Soil Conditions Research Articles

Effect of Three Different Types of Biochar on Bioelectricity Generated from Plant Microbial Fuel Cells under Unsaturated Soil Condition.

Plant microbial fuel cell (PMFC) is an emerging technology, showing promise for environmental biosensors and sustainable energy production. Despite its potential, PMFCs struggle with issues like low power output and limited drought resistance. Recent studies proposed that integrating biochar may enhance PMFC performance due to its physicochemical properties. The influence of different biochar types on PMFC efficiency has been minimally explored. This study aims to fill this gap by evaluating the performance of PMFCs integrated with various biochar types under unsaturated soil conditions. The study found that the addition of biochar types─specifically reed straw biochar (RSB), apple wood biochar (AWB), and corn straw biochar (CSB)─significantly influenced the performance of PMFCs. RSB, with its large surface area and porous structure, notably increased the current output by reducing soil resistance and enhancing electron transfer efficiency in microbial reduction reactions, achieving a peak power density of approximately 1608 mW/m2. AWB, despite its less porous structure, leveraged its high cation exchange capacity and hydrophilic functional groups to foster microbial community growth and diversity, thereby also increasing bioelectricity output. Conversely, CSB, with its large surface area, showed the least improvement in PMFC performance due to its layered structure and lower water retention capacity. Additionally, under drought conditions, PMFCs with added RSB and AWB exhibited better drought resistance due to their ability to improve soil moisture characteristics and enhance soil conductivity. The addition of biochar reduced soil resistance, increasing the bioelectric output of PMFCs and maintaining good performance even under low moisture conditions. This study highlights the critical role of biochar's surface area and functional groups in optimizing PMFC performance. It enhances our understanding of PMFC optimization and might offer a novel power generation method for the future, while also presenting a fresh strategy for soil monitoring.

Characterizing Flow Dynamics in a Two-dimensional Flow Cell: Developing Methodologies for Enhanced Subsurface Contaminant Remediation Research

This study used a two-dimensional (2-D) flow cell apparatus (25 cm × 25 cm × 1 cm) to characterize water flow and contaminant transport in porous media. The primary objective was to enhance the understanding of flow dynamics and contaminant behavior in controlled 2-D environments, which is crucial for optimizing the application of remediation technologies to treat contaminants in saturated and unsaturated soil conditions. The 2-D cell was designed with transparent walls to simulate subsurface conditions using medium grained sand, allowing for precise control and observation of fluid movement under saturated and quasi-saturated (trapped air) conditions. Visualization techniques and flow measurement tools were employed to capture detailed data on flow patterns, velocities, and dispersion characteristics. Analysis of breakthrough curves for salt tracer tests using electrical conductivity measurements, alongside varying flow rates, flow fractions, and port configurations, provided significant insights into fluid behavior and contaminant transport. The study also explored the effects of varying salt concentrations (and solution densities) on flow dynamics, contributing to a better understanding of the role of contaminant concentration in contaminant plume development and remediation processes. Visual analysis using dyed contaminant complemented the quantitative data, offering real-time observations of flow patterns and contaminant distribution. A custom-built apparatus was used to control the hydraulic head of multiple outlet ports to sample water from different depths. The experiments demonstrated that gravity plays a crucial role in solute (salt) breakthrough, with lower ports showing earlier breakthrough. Flow fields formed vertically, from bottom-to-top, and horizontally, from inlet-to-outlet, with lower portions advancing sooner. However, multi-port configurations, especially involving five ports, disrupted the sequential breakthrough order, possibly due to convection in the clear well that formed the outlet boundary of the flow cell. These findings will support research students in conducting similar experiments with flow and transport that varies with depth, with future insights for professionals in developing and optimizing remediation strategies related to subsurface contaminant flow. Special thanks are extended to Liam Price, Julia-Barnes James, and Brooke Belfall who were helpful during the research and the experimentation process.

Influence of degree of saturation on the thermal conductivity of soils: Experimental and comparative model analysis

The thermal conductivity can characterize thermal behaviour of soils in different engineering studies: environmental, geothermal, geotechnical and buildings construction. However, accurately measuring and predicting this parameter poses a challenging task. Measuring this parameter can be very complex, considering several factors, such as soil heterogeneity and external climatic conditions. In addition, predictions models may not capture all the nuances of real-world soil conditions, leading to less accurate predictions of ?. The objectives of this paper encompassed two primary aspects: (i) Evaluation of laboratory tests of thermal conductivity of unsaturated soil. (ii) Assessment of five highly recommended soil thermal conductivity models to determine their validity and strengthen their trustworthiness. The studied material consisted of calcareous tufa locally available in Beni-Saf region (Algeria). The tested samples were compacted to the Standard and Modified Proctor Optimum (SPO, MPO) followed by drying periods under laboratory conditions. The thermal conductivity of samples was evaluated using transient method. The models’ predictive results of the thermal conductivity were assessed with different criteria such as Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Coefficient of Determination R². Furthermore, this work also attempts to deliver an in-depth discussion of the effect of degree of saturation Sr on the thermal conductivity of soils.

Experimental assessment of strength characteristics of anthropogenic soils in a given mining area for justification of tractor propulsion type

BACKGROUND: In mining, there is a need to develop tractors as special robotic vehicles of the robotic mining facility that can efficiently move and work on soils with low bearing capacity, in waterlogged areas and in the underwater position. A preliminary evaluation of the strength characteristics of such a heterogeneous surface of the exploitation area helps to choose an effective concept and technical characteristics of the propulsor of the tractor. AIM: Formation of the database of the physical condition and mechanical properties of the environment in which the tractor will move and operate. METHODS: In order to achieve the aim, preliminary experiments were conducted on the terrain. Typical kinds of soil sites and watered areas, including those of anthropogenic origin, of a given mining area were identified. Full-scale instrumental tests were conducted to determine: granulometric composition of soils; physical and mechanical parameters of these soils at the selected sites using the developed original types of a penetrometer and a shear rig. RESULTS: The database of numerical values of measured strength characteristics of one of the soil types (as an example) as a possible supporting surface for vehicle motion in the area of mining facility operation is presented in a graphical form. The basis of this database is the graphs according to the results of experiments on free settlement and shear with the help of dies of two types of configuration (the round die and the original caterpillar track respectively); the granulometric composition of the selected soils has been evaluated. CONCLUSION: The methodology of preliminary assessment of the soil condition by two indicators of soil strength (the rut depth z depending on the average pressure under the die) and shear (average tangential stresses τ in the contact patch on the motion of the die relative to the soil, depending on the ratio of the normal force and the traction force in the contact plane) has been developed. The 3D model of the coastal and bottom area of the technogenic mining zone has been developed. Design variants of highly efficient types of tractor propulsors are selected on the basis of prediction of maximum allowable stresses in the contact patch with the ground for the bearing surface areas of the considered area of operation.

MRI and HR-MAS NMR spectroscopy to correlate structural characteristics and the metabolome of Fiano and Pallagrello grapes with the action of field spray preparation 500 and the soil spatial microvariability

BackgroundA number of Italian grape berry varieties, such as Fiano (F) and Pallagrello Nero (P), represent National strategic products. Therefore, it is important to identify soil conditions emphasizing their peculiar characteristics as well as find innovative and sustainable treatments improving their compositional and nutraceutical quality. The field spray preparation 500 is a biodynamic product that is presumed to serve as biostimulant on the vine. However, so far, the scientific results probing its effectiveness are still lacking. Moreover, it is necessary to establish a reliable relationship between the grape quality and the spatial microvariability of the vineyard’s soil. On this basis, the main objective of this work consisted in correlating structural and morphological characteristics (via MRI), the primary metabolome (via semi-solid state HRMAS NMR) and important nutraceutical parameters (total phenols and antioxidants via DPPH assay) of F and P grapes with both the action of preparation 500 biostimulant and the vineyard soil microvariability, based on soil apparent electrical conductivity.ResultsHRMAS enabled the identification of the primary metabolome of F and P. The elaboration of 1H NMR spectra through chemometrics revealed significant changes in F and P grapes, accounting for both soil microvariability and the application of field spray (the latter also confirmed by PLS-DA and Heat-map clustering). Interestingly, for both F and P it was observed a significantly lower content of carbohydrates after biostimulant treatment while MRI revealed diagnostic structural and internal details of intact grapes. The combined use of proton parametric indices, such as relaxation times and diffusion coefficients, indicated alterations induced in grapes by both the spatial microvariability of the soil and the effects of investigated biostimulant. Interestingly, a tight correlation was found between MRI transverse relaxation time and the contents in total phenols and antioxidants.ConclusionsOur results have proven that both soil spatial microvariability and the application of field spray preparation 500 significantly affect the structural, metabolomic and nutraceutical characteristics of grapes. Moreover, the preparation 500 treatment has increased the nutraceutical value of grapes. Importantly, these data may be potentially used to promote and protect biodynamic grape and predict the quality of the resulting wines.Graphical

Advancing Food Security in the Cryolithozone and Exploring Organic and Mineral Fertilizer Strategies for Enhanced Crop Yields

The Cryolithozone, characterized by its frozen soil and harsh climatic conditions, presents unique challenges to agricultural productivity and food security. As global temperatures rise, the thawing of permafrost in the Cryolithozone offers opportunities for agricultural expansion but also raises concerns about soil degradation and nutrient loss. In this article, we explore innovative approaches to enhance crop yields and food security in the Cryolithozone, focusing on the integration of organic and mineral fertilizer strategies. We discuss the potential benefits and challenges of utilizing organic fertilizers, such as compost and manure, to improve soil fertility and mitigate nutrient deficiencies. Additionally, we examine the role of mineral fertilizers in supplying essential nutrients to crops in nutrient-deficient Cryolithozone soils. By synthesizing current research and best practices, we propose holistic fertilizer management strategies tailored to the unique environmental conditions of the Cryolithozone. These strategies aim to optimize nutrient utilization efficiency, minimize environmental impacts, and promote sustainable agricultural development in cold regions.

Soil volatilomics uncovers tight linkage between soybean presence and soil omics profiles in agricultural fields

Securing a stable food supply and achieving sustainable agricultural production are essential for mitigating future food insecurity. Soil metabolomics is a promising tool for capturing soil status, which is a critical issue for future sustainable food security. This study aims to provide deeper insights into the status of soybean-grown fields under varying soil conditions over three years by employing comprehensive soil volatile organic compound (VOC) profiling, also known as soil volatilomics. Profiling identified approximately 200 peaks in agricultural fields. The soil of soybean-presented plots exhibited markedly higher VOC levels than those of non-soybean plots during the flowering season. Pentanoic acid, 2,2,4-trimethyl-3-carboxyisopropyl, isobutyl ester, a discriminative soil VOC, was identified through multivariate data analysis as a distinctively present VOC in fields with or without soybean plants during the flowering period. Soil VOC profiles exhibited strong correlations with soil-related omics datasets (soil ionome, microbiome, metabolome, and physics) and no significant correlations with root microbiome and rhizosphere chemicals. These findings indicate that soil VOC profiles could serve as a valuable indicator for assessing soil status, thereby supporting efforts to ensure future global food security.

Isolation of Rhizobium from Moisture Stress Imposed Groundnut Nodules

Groundnut is an important oil seed crop accounts for a less than half of the major oilseeds produced in the country. Oil content of Groundnut varies from 44 % to 50 % depending upon the varieties and agronomic practices. It is also called as ‘king of oil seeds’ More than 85 % of the crop Is grown under rainfed conditions in low fertile soils. Rhizobium is a well-known symbiotic nitrogen fixing bacteria. Inoculation of Rhizobium improves plant growth, pod kernel and Oil yield. Rhizobium species help in improving root nodulation and nitrogen fixation, enhancing plant growth and yield of leguminous plants including groundnut under moisture stress conditions. Hence the present study is to isolate Rhizobium species from groundnut nodules by following method given by Vincent (1970) after growing them on Yeast Mannitol Agar Media morphological characteristics were studied, which can be further used for improving nodulation efficiency and plant growth promotion under moisture stress conditions.

Seasonal dynamics of soil ecosystems in the riparian zones of the Three Gorges Reservoir, China

Riparian soils, together with vegetation, play a crucial role in supporting biodiversity and driving biogeochemical processes within river ecosystems. Conservation of riparian soils and artificial planting are essential for river ecosystem recovery following land degradation. Researchers focus on examining soil nutrients, microbial biomass, and organic acid metabolism in the interactions between plants and soil along riverbanks. However, the seasonal responses of riparian soils to artificial plantations have been infrequently reported in the existing literature. This study investigates the influence of seasonal variations on soil conditions and the growth of artificially planted species in the riparian zones of the Three Gorges Dam Reservoir (TGDR) in China. The species sampled include Cynodon dactylon, Hemarthria altissima, and Salix matsudana. These species provide valuable insight into soil properties along riparian zones, assessing interactions across different seasons: T1 (spring), T2 (summer), and T3 (autumn). The results demonstrated significant seasonal changes in soil organic matter, ammonium nitrogen, nitrate nitrogen, and other indicators between T1 and T3. Apart from invertase activity in H. altissima soil, enzyme activity peaked during T1. Dominant soil bacteria were examined using high-throughput 16S rDNA sequencing, revealing that the available bacteria belong to 62 phyla and 211 classes. Among the most abundant were Proteobacteria and Actinobacteria, averaging over 60 % across all soil samples. Principal component analyses accounted for 62.81 % (T1), 50.57 % (T2), and 54.08 % (T3) of the variation observed in the study, indicating that soil properties were predominantly influenced by the different seasonal phases, assuming all other factors remained constant. Pearson correlation analysis (p < 0.05) identified strong positive correlations between physical properties and all three plant species during T1 (r ≤ 0.94), as well as significant negative correlations with bacterial communities in T2 and T3 (r ≤ −1.00). These findings suggest that the selected plant species are well-suited to cultivation in the riparian zone of the TGDR. This study enhances our understanding of seasonal dynamics in riparian environments, offering practical insights into their management.

Silvicultural regime shapes understory functional structure in European forests

Abstract Managing forests to sustain their diversity and functioning is a major challenge in a changing world. Despite the key role of understory vegetation in driving forest biodiversity, regeneration and functioning, few studies address the functional dimensions of understory vegetation response to silvicultural management. We assessed the influence of the silvicultural regimes on the functional diversity and redundancy of European forest understory. We gathered vascular plant abundance data from more than 2000 plots in European forests, each associated with one out of the five most widespread silvicultural regimes. We used generalized linear mixed models to assess the effect of different silvicultural regimes on understory functional diversity (Rao's quadratic entropy) and functional redundancy, while accounting for climate and soil conditions, and explored the reciprocal relationship between three diversity components (functional diversity, redundancy and dominance) across silvicultural regimes through a ternary diversity diagram. Intensive silvicultural regimes are associated with a decrease in functional diversity and an increase in functional redundancy, compared with unmanaged conditions. This means that although intensive management may buffer communities' functions against species or functional losses, it also limits the range of understory response to environmental changes. Policy implications. Different silvicultural regimes influence different facets of understory functional features. While unmanaged forests can be used as a reference to design silvicultural practices in compliance with biodiversity conservation targets, different silvicultural options should be balanced at landscape scale to sustain the multiple forest functions that human societies are increasingly demanding.

Application of Magnetized Ionized Water and Bacillus subtilis Improved Saline Soil Quality and Cotton Productivity.

Soil salinization, a significant global challenge, threatens sustainable development. This study explores the potential of magnetized ionized water irrigation and Bacillus subtilis application to mitigate this issue. The former method is hypothesized to enhance soil salt leaching, while the latter is expected to improve soil nutrient availability, thereby increasing microbial diversity. To address the unclear impact of these interventions on soil quality and cotton productivity, this study employs four different experimental methods: magnetized ionized water irrigation (M), application of 45 kg ha-1B. subtilis (B), a combination of 45 kg ha-1B. subtilis with magnetized ionized water irrigation (MB), and a control treatment with no intervention (CK). This study aims to clarify the effects of these treatments on soil bulk density (BD), field capacity (FC), salinity and alkalinity, nutrient content, microbial activity, and cotton crop yield and quality. Additionally, it aims to evaluate the efficacy of these methods in improving saline soil conditions by developing a soil quality index. The results showed that using magnetized ionized water for irrigation and applying B. subtilis, either alone or together, can effectively lower soil pH and salt levels, enhance microbial diversity and abundance, and improve the yield and quality of cotton. Notably, B. subtilis application significantly decreased BD and enhanced FC and nutrient content (p < 0.05). A correlation was found where soil nutrient content decreased as pH and salt content increased. Furthermore, a strong correlation was observed between the major soil bacteria and fungi with BD, FC, and salt content. Comparatively, M, B, and MB significantly boosted (p < 0.01) the soil quality index by 0.21, 0.52, and 0.69 units, respectively, and increased (p < 0.05) cotton yield by 5.7%, 14.8%, and 20.1% compared to CK. Therefore, this research offers eco-friendly and efficient methods to enhance cotton production capacity in saline soil.

Digitalization and digital technologies of agriculture in the European Union

Today, many agricultural organisations already use sensors, smartphones, tablets, drones and satellites in their operations. Digital technologies provide, for example, solutions for remotely measuring soil conditions, better water management, livestock and crop monitoring.By analysing data collected by sensors, farming organisations can gain insight into the likely pattern of crops or the health and welfare of animals, etc. This allows them to plan activities more effectively, to be more efficient.Digitalisation can increase farm profitability, improve working conditions and reduce environmental impact.

Methodology for Obtaining the Core of the Base Model Based on the Results of Experimental Studies of the Interactions of Plates and Stamps with a Pliable Base

Article, by way of discussion, provides a description of a technique to determine the core of foundation modelfor the subsequent generation of forces and deformations in the foundation plate on a pliable base by an analytical method. The technique described in the article can also be used to determine the contact model of the base that is closest to these soil conditions, as well as to check the soil conditions for identity from the point of view of soil models. Main goal of conducted research is to obtain relationship between displacements and contact soil stresses, which is an integral Fredholm equation of the 1st kind with the core of soil model described by B.G. Korenev.

Predicting Seasonal Deformation Using InSAR and Machine Learning in the Permafrost Regions of the Yangtze River Source Region

AbstractQuantifying seasonal deformation is essential for accurately determining the thickness of the active layer and the distribution of water content within it, providing insights into the freeze‐thaw dynamics of permafrost environments and their sensitivity to climate change. Due to the limited hydraulic conductivity of the underlying permafrost, the freeze‐thaw processes are largely confined to the active layer, allowing for predictable seasonal deformations. This study employed Independent Component Analysis to isolate large‐scale seasonal deformation from Interferometric Synthetic Aperture Radar (InSAR) measurements taken from 2016 to 2020 in the Yangtze River Source Region (YRSR) of the Qinghai‐Tibet Plateau (QTP), covering 18,500 km2. We developed dedicated machine learning (ML) models that integrate these InSAR‐derived measurements with various environmental proxies. By applying these models to the YRSR, we generated a comprehensive, full‐coverage deformation map for permafrost terrains, achieving an R2 value of 0.91 and an Root Mean Squared Error of approximately 0.5 cm, thus confirming the model's strong predictability of seasonal deformation in permafrost regions. Deformation magnitude varied from less than 1 cm to over 10 cm. Our analysis suggests that terrain attributes, influenced by climate and soil conditions, are the primary factors driving these deformations. This research provides valuable insights into quantifying permafrost‐related seasonal deformation across expansive and rural landscapes. It also aids in assessing subsurface hydrological processes and the resilience and vulnerability of permafrost. The developed ML algorithm, with access to precise environmental data, is capable of forecasting seasonal deformations across the entire QTP and potentially throughout the Arctic.

INVESTIGATING THE KEY LIMITATIONS AND IMPROVEMENTS INFLUENCING THE COMPETITIVE SUCCESS OF SOUTH AFRICA’S ORANGER EXPORTERS.

The objective of identifying constraining factors is to reveal that the key obstacles affecting the competitiveness of South Africa's domestic orange industry include issues such as the "quality of unskilled labor," "trust in the honesty of politicians," "electricity suppliers," "health," "South Africa’s land reform policy," "South Africa’s BEE policy," and "crime." Additionally, challenges related to the lack of quality infrastructure, bilateral agreements with trading countries, and poor performance of ports relative to their global counterparts have been identified. The constraining factors were ranked, with the top issues aligning closely with the industry's current challenges. In contrast, enhancing factors play a crucial role in boosting industry competitiveness in both domestic and international markets. The key elements contributing positively include the availability of unskilled labor, local input suppliers, scientific research institutions, technological quality, the cost of unskilled labor, soil conditions, and the sustainability of local input suppliers. Attention to maintaining and improving these factors is crucial for the sustained competitiveness of the South African orange sector.

Smart farming: Leveraging IoT and deep learning for sustainable tomato cultivation and pest management

Since the world's population is rising continuously, more cultivable land is being utilized for their dwellings. As a result, the amount of food supply is decreasing day by day. In order to address the food shortage, a proper plan and technological breakthroughs is must. Tomato is a kind of vegetable which has the healthy ingredients and essential for our daily food list. The proposed system suggests an IoT based tomato cultivation and pest management system, with the help of deep learning methods. In the IoT implementation, camera module and moisture sensor are used to collect images of tomato plant, soil condition respectively. Based on the moisture content, the water pump will supply the water when it necessary. Besides, the real-time images of tomato leaf will be sent to the server to identify and classify natural enemies like various insect species. In the proposed system seven types of pests are identified with the help of ten deep learning models like InceptionV3, Xception, InceptionResNetV2, MobileNet, MobileNetV2, MobileNetV3Large, MobileNetV3Small, DenseNet121, DenseNet169, DenseNet201. This study has trained with leaves and insects separately to identify whether an image from a tomato plant is insectoid or not. 458 images of pests and 912 images of leaves are utilized in the proposed architecture. The accuracy of classifying insects or leaves using DenseNet201 is 100 ​%. The highest accuracy of 94 ​% is obtained to classify the different insects using the DenseNet201 model.

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity (VS) structure, which is the main ingredient for estimating the variability of site response. As such, VS can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus VS can substantially modify ground shaking during earthquakes. We apply a novel VS randomization approach to propagate the small-scale heterogeneities of VS to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of VS profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of VS small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

The effectiveness of combination of arbuscular mycorrhizal fungi and compost ameliorant on sengon growth in former coal mine soil

Abstract Mining activities give a negative impact to the soil which become the ex-coal mine soil. The soil has a solid soil structure and low nutrient content so is not suitable for planting. The problems need to be improved by being treated with biological agents from soil microorganisms such as Arbuscular Mycorrhizal Fungi (AMF). The provision of AMF on ex-coal mine soil with the addition of ameliorant compost can be one strategy that can be used. AMF can help increase plant growth and help the process of absorption of phosphate (P) by plants. Compost from goat manure can help the association between AMF and plant roots, also being a source of nutrients that are free from chemicals. The plants which suitable for this association are sengon. Sengon commonly used to help revegetation of ex-mining soil because it is able to withstand various conditions of overgrown soil. This study aims to determine the effect of the addition of a combination of AMF and compost on the growth of sengon plants in the soil of ex-coal mines. Observations were made weekly until the age of three months, the best results were the results at the end of the observation. The results showed that the AMF dose and the addition of compost had an effect on percent AMF colonization, increasing plant height, dry weight of plant roots increasing plant stem diameter, and number of leaves.

ВСХОЖЕСТЬ, ЭНЕРГИЯ ПРОРАСТАНИЯ И ПРОДУКТИВНОСТЬ РЫЖИКА ОЗИМОГО

The current structure of arable land in the Volgograd region leads to a number of problems in our agricultural complex, which must be solved through expanding the set of crops. In the current situation, winter ginger may turn out to be a real alternative to sunflower, partially replacing it in the group of oilseeds. In this regard, it is extremely important to improve the elements of the technology of growing winter ginger in relation to the conditions of light chestnut soils of the Volgograd region. The aim of the research was to study the effect of sowing dates and growth regulators on the productivity of winter ginger in the subzone of light chestnut soils of the Volgograd region. Field experiments were conducted in 2014-2017 in the conditions of the UNPC of the Volgograd State Agrarian University "Gornaya Polyana", Volgograd. Laboratory germination of winter ginger seeds of the Penzyak variety before sowing on average for 2014-2016 in the variant without treatment with growth stimulants was within 95.3%. On the Humat + KalMag variant, it was 1.8% more. In the variant with Humate, the laboratory germination was 2.7% higher compared to the control. In the variant treated with Zircon, laboratory germination was 3.0% higher compared to the control. And the highest laboratory germination was observed on the variant with the Epin-extra preparation and amounted to 99.4%, thereby exceeding the laboratory germination of the variant without growth stimulants by 5.1%. The field germination of winter ginger by sowing dates was not the same and on average over 3 years of research ranged from 62.0% at the first sowing period to 68.2% at the third term. The influence of growth regulators on field germination turned out to be more significant. Zircon increased field germination from 5 to 8.2%, and Epin-extra from 7.3 to 8.2%. Over the years of research, the winter hardiness of winter ginger varied from 66.1 to 77.4%. The maximum yield of winter ginger on average for 2015-2017 was formed on option 3 of the sowing period (September 17-20) and was equal to 2.26 t/ha. The minimum yield for an average of three years of research was formed on the control variant without seed treatment with growth regulators at the first sowing period and amounted to 1.57 t/ha.

A simple analytical method to estimate runoff generation and accumulation

The study of runoff formation in semiarid regions relies generally on the solution of Richards equations using numerical approaches such as those provided by Hydrus-1D. We demonstrate here that a Simple Analytical Method (SAM) could be easily applied to estimate areas under flooding risk, under different soil and rainfall conditions, without the need to run burdensome numerical models. The impact of antecedent soil moisture condition was expressed quantitatively, conferring to SAM a predictive capability based on a-priori information on soil properties, rainfall characteristics, and initial conditions. The SAM was applied to the Shikma catchment, in the center of Israel, to illustrate its capability to estimate the spatial distribution of time of runoff occurrence and runoff coefficient for a prescribed rainfall event. The results suggest that SAM can be used as part of early warning systems of flood risks. Radars, carried by satellites and drones, can be used to provide refined data on rainfall intensity and soil surface initial conditions. SAM could be then coupled with these remotely sensed data to improve runoff initiation and accumulation estimates, thus reducing the time interval required to reach operational decisions regarding potential floods and inundations, and related water erosion hazards.