal. [ABSTRACT FROM AUTHOR]

A field experiment was conducted during the 2009 and 2010 growing seasons to determine the effect of subsurface drainage (SSD) on evapotranspiration (ET) and crop coefficients () for a farm field in the Red River Valley of North Dakota. The total area of the field was 44 ha, half of which had subsurface drainage installed in the fall of 2002 at an approximate depth of 1.1 m and a spacing of 18.3 m. Corn ( Zea mays) was planted in 2009 and soybean ( Glycine max) in 2010. Evapotranspiration rates were measured in both the SSD and surface drained [or undrained (UD)] by using the eddy covariance (EC) method. The changes in water table and soil moisture content were monitored continuously in both fields. The for corn and soybean was developed by using the ET measured by the EC system, and the reference ET was estimated by using the American Society of Civil Engineers Environmental and Water Resources Institute alfalfa reference method. As expected, the use of SSD affected the ET in a seasonal pattern and the ET was crop dependent. Seasonally, higher ET was observed during spring and fall in the UD field attributable to shallower water table and higher soil moisture content. In the summer, a higher ET was found in the SSD field. The higher ET in the UD field in spring and fall, which was 109 and 191 mm in 2009 and 2010, compared with 105 and 176 mm in 2009 and 2010 in the SSD field, did not offset the higher ET in the SSD field in the summer, which was 310 and 351 mm in 2009 and 2010, compared with 249 and 324 mm in 2009 and 2010 in the UD field. For July and August, the ET in the SSD field was 31% greater in 2009 for corn and 14% greater in 2010 for soybean than that in the UD crop fields. For the entire growing season, the ET in the SSD field was 16% higher in 2009 and 7% higher in 2010 compared with the UD field. During the peak growing season (July), the was greater in the SSD field, with peak values of 0.70 for corn and 0.76 for soybean, but in the UD field, the peak values were only 0.54 for corn and 0.65 for soybean. [ABSTRACT FROM AUTHOR]

In North Dakota, agriculture contributes a large sector of the state's economy, but vegetable production is limited due to the state's climate condition. Inadequate soil moisture and low soil temperature are the two major factors prohibiting quality produce and high-yield vegetable production. In this study, a soil-water potential, sensor-based drip irrigation system was developed, designed, and installed to evaluate its application on tomato and watermelon productions in a two-year field experiment in 2019 and 2020. The experimental treatments were drip irrigation and no irrigation under three mulches: black plastic, clear plastic, and landscape fabric mulches. Irrigation was scheduled at 8:00 am for watermelon and 9:00 a.m. for tomato, with the ability for each irrigation event to be bypassed based on the soil moisture conditions. Due to rainfall differences in the two years, irrigation was barely needed in 2019, but in 2020, drip irrigation was applied frequently. On average, for the two-years' field experiment, the highest yield for tomatoes was obtained from drip irrigation under black plastic drip irrigation treatment with 40.24 Mg ha−1 in 2020, whereas the highest yield for watermelon was from drip irrigation under clear plastic mulch with 165.55 Mg ha−1 in 2020. The effect of mulch, irrigation, and combined practices were analyzed based on the average fruit weight and diameter, electrical conductivity (EC), pH, and sugar content of the samples. The results showed that for watermelon, the average weight and diameter were significantly heavier and higher with irrigation treatments, but the EC and the pH values were significantly higher with mulch treatments. For tomatoes, the average weight, diameter, pH, and sugar content were all significantly higher with mulch treatment, but the EC was higher with irrigation treatment. [ABSTRACT FROM AUTHOR]

Predicting surface runoff and flooding in seasonally frozen areas such as the Red River of the North Basin (RRB) in USA is a challenging task. It depends on the knowledge of the complex process of infiltration in frozen soil, such as phase changes of water, ice content and distribution in the infiltration zone (the top 0–30 cm of the soil profile), soil pore size distribution, soil temperature and freeze–thaw cycles. In this study, the infiltration rates into frozen soil (Colvin silty clay loam according to the United States Department of Agriculture (USDA) Classification, and Chernozem according to Food and Agriculture Organization of the United Nations (FAO) international soil Classification) were measured at three different initial water contents: permanent wilting point (PWP), θpwp; field capacity (FC), θfc; and between FC and PWP, θmid. Laboratory infiltration experiments were conducted using a Cornell sprinkle infiltrometer with three replications for each initial water content. Volumetric soil water content (θv) and soil temperature at three depths were also continuously monitored using sensors. The average infiltration rates were 0.66, 0.38, and 0.59 cm/min for three initial water contents (θpwp, θmid, and θfc, respectively). Initial infiltration into frozen soil occurred quickly in the soil with θpwp because the soil was dry. Melted ice water contributed to the total soil water content over time, so it made the initial infiltration comparatively slower in the soil with θmid. Initial infiltration was also slower in the soil with θfc because the wet soil had very small pore space, so the soil rapidly reached its saturation after the infiltration started. The Horton infiltration equation was fitted with the observed infiltration rates for the soils with three initial water contents, and the goodness of fit was evaluated by using the coefficient of determination (R2) and the root-mean-square error (RMSE). The final infiltration rates from the fitted Horton equations were 0.060, 0.010, and 0.027 cm/min for the initial water contents (θpwp, θmid, and θfc, respectively). The soil water content along the soil profile changed with the amount of infiltrating water over time. However, the initial soil water content and melt water from ice resulting from soil temperature rise regulated the change in soil water content. The amount of ice melt water contribution to soil water content change varied among the soils with different initial water contents (θpwp, θmid, and θfc, respectively). The θv changed gradually in the θpwp soil, rapidly at 0 °C in the θmid soil, and less in the θfc soil. The change in pore distribution due to freeze–thaw cycles and soil packing altered the soil hydraulic properties and the infiltration into the soil. This study can provide critical information for flood forecasting model and subsurface drainage design in the RRB. [ABSTRACT FROM AUTHOR]

As an important component of the water budget, quantifying actual crop evapotranspiration (ET) will enable better planning, management, and allocation of the water resources. However, accurate ET measurement has always been a challenging task in agricultural water management. In the upper Midwest, where subsurface drainage is a common practice due to the shallow ground water depth and heavy clayey soil, ET measurement using traditional ground-based methods is more difficult. In this study, ET was measured using the eddy covariance (EC), Bowen ratio-energy balance (BREB), and soil water balance (SWB) methods during the 2018 corn growing season, and the results of the three methods were compared. To close the energy balance for the EC system, the residual method was used. For the SWB method, capillary rise was included in the ET estimation and was calculated using the measured soil water potential. The change of soil water content for ET estimation using the SWB method was calculated in four different ways, including daily average, 24:00–2:00 average, 24:00–4:00 average, and 4:00 measurement. Through the growing season, six observation periods (OPs) with no rainfall or minimal rainfall events were selected for comparisons among the three methods. The estimated latent heat flux (LE) by the EC system using the residual method showed a 29% overestimation compared to LE determined by the BREB system for the entire growing season. After excluding data taken in May and October, LE determined by the EC system was only 10% higher, indicating that the main difference between the two systems occurred during the early and late of the growing season. By considering all six OPs, a 6%–22% LE difference between the EC and the BREB systems was observed. Except during the early growing and late harvest seasons, both systems agreed well in LE estimation. The SWB method using the average soil water contents between 24:00 and 2:00 time period to calculate the daily capillary rise produced the best statistical fit when compared to the ET estimated by the BREB, with a root-mean-square error of 1.15. Therefore, measuring ET using the capillary rise from a shallow water table between 24:00 and 2:00 could improve the performance of the SWB methodology for ET measurement. [ABSTRACT FROM AUTHOR]

• Enhanced evapotranspiration due to subirrigation application in dry years. • Positive yield effect due to controlled drainage during a wet year. • Developed crop coefficients for days with more than 45% of total available water in the corn root zone. • Off-season precipitation recharged the soil profile and benefited crop growth in the spring. Over the past 20 years, marketplace demand for corn has prompted many farmers in the Red River Valley (RRV) of the north to include more corn in their crop rotations. With a very flat topography and heavy clayey soils, the RRV can have shallow water tables in the spring and fall but can be dry in the summer. Due to these field conditions, some farmers have installed subsurface drainage (SD) systems with structures for controlled drainage (CD, manage the water table in a field) and subirrigation (SI, add water to the field via the SD system) to improve corn production. In a CD + SI field, an eddy covariance system was used to measure and quantify energy flux components along with soil moisture content (SWC) and water table depth (WTD) measurements during four corn growing seasons in 2012, 2013, 2016 and 2017. The results show that the average SWC in 2012 was significantly different from the other three years. The SWC and WTD in 2016 were more stable compared to the other years. The CD practice had a positive effect during a wet year in 2013, which resulted in 26.7% higher yield than the county average. During the dry growing season of 2017, the use of subirrigation resulted in 6.6% higher yield than the county average. The corn evapotranspiration totals (ET a) were 468, 476, 551, and 537 mm for 2012, 2013, 2016, and 2017 growing seasons, respectively. The average crop coefficients were 0.49, 0.73, 0.88, 0.86, and 0.69 for the initial, development, tasseling, reproductive, and maturity stages, respectively. They were calculated from the daily ET a , values only from days with more than 45% of total available water in the root zone, and the ASCE-EWRI standardized grass-based reference evapotranspiration. This study showed that the SD along with the CD + SI system can be used for optimal water management of field corn during both wet and dry years. [ABSTRACT FROM AUTHOR]

Lysimeter experiments were conducted under greenhouse conditions to investigate canola (Brassica napus L.) plant water use, growth, and yield parameters for three different water table depths of 30, 60, and 90 cm. Additionally, control experiments were conducted, and only irrigation was applied to these lysimeters without water table limitations. The canola plant's tolerance level to shallow groundwater was determined. Results showed that groundwater contributions to canola plant for the treatments at 30, 60, and 90 cm water table depths were 97%, 71%, and 68%, respectively, while the average grain yields of canola were 4.5, 5.3, and 6.3 gr, respectively. These results demonstrate that a 90 cm water table depth is the optimum depth for canola plants to produce a high yield with the least amount of water utilization. [ABSTRACT FROM AUTHOR]

Water table contribution to plant water use is a significant element in improving water use efficiency (WUE) for agricultural water management. In this study, lysimeter experiments were conducted in a controlled greenhouse environment to investigate the response of soybean water uptake and growth parameters under four different water table depths (WTD) (30, 50, 70, and 90 cm). Soybean crop water use, WUE, and root distribution under the different WTD were examined. For 30, 50, 70, and 90 cm of WTD treatments, the average water table contributions were 89, 83, 79, and 72%; the grain yields were 15.1, 10.5, 14.1, and 17.2 g/lys.; and the WUEs were 0.22, 0.18, 0.25, and 0.31 g/lys./cm, respectively. Further analysis of the root mass and proportional distribution among the different soil layers illustrated that the lysimeters with 70 and 90 cm WTD had greater root mass with higher root distribution at 40–75 cm of the soil layer. The results indicated that 70 and 90 cm of constant WTD can yield higher grain yield and biomasses with greater WUE and better root distribution than the irrigated or shallow WTD treatments. [ABSTRACT FROM AUTHOR]

Two types of fibrous adsorbents, thiol- and amino- functionalized polysilsesquioxane coated poly( p -phenylenetherephthal amide) (PPTA) fibers (PPTA-PAPSQ and PPTA-PMPSQ), were prepared via the in situ condensations with aminopropyltriethoxysilane (APTES) and mercaptopropyltriethoxysilane (MPTES) on the surface of PPTA fibers, respectively. Their structures were characterized by FTIR, FE-SEM, XPS, XRD, TG, Elemental analysis, and pore structure analysis. The effect of the ratio of reactants on the structures of these two modified fibers was investigated. The results of nitrogen adsorption-desorption isotherms revealed that the polysilsesquioxane coating on the surface of PPTA-PMPSQ samples exhibited open meso- or macroporous features, while those on the surface of PPTA-PAPSQ samples formed dense gel structures. Moreover, Hg (II) was chosen as a representative to evaluate the adsorption properties of PPTA-PAPSQ and PPTA-PMPSQ samples. The results showed that the adsorption processes of Hg(II) followed well pseudo-second-order model onto the two series adsorbents. The Langmuir was the better-fit model to predict the experimental data. The theoretical saturation adsorption capacities of polysilsesquioxanes coated on the PPTA-PAPSQ and PPTA-PMPSQ adsorbents can reach 3.52–10.64 mmol g −1 and 7.43–10.22, mmol g −1 , respectively. The result showed that PPTA-PAPSQ and PPTA-PMPSQ adsorbents can selectively adsorb Hg(II) from binary component metal ion systems. [ABSTRACT FROM AUTHOR]