The City of Meycauayan is considered as one of the most polluted cities in the developing world on the account of industrial discharges of toxic materials to the environment. This work investigated the sources of the heavy metal pollution by analyzing soil and sediment samples for heavy metals (Cr, Hg, Ni, and Pb) together with selected environmental indicators (TN, TOM, and TP) located along the Meycauayan River. Hierarchical cluster analysis (HCA), principal components analysis (PCA), and Pearson correlation analysis (CA) were used to identify the sources of the metals. Results showed delineated locations of severe levels of heavy metal pollution downstream because of the concentration of industrial activities. Cr contributed more than any other heavy metals analyzed due to proliferation of tanneries discharging untreated wastewaters to the river. Significant inputs of Pb and Hg from Pb-acid battery recycling and gold smelting industries were also found. Risk assessments indicated severe levels of heavy metal pollution where industrial activities are concentrated. The mean Cr, Pb, Ni, and Hg in the sampling locations have mean incidences of toxicity of 91.7 %, 53.6 %, 27.7 %, and 70.0 %, respectively. Our study showed a serious need to address heavy metal pollution in Meycauayan.

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems, enhancing the understanding hydrological processes, optimizing the allocation and distribution of water resources, and assessing, forecasting and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors or satellite observations. These data are utilized in describing both small and large scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically evolve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing not just high spatial detail over relatively large areas in a cost-effective way, but as importantly providing an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and applications specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, post-processing techniques, retrieval algorithms and evaluations techniques need to be harmonized. The aim of this paper is to provide a comprehensive general overview of the existing research on studies and applications of UAS in environmental monitoring in order to suggest users and researchers on future research directions, applications, developments and challenges.

The research objectives were (1) to examine the determinants of community empowerment towards the revegetation of Arjuna mount forests; (2) assessing the influence of geography and soil conditions on the revegetation of Arjuna mount forests; (3) reviewing the effect of Arjuna mount forest revegetation on the preservation of spring water sources and (4) formulate a model of community empowerment around the forest based on revegetation of Arjuna mount and preservation of the area around the springs. The method used was descriptive method. While based on the techniques and tools used to research, the author uses the survey method to obtain facts that occur in the research area, namely in the area around the spring of the Kedunglarangan and Gumandar Prigen watersheds, Pasuruan Regency. Data obtained in the field are then processed and analyzed using GIS, ArcView 3.3 and Google Earth programs. The study population covering the community around the forest and springs, who lived in three villages, namely Leduk, Jatiarjo and Dayurejo village, Pasuruan, East Java-Indonesia. Data obtained from respondents with questionnaires and analyzed using SEM (structural equation modeling), to find out a general description of respondents' responses about community participation in the preservation of Arjuna mount forest. The results showed that (1) human resources, economic, social, local institutional factors, facilities and infrastructure had a very significant effect on forest revegetation; (2) geography and land variables have a significant effect on forest revegetation; (3) forest revegetation variables have a significant effect on the preservation of springs; and (4) The development of human resources, economic, local institutional, facilities and infrastructure in the community around the forest was a relevant model for the success of forest revegetation and the preservation of springs in Arjuna mount.

P-band radar remote sensing applied during the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) mission has shown great potential for estimation of root zone soil moisture. When retrieving the soil moisture profile (SMP) from P-band radar, a mathematical function describing the vertical moisture distribution is required. Because only a limited number of observations are available, the number of free parameters of the mathematical model must not exceed the number of observed data. For example, a second order polynomial that contains 3 free parameters was presumed based on in-situ SMP data. The polynomial is currently parameterized based on 3 backscatter observations provided by AirMOSS (i.e. one frequency at three polarizations of HH, VV and HV). In this paper, a more realistic, physically-based SMP model containing 3 free parameters is derived based on a solution to Richards’ equation for unsaturated flow in soils. Evaluation of the new SMP model based on both numerical simulations and measured data revealed that it exhibits greater flexibility for fitting measured and simulated SMPs than the currently applied polynomial. It is also demonstrated that the new SMP model can be reduced to a second order polynomial at the expense of fitting accuracy.

Green manure could improve soil nutrients and crop production, playing a significant role in sustainable agriculture. However, the impacts of green manure on crop health and the roles soil microbial communities play in the process haven’t been clarified clearly yet. In this study, we investigated soil microbial community composition and structure in four tobacco farmlands, which were treated with different green manure (control, ryegrass, pea and rape), using 16S rRNA gene amplicons sequencing. Results showed that green manure had significant impacts on soil properties, microbial communities and tobacco health. First, soil total C, N and Ca content increased significantly in groups treated with green manure than control. Second, soil community diversity was significantly higher in groups treated with green manure. Third, green manure especially ryegrass, decreased tobacco disease (bacterial wilt) rate dramatically, and the process might be mediated by soil microbial communities. On the one hand, several microbial populations were found to be potentially disease inducible or suppressive. For example, the abundances of Dokdonella and Rhodanobacter were positively correlated to tobacco disease rate, while Acidobacteira_Gp4 and Gp6 had negative correlations with tobacco disease. On the other hand, soil microbial communities were shaped by soil properties (e.g., pH, C and N content). In conclusion, our research showed that green manure could increase soil nutrients directly, and further improve tobacco health mediated by soil microorganisms, which may shed light on revealing interactions among soil properties, microorganisms and plants.

This study was conducted to explore the potential of superabsorbent polymers (SAPs) from used disposable diapers as soil moisture conditioner. Swelling behavior of the proposed hydrogel in response to external stimuli such as salt solutions, temperature and pH was studied. In addition, laboratory experiments were carried out to evaluate the effects of incorporation hydrogel on germination of bean (Phaseolus vulgaris L.) and pumpkin (C. pepo) seeds. The structure of the superabsorbent was characterized by Fourier transform infrared spectroscopy (FTIR). The results indicate that the proposed SAP exhibited a maximum swelling capacity of 189 g.g-1 of dry gel. It was observed that the swelling capacity decreased with an increase in the ionic strength of the swelling medium. When this SAP was mixed with sandy soil, the mixture was able to lose water more slowly. The seeds germination and seedling growth was remarkably influenced by the application of 0.5, 1.0 and 2.0 w/w% of SAP compared to the untreated soil. Therefore, it follows that it is possible to take advantage of SAPs property from used disposable diapers to retain the moisture in soil as an alternative to value the use of such waste, showing that it has potential for diverse applications in agriculture.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

The objectives of the study were to determine the spatial rate of CO₂ flux (Net Ecosystem Exchange) and soil moisture in a wetland ecosystem applying Sentinel-1 IW (Interferometric Wide) data of VH (Vertical Transmit/Horizontal Receive—cross polarization) and VV (Vertical Transmit/Vertical Receive—like polarization) polarization. In-situ measurements of carbon flux, soil moisture, and LAI (Leaf Area Index) were carried out over the Biebrza Wetland in north-eastern Poland. The impact of soil moisture and LAI on backscattering coefficient (σ°) calculated from Sentinel-1 data showed that LAI dominates the influence on σ° when soil moisture is low. The models for soil moisture have been derived for wetland vegetation habitat types applying VH polarization (R² = 0.70 to 0.76). The vegetation habitats: reeds, sedge-moss, sedges, grass-herbs, and grass were classified using combined one Landsat 8 OLI (Operational Land Imager) and three TerraSAR-X (TSX) ScanSAR VV data. The model for the assessment of Net Ecosystem Exchange (NEE) has been developed based on the assumption that soil moisture and biomass represented by LAI have an influence on it. The σ° VH and σ° VV describe soil moisture and LAI, and have been the input to the NEE model. The model, created for classified habitats, is as follows: NEE = f (σ° Sentinel-1 VH, σ° Sentinel-1 VV). Reasonably good predictions of NEE have been achieved for classified habitats (R² = 0.51 to 0.58). The developed model has been used for mapping spatial and temporal distribution of NEE over Biebrza wetland habitat types. Eventually, emissions of CO₂ to the atmosphere (NEE positive) has been noted when soil moisture (SM) and biomass were low. This study demonstrates the importance of the capability of Sentinel-1 microwave data to calculate soil moisture and estimate NEE with all-weather acquisition conditions, offering an important advantage for frequent wetlands monitoring.

Shutdown for just six days enables land plants to entirely fix CO₂ excess of +4 Gt C per yr. Rebuilding soil organic carbon (SOC) in worm-worked humus is the only practical carbon capture and storage (CCS) capable of freely offsetting annual anthropogenic emissions. A case is made to redirect all available resources towards proven, earthworm-based, organic husbandry. Priority is to safely combat mounting global threats due to irreversible species extinction, perilous climate change and deteriorating human wellbeing (mental/physical health). All three interlinked risks are underpinned by a relentless, yet largely ignored, critical loss of precious topsoil. A first step to topsoil recovery is vermi-composting all vegetable and animal ‘wastes’ for return to the field.

Frost heave, which is the volumetric expansion of frozen soil, has great ecological significance, since it creates water storage spaces in soils at the beginning of the growing season in cold temperate forests. To understand the characteristics of frost heave in seasonally frozen soil and the factors that impact its extent, we investigated the frost heave rates of forest soil from different depths and with different soil moisture contents, using both lab-based simulation and in situ measurement in a broadleaved Korean pine forest in the Changbai Mountains (northeastern China). We found that frost heave was mainly affected by soil moisture content, soil type, and gravitational pressure. Frost heave rate increased linearly with soil moisture content, and for each 100% increase in soil moisture content, the frost heave rate increased by 41.6% (loam, upper layer), 17.2% (albic soil, middle layer), and 4.6% (loess, lower layer). Under the same soil moisture content, the frost heave rate of loam was highest, whereas that of loess was lowest, and the frost heave of the uppermost 15 cm, which is the biologically enriched layer, accounted for ~55% of the frost heave. As a result, we determined the empirical relationship between frost heave and freezing depth, which is important for interpreting the effects of frost heave on increases in the storage space of forest soils and for calculating changes in soil porosity.

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy lidar (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence at multiple spatial scales ≤ 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more evenly distributed by height and depth, respectively, as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5-4 meters, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing lidar and radar technologies to quantitatively couple above- and belowground ecosystem structure.

In this study the effects of three different main preparatory tillage operations [ploughing at 0.4 m (P40) and 0.20 m (P20) depth and minimum tillage at 0.20 m depth (MT) each of them carried out at two different soil water contents (WC) [low, 58% (LH) and high, 80% (HH) of field capacity] were investigated. The results obtained in this research show high values of soil strength in term of Penetration resistance (CI) and shear strength (SS) particularly in deeper soil layers at lower water content. Fossil-fuel energy requirements both for P40 LH and P20 LH were 25 and 35% higher with respect to the HH treatments and tractor slip were very high (P40 LH = 32.4%) with respect to the P40 HH treatment (16%). Therefore soil water content had significantly influenced tractor performance during soil ploughing, particularly at 0.40 m depth while MT was not influenced at all. A significant correlation between grain yield and soil penetration resistance was found highlighting how soil strength may be good indicator of its productivity. Obtained results during these field tests allowed considering MT and P20 treatments more suitable for this type of soil in climate change scenarios.

This new study revised interlinked issues of global soil organic carbon (SOC), annual net primary productivity (NPP) and atmospheric CO₂ turnover time (τ). Soil is confirmed as both the greatest sink and source for excess atmospheric CO₂. Most terrestrial NPP (~218 Gt C/yr) is ultimately processed in topsoil and SOC stocks now total >10,000–12,000 Gt. More excess carbon is released into the air and water from SOC loss (>20 Gt C/yr) due to land clearance for pasture/crops, fires, agrichemical poisoning and erosion, than from fossil fuels (~10 Gt C/yr). NOAA’s Barrow bounce and isotopic analyses support high terrestrial flux up to ~800 Gt C/yr and CO₂ turnover time of ~1–4 years. Earth’s re-humification via compost offers the best and only practical/time-critical fix for climate, strategy for species extinction plus remedy for human health.

The present study was performed to examine that transforming growth factor beta (TGF-β) in root-surrounding tissues on deciduous teeth during the physiological root resorption regulates the differentiation induction into odontoclast. We prepared root-surrounding tissues with (R) or without (N) physiological root resorption scraped off at three regions (R1-R3 or N1-N3) from the cervical area to the apical area of the tooth and measured both TGF-β and the tartrate-resistant acid phosphatase (TRAP) activities. The TGF-β activity level was increased in N1-N3, whereas the TRAP activity was increased in R2 and R3. In vitro experiments for RANKL-mediated osteoclast differentiation revealed that TGF-β in N1-N3 and R1-R3 enhanced the TRAP activity in RAW264 cells. A genetic study indicated that the mRNA level of TGF-β1 in N1 and N2 was significantly increased, and corresponded with that of osteoprotegerin (OPG). In contrast, the expression level of receptor activator of NF-κB ligand (RANKL) was increased in R2 and R3. Our findings suggest that TGF-β is closely related to the regulation of OPG induction and RANKL-mediated odontoclast differentiation depending on the timing of RANKL and OPG mRNA expression in the root-surrounding tissues of deciduous teeth during physiological root resorption.

The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

An adequate representation of the water infiltration process in the soil allows improving the efficiency in application and the uniformity in surface irrigation. The Green and Ampt model has shown a good representation of the process, and researchers from the United States Department of Agriculture (USDA) determined the values of their parameters for soils of that country, which are shown in tables or through functional relationships and this information is used as reference in several parts of the world, although there is no certainty that they are representative of the soils in Mexico. In this study, the parameters of the Green & Ampt equation were determined and evaluated in some soils of agricultural importance in Mexico. The parameters were obtained in four ways: one of them applied a methodology adapted from Brooks and Corey to quantify the wetting front capillary pressure head and used an permeameter under constant hydraulic head to determine the saturated hydraulic conductivity, and the other three consisted in taking them from three studies reported by the USDA. The values of the parameters suggested in Mexico drastically underestimated the results with relative errors (RE) in a range of -49.0 to -94.0% and the most representative were those obtained with the methodology proposed in this research with RE of -15.0 to 6.0%.

Our work is regarding the analysis of land use changes, in the light of “saving soil” against the expansion due to unearned plus value of land: The loss of natural and agricultural surface in front of the expanding urban environment is a critical aspect of unsustainability of urban development, especially in the way it was carried out in the past decades. The measure of the physical transition of land use and characters from a more natural condition of land surface to a new artificial one, joint with a parallel analysis of the increase of land value due to such change is nowadays a major land-policy tool. The interplay of urban economics regulation with planning, reveals new key issues in urban governance and environmental preservation. In this paper it will be shown some experiment about the impact assessment of soil take, related with the seek of valorization of property inside the planning process. Our paper reports as well about the experimental activity carried out inside the MITO Lab of the Polytechnic of Bari, where reports about property values and environmental values have been produced, specially looking at the reality of the Apulia, a southern Italian Region, that is rich of farmlands and coastlines, often invaded by constructions with a severe loss of nature, landscape and ecosystems services.

Forest ecosystems make a greater contribution to carbon (C) stocks than any other terrestrial ecosystem. To understand the role of regional forest ecosystems in global climate change and carbon exchange, forest C stock and its spatial distribution within the small (2,300 km2) Liuxihe River basin were analyzed to determine the different contributors to the C stock. Forest C stocks were quantified by measuring the biomass of trees, understory vegetation, litter and roots, as well as soil organic C, using data from field samples and laboratory experiments. The results showed that forests stored 38.04 Tg C in the entire basin, with secondary and planted forests accounting for 89.82% and 10.18%, respectively, of the stored C. Five types of forests, a subtropical evergreen broad-leaved forest, a subtropical coniferous and broad-leaved mixed forest, a subtropical coniferous forest, a timber forest, and a non-wood forest, stored 257.55 ± 15.01, 218.92 ± 9.59, 195.24 ± 18.29, 177.42 ± 17.55, and 117.86 ± 6.04 Mg C ha−1, respectively. In the forest ecosystem C stocks of the basin, soils averagely contribute about 73.78%, not including root underground biomass. It provides a comprehensive method for forest ecosystem carbon investigation and forest management in small basin scale.

Current problem facing researchers globally is microplastics as well as toxic chemical pollution of the ecosystem. Microplastics carry toxic chemicals in the ecosystem.serving as a vector for transport. In this study, a review of the literature has been conducted with the following objectives: (1) to summarise the concentrations of toxic chemicals such heavy metals and hydrophobic organic contaminants sorped on microplastics; (2) to evaluate their spatial distribution regarding adsorbed contaminant (3) to discuss plausible mechanism by which microplastics adsorp or desorp toxic chemicals in the environment; (4) to discuss implications of their occurrence in air, water and soil media; and (5) to discuss the impact of ingested microplastics to human health. Microplastics are ubiquitous environmental contaminant. Concentrations of sorped toxic chemical varied with location which represents a local problem; industrialized areas (especially areas experiencing crude oil related activities or have history of crude oil pollution) have higher concentrations than less industrialized areas. Ingestion of microplastics has been demonstrated in a range of marine and soil organisms as well as edible plants, thus possible contaminating the base of the food-web. Potential health effect to human is by particle localization, chemical toxicity and microbal toxins. We conclude by highlighting the gap in knowledge and suggesting key future areas of research for scientists and policymakers.

Soil-structure interaction (SSI) could affect the seismic response of structures. Since liquid storage tanks are vital structures and must continue their operation under severe earthquakes, their seismic behavior should be studied. Accordingly, the seismic response of liquid storage tanks founded on half space soil is scrutinized under different earthquake ground motions. To better comparison, the six considered ground motions are classified based on their pulse like characteristics, into two groups, named far and near fault ground motions. To model the liquid storage tanks, the simplified mass-spring model is used and the liquid is modeled as two lumped masses known as sloshing and impulsive, and the interaction of fluid and structure is considered using two coupled springs and dashpots. The SSI effect, also, is considered using a coupled spring and dashpot. Besides, four types of soils are used to consider wide variety of soil properties. To this end, after deriving the equations of motion, the MATLAB programming is employed to obtain the time history responses. Results show that although the SSI effect leads to decrease the impulsive displacement, overturning moment and normalized base shear, the sloshing (or convective) displacement is not affected by such effects due to its long period.

Capital structure decision plays an imperative role in firm’s performance. Recognizing the importance, there has been many studies inspected the rapport of capital structure with performance of firms and findings of those studies are inconclusive. In addition, there is relative deficiency of empirical studies examining the link of capital structure with performance of banks in Bangladesh. This paper attempted to fill this gap. Using panel data of 22 banks for the period of 2005-2014, this study empirically examined the impacts of capital structure on the performance of Bangladeshi banks assessed by return on equity, return on assets and earnings per share. Results from pooled ordinary least square analysis show that there are inverse impacts of capital structure on bank’s performance. Empirical findings of this study is of greater significance for the developing countries like Bangladesh because it will call upon concentration of the bank management and policy makers to pursue such policies to reduce reliance on debt and to accomplish optimal level capital structure. This research also contributes to empirical literatures by reconfirming (or otherwise) findings of previous studies.

Fresh water is valuable nonrenewable resource and plays an important role of maintaining economic and social development. Condisering its large population and consumption potential, water resources deficit will certainly impede basic industries sustainable development of China in the near future. Application of sewage irrigation, to some extent, was regarded as an alternative way to solve the problem of agricultural irrigation water shortage in some areas (such as North China). However, accompanied with extensive implementation of sewage irrigation, some problems on sewage irrigation in agriculture are gradually obvious, especially serious pollution and destruction for farmland. In this paper, the effects of sewage irrigation on soil physical (soil bulk density, soil resistance to penetration and field capacity), chemical (pH, soil organic matter, nitrogen, phosphrous, patassium, heavy metal and organic pollutants) and biological characteristics (soil microorganism and enzyme activities) of farmland in China were systematically reviewed on the base of the current utilization status of China’s farmland sewage irrigation and some feasible suggestions were put forward to the development prospect for the future. This review will be beneficial for promoting healthy development of sewage irrigation and providing theoretical support for reclamation and high efficiency of effluents in China.

Among the plant nutrients potassium (K) is one of the vital elements required for plant growth and physiology. Potassium is not only a constituent of plant structure but also plays regulatory function in several biochemical processes related to protein synthesis, carbohydrate metabolism, enzyme activation. There are several physiological processes like stomatal regulation and photosynthesis are dependent on K. In the recent decades K was found to provide abiotic stress tolerance. Under salt stress, K helps in maintaining ion homeostasis and regulation of osmotic balance. Under drought stress condition K regulates the stomatal opening and makes the plants adaptive to water deficit. Many reports provided the notion that K enhances the antioxidant defense in plants and therefore, protects the plants from oxidative stress under various environmental adversities. Also, it provides some cellular signaling alone or in association with other signaling molecules and phytohormones. Although a considerable progress in understanding K-induced abiotic stress tolerance in plants has been achieved the exact molecular mechanisms of such protections are still under research. In this review, we summarized the recent literature on the biological functions of K, its uptake, and translocation and its role in plant abiotic stress tolerance.

Implementation of the German Climate change Strategy in the Federal State of Saxony-Anhalt is discussed in this paper. It shares the requirement and importance of sustainable development. An overview of strategy, The DAS Indicator System is provided with results of a portion of work being done for the ministry of agriculture by Deutscher Wetterdienst (DWD). Applicability of the indicator system is also shown by evaluation of results for specific indicators from 1961-2015.

Soil transmitted helminthic infections (STHIs) are common public health concern among children in Sub saharan Africa. A study to determine the prevalence of these infections among pupils in two primary schools in Nkpor and Mgbodohia communities, Obio/Akpor Local Government Area, Rivers State, Nigeria was conducted. The formo-ether concentration technique was used to concentrate and separate the eggs and cysts from the faeces. Out of 107 pupils investigated, 81 (75.7 %) were positive for at least one helminthic infection. Although more females (54.3%) were infected than males (45.7%), there was no significant (P>0.05) difference in the prevalence of Soil transmitted helminthic infections in relation to sex. There was a significant difference (P>0.5) in infection among two major age groups (5-10years-45% and 11-15years-41.9%). Children within the age group of 16-20years had the least infection (9.9%). Out of the 81 children positive for STH, 47 (43.9 %,), 23 (21.5%), 11 (10.3%) and 5(4.7%) had Ascaris lumbricoide, Hookworm, Trichirus trichiura and mixed infection (A.lumbricoide + T. trichiura) respectively. Ascaris lumbricoide (43.9%) was significantly (P<0.05) higher in prevalence than other parasites. Soil transmited helminthic infections are a public health among children concern in the study area. Provision of portable water, toilet facilities and good education on the epidemiology of STHIs in addition to regular de-worming will enhance control measures.

This paper deals with the environmental characterization of a large and densely populated area, with a poor reputation for contamination, considering the contribution of environmental features (air, soil, soil hydraulic and groundwater) and the potential effects on human health. The use of Geographic Information System (GIS) has made possible a georeferenced inventory and, by overlaying environmental information, an operational synthesis of comprehensive environmental conditions. The cumulative effects on environmental features were evaluated, taking into account superposition effects, by means of the spatial multicriteria decision analysis (S-MCDA). The application of the S-MCDA for converging the combination of heterogeneous factors, related to soil, land and water, deeply studied by heterogeneous groups of experts, constitutes the novelty of the paper. The results confirmed an overall higher potential of exposure to contaminants in the environment and higher mortality rates in the study area for some tumours, but hospital admissions for tumours were generally similar to the regional trend. Besides, mortality data may be strictly dependent on the poor socioeconomic conditions, quality of therapy and a lack of welfare in the area relative to the rest of Italy. Finally, as regards the possible relationship between presence of contaminants in the environment and health conditions of the population no definite conclusions can be drawn, although the present study encourages the use of the new proposed methods, that increase the possibilities for studying the combined effect of more environmental factors.

Field experiments were carried out during 2011-2014 at the Research and Experimental Center to Combating Desertification located in the Elsen Tasarkhai station of central Mongolia. The study was aimed to identify the effects of oxidized brown coal humic acid fertilizer on the relative growth rate of several trees for forest rehabilitation. The trees used were Populus sibirica, Salix ledebouriana and Acer tataricum. The experiment was carried out with the concentrations of 2,000, 10,000 and 20,000 mg L-1 of humic acid fertilization treatments. The measurement of relative height growth rate (RHGR) was conducted for a period of 4 years. The treatments showed significant differences within humic fertilizer concentrations which differed depending on the species. Compared to the monthly RHGR over the study, the treatment of fertilizers were significantly better for tree growth. P. sibirica in the 10,000 and 20,000 mg L-1 humic acid fertilizers had significant height growth rates. In addition, when the humic acid treatments were compared to control, A. tataricum decreased over the years which were statistically significant for high growth rate and a positive effect of humic acid fertilization treatments was observed. Furthermore, results showed that oxidized brown coal humic acid fertilizers as organic fertilizer can have a positive effect for the growth of A. tataricum during the study years. The results showed that the soil chemical properties EC, CO2, NO3, and K2O were significant among all the treatments compared to the control. The effect on P2O5 statistically significantly increased among all the treatments. However, pH and Mg were not significant effect among all the treatments. Combining the results obtained from the oxidized brown coal humic acid fertilization with sustainable land management practices can help improve soil organics for environmental issues in degraded sandy soil regions.

If given the correct remotely sensed information, machine learning can accurately describe soil moisture conditions in a heterogeneous region at the large scale based on soil moisture readings at the small scale through rule transference across scale. This paper reviews an approach to increase soil moisture resolution over a sample region over Australia using the Soil Moisture Active Passive (SMAP) sensor and Landsat 8 only and a validation experiment using Sentinal-2 and the Advanced Microwave Scanning Radiometer (AMSR-E) over Nevada. This approach uses an inductive localized approach, replacing the need to obtain a deterministic model in favor of a learning model. This model is adaptable to heterogeneous conditions within a single scene unlike traditional polynomial fitting models and has fixed variables unlike most learning models. For the purposes of this analysis, the SMAP 36 km soil moisture product is considered fully valid and accurate. Landsat bands coinciding in collection date with a SMAP capture are down sampled to match the resolution of the SMAP product. A series of indices describing the Soil-Vegetation-Atmosphere Triangle (SVAT) relationship are then produced, including two novel variables, using the down sampled Landsat bands. These indices are then related to the local coincident SMAP values to identify a series of rules or trees to identify the local rules defining the relationship between soil moisture and the indices. The defined rules are then applied to the Landsat image in the native Landsat resolution to determine local soil moisture. Ground truth comparison is done via a series of grids using point soil moisture samples and air-borne L-band Multibeam Radiometer (PLMR) observations done under the SMAPEx-5 campaign. This paper uses a random forest due to its highly accurate learning against local ground truth data yet easily understandable rules. The predictive power of the inferred learning soil moisture algorithm did well with a mean absolute error of 0.054 over an airborne L-band retrieved surface over the same region.

This study investigated the effects of soil crust development on the underlying soil properties. The field sampling work was conducted in June 2016 in the Hobq Desert in Inner Mongolia, North China. Soil crust samples and 0–6, 6–12, 12–18, 18–24, 24–30 cm deep underlying soil samples were taken from five representative areas of different soil crust development stages. All samples were analyzed for physicochemical properties including water content, bulk density, aggregate content, organic matter content, enzyme activities, and microbial biomass carbon and nitrogen. The results showed that the thickness, water content, macroaggregate (>250 μm) content, organic matter content, microbial biomass and enzyme activities of the soil crusts gradually increased along the soil crust development gradient, while the bulk density of the soil crusts decreased. Meanwhile, the physicochemical and biological properties of the soils below the algal and moss crusts were significantly ameliorated when compared with the physical crust. Moreover, the amelioration effects were significant in the upper horizons (approx. 0–12 cm deep) and diminished quickly in the deeper soil layers.

The production of lithium-ion battery cells is characterized by a high degree of complexit due to numerous cause-effect relationships between process characteristics. Knowledge about the multi-stage production is spread among several experts, rendering tasks such as failure analysis challenging. In this paper, a method is presented, which includes expert knowledge acquisition in production ramp-up by combining Failure Mode and Effects Analysis (FMEA) with a Bayesian Network. We show the effectiveness of this holistic method by building up a large scale, cross-process Bayesian Failure Network in lithium-ion battery production. Using this model, we are able to conduct root cause analyses as well as analyses of failure propagation. The former support operators in identifying root causes once a cell possesses a specific failure by calculating most-probable explanations matched to the individual battery cell data. The latter enable us to analyze propagation of failures and deviations in the production chain and thus provide support for placement of quality gates, leading to a significant reduction in scrap rate. Moreover, it gives an insight into which process steps are key drivers for which final product characteristics.

Land’s basic metric is soil organic carbon (SOC) yet global estimates range 1,417–15,000 Gt C. Erosion of ancient topsoil and loss of soil taxa are most urgent of all context-triage concerns, and most ignored. Re-evaluation of topographical terrain on a non-flat Earth increases most soil dynamic inventories. Carbon credits of our neglected and disappearing SOC stocks are enumerated for mineral soils (~4,100 Gt C plus ca. 20–30% glomalin), Permafrost (>4,200 Gt C), peat (1,123 Gt C), plant roots (916 Gt C), litter (600 Gt C), microbes (200 Gt C), fungi (30 Gt C), biocrust (10–20 Gt C), earthworms (2.3–3.6 Gt C), termites (0.15 Gt C), nematodes (0.06 Gt C), ants (0.024 Gt C), and soil viruses (0.02–4.0 Gt C). Net contribution to atmospheric CO₂ is more from biotic topsoil loss (>10 Gt C/yr) than fossil fuels (<10 Gt C/yr). Although higher CO₂ results in a terrestrial greening effect with Net Primary Productivity (NPP) now ~220 Gt C/yr (cf. ~20 Gt C/yr Ocean NPP), this is arguably offset by topsoil erosion, desert expansion, plus fire at net ~16–20 Gt C/yr lost due, in part, to extravagant meat-eating with unsupportable, humus-depleting farm management. In particular, excess synthetic Nitrogen acidifies topsoil and destroys the natural SOC biota. Review shows critical topsoil loss up to 20,000 tonnes per second and, when soil microbes/invertebrates are properly considered, extinctions as high as 23 taxa per second. Sustainable Development Goals (SDGs) fail without solid soil foundation. Rather, heritage farm-data points to resolution in organic husbandry. Remedy via natural vermi-compost, 100% organic farming and practical Permaculture is under a simple premise that the Problem (i.e., SOC loss) is the Solution (viz., SOC restoration).

The assimilation of Soil Moisture and Ocean Salinity (SMOS) data into the ECMWF (European Centre for Medium Range Weather Forecasts) H-TESSEL (Hydrology revised - Tiled ECMWF Scheme for Surface Exchanges over Land) model is presented. SMOS soil moisture (SM) estimates have been produced specifically by training a neural network with SMOS brightness temperatures as input and H-TESSEL model SM simulations as reference. This can help the assimilation of SMOS information in several ways: (1) the neural network soil moisture (NNSM) data have a similar climatology to the model, (2) no global bias is present with respect to the model even if regional differences can exist. Experiments performing joint data assimilation (DA) of NNSM, 2 metre air temperature and relative humidity or NNSM-only DA are discussed. The resulting SM was evaluated against a large number of in situ measurements of SM obtaining similar results to those of the model with no assimilation, even if significant differences were found from site to site. In addition, atmospheric forecasts initialized with H-TESSEL runs (without DA) or with the analysed SM were compared to measure of the impact of the satellite information. Although, NNSM DA has an overall neutral impact in the forecast in the Tropics, a significant positive impact was found in other areas and periods, especially in regions with limited in situ information. The joint NNSM, T2m and RH2m DA improves the forecast for all the seasons in the Southern Hemisphere. The impact is mostly due to T2m and RH2m, but SMOS NN DA alone also improves the forecast in July- September. In the Northern Hemisphere, the joint NNSM, T2m and RH2m DA improves the forecast in April-September, while NNSM alone has a significant positive effect in July-September. Furthermore, forecasting skill maps show that SMOS NNSM improves the forecast in North America and in Northern Asia for up to 72 hours lead time.

Understanding the dynamics of Organic Carbon mineralization is fundamental in forecasting biosphere to atmosphere Net Carbon Ecosystem Exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid Process Based Model 3D‐CMCC FEM where also heterotrophic respiration (R_h) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting Ecosystem Respiration (R_eco) to Gross Primary Productivity (GPP). To do so, we developed a simplification of the Soil Carbon dynamics routine proposed in DNDC [1]. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameters distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

The accurate assessment and monitoring of soil erosion is of great significance for guiding food production and ensuring ecological security, and it is a current research hotspot. In this paper, remote sensing and geographic information systems (GISs) are combined with the Revised Universal Soil Loss Equation (RUSLE model) to carry out research on soil erosion monitoring and make a quantitative evaluation. According to five factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, crop management and water and soil conservation measures, the distribution of the soil erosion rate in Jilin Province in 2019 was mapped, and the soil erosion rate was divided into 5 levels according to the degree of erosion, including very slight, slight, moderate, severe and extremely severe erosion. Based on the segmented S-slope factor model and the unique topographical features of the study area, the relationships among the soil erosion rate, erosion risk level, erosion area, erosion amount and slope angle (θ) were systematically analysed, and a slope angle of 15° was identified as the threshold for soil erosion on sloped farmland in Jilin Province. The total soil erosion in Jilin Province was 402.14×106 t in 2019, the average soil erosion rate was 21.6 t·ha-1·a-1, and the average soil loss thickness was 1.6 mm·a-1; these values were far greater than the soil erosion rate risk threshold of 10 t ·Ha-1·a-1. Thus, the province has a strong level of soil erosion. We conclude that soil degradation is accelerating, and food production and the ecological environment will face severe challenges. It is suggested that soil erosion control should be carried out according to different types and slopes of land, with an emphasis on the management of forestland and farmland because forestland and farmland are currently the first types of land to be managed in Jilin Province. This paper aims to explore a timely, fast, efficient and convenient soil erosion monitoring and evaluation method and provide effective monitoring tools for agricultural water and soil conservation, ecological safety management and stable food production in Jilin Province and similar black soil areas.

Crop productivity is directly dependent to soil fertility. High soil organic carbon (SOC) content in soil is vital as it leads to improved soil quality, increased productivity, and stable soil-aggregates. In addition, with the signing of the climate agreement, there is growing interest in carbon sequestration in landscapes. This paper looks at how SOC can be increased so that it not only contributes to reduction of CO₂, but also translates to increased food production thereby enhancing food security. This synergy between mitigation and enhancing food security is even more relevant for mountain landscapes of the Hindu Kush Himalayan (HKH) region where there remains huge potential to increase CO₂ sequestration and simultaneously address food security in the chronic food deficit villages. Soil samples were collected from seven transects each in Bajhang and Mustang and from 4 land use types in each transect. Samples of soils were taken from two depths in each plot; 0-15 cm below the soil surface and 15-30 cm below the soil surface to compare the top soil and subsoil dynamics of the soil nutrients. The lab analysis was performed to assess the soil texture, soil color, soil acidity in 'power of hydrogen' (pH), macro-nutrients as soil fertility. Secondary data was used to analyze the level of food deficit in the villages. The result shows that most of the sample soils from Mustang were clay (82.1%) which is 46 samples out of 56. The pH value of soil from Bajhang ranged from 5.29 to 9.09. The pH value of soil ranged from 5.65 to 8.81 in Mustang. SOC contents of sampled soils from Bajhang ranged from 0.20% to 7.69% with mean amount of 2.47% ± 0.17. SOC contents of sampled soils from Mustang ranged from 0.51% to 8.56% with mean amount of 2.60% ± 0.25. By land use type, forest land had the highest carbon (C) content of 53.61 t ha^-1 in Bajhang whereas in Mustang, agricultural land had the highest C content of 52.02 tons ha-1. Based on these data, we can say that there is potential for increasing SOC through improved soil health and crop production and soil. Sustainable soil management should be practiced for higher productivity. Livestock may also provide farmyard manure, which can be used to fertilize cultivated soils, which increases soil productivity. Increasing productivity would aid in increasing the access and availability of food in these mountain villages.

Sourced so far mostly from beet root juice, betanin is a red-violet natural colorant increasingly used by the food, beverage and nutraceutical industries. We provide an updated bioeconomy perspective into a valued betacyanin whose supply and applications, we argue in this study, will rapidly expand.

Interactions of soil moisture with plant root systems are very important for plant growth. For non-invasive determination of volumetric soil moisture in a rhizobox, a microwave system based on transmittance of electromagnetic waves in the microwave frequency range was developed using microstrip patch antennas. Vector Network Analyzers (VNAs) were used to measure the S-parameters at frequency ranges close to 5 GHz. A transmission system with microstrip patch antennas was developed. The result of this attenuation is in the frequency domain. The antennae were designed as resonant microstrip antennae. The antennae were placed on both sides of a rhizobox, which allowed non-invasive measuring soil moisture in the box. The attenuation (S21(dB)) was used to measure the effect of temperature, and different types of soil; as well as sensitivity, reproducibility and repeatability of the system. In this work we present quantitative results of soil moisture in rhizobox. The microwave technique, using microstrip patch antennas, is a reliable and accurate system, and showed very promising potential applications for rhizobox-based investigations of root performance.

This study aims to assess the potential of the LDAS-Monde a land data assimilation system developed by Météo-France to monitor the impact of the 2018 summer heatwave over western Europe vegetation state. The LDAS-Monde is forced by the ECMWF’s (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (IFS-HRES), used in conjunction with the assimilation of Copernicus Global Land Service (CGLS) satellite derived products, namely the Surface Soil Moisture (SSM) and the Leaf Area Index (LAI). Analysis of long time series of satellite derived CGLS LAI (2000-2018) and SSM (2008-2018) highlights marked negative anomalies for July 2018 affecting large areas of North Western Europe and reflects the impact of the heatwave. Such large anomalies spreading over a large part of the considered domain have never been observed in the LAI product over this 18-yr period. The LDAS-Monde land surface reanalyses were produced at spatial resolutions of 0.25°x0.25° (January 2008 to October 2018) and 0.10°x0.10° (April 2016 to December 2018). Both configuration of the LDAS-Monde forced by either ERA5 or HRES capture well the vegetation state in general and for this specific event, with HRES configuration exhibiting better monitoring skills than ERA5 configuration. The consistency of ERA5 and IFS HRES driven simulations over the common period (April 2016 to October 2018) allowed to disentangle and appreciate the origin of improvements observed between the ERA5 and HRES. Another experiment, down-scaling ERA5 to HRES spatial resolutions, was performed. Results suggest that land surface spatial resolution is key (e.g. associated to a better representation of the land cover, topography) and using HRES forcing still enhance the skill. While there are advantages in using HRES, there is added value in down-scaling ERA5, which can provide consistent, long term, high resolution land reanalysis. If the improvement from LDAS-Monde analysis on control variables (soil moisture from layers 2 to 8 of the model representing the first meter of soil and LAI) from the assimilation of SSM and LAI was expected, other model variables benefit from the assimilation through biophysical processes and feedbacks in the model. Finally, we also found added value of initializing 8-day land surface HRES driven forecasts from LDAS-Monde analysis when compared with model only initial conditions.

Transient flows result in unbalanced forces and high pressure in pipelines. Under these conditions, the combined effects of flow-induced forces along with sudden pipe displacements can create cracks in the pipeline, especially at the junctions. This situation consequently results in water leakage and reduced operational efficiency of the pipeline. In this study, displacements and stresses in a buried pressurized water transmission pipe installed by pipe jacking method are investigated using numerical modeling and considering interactions between fluid, pipe, and soil. The analyses were performed consecutively under no-flow, steady flow, and transient flow conditions, in order to investigate the effects of flow conditions on displacements and stresses in the system. Analyses of the results show that displacements and stresses in the jointed concrete pipes are significant under transient flow conditions. Moreover, because of pressure transient effects, maximum tensile stresses exceed the tensile strength of concrete at the junctions, leading to cracks and consequent water leakage.

Subseasonal-to-seasonal (S2S) weather forecasting has improved in recent years, thanks partly to better representation of physical variables in models. For instance, realistic initializations of snow and soil moisture in models yield enhanced predictability on S2S time scales. Snow depth and soil moisture also mediate month-to-month persistence of near-surface air temperature. Here the role of snow depth as predictor of temperature one month ahead in the Northern Hemisphere is probed via two causal pathways. Through the first pathway, snow depth anomalies in month 1 cause snow depth anomalies in month 2, which then cause temperature anomalies in month 2. This pathway represents the snow–albedo feedback, as well as cooling due to insulation, emissivity and heat loss. It is active from fall to summer, and its effect peaks in March/April in the midlatitudes and in May/June at high latitudes. A complementary second pathway, where snow depth anomalies in month 1 cause soil moisture anomalies in month 2, which then cause temperature anomalies in month 2 through soil moisture–temperature feedbacks, is only active in spring and summer. Its effect peaks later in the warm season than the effect of the first pathway. Geographically, snow depth mediates north of, and soil moisture south of, the areas with the highest temperature predictability from snow depth. These results indicate that the two pathways describe complementary physical mechanisms. The first pathway embodies month-to-month persistence of snow depth, and the second pathway represents melting of snow from one month to the next.

Soil microbial fuel cells (sMFC) are a novel technique that use organic matters in soils as an alternative energy source. External resistance (ER) is a key factor influencing sMFC performance and, furthermore, alters the soil’s biological and chemical reactions. However, little information is available on how the microbial community and soil component changes in sMFC with different ER. Therefore, the effects of anodes of sMFC at different ER (2000 Ω, 1000 Ω, 200 Ω, 80 Ω and 50 Ω) were examined by measuring organic matter (OM) removal efficiency, trace elements in porewater and bacterial community structure in contaminated paddy soil. The results indicated that ER has significant effects on sMFC power production, OM removal efficiency and bacterial beta diversity. Moreover ER influences iron, arsenic and nickel concentration as well in soil porewater. In particular, greater current densities were observed at lower ER (2.4mA, 50Ω) compared to a higher ER (0.3mA, 2000Ω). The removal efficiency of OM increased with decreasing ER whereas it decreased with soil distance away from the anode. Furthermore, principal coordinate analysis (PCoA) revealed that ER may shape the bacterial communities that develop in the anode vicinity but have minimal effect on that of the bulk soil. The current study illustrates that lower ER can be used to selectively enhance the relative abundance of electrogenic bacteria and lead to high OM removal.

The main objective of the present study was to investigate arsenate [As (V)] resistance genes in rice cultivars grown in arsenic contaminated Egyptian soil in order to genetically induce resistance against arsenic in the local rice varieties as well as defining contaminated rice grains and/or soil. Three local rice cultivars; Sakha 102-104 were cultivated on modified Murashige and Skoog Basal Medium (MS medium) containing elevated concentrations of arsenate (0.1, 1 and 10 mg/l). The three varieties showed different resistant attitudes against arsenate with Sakha 104 being the most resistant. Extracted messenger RNA (mRNA) from treated and untreated Sakha 104 plantlets was scanned using differential display to demonstrate the arsenate resistant genes using three different arbitrary primers. About 100 different RNAs with (1500 bp - 50 bp) were obtained from which seven were up-regulated genes, subjected to DNA cloning using TOPO TA system and the selected clones were sequenced. The sequence analysis described four genes out of the seven namely disease resistance protein RPM1, Epstein-Barr virus EBNA-1-like, CwfJ family protein and outer membrane lipoprotein OmlA while the other three genes were hypothetical proteins. It is concluded the four induced genes in the resistant rice cultivar considered as a direct response to arsenic soil pollution. Genes detected in the present study can be used as geno-sensors for rice grains and soil contamination with As (V). Moreover, local rice cultivars may be genetically modified with such genes to induce high resistance and to overcome arsenic soil pollution.

Aeroponics is a relatively new soilless culture technology, which may produce food in space limited cities or non-arable land with high water use efficiency. The shoot and root growth, root characteristics, mineral contents of two lettuce cultivars were measured in aeroponics, as compared with hydroponics and substrate culture. The results showed that aeroponics remarkably improved the root growth with a significant greater root biomass, root/shoot ratio, and several times higher total root length, root area and root volume. However, the greater root growth did not lead to a better shoot growth compared with hydroponics, due to the limited availability of nutrients and water. It can be concluded that aeroponics systems may be better for high value true root crops production. Further research is necessary to figure out the suitable pressure, droplet size, and misting interval in order to improve the continuously availability of nutrients and water in aeroponics, if it is used to grow crops like lettuce for harvesting above-ground parts.

A continuous spatio-temporal database of accurate soil moisture (SM) measurements is an important asset for agricultural activities, hydrologic studies, and environmental monitoring. The Advanced Microwave Scanning Radiometer 2 (AMSR2), launched in May 2012, has been providing SM data globally with a revisit period of two days. It is imperative to assess the quality of this data before performing any application. Since resources of accurate SM measurements are very limited in Puerto Rico, this research will assess the quality of the AMSR2 data by comparing with ground-based measurements and perform a downscaling technique to provide a better description of how the sensor perceives the surface soil moisture as it passes over the island. The comparison consisted of the evaluation of the mean error, root mean squared error, and the correlation coefficient. Two downscaling techniques were used and their performances were studied. The results revealed that AMSR2 products tend to underestimate. This is due to the extreme heterogeneous distributions of elevations, vegetation densities, soil types, and weather events on the island. This research provides a comprehensive study on the accuracy and potential of the AMSR2 products over Puerto Rico. Further studies are recommended to improve the AMSR2 products.

Phospholipid fatty acids (PLFAs) can be used as biomarkers for qualitative and quantitative analyses of soil microbial community diversity. In this study, we collected soil samples at 10-cm intervals to a depth of 1 m from Robinia pseudoacacia plantations of four different ages (10, 15, 25 and 40 years) in a loess area and analysed the soil microbial community structure by PLFA analysis. A total of 97 PLFAs were detected in soils of R. pseudoacacia plantations of different ages. The individual PLFA contents gradually decreased in the 0- to 40-cm soil layers, with little variation in the 40- to 100-cm soil layers. The individual PLFAs were similarly distributed in the soils of R. pseudoacacia plantations of different ages, and there was a clear variation with stand age and soil depth. The individual PLFA contents in the 0- to 20-cm soil layers were highest for the 25-year-old plantation, while those in the 20- to 40-cm soil layers were relatively high for the 25- and 40-year-old plantations; the 16:0 content was the highest among individual PLFAs. The total PLFA content and the PLFA contents of different microbial groups [bacteria, fungi, Gram-positive bacteria (G⁺), Gram-negative bacteria (G^-) and actinomycetes] initially increased before decreasing in the soils of R. pseudoacacia plantations with increasing stand age, whereas these contents gradually decreased with increasing soil depth; the highest PLFA contents was found in the 25-year-old plantation. The total PLFA content and the contents of fungal, G^- and actinomycete PLFAs in the soils of R. pseudoacacia plantations differed significantly among stands of different ages in the 0- to 10-cm, 10- to 20-cm and 30- to 40-cm soil layers, while no significant differences were found in the 20- to 30-cm soil layers; the G⁺ and bacterial PLFAs contents in each of the 0- to 40-cm soil layers were significantly different. The PLFA ratios between different microbial groups differed among the stands of different ages. The fungi/bacteria ratio showed a “decrease-increase-decrease” trend with stand age, while the G⁺/G^- ratio showed an “increase-decrease” trend. The saturated/monounsaturated PLFA ratio initially decreased before plateauing, while the opposite trend was observed for the cyclopropyl/precursor ratio. The PLFA contents of different microbial groups were ranked as follows: bacteria > G^- > G⁺ > actinomycetes > fungi. In the principle component analysis, 18:1ω9c, 10Me18:0, i17:0, a17:0, 18:1ω7c, 18:1ω5c and 18:0 made the greatest contribution to principal component 1, and a14:0, i14:0 3OH, i14:0, i14:1ω7c and 14:0 made the greatest contribution to principal component 2. In conclusion, soil nutrient status and other soil eco-environmental stress factors should be considered in 10- to 25-year-old (particularly ~15-year-old) plots for the management of R. pseudoacacia plantations to prevent forest soil degradation and improve forest stand quality, thereby achieving better soil and water conservation and environmental improvement in R. pseudoacacia plantations.

Infiltration based stormwater best management practices bring considerable economic, social and ecological benefits. Controlling stormwater quantity and quality are primarily important to prevent urban flooding and minimizing loads of pollutants to the receiving waters. However, there have been growing concerns about how the traditional design approach contributes to the failure of infiltration based BMP’s that have caused flooding, ponding, prolonged movement of surface water, and frequent clogging, etc. Many of these problems were due to the fact that the current design approaches of stormwater BMP’s only focus on surface hydrology and give little or no attention to the underline subsoil permeability rate and other constraints during the design and sizing process. As a result, we are exhibiting many newly constructed infiltration based BMP’s are failing to function well. This paper presents and demonstrates a new paradigm shift in designing infiltration-based stormwater BMP’s by combining subsurface hydrology and undelaying native soil constraints to establish acceptable criteria for sizing infiltration based BMPs.

Soil moisture plays a key role in the Earth’s water and carbon cycles, but acquisition of continuous (i.e., gap-free) soil moisture measurements across large regions is a challenging task due to limitations of currently available point measurements. Satellites offer critical information for soil moisture over large areas on a regular basis (e.g., ESA CCI, NASA SMAP), however, there are regions where satellite-derived soil moisture cannot be estimated because of certain circumstances such as high canopy density, frozen soil, or extreme dry conditions. We compared and tested two approaches--Ordinary Kriging (OK) interpolation and General Linear Models (GLM)--to model soil moisture and fill spatial data gaps from the European Space Agency Climate Change Initiative (ESA CCI) version 3.2 (and compared them with version 4.4) from January 2000 to September 2012, over a region of 465,777 km² across the Midwest of the USA. We tested our proposed methods to fill gaps in the original ESA CCI product, and two data subsets, removing 25% and 50% of the initially available valid pixels. We found a significant correlation coefficient (r = 0.523, RMSE = 0.092 m³m^-3) between the original satellite-derived soil moisture product with ground-truth data from the North American Soil Moisture Database (NASMD). Predicted soil moisture using OK also had significant correlation coefficients with NASMD data, when using 100% (r = 0.522, RMSE = 0.092 m³m^-3), 75% (r = 0.526, RMSE = 0.092 m³m^-3) and 50% (r = 0.53, RMSE = 0.092 m³m^-3) of available valid pixels for each month of the study period. GLM had lower but significant correlation coefficients with NASMD data (average r = 0.478, RMSE = 0.092 m³m^-3) when using the same subsets of available data (i.e., 100%, 75%, 50%). Our results provide support for OK as a technique to gap-fill spatial missing values of satellite-derived soil moisture products across the Midwest of the USA.

Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research study develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).

The sustainable production of food faces formidable challenges. Foremost is the availability of arable soils, which have been ravaged by the overuse of fertilizers and detrimental soil management techniques. As such, maintenance of soil quality, and reclamation of marginal soils, has become an increasingly important endeavor. Recently, there has been emerging interest in the use of biochar, a carbon rich, porous material thought to improve various aspects of soil performance. Biochar (BC) is produced through the thermochemical decomposition of organic matter at high temperature in an oxygen limited environment, in a process known as pyrolysis. Importantly, the source of organic material, or ‘feedstock,’ used in this process and different parameters of pyrolysis, especially temperature, determine the chemical and physical properties of biochar. Incorporation of BC impacts soil-water relations, tilth and nutrient status, pH, soil organic matter (SOM), and microbial activity. Soil amendment with BC has been shown to have an overall positive impact on soil health and crop productivity; however, initial soil properties need to be considered prior to the application of BC. There is an urgent need to understand the effects of long-term field application of BC and how it influences the soil microcosm. This knowledge will facilitate predictable enhancement of crop productivity and meaningful carbon sequestration.

Increased nutrient withdrawal by rapidly expanding intensive cropping systems, in combination with imbalanced fertilization, is leading to potassium (K) depletion from agricultural soils in Asia. There is an urgent need to better understand the soil K-supplying capacity and K-use efficiency of crops to address this issue. Maize is increasingly being grown in rice-based systems in South Asia, particularly in Bangladesh and North East India. The high nutrient extraction, especially K, however, causes concerns for the sustainability of maize production systems in the region. The present study was designed to estimate, through a plant-based method, the magnitude, and variation in K-supplying capacity of a range of soils from the maize-growing areas and the K-use efficiency of maize in Bangladesh. Eighteen diverse soils were collected from several upazillas (or sub-districts) under 11 agro-ecological zones to examine their K-supplying capacity from the soil reserves and from K fertilization (@ 100 mg K kg-1 soil) for successive seven maize crops grown up to V10-V12 in pots inside a net house. A validation field experiment was conducted with five levels of K (0, 40, 80, 120 and 160 kg ha-1) and two fertilizer recommendations based on “Nutrient Expert for Maize-NEM” and “Maize Crop Manager-MCM” decision support tools (DSSs) in 12 farmers’ fields in Rangpur, Rajshahi and Comilla districts in Bangladesh. Grain yield and yield attributes of maize responded significantly (P < 0.001) to K fertilizer, with grain yield increase from 18 to 79% over control in all locations. Total K uptake by plants not receiving K fertilizer, considered as potential K-supplying capacity of the soil in the pot experiment, followed the order: Modhukhali >Mithapukur >Rangpur Sadar >Dinajpur Sadar >Jhinaidah Sadar >Gangachara >Binerpota >Tarash >Gopalpur >Daudkandi >Paba >Modhupur >Nawabganj Sadar >Shibganj >Birganj >Godagari >Barura >Durgapur. Likewise in the validation field experiment, the K-supplying capacity of soils was 83.5, 60.5 and 57.2 kg ha-1 in Rangpur, Rajshahi, and Comilla, respectively. Further, the order of K-supplying capacity for three sites was similar to the results from pot study confirming the applicability of results to other soils and maize-growing areas in Bangladesh and similar soils and areas across South Asia. Based on the results from pot and field experiments, we conclude that the site-specific K management using the fertilizer DSSs can be the better and more efficient K management strategy for maize.

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions, (ii) in order to specify and operate the simplified radiative transfer equation (RTE), (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need (i) for formal atmospheric correction, (ii) nor for conversion of relative radiance into calibrated reflectance , (iii) nor for existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

Alterations in root morphology and physiology are important strategies in plants to adapt to low-phosphorus (P) environments. Maize genotypes differed in nitrogen (N) efficiency may also respond differently to low P stress. This study aimed to investigate the responses of root morphological and physiological traits of these two maize cultivars to P deficit and how these traits were linked with the acquisition of soil P. Two maize cultivars, XY335 (N efficient) and ZD958 (N inefficient), were cultivated for 40 days in a calcareous loamy soil amended with (high P) or without (low P) P. Functional root traits were used to evaluate the morphological and physiological responses to low P supply. Two separate short-term experiments determined the correlation between P uptake rate and P supply intensity (hydroponic) or root hair length under two P treatments (rhizobox). Low P status significantly simulated biomass allocation to roots, specific root length and exudations of carboxylates, while decreased root diameter and rhizosphere pH in both maize cultivars. Two cultivars had different total root length and root surface area under low P stress: increased in ZD958 and decreased in XY335. Both genotypes developed longer root hair under P deficit. ZD958 (greater biomass and shoot P content) has a greater capability at accessing soil P than XY335. Rhizosphere exudation of citric acid was significantly higher in ZD958 than in XY335, while there was not significant genotypic difference in rhizosphere pH and exudation of malic acid and acid phosphatase activity. ZD958 had higher P uptake rate than XY335 when solution P was between 12.5 and 250 µM. This study identified ZD958 as a P-efficient genotype, which better adapted to low P stress by altering root physiological traits (exudation of citric acid and P uptake rate), rather than root morphological traits (total root length, root surface area, root hair length). Our results highlight the importance of analyzing root morphological and physiological traits to enhance our understanding of the physiological mechanisms of P acquisition.

Eggplant is a functional food owing to its anti-diabetic, anti-inflammatory, and cardio-protective properties. Root-knot nematodes (RKN) are a threat to the successful production of eggplant. RKN infestation manifests as root damage, stunted development, and structural deformations of the plant. RKN infestation can be managed using a variety of management techniques like soil amendments and chemical treatments. Breeding for nematode tolerance is critical for high yields and stable results. As a result, breeding approaches are the most efficient and cost-effective nematode management methods. Furthermore, with advances in breeding technology and genomics assistance, it is becoming more feasible and straightforward. As a result, we've compiled a list of the most recent breeding developments for Meloidogyne spp. resistance in eggplant. We hope this information will serve as an important resource for the eggplant breeders.

Droplet digital polymerase chain reaction (ddPCR) is a method used to detect and quantify nu-cleic acids even when present in exceptionally low numbers. While it has proven to be valuable for clinical studies, it has failed to be widely adopted for environmental and applied studies. Due to the complexity of the chemical and biological composition of environmental samples, protocols tailored to clinical studies are not appropriate, and results are difficult to interpret. We used en-vironmental DNA samples originating from field studies to determine a protocol for environ-mental samples. Samples included field soils which had been inoculated with the soil fungus Rhizophagus irregularis (environmental positive control), field soils that had not been inoculat-ed and the targeted fungus was not naturally present (environmental negative control), and root samples from both field categories. To control for the effect of soil inhibitors, we also in-cluded DNA samples of an organismal control extracted from pure fungal spores (organismal positive control). Finally, we included a no-template control consisting only of the PCR reaction reagents and nuclease free water instead of template DNA. Using original data, we examined which factors contribute to poor resolution in root and soil samples and propose best practises to ensure accuracy and repeatability. Furthermore, we evaluated manual and automatic threshold determination methods and we propose a novel protocol based on multiple controls that is more appropriate for environmental samples.

Accurate estimates of daily rainfall are essential for understanding and modeling the physical processes involved in the interaction between the land surface and the atmosphere. In this study, daily satellite soil moisture observations from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) generated by implementing the standard NASA- algorithm are employed for estimating rainfall, firstly, through the use of recently developed approach, SM2RAIN (Brocca et al., 2013) and, secondly, the nonlinear autoregressive network with exogenous inputs (NARX) neural modelling at five climate stations in the Karkheh river basin (KRB), located in southwest Iran. In the SM2RAIN method, the period 1 January 2003 to 31 December 2005 is used for the calibration of algorithm and the remaining 9 months from 1 January 2006 to 30 September 2006 is used for the validation of the rainfall estimates. In the NARX model, the full study period is split into a training (1 January 2003 to 31 September 2005) and a testing (1 September 2005 to 30 September 2006) stage. For the prediction of the rainfall as the desired target (output), relative soil moisture changes from AMSR-E and measured air temperature time series are chosen as exogenous (external) inputs in NARX. The quality of the estimated rainfall data is evaluated by comparing it with observed rainfall data at the five rain gauges in terms of the correlation coefficient R, the RMSE and the statistical bias. For the SM2RAIN method, R ranges between 0.44 and 0.9 for all stations, whereas for the NARX- model the values are generally slightly lower. Moreover, the values of the bias for each station indicate that although SM2RAIN is likely to underestimate large rainfall intensities, due to the known effect of soil moisture saturation, its biases are somewhat lower than those of NARX. In conclusion, the results of the present study show that with the use of AMSR-E soil moisture products in the physically based SM2RAIN- algorithm as well as in the NARX neural network, rainfall for poorly gauged regions can be fairly predicted.

Oilfield produced water (OPW) is used to boost freshwater sources for crop irrigation in California's agriculturally important Central Valley. OPW is known to contain salts, metals, hydrocarbons, alkylphenols, naturally radioactive materials, biocides, and other compounds from drilling and production processes. Less is known about the potential uptake and accumulation of these compounds in crops and soil irrigated with OPW. In this study 23 potted mandarin orange plants were irrigated 2-3 times weekly (depending on season) with water containing three different concentrations of the known OPW heavy metals barium, chromium, lead, and silver. Seven sets of samples of soil and leaves and all fruits were collected and processed using microwave-assisted digestion (EPA Method 3051A). Processed samples were analyzed using ICP-OES. ANOVA, ANCOVA, and Tukey’s honest significant difference test were used to examine the effects of metal concentrations in the irrigation water, sample number, and number of watering days on the metal concentrations in the soil, leaf, and fruit samples. Accumulation of barium in soil and leaves was strongly positively associated with sample and number of watering days, increasing nearly 2,000-fold. Lead also showed an upward trend, increasing up to 560-fold over baseline level. Chromium showed an increase in the soil that tapered off, but less consistent results in the leaves and fruit. The silver results were more volatile, but also indicated at least some level of accumulation in the tested media. The smallest absolute accumulation was observed for chromium. Concentrations in the fruit were highest in the peel, followed by pith and juice. Accumulation of all heavy metals was generally highest in the soil and plants that received the highest irrigation water concentration. Considering the potential for adverse human health effects associated with ingesting soluble barium contained in food and drinking water, and to a lesser extent chromium and lead, the study signals that it is important to conduct further research into whether OPW contaminants can enter the food chain and pose risks to consumers.

In this research paper, a hybrid Artificial Neural Network (ANN)-Fuzzy Logic Control (FLC) tuned Flower Pollination Algorithm (FPA) as a Maximum Power Point Tracker (MPPT) is employed to emend root mean square error (RMSE) of photovoltaic (PV) modeling. Moreover, Gaussian membership functions have been considered for fuzzy controller design. This paper interprets Luo converter occupied brushless DC motor (BLDC) directed PV water pump application. Experimental responses certify the effectiveness of the suggested motor-pump system supporting diverse operating states. Luo converter is newly developed dc-dc converter has high power density, better voltage gain transfer and superior output waveform and able to track optimal power from PV modules. For BLDC speed controlling there is no extra circuitry and phase current sensors are enforced for this scheme. The recentness of this attempt is adaptive neuro-fuzzy inference system (ANFIS)-FPA operated BLDC directed PV pump with advanced Luo converter has not been formerly conferred.

Decision tables have been used for many years in data processing and business applications to simulate complex rule sets. Several computer languages have been developed based on rule systems and they are easily programmed in several current languages. Land management and river-reservoir models simulate complex land management operations and reservoir management in highly regulated river systems. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. In this study, we discuss the suitability of decision tables to simulate management in the river basin scale Soil and Water Assessment Tool (SWAT+) model. Decision tables are developed to simulate automated irrigation and reservoir releases. A simple auto irrigation application of decision tables was developed using plant water stress as a condition for irrigating corn in Texas. Sensitivity of the water stress trigger and irrigation application amounts were shown on soil moisture and corn yields. In addition, the Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. The release rules as implemented by the decision table realistically simulated flood releases as evidenced by a daily NSE (Nash-Sutcliffe Efficiency) of 0.52 and a percent bias of -1.1%. Using decision tables to simulate management in land, river and reservoir models was shown to have several advantages over current approaches including: 1) mature technology with considerable literature and applications, 2) ability to accurately represent complex, real world decision making, 3) code that is efficient, modular and easy to maintain, and 4) tables that are easy to maintain, support, and modify.

The increased availability of high resolution remote sensor data for precision agriculture 1 applications permits users to aquire deeper and more relevant knowledge about crops states that lead 2 inevitably to better decisions. The algorithm libraries being developed and evolved around these 3 applications rely on multi-spectral or hyper-spectral data acquired by using manned or unmanned 4 platforms. The current state of the art makes thorough use of vegetational indicies to guide the 5 operational management of agricultural land plots. One of the most challenging sub-problems is 6 to correctly identify and separate crop from soil. Thresholding techniques based on Normalized 7 Difference Vegetation Index (NDVI) or other such similar metrics have the advantage of being simple, 8 easy to read transformations of the data packed with useful information. Obvious difficulties arise 9 when crop/tree and soil have similar spectral responses as in case of grass filled areas in vineyards. 10 In this case grass and canopy are close in terms of NDVI values and thresholding techniques will 11 generally fail. Radiometric approaches could be integrated or replaced by a geometric approach that 12 is based on terrain data like Digital Surface Models (DSMs). These models are one of the ouputs 13 of orthorectification engines usually present in data acquired by using unmanned platforms. In 14 this paper we present two approaches based on DSM that are able to segment crop/tree from soil 15 while over gradient terrain. The DSM data are processed through a two dimensional data slicing or 16 reduction technique. Each slice is separately processed as a one dimensional time series to derive the 17 terrain and tree structures separately, here interpreted as object probability densities. In particular 18 the first approach is a Cartesian grid rasterization (CARSCAN) of the terrain and the second is its 19 immediate generalisation or radial grid rasterization of the DSM model (FANSCAN). The FANSCAN 20 recovers information from the original image at greater frequencies on the Fourier plane. These 21 approaches enable the identification of crop/tree from soil in case of slopes or hilly terrain without 22 any constraint on the displacement / direction of plant/tree row. The proposed algorithm uses pure 23 DSM information even if it is possible to fuse its output with other classifiers.

The energy sector plays an important role in Mexico’s development trajectory. Mexico makes an interesting case study, because it shows how difficult it is to reduce fossil energy dependence despite geographic and climatic conditions that favour renewable energy deployment and use. Resolving path dependencies and the related carbon lock-in are key to Mexico’s sustainable energy transition. This case study aims to identify and discuss how carbon lock-in affects Mexico’s sustainable energy transition. Mexico’s carbon lock-in involves oil and oil-run power plants that are costly to build but relatively inexpensive to operate. This case study identifies potential entry points for transitioning towards sustainable energy in Mexico – resources that can promote the use of clean energy despite carbon lock-in. For example, focusing on electrification – particularly of the carbon-intensive sectors – can help Mexico transit towards sustainable energy despite institutional constraints. Complementing this case study is a teaching guide with recommendations for using Mexico’s energy transition in courses on sustainability. It introduces a “learning activation framework” to identify emerging opportunities that can advance sustainable energy transitions in different cases of carbon lock-in. Finally, the framework also gives students a chance to help dismantle or cope with carbon lock-ins.

In this paper, firstly, some questionable formulas and conceptual oversights of previous reduced sigma set unscented transformation (UT) methods are revised through theoretical analysis. Then the revised UT methods based Kalman filters are used in a GPS/INS tightly-coupled system. The Kalman filter flows are the kind of square-root, since the square-root unscented Kalman filters (SRUKFs) can guarantee the stability of the system. By using the reduced sigma set SRUKFs (which contain simplex sigma set square-root unscented Kalman filter (S-SRUKF), spherical simplex sigma set square-root unscented Kalman filter (SS-SRUKF) and minimum sigma set square-root unscented Kalman filter (M-SRUKF)), the computation cost is greatly saved compared with the standard SRUKF, while the accuracy of the GPS/INS tightly-coupled system still maintained. The structure of the GPS/INS tightly-coupled system is in the form of error state, and the time updates of the state and the state covariance of SRUKFs are directly estimated without using UT, thus the computational time is also greatly saved. The pseudo-satellite is introduced to aid the system when the observation information is deficient, for example, when the GPS signal is deficient in the maneuver environment. By using the pseudo-satellite, the optimal performance of the system is guaranteed. Experiment of unmanned aerial vehicle (UAV) showed that the pseudo-satellite aided mechanism worked well.

The barley (Hordeum vulgare) genome comprises over 32,000 genes, with differentiated cells expressing only a subset of genes; the remainder being silent. Mechanisms by which tissue-specific genes are regulated are not entirely understood, although DNA methylation is likely to be involved. DNA methylation patterns are not static during plant development, but it is still unclear whether different organs possess distinct methylation profiles. Methylation-sensitive GBS was used to generate DNA methylation profiles for roots, leaf-blades and leaf-sheaths from five barley varieties, using seedlings at the three-leaf stage. Differentially Methylated Markers (DMMs) were characterised by pairwise comparisons of roots, leaf-blades and leaf-sheaths of three different ages. While very many DMMs were found between roots and leaf parts, only a few existed between leaf-blades and leaf-sheaths, with differences decreasing with leaf rank. Organ-specific DMMs appeared to target mainly repeat regions, implying that organ differentiation partially relies on the spreading of DNA methylation from repeats to promoters of adjacent genes. Furthermore, the biological functions of differentially methylated genes in the different organs correlated with functional specialisation. Our results indicate that different organs do possess diagnostic methylation profiles and suggest that DNA methylation is important for both tissue development and differentiation and organ function.

The biomass fraction of processed municipal and industrial wastes added to soil can maintain, and in some case improve, the soil’s organic fertility. One of the main constraints in the agricultural use of the sewage sludge is its content of heavy metals. In the long term, soil administration of sewage sludge in agriculture could result in a risk of environmental impact. The aim of this research was to evaluate the effects of medium-term fertilization with sewage sludge diversely processed on the soil’s organic carbon content and humification – mineralization soil’s processes and on the physical and mechanical properties of soil. Furthermore, the heavy metals accumulation in soil, in their total and available form, has been investigated. After eight years of administration to soil, the use of sewage sludge as an agricultural soil amendment has contributed to maintaining the soil’s organic fertility. An increase in concentrations of total Ni and Zn was detected in soil. For bioavailable form (DTPA-extractable) this trend was evidenced for all heavy metals analysed. However, the concentrations of total and available heavy metals in the soil did not exceed the legal threshold established by Italian law for unpolluted soils.

Farmers’ conventional tillage (CT) and residue removal practices in rice-maize systems in South Asia’s Eastern Gangetic Plain (EGP) are input-intensive, costly and soil degradative. We conducted a rice-maize-mungbean (R-M-MB) system experiment with six tillage and three residue management treatments in Bangladesh representing the EGP. Maize yields were significantly (p≤0.05) higher under permanent (PB) or fresh (FB) beds and strip tillage (ST) than CT but no differences in mungbean yields. Rice yields under PB, FB and CT were similar, but significantly higher than under zero or minimum tillage and ST. Yields of all crops increased significantly (p≤0.05) with residue retention compared to no retention. Total system productivity was highest under PB followed by FB and ST. Compared with CT, gross margins in PB, FB and ST increased by 18, 13 and 11%, and soil organic matter (SOM) and total N contents across tillage treatments increased by 11-16% and 12-24%, respectively. After three years, SOM and total N and available P and S contents increased significantly (p≤0.05) by residue retention. Results demonstrate the potential of PB, FB and ST with residue retention, for improving the productivity, profitability and soil health under R-M-MB systems in Bangladesh and similar soils in the EGP.

Land use and land cover change (LULCC) is a critical factor for enhancing the soil erosion risk and land degradation process in the Wabi Shebelle Basin. Up-to-date spatial and statistical data on basin-wide erosion rates can provide an important basis for planning and conservation of soil and water ecosystems. The objectives of this study were to examine the magnitude of LULCC and consequent changes in the spatial extent of soil erosion risk, and identify priority areas for Soil and Water Conservation (SWC) in the Erer Sub-Basin, Wabi Shebelle Basin, Ethiopia. The soil loss rates were estimated using an empirical prediction model of the Revised Universal Soil Loss Equation (RUSLE) outlined in the ArcGIS environment. The estimated total annual actual soil loss at the sub-basin level was 1.01 million tons in 2000 and 1.52 million tons in 2018 with a mean erosion rate of 75.85 t ha^–1 y^–1 and 107.07 t ha^–1 y^–1, respectively. The most extensive soil loss rates were estimated in croplands and bare land cover, with a mean soil loss rate of 37.60 t ha^–1 y^–1 and 15.78 t ha⁻¹ y⁻¹, respectively. The soil erosion risk has increased by 18.28% of the total area, and decreased by 15.93%, showing that the overall soil erosion situation is worsening in the study area. We determined SWC priority areas using the Multi-Criteria Decision Rule (MCDR) approach, indicates that the top three levels identified for intense SWC account for about 2.50%, 2.38%, and 2.14%, respectively. These priority levels are typically situated along the steep slopes in Babile, Fedis, Fik, Gursum, Gola Oda, Haramaya, Jarso, and Kombolcha districts that need emergency SWC measures.

Loess was deposited in the Negev during the Pleistocene, but such sediments seem to be missing for the Holocene. This could be due to erosion unless structures such as ruins offered protection. We studied soils developed on archaeological hilltop ruins in the Negev and the Petra region and compared them with local soils, paleosols, geological outcrops, and current dust. The ruin soils in both regions were found to consist of similarly complex mixtures of local and remote sediment sources. They differ from sediments deposited during current dust storms. This seems due to fixation processes: average accretion rates are estimated to ~0.14 mm/a, suggesting that only ~3% of the current dust that can be trapped with dry marble dust collectors is stored in the soils. Vegetation, biocrusts, and/or clast pavements associated with vesicular layers seem to act as sediment-fixing agents. As well, climate might play a role: rain, and in particular one snowstorm in the Petra region brought a high amount of sediment that was more similar to the ruin soils. Wet deposition and snow might catalyze dust deposition and enhance fixation by fostering vegetation and crust formation. Frequent snow during the Pleistocene might be one explanation of enhanced loess deposition.

Plant growth promoting rhizobacteria (PGPR) are capable to reduce the use of chemical fertilizers input cost of farmer. Keeping in view the study was designed to investigate and evaluate inoculation effect of indigenous rhizospheric bacteria on growth and yield of wheat (Triticum aestivum L.) under in vitro and in vivo conditions using different treatments. Ten potential strains were selected on the basis of their ACC deaminase activity, siderophore production, P-solubilization and production of indole acetic acid (IAA). Further these strains were tested in three different experiments (growth chamber, pot and field). We found significant increase in crop growth response to the inoculants in comparison with un-inoculated control. In pot and field trial we tested PGPR with recommended dose of inorganic fertilizers. The results of present study revealed that inoculation of bacterial strains with wheat seeds significantly increased plant growth and improved crop yield. Results of present study reveal that these strains could be employed in different combinations and can get higher yield in case of half recommended doses of inorganic fertilizers along with consortium of strains in comparison with sole application of recommended dose of fertilizer and with consortium of strains. These strains were further identified by 16Sr RNA gene sequencing, fatty acid profile and biolog. It can be concluded that inoculated bacteria have more potential and contributes in good crop quality, increased yield when they are applied in combination, thus have potential to minimize use of chemical fertilizers.

VpStyA1 and VpStyA2B of Variovorax paradoxus EPS is annotated and characterized as the first representative of an E2-type styrene monooxygenase of proteobacteria. It comprises a single epoxidase (VpStyA1) and a fusion protein (VpStyA2B) which serves mainly as NADH:FAD-oxidoreductase. VpStyA2B had a Km of 33.6 ± 4.0 µM for FAD and a kcat of 22.3 ± 1.1 s-1. VpStyA2B and VpStyA1 showed monooxygenase activity on styrene of 0.14 U mg-1 and 0.46 U mg-1 as well as on benzyl methyl sulfide of 1.62 U mg-1 and of 3.11 U mg-1. A putative fusion region at position 408 (AREAV) was mutated to provide insights on VpStyA2B-function. The best mutant (408-AAAAA) obtained showed a 6.6-times higher affinity for FAD while keeping the NADH-affinity and -oxidation activity. Corresponding epoxidase activity increased (1.6-times). But, other mutants showed still NADH:FAD-oxidoreductase activity, but lost mostly their epoxidase activity indicating effects on the monooxygenase-part as well. Thus, this monooxygenase system represents an interesting candidate for biocatalyst development.

Exclosures are used to regenerate native vegetation as a way to reduce soil erosion, increase rain water infiltration and provide fodder and woody biomass in degraded grazing lands. Therefore, this study assessed the impact of grazing exclosure on vegetation biomass, carbon sequestration and soil nutrients under five and ten years of grazing exclosures and freely grazed areas in Tigray, northern Ethiopia. Vegetation biomass, carbon stocks and soil nutrients increased with increasing grazing exclusion. However, open grazing lands and five years of grazing exclosure did not differ in aboveground biomass, above-and-belowground carbon stocks. Moreover, ten years of grazing exclosure had a higher (P<0.01) grass, herb and litter carbon stocks compared to five years exclosure and open grazing lands. The total carbon stock was higher for ten years exclosure (193.3 t C ha-1) than the five years exclosure (154.0 t C ha-1) and in open grazing areas (146.6 t C ha-1). Grazing lands closed for ten years had a higher SOC, organic matter, total N, available P, and exchangeable K+ and Na+ compared to five year’s exclosure and open grazing lands. Therefore, establishment of grazing exclosures had a positive effect in restoring degraded grazing lands, thus improving vegetation biomass, carbon sequestration potentials and soil nutrients under the changing climate and global warming.

A recent survey that determined heavy metal concentrations in an abandoned Hg mine in Palawan, Philippines, found the occurrence of Hg with As, Ba, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Sb, Tl, V, and Zn. While the Hg originated from the mine waste calcines as supported by previous studies, the critical knowledge about the origin of the other heavy metals remains to be unknown. Our study investigated the sources of heavy metal pollution surrounding the abandoned Hg mine; and assessed the soil and sediment quality, ecological risks, and health risks associated with these toxic metals. Multivariate analyses, such as hierarchical cluster analysis (HCA), principal component analysis (PCA), and Pearson correlation analysis, were used to identify the heavy metal sources from the results of a previous paper. Our results showed that Fe, Ni, Cr, Co, and Mn are associated with the ultramafic geology of the study, whereas As, Ba, Cd, Cu, Pb, Sb, Tl, V, and Zn are likely due to historical mining and processing of cinnabar from 1953-1976. The mine waste calcines were used as construction material for the wharf and as land filler for the adjacent communities. The modified contamination factor (mCdeg) showed that the coast of Honda Bay is highly contaminated, while the inland areas, including the rivers, are very- to ultra-highly contaminated. There is a considerable ecological risk associated with the heavy metals, wherein Ni, Hg, Cr, and Mn contribute an average of 46.3 %, 26.3 %, 11.2 %, and 9.3 % to the potential ecological risk index (RI), respectively. The overall mean hazard index (HI) for both adults (1.4) and children (12.1) exceeded 1, implying the probability of non-carcinogenic adverse effects. The mean total cancer risk over a lifetime (LCR) for both adults (1.19×10-3) and children (2.89×10-3) exceeded the tolerable threshold of 10-4, suggesting a potentially high risk for developing cancer mainly by Ni, Co, and Cr exposure.

Conservation Agriculture (CA) alters soil properties and microbial processes compared to conventional agriculture. These changes can affect soil-atmosphere greenhouse gas (GHG) fluxes. In this overview, we summarized the results of global literature and the gaps in measuring and understanding of GHG fluxes in CA systems and conventional agriculture. Some studies compared soil carbon sequestration and soil respiration in conservation agriculture and no-tillage system with conventional agriculture and the results were not consistent in all experiments. Interactions between CA pillars and soil factors such as soil moisture, temperature, texture can determine the rate of respiration rate and soil-atmosphere CO₂ fluxes. The majority of studies reported larger N₂O emissions in no-tillage treatment compared with conventional tillage while some other studies reported no difference between no-tillage and conventional tillage systems. In the majority of CA studies, there is lack of required information which is necessary to understand the mechanisms and processes that affect soil GHG fluxes. Determining factors like climate, amount of plant residues, soil type, crop types included in crop rotation and cover crops and duration of the study are not considered. Static chamber method was used for measuring soil-atmosphere GHG fluxes in the majority of studies. Spatial and temporal changes in GHG flux rates are high and missing part of highly episodic events by using static chamber method may result over- or under-estimation in flux balance calculation. Applying standard techniques for measuring continuous fluxes can help to calculating accurate GHG balance.

The aims of the study were to evaluate seedling growth and survival of Prunus africana provenances in awi highland based on ecological requirement of the tree. We measured survival and growth of three P.africana provenances seedlings found in Ethiopia (provenances sources namely: Gedeo, Jibat and Munnessa). Design of experiment with randomized complete block design (RCBD) with three replications. Seedlings planted at 2m, 2.5m and 3m distance between plants, plot, and blocks respectively. A plot size of 10mx10m and 25 plants are found per plot (0.01ha). We used ANOVA to test differences in survival, and growth among provenances over time. Results concluded that, provenances have no significant variation among in establishment rate, plant height and collar diameter growth. Of these provenances, Jibat was the first in establishment (56%), second in height (1.97m) and diameter (2.89cm). Gedeo was stood first in height (2.30m) but second in establishment rate (52%) and thickness(3.45cm), but Munessa with very good growth in diameter(3.59cm) might be prefreed for bark extraction followed by Gedeo, last in height (1.75m),but established second (52%). Contrary to expectations, seedlings were still at substantial risk of mortality ≥3 years after planting. Probably the plants survival rate and growth probably affected by altitude, soil water potential, light exposure, and wild animal presence in the surrounding. In steep slope sites, canopy shade, existing weed vegetation as well as wild animals such as apes is unlikely to enhance seedling survival after planting. Our results suggest that seedling mean growth increased with 0.008mm thickness and 0.41mm per day while 2.8mm thickness and 146.8mm tall increment recorded in 2560meter elevated high land or injibara with mean value of 18.5°C and rain fall is 1300mm.

Concentrations of six polycyclic aromatic hydrocarbons (benzanthrone, benz[a]anthracene, chrysene, fluoranthene, pyrene, and triphenylene) of soil samples from Diboll, an East Texas city (USA), were analyzed with gas chromatography-mass spectrometry (GC-MS). Samples were collected from five sites; Old Orchard Park, two heavy traffic intersections (Judd Street and Lumberjack Drive), an industrial site (West Borden Drive), and a truck stop. Acetone and dichloromethane extracts in all samples showed the presence of fluoranthene and pyrene. The sum of fluoranthene and pyrene concentrations in sites followed the order West Borden Drive > Judd Street > Lumberjack Drive > Old Orchard Park > truck stop. Concentrations of fluoranthene and pyrene were in the range 12.3 – 396.5 μg kg^-1 (ppb) and 13.6 – 209.8 μg kg^-1 ₍in dry soil₎, respectively. Benzanthrone, benz[a]anthracene, chrysene, and triphenylene concentrations were < 2 ppb levels. The higher concentrations in soils were associated with sites close to heavy traffic and vehicular emissions.

Biochar application to soil has been proposed as a means for reducing soil greenhouse gas emissions and mitigating climate change. The effects, however, of interactions between biochar, moisture and temperature on soil CO₂ and N₂O emissions, remain poorly understood. Furthermore, the applicability of lab-scale observations to field conditions in diverse agroecosystems remains uncertain. Here we investigate the impact of a mixed wood gasification biochar on CO₂ and N₂O emissions from loess-derived soils using: (1) controlled laboratory incubations at three moisture (27, 31 and 35%) and three temperature (10, 20 and 30°C) levels, and (2) a field study with four cropping systems (continuous corn, switchgrass, low diversity grass mix, and high diversity grass-forb mix). Biochar reduced N₂O emissions under specific temperatures and moistures in the laboratory and in the continuous corn cropping system in the field. However, the effect of biochar on N₂O emissions was only significant in the field, and no effect on cumulative CO₂ emissions was observed. Cropping system also had a significant effect in the field study, with soils in grass and grass-forb cropping systems emitting more CO₂ and less N₂O than corn cropping systems. Observed biochar effects were consistent with previous studies showing that biochar amendments can reduce soil N₂O emissions under specific, but not all, conditions. The disparity in N₂O emission responses at the lab and field scales suggests that laboratory incubation experiments are not reliable for predicting the impact of biochar at the field scale.

In Ethiopia, bamboo thickets and woodlands play an important role in soil-water conservation and climate change mitigation in arid and semi-arid regions. However, bamboo mass flower-ing, rapid demographic changes and expansion of agricultural investments to bamboo domi-nated areas have led to deforestation and land degradation. In this study, we determined the effects of deforestation and subsequent cultivation on soil physical and chemical properties along a chronosequence of closely located agricultural lands with different ages (1, 3, 5 and 7 years) since converted from natural lowland bamboo forest. Hence, soil samples (n = 90) have been taken from both natural bamboo forests and adjacent agricultural lands at two soil depths (0-20 cm and 20-40 cm). Our result showed that CEC, K+, Ca+, Mg+ and available P were varied significantly with respect to cultivation periods and soil depth, while soil pH and Na+ varied with soil depth (P < 0.001). Soil C and total N contents (g/kg) in 0-20 cm soil layer declined significantly and exponentially with increasing years under cultivation. Conversion of natural bamboo forest to cropland during the past seven-year period significantly increased soil pH with soil depths, while CEC was declined throughout the cultivation period and soil depth. In general, the result revealed that conversion of natural lowland bamboo and subsequent cultivation of soil had negative effects on measured soil physicochemical properties.

: There remains no acquiescence that confirms the extent to which unemployment and entrepreneurship influence each other in developing countries. Thus, an incessant invite for further debate attracted the need to assess the relationship between unemployment and entrepreneurship in terms of business formation in Namibia Given that, this study examines the relationship between unemployment and entrepreneurial activities in Namibia. Time series data were collected from the World Bank database to investigate the relationship between unemployment and entrepreneurship in Namibia. Unit root test was conducted using both the Augmented Dickey-Fuller test and the Phillips-Perron test to measure stationarity of the data and found all the variables to have no unit root after the first difference. Thus, we employed the Johansen-Juselius test of cointegration, and the results revealed the absence of a long-run relationship between the variables. Hence, we performed a vector autoregressive (VAR) model to estimate the short-run relationships and found that Namibia exhibit both the refugee and Schumpeter effects. Finally, the direction of causality between the variables was measured using the Pairwise Granger causality test and the results revealed that none of the variables was proven to granger cause the other, concluding that they are all independent of each other. Therefore, in pursuit of unemployment mitigation, we recommend policymakers to focus on other aspects beyond entrepreneurship when devising policies without jeopardizing the ease of business start-up procedures. This will incentivize entrepreneurial activities, which can eventually address other macroeconomic issues beyond unemployment.

Hydrological models have been widely used for many purposes in water sector projects, including streamflow prediction and flood risk assessment. Among the input data used in such hydrological models, the spatial-temporal variability of rainfall datasets has a significant role on the final discharge estimation. Therefore, accurate measurements of rainfall are vital. On the other hand, ground-based measurement networks, mainly in developing countries, are either nonexistent or too sparse to capture rainfall accurately. In addition to in-situ rainfall datasets, satellite-derived rainfall products are nowadays available globally with high spatial and temporal resolution. An innovative approach called SM2RAIN that estimates rainfall from soil moisture data has been applied successfully to various regions. In this study, firstly soil moisture content derived from the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E) is used as input into the SM2RAIN algorithm to estimate daily rainfall, SM2R-AMSRE, at different sites in the Karkheh river basin (KRB), southwest Iran. Secondly, the SWAT (Soil and Water Assessment Tool) hydrological model is applied to simulate runoff using both ground-based observed rainfall and SM2R-AMSRE rainfall as input. The results reveal that the SM2R-AMSRE rainfall data are, in most cases, in good agreement with ground-based rainfall, with correlations R ranging between 0.58 and 0.88, though there is some underestimation of the observed rainfall, due to soil moisture saturation, not accounted for in the SM2RAIN equation. The subsequent SM2R-AMSRE- SWAT- simulated monthly runoff reproduces well the observations at the 6 gauging stations (with coefficient of determination, R² > 0.72), though with slightly worse performances in terms of bias (Bias) and root-mean-square error (RMSE) and, again, some systematic flow underestimation than the SWAT model with ground-based rainfall input. Furthermore, rainfall estimations of two satellite products of the Tropical Rainfall Measuring Mission (TRMM), 3B42 and 3B42RT, are used in the calibrated SWAT- model. The monthly runoff obtained with 3B42- rainfall have 0.39< R2 < 0.70 and are slightly better than those obtained with 3B42RT- rainfall, but not as good as the SM2R-AMSRE- SWAT- simulated runoff above. Therefore, in spite of the afore-mentioned limitations, using SM2R-AMSRE rainfall data in a hydrological model like SWAT, appears to be a viable approach in basins with limited ground-based rainfall data.

The sustainability of irrigated agriculture depends on the quality of irrigation water used. The electrolyte concentration (EC) of irrigation water may lead to the accumulation of salts in the root zone layers and affect the physiological functions of the crop by osmotic and ion toxicity effects. Further, the cationic and anionic composition of the water may alter the exchangeable cation composition of the soil and as well as its pH. Because of the dominance of sodium salts in many sources of irrigation water, parameters related to sodium such as exchangeable sodium percentage (ESP) of soils and sodium adsorption ratio (SAR) of soil solutions have been commonly used to study the effects of sodium in irrigation water on soil structural stability. Quirk and Schofield concept of ‘threshold electrolyte concentration’ (TEC) has shown the importance of electrolytes in preventing the effects of sodium on soil structure. Based on this concept, several models have been proposed to relate ESP or SAR with EC to predict the possible impacts of irrigation water on soil structural stability. However, many research reports indicate that this relationship varies with soils and a given model is not suitable for all types of soils. Further, the effects of potassium and magnesium in the processes leading to clay dispersion are disregarded in these models. This essay analyses all the factors involved in the structural failure of soils with different cationic composition, identify the defects in these TEC models and re-defines TEC on the basis of new insights on dispersive and flocculating charges of soils. This review does not deal with EC effects on crops and also the role of contaminant ions not involved with soil structural stability.

Visible and near-infrared reflectance (Vis–NIR) techniques are a plausible method to soil analyses. The main objective of the study was to investigate the capacity to predicting soil properties Al, Ca, K, Mg, Na, P, pH, total carbon (TC), H and N, by using different spectral (350–2500 nm) pre-treatments and machine learning algorithms such as Artificial Neural Network (ANN), Random Forest (RF), Partial Least-squares Regression (PLSR) and Cubist (CB). The 300 soil samples were sampled in the upper part of the Itatiaia National Park (INP), located in Southeastern region of Brazil. The 10 K-fold cross validation was used with the models. The best spectral pre-treatment was the Inverse of Reflectance by a Factor of 104 (IRF4) for TC with CB, giving an averaged R² among the folds of 0.85, RMSE of 1.96; and 0.67 with 0.041 respectively for H. Into the K-folds models of TC, the highest prediction had a R² of 0.95. These results are relevant for the INP management plan, and also to similar environments. The good correlation with Vis–NIR techniques can be used for remote sense monitoring, especially in areas with very restricted access such as INP.

Mining activities could produce a large volume of spoils, waste rocks, and tailings, which are usually deposited at the surface and become sources of metal pollution. Phytostabilization of the mine spoils could limit the spread of these heavy metals. Phytostabilization can be enhanced by using soil amendments like manure-based biochar capable of immobilizing metal(loid)s when combined with plant species that are tolerant of high levels of contaminants while simultaneously improving properties of mine soils. However, the use of manure-based biochar and other organic amendments for mine spoil remediation are still unclear. In this greenhouse study, we evaluated the interactive effect of biochar application and compost on shoots biomass yield (SBY), roots biomass yield (RBY), uptake, and bioconcentration factor (BCF) of Zn and Cd in corn (Zea mays L.) grown in mine soil. Biochar sources (BS) consisted of beef cattle manure (BCM); poultry litter (PL); and lodge pole pine (LPP) were applied at 0, 2.5, and 5.0% (w/w) in combination with different rates (0, 2.5, and 5.0%, w/w) of cattle manure compost (CMC), respectively. Shoots and roots uptake of Cd and Zn were significantly affected by BS, CMC, and the interaction of BS and CMC. Corn plants that received 2.5% PL and 2.5% BCM had the greatest Cd and Zn shoot uptake, respectively. Corn plants with 5% BCM had the greatest Cd and Zn root uptake. When averaged across BS, the greatest BCF for Cd in the shoot of 92.3 was from the application BCM and the least BCF was from the application of PL (72.8). Our results suggest that incorporation of biochar enhanced phytostabilization of Cd and Zn with concentrations of water-soluble Cd and Zn lowest in soils amended with both manure-based biochars while improving biomass productivity of corn. Overall, phytostabilization technique and biochar application have the potential to be combined in the remediation of heavy metals polluted soils.

Here we evaluate the chemistry of mineral soil solutions collected by suction lysimeters in a small mountain catchment that was affected by acidification-related spruce die-back. The aim was to obtain new insights into spatial patterns of nutrient partitioning during acidification recovery. This was achieved by comparing nutrient concentrations in soil solutions, collected along a V-shaped valley, with those in runoff. Five nests of suction lysimeters were installed in the 33-ha UDL catchment at different topographic positions (hilltops, slopes and valley). Following a 1-year equilibration, monthly samples of soil solutions were collected over a 2-year period. In the vicinity of each lysimeter nest, soil pits were excavated for a study of soil chemistry. Soil solutions were analyzed for SO42-, NO3-, DOC, NH4+, Na+, K+, Ca2+, Mg2+, and total dissolved Al concentrations, DOC and pH. For a P release estimation, ammonium oxalate extraction of soil samples was performed. Comparison of soil water data from this study with other European studies indicated that major environmentally relevant chemical species at UDL had concentrations similar to median concentrations across numerous previously acidified sites. CEC (≤ 58 meq kg-1) and BS (≤ 13 %), however, were significantly lower at UDL than at other European sites, documenting incomplete recovery from acidification. Spatial trends and seasonality in soil water chemistry support belowground inputs from mineral-stabilized legacy pollutants and soil nutrients. Seasonal variability of soil water sulfate and nitrate was significant. High nitrate in soil solutions during summer originated during the preceding dormant season, and high sulfate concentrations observed during the winter originating from recycled organic S during the summer. Higher concentrations of SO42-, NO3-, and base cations in runoff than in soil solutions may be explained by lateral surficial runoff leaching pollutants and nutrients from very shallow soil horizons. Nearly 30 years after peak acidification, solutions in mineral subsoil at UDL exhibited similar concentrations of SO42-, Ca2+ and Mg2+ as median values at the Pan-European International Co-operative Program (ICP) Forest sites, yet NO3- concentrations were an order of magnitude higher than the ICP sites. Calcium applied on soil surface by liming 32 to 11 years ago affected runoff more than soil solutions, suggesting contribution of both shallow soil water and groundwater to runoff.

The heavy demand of water resources from the Zarqa River Basin (ZRB) has resulted in a base-flow reduction of the River from 5m³/s to less than 1m³/s. This paper aims at predicting Curve Numbers (CN) as a baseline scenario and proposing restoration scenarios for ZRB. The method includes classifying the soil type and land use, predicting CNs, and proposing CN restoration scenarios. Prediction of existing CNs will be in parallel with the runoff prediction using the US Army Corps of Engineers HEC-1 Model, and Rainfall-Runoff Model (RRM). The models have been set up at the land use distribution of 0.3% water body, 9.3% forest and orchard, 71% mixture of grass, weeds, and desert shrubs, 7.0% crops, 4.0% urban areas, and 8.4% bare soil. The results show that CN under dry condition are 59, 78 under a normal condition and 89 under a wet condition. During vegetation period, CN are 52, 72 and 86 for the dry, normal and wet condition respectively. The restoration scenarios; CN decreases runoff, and increases soil moisture when using the contours, terraces and crop residues. Analyzing results of CN scenarios will be a fundamental tool to support end-users related to their targets to achieve watershed restoration.

The information on the land use and soil conservation practice based on year 2006, 2010 and 2014, hence offering an opportunity to model the impacts of land use change on erosion, deposition and surface water runoff. Limitation in the use of hydrological models had been their inability to handle the large amount of input data that describe the heterogeneity of the natural system. In this study, a procedure that takes into account soil conservation practice based on the land use change, the response of soil erosion and sediment export from the George Town Conurbation catchment area, and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion areas of rural and urban planning proposes. Average annual sediment yield and data on a grid basis estimated using Universal Soil Loss Equation (USLE) and an emerging technology represented by Geographic Information System (GIS) used as a tool to produce a map for erosion rate. The changing of the land use from forest to agriculture and then to an urban area is a challenging task to research on land use demand for population, and environmental impact assessment is important for the planning of natural resources management, allowing research the modification of land use properly and implement more sustainable for long term management strategies. The challenge is to formulate strategies that would promote an integrated approach to the land use planning at an appropriate level as to address the issues that arose. Modelling for creating urban growth boundary for the George Town Conurbation must have to be controlled surface runoff and soil loss and sediment export from land use of the George Town Conurbation catchment.

Fossils constitute the principal repository of data that allow for independent tests of hypotheses of biological evolution derived from observations of the extant biota. Traditionally, transformational series of structure, consisting of sequences of fossils of the same lineage through time, have been employed to reconstruct and interpret morphological evolution. More recently, a move toward an updated paradigm was fueled by the deliberate integration of developmental thinking in the inclusion of fossils in reconstruction of morphological evolution. The vehicle for this is provided by structural fingerprints – recognizable morphological and anatomical structures generated by (and reflective of) the deployment of specific genes and regulatory pathways during development. Furthermore, because the regulation of plant development is both modular and hierarchical in nature, combining structural fingerprints recognized in the fossil record with our understanding of the developmental regulation of those structures produces a powerful tool for understanding plant evolution. This is particularly true when the systematic distribution of specific developmental regulatory mechanisms and modules is viewed within an evolutionary (paleo-evo-devo) framework. Here, we discuss several advances in understanding the processes and patterns of evolution, achieved by tracking structural fingerprints with their underlying regulatory modules across lineages, living and fossil: the role of polar auxin regulation in the cellular patterning of secondary xylem and the parallel evolution of arborescence in lycophytes and seed plants; the morphology and life history of early polysporangiophytes and tracheophytes; the role of modularity in the parallel evolution of leaves in euphyllophytes; leaf meristematic activity and the parallel evolution of venation patterns among euphyllophytes; mosaic deployment of regulatory modules and the diverse modes of secondary growth of euphyllophytes; modularity and hierarchy in developmental regulation and the evolution of equisetophyte reproductive morphology. More generally, inclusion of plant fossils in the evo-devo paradigm has informed discussions on the evolution of growth patterns and growth responses, sporophyte body plans and their homology, sequences of character evolution, and the evolution of reproductive systems.

Boreal forests are one of the largest stores of carbon on Earth, and two-thirds of them are located in Siberia. Despite the fact that these forests have a significant influence on the global climate, they continue to remain understudied. Chernevaya taiga is a unique example of a highly productive Siberian boreal ecosystem. This type of forest is characterized by a series of unique ecological traits, the most notable of which are the gigantism of the perennial herbaceous plants and bushes, complete lack of moss cover on soil surface, and the type of soil it grows on, notable for its particularly high rate of decomposition of vegetative remains and low humic acid content. Abundant rainfall actively washes out nutrients from the top layers of the soil, but its fertility level remains very high. In fact, based on the existing data, it is twice as high as that of fertilized agricultural lands. In some ways the conditions within this type of forest closely resemble those observed in tropical rainforests. Microbiota associated with soil and plants represent an integral part of an interconnected system and contribute significantly to productive processes in soils. Its impacts on the environment require further study, since it could lead to discoveries that will help improve soil fertility without harming the natural environment.

The sustainability of grazing lands lies in the nexus of human consumption behavior, livestock productivity, and environmental sustainability. Due to fast growing global food demands, many grazing lands have suffered from overgrazing, leading to soil degradation, air and water pollution, and biodiversity losses. Multidisciplinary efforts are required to understand how grazing lands can be better monitored, assessed and managed to attain predictable outcomes of optimal benefit to society. This paper synthesizes our understanding based on previous work done on impacts of grazing on ecosystem goods and services, identifies current knowledge gaps, and formulates a plan forward. We review the impacts of two contrasting grazing systems, continuous and multi-paddock rotational grazing, on soil carbon (C), nutrient cycling and greenhouse gas emissions (GHGs). We then extend our review to explore challenges of incorporating spatial heterogeneity and temporal variability into monitoring and modelling C and nutrient cycling in grazing lands. We revisit two process-based models (i.e., DNDC and DayCent) and two watershed models (i.e., SWAT and VIC) widely used to simulate C, nutrient and water cycles of these lands. Finally we identify research directions for improving the knowledge base which is essential to conserve grazing lands and maintain their ecosystem goods and services.

As a procedure deriving UH (unit hydrograph), the root selection method necessitates only storm runoff data. However, this method must deal with the uncertainty related to the noise fluctuation of runoff ordinates and derive one optimal UH from many storms. This study proposes a procedure that applies the Savitzky-Golay filter to smooth the noise fluctuation of the runoff ordinates and uses the linear combination of UHs from individual storms to derive an optimal UH. The proposed method is applied to the storms of the Nenagh River basin in Ireland. The applicability of the Savitzky-Golay filter for smoothing the noise fluctuation of storm runoffs is examined by means of the Nash-Sutcliffe efficiency index. Furthermore, the root selection method is extended to also estimate IUHs. The results show that the adoption of the Savitzky-Golay filter improves the applicability of the root selection method and that the optimal UH predicts accurately the time-to-peak and peak discharge.

One of society’s greatest challenges is sequestering vast amounts of carbon to avoid dangerous climate change without driving competition for land and resources. Here we assess the potential of an integrated approach based on enhancement of natural biogeochemical cycles in agro-ecosystems that stimulate carbon capture and storage while increasing resilience and long-term productivity. The method integrates plant photosynthesis in the form of (cover) crops and agroforestry which drives carbon capture. Belowground plant-carbon is efficiently stored as stable soil organic carbon (SOC). Aboveground crop and tree residues are pyrolyzed into biochar, which is applied to the soil reducing carbon release through decomposition. Enhanced weathering of basalt powder worked into the soil further captures and stores carbon, while releasing nutrients and alkalinity. The integrated system is regenerative, through enhanced virtuous cycles that lead to improved plant capture, biomass storage and crop yield, the prerequisites for large-scale carbon sequestration along with food security.

The study explores antibacterial, antiinflammatory and cytoprotective capacity of Pelargonium sidoides DC root extract (PSRE) and proanthocyanidin fraction from PSRE (PACN) under conditions characteristic for periodontal disease. Following previous finding that PACN exerts stronger suppression of Porphyromonas gingivalis compared to the effect on commensal Streptococcus salivarius, the current work continues antibacterial investigation on Staphylococcus aureus, Staphylococcus epidermidis, Aggregatibacter actinomycetemcomitans and Escherichia coli. PSRE and PACN are also studied for their ability to prevent gingival fibroblast cell death in the presence of bacteria or bacterial lipopolysaccharide (LPS), to block LPS- or LPS+IFNγ-induced release of inflammatory mediators, gene expression and surface antigen presentation. Both PSRE and PACN were more efficient in suppressing Staphylococcus and Aggregatibacter compared to Escherichia, prevented A. actinomycetemcomitans- and LPS induced death of fibroblasts, decreased LPS-induced release of interleukin 8 and prostaglandin E2 from fibroblasts and IL-6 from leukocytes, blocked expression of IL-1β, iNOS, and surface presentation of CD80 and CD86 in LPS+IFNγ-treated macrophages, and IL-1β and COX-2 expression in LPS-treated leukocytes. None of the investigated substances affected either the level of secretion or expression of TNFα. In conclusion, PSRE, and especially PACN, possess strong antibacterial, antiinflammatory and gingival tissue protecting properties under periodontitis mimicking conditions and are suggestable candidates for treatment of the disease.

Soil moisture (SM) plays an essential role in environmental studies related to wetlands, an ecosystem sensitive to climate change. Hence, there is the need for its constant monitoring. SAR (Synthetic Aperture Radar) satellite imagery is the only mean to fulfill this objective regardless of the weather. The objective of the study was to develop the methodology for SM retrieval under wetland vegetation using Sentinel-1 (S-1) satellite data. The study was carried out during the years 2015–2017 in the Biebrza Wetlands, situated in northeastern Poland. At the Biebrza Wetlands, two Sentinel-1 validation sites were established, covering grassland and marshland biomes, where a network of 18 stations for soil moisture measurement was deployed. The sites were funded by the European Space Agency (ESA), and the collected measurements are available through the International Soil Moisture Network (ISMN). The NDVI (Normalized Difference Vegetation Index) was derived from the optical imagery of a MODIS (Moderate Resolution Imaging Spectroradiometer) sensor onboard the Terra satellite. The SAR data of the Sentinel-1 satellite with VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) polarization were applied to soil moisture retrieval for a broad range of NDVI values and soil moisture conditions. The new methodology is based on research into the effect of vegetation on backscatter () changes under different soil moisture and vegetation (NDVI) conditions. It was found that the state of the vegetation may be described by the difference between  VH and  VV, or the ratio of  VV/VH, as calculated from the Sentinel-1 images. The most significant correlation coefficient for soil moisture was found for data that was acquired from the ascending tracks of the Sentinel-1 satellite, characterized by the lowest incidence angle, and SM at a depth of 5 cm. The study demonstrated that the use of the inversion approach, which was applied to the new developed models and includes the derived indices based on S-1, allowed the estimation of SM for peatlands with reasonable accuracy (RMSE ~ 10 vol. %). Due to the temporal frequency of the two S-1 satellites’ (S-1A and S-1B) acquisitions, it is possible to monitor SM changes every six days. The conclusion drawn from the study emphasizes a demand for the derivation of specific soil moisture retrieval algorithms that are suited for wetland ecosystems, where soil moisture is several times higher than in agricultural areas.

The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. In this paper, a RUSLE model-based soil loss quanti-fication technique is presented to estimate the annual soil loss and identify the severity of the erosion in the catchment. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. A model builder for the RUSLE model was developed and raster map calcula-tion algebra was applied in ArcGIS version 10.4 to quantify the total annual soil loss. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. The information about the spatial variation of soil loss severity map generated in RUSLE model has a paramount role to alert land resources man-agers and all stakeholders in controlling the effects via implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

Highly weathered soils in the tropics are low in fertility, negatively affecting plant growth. The potential of biochar for improving soil nutrient retention is reportedly promising, triggering this study to assess the nutrient retention capacities of two biochars when applied at 2% in combination with two composts also applied at 2% to an Ultisol (Ustic Kanhaplohumult, Leilehua series) and an Oxisol (Rhodic haplustox, Wahiawa series) of Hawai’i. Chinese cabbage (Brassica rapa cv. Bonsai) was used as the test plant in two greenhouse plantings, which had a factorial completely randomized design with three replicates per treatment. The results indicated that the combined additions of biochar and compost significantly increased the pH, EC, P and K of the soils; improved Ca, Mg and Fe uptake; and increased shoot and total cabbage fresh and dry matter. Exchangeable aluminum in the Ultisol was decreased from 2.5 cmol+/kg to virtually zero. Extractable Mn and Fe in the high Mn-Oxisol were decreased by 55 and 42%, respectively. Chinese cabbage growth in the Ultisol amended with the lac tree (Schleichera oleosa) wood biochar and vermicompost was almost twice over lime at 2 cmol+/kg. Essential nutrients in the plant tissues, with the exception of N and K, were sufficient for the cabbage growth, suggesting increases in nutrients and reduced soil acidity by the additions of biochar combined with compost were the probable cause.

Soil hydraulic properties are often derived indirectly, i.e. computed from easily available soil properties with pedotransfer functions (PTFs), when those are needed for catchment, regional or continental scale applications. When predicted soil hydraulic parameters are used for the modelling of the state and flux of water in soils, uncertainty of the computed values can provide more detailed information when drawing conclusions. The aim of this study was to update the previously published European PTFs (Tóth et al., 2015, euptf v1.4.0) by providing prediction uncertainty calculation built into the transfer functions. The new set of algorithms was derived for point predictions of soil water content at saturation (0 cm matric potential head), field capacity (both -100 and -330 cm matric potential head), wilting point (-15.000 cm matric potential head), plant available water, and saturated hydraulic conductivity, as well as the Mualem-van Genuchten model parameters of the moisture retention and hydraulic conductivity curve. The minimum set of input properties for the prediction is soil depth and sand, silt and clay content. The effect of including additional information like soil organic carbon content, bulk density, calcium carbonate content, pH and cation exchange capacity were extensively analysed. The PTFs were derived adopting the random forest method. The advantage of the new PTFs is that they i) provide information about prediction uncertainty, ii) are significantly more accurate than the euptfv1, iii) can be applied for more predictor variable combinations than the euptfv1, 32 instead of 5, and iv) are now also derived for the prediction of water content at -100 cm matric potential head and plant available water content.

We present an improved algorithm for fast calculation of the inverse square root for single-precision floating-point numbers. The algorithm is much more accurate than the famous fast inverse square root algorithm and has a similar computational cost. The presented modification concern Newton-Raphson corrections and can be applied when the distribution of these corrections is not symmetric (for instance, in our case they are always negative).

Soil erosion seriously affects vineyards. In this study, the influence of two plant covers on soil moisture and the effect of different physiographic conditions on runoff and sediment yields were evaluated in a rainfed vineyard formed by four fields (NE Spain) during 15 months. One field had spontaneous vegetation as plant cover and three fields had a cover crop of common sainfoin. The vineyards’ rows were dry and stable, whereas the inter-row areas were wet although very variable, and the corridors were wet and very stable. Soil moisture in the inter-row areas with Common sainfoin was much higher than in the rows (62% - 70%) whereas this difference was lower with spontaneous vegetation (40%). Two runoff and sediment traps (STs) were installed in two ephemeral gullies, and 26 time-integrated surveys (TIS) done. The mean and maximum runoff yields were 9.8 and 30.7 l TIS^–1 in ST2 and 13.5 and 30.2 l TIS^–1 in ST3. The mean turbidity was 333 and 19 g l^–1, and the maximum sediment yields were 41,260 and 2,778 g TIS^–1 in ST2 and ST3. Changes in the canopy covers (grapevines and plant covers) and rainfall parameters explained the runoff and sediment dynamics.

The development of compartmentalized neuron culture systems has been invaluable in the study of neuroinvasive viruses, including the alpha herpesviruses Herpes Simplex Virus 1 (HSV-1) and Pseudorabies Virus (PRV). This chapter provides updated protocols for assembling and culturing rodent embryonic superior cervical ganglion (SCG) and dorsal root ganglion (DRG) neurons in Campenot trichamber cultures. In addition, we provide several illustrative examples of the types of experiments that are enabled by Campenot cultures: 1. Using fluorescence microscopy to investigate axonal outgrowth/extension through the chambers, and alpha herpesvirus infection, intracellular trafficking, and cell-cell spread via axons. 2. Using correlative fluorescence microscopy and cryo electron tomography to investigate the ultrastructure of virus particles trafficking in axons.

During composting process, soils undergo many changes in their physical, chemical and biological properties. Composting has been widely known as an aerobic process during which organic matter is decomposed to humus like substances broken into many organic materials or compounds. The project aims to compare and analyze different combination of composting that yield different properties and nature of soils, and testing their soil physical properties. Dug three compost pits each 1.5 m in depth, labeled compost pit A consisting of potato peels – the only kitchen waste most common around the college hostels, compost pit B consisting of leaf litter and other garden trimmings and compost pit C consisting of cow dung and the other as a controlled experiment with no composting practices.

Among the different applicable irrigants for root canal disinfection, sodium hypochlorite 5.25% is one of the most attractive ones. The quality of root canal disinfection is dependent on some factors such as the employed approach, type of flow rate of irrigant and the size of needle. The majority of studies in the field of root canal disinfection are experimentally carried out. In the current article, Computation Fluid Dynamic (CFD) is used for modeling the antimicrobial liquid flow in the root canal and evaluate the effects of needle size and flow rate. Two needles, G28 and G30, are used for irrigation in three volumetric rates of flow including 0.10 mL⁄s , 0.20 mL⁄s and 0.30 mL⁄s. The results of numerical simulations revealed the improved quality of root canal disinfection by augmentation in the rate of flow and decrease in the inner diameter of the needle. According to the outcomes of the modeling, the highest average wall shear stress obtained in the case of using G28 needle and 30 mL⁄s flow rate, which was approximately 10.21 Pa.

Two histamine receptor subtypes (HR), namely H1R and H4R, as key components, are involved in the transmission of histamine-induced itch. Although exact downstream signaling mechanisms are still elusive, transient receptor potential (TRP) ion channels play important roles in the sensation of histaminergic and non-histaminergic itch. Aim of this study was to investigate the involvement of TRPV1 and TRPA1 channels in the transmission of histaminergic itch. The potential of TRPV1 and TRPA1 inhibitors to modulate H1R- and H4R-induced signal transmission was tested in a scratching assay in mice in vivo and in vitro via Ca2+ imaging of murine sensory dorsal root ganglia (DRG) neurons. The TRPV1 inhibition led to a reduction of H1R- and H4R- induced itch and reduced Ca2+ influx into the neurons. The TRPA1 inhibitor reduced H4R-induced itch and both H1R- and H4R-induced Ca2+ influx. In conclusion, these results indicate that both channels, TRPV1 and TRPA1 are involved in the transmission of histamine-induced pruritus.

Soil above a platinum-group element (PGE)-bearing horizon within the Freetown Layered Intrusion, Sierra Leone contains anomalous concentrations of n-alkanes (CnH2n+2) in the range C14 to C22 not readily attributable to an algal or lacustrine origin. Longer chain n-alkanes (C23 to C31) in the soil were derived from the breakdown of leaf litter beneath the closed canopy humid tropical forest. Spontaneous breakdown of the longer chain n-alkanes to form C14-22 n-alkanes without biogenic or abiogenic catalysts is unlikely as the n-alkanes are stable. In the Freetown soil, the catalytic properties of the PGE (Pt in particular) may lower the temperature at which oxidation of the longer chain n-alkanes can occur. Reaction between these n-alkanes and Pt species such as Pt2+(H2O)2(OH)2 and Pt4+(H2O)2(OH)4 can bend and twist the alkanes, and significantly lower the Heat of Formation. Acknowledging the possibility of microbial catalysis and the difficulty of identifying a direct organic geochemical source of the lighter n-alkanes, this paper explores the theoretical potential for abiogenic Pt species catalysis as a mechanism of breakdown of the longer n-alkanes to form C14-22 alkanes. This novel mechanism could substantiate the presence of the PGE in solution predicted by soil geochemistry and illustrate processes involving the PGE. Graphical Abstract