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The core objective of this research paper is to classify soil a particular region and also perform the scientific study for the prediction of suitable crops, which will yield more profit to the agronomist. The production of agriculture is mainly depends on soil type, cultivation seasons (climate), irrigation method (such as surface, sprinkler, drip/trickle, subsurface etc) and fertilizers (to increase the crop productivity). Soil is classified based on its physical properties (color, texture, structure, porosity, density etc) and chemical properties (phosphorous, nitrogen, carbon, calcium, magnesium, sodium, pH, potassium, sulfur etc). In this research paper soil types are classified by applying Bayesian models to decision tree algorithm and performed various analysis to verify that soil types are correctly classified and as wells to predict suitable crop cultivation during Kharif (monsoon), Rabi (winter) and Zaid (summer) seasons along with suitable irrigation methods and proper use of fertilizers to increase the crop productivity. The proposed algorithm offers unique features by adopting other tree inducers which produce optimum results even though the conditions are leads to chaotic behavior. The final results obtained are presented which illustrates optimum results and generates best decision tree for classification of soil type from the soil dataset. The Bayesian approach guarantees that the classifications of soil types are more accurate than the existing Support Vector Machine (SVM), K-Nearest Neighbor (KNN) and Decision Tree (DT) algorithms.

The most important factors affecting maize production are water stress and nitrogen deficiency. A greenhouse experiment was conducted to assess the influence of different N fertilizers and soil moisture levels on the growth and yields of the WEMA variety on two different soils. The experiment was designed in a factorial of 5 × 2 × 2 fitted into a three replicate completely randomized design. Treatments included five N fertilizer rates (0, 60, 120, 180, and 240 kg N/ha), two soil moisture levels [45 and 100% field capacity], and two soil types. The morphological traits, physiological traits, drought indices and agronomic efficiency were determined. The data were analyzed using GenStat, version 11, analysis of variance (ANOVA), and differences in treatment means were assessed with a probability of 5% using the Duncan Multiple Range Test (DMRT). The associations between the measured parameters were examined using regression and correlation analysis. Data were analyzed using analysis of variance (ANOVA) of GenStat, edition 11, and differences in treatment means were tested using the Duncan Multiple Range Test (DMRT) with a probability of 5%. The regression and correlation analyses were used to examine the relationships between the measured parameters.

This study provided insights into the morpho-anatomy of Xanthostemon verdugonianus Náves ex Fern.-Vill., a threatened species endemic to the Philippines. Sampling was conducted in its natural habitat with the presence of dominant vegetation and rehabilitated sites of the species. Quadrats were established to study the population size and document associated species & soil particle characteristics. The leaves are alternate in arrangement, reddish when young, and are hypostomatic with paracytic stomata. The distinctly thick cuticle and the compact spongy layer could be an adaptation to tropical island conditions. The stem and roots contain tissues manifesting secondary growth with secondary xylem and outer bark formation. The inflorescence is a corymb, and the flowers are bright red, with a prominent cup-shaped hypanthium, persistent lobe-shaped calyx, and a superior ovary. Fruit is a globular capsule round-ovoid in shape with a woody texture. Placental seeds are visible upon splitting matured fruits which are flattened and deltoid to semicircular shape. Twenty-nine species of plants belonging to 19 families were found to be associated with X. verdugonianus, with a mean abundance of eight species per plot. The ultramafic substrate was dominantly composed of medium sand particles, and the reddish color indicated the oxidation of metallic elements in the soil. Analyzing the morpho-anatomical features can help explain endemicity, survival, and adaptation to climate change. [ABSTRACT FROM AUTHOR]

Abstract—The response of sandy and clay subsurface soils, representing classes of non-cohesive and cohesive soils, during seismic motion of various intensities is analyzed based on the in situ observations—records by seismic vertical arrays of the Japanese strong motion network KiK-net. From a total of ~800 stations, five stations with sandy and five stations with clayey subsurface soils represented in the upper layers in their purest forms were selected for the analysis. For sandy and clayey stations, models of soil behavior during strong motion were constructed by the method of (Pavlenko and Irikura, 2003), showing vertical distributions of stresses and strains induced by strong motion in soil layers; and the behaviors were compared. Similar estimates of the amplification of seismic waves in sands and clays during weak motions and similar stress-strain relations describing the behavior of subsurface soils during moderate seismic motions are obtained. The liquefaction of sandy soils during strong motions (the 2011 Tohoku earthquake, Mw ~ 9.0) and the effects of extended seismic source (the directivity of seismic radiation) on the behavior of sandy and clayey soils and amplification of seismic waves are analyzed. Differences in the behavior of sandy and clayey soils are observed only during strong motions, namely, liquefaction occurs in sandy soils (when the groundwater level is about several meters from the surface), but never in clayey soils. [ABSTRACT FROM AUTHOR]

In this study, we focus on the classification of soil types in a specific region, employing a stacking ensemble learning approach with the decision tree algorithm. The importance of this research stems from the fact that a significant portion of the population in rural areas relies heavily on agriculture for their livelihood, making agriculture the backbone of our nation's economy. In India, a country with diverse soil types, understanding soil characteristics is critical for agricultural development as it profoundly influences crop productivity. Data mining techniques play a pivotal role in predicting soil types assisting farmers in selecting the most suitable crops for cultivation. To address this agricultural challenge, we propose a novel method named "Stacking Ensemble Learning with the Decision Tree Model" for soil type classification. Our approach outperforms existing Decision Tree-based methods and exhibits unique advantages in solving complex soil classification problems. Our experimental results demonstrate the effectiveness of our approach in creating an optimal decision tree model for soil type classification. Specifically, our study reveals that the Ensemble Learning technique, leveraging stacking with the Decision Tree model, offers more accurate soil type classification compared to several machine-learning algorithms employed in this research, such as K-Nearest Neighbours (KNN), Support Vector Machine (SVM), traditional Decision Tree, and a Bayesian approach to the Decision Tree model. [ABSTRACT FROM AUTHOR]

Natural environmental radioactivity aroused mainly from primordial radionuclides such as 40K and 238U and 232Th decay series, and have been present in varying concentrations within the earth and in the tissue of every living being. Natural radioactivity can be found everywhere; in the soil, public water supplies, oil, and the atmosphere and it poses a measurable exposure to human beings. The present study developed a statistical model that can be used to predict the Terrestrial Gamma Radiation Dose rates (TGRD) based on soil types and geological formations irrespective of the environment. About 295 TGRD measurements were taken using a micro-Roentgen survey meter (model 19) manufactured by Ludlum, from different locations within the study area. Statistical Package for Social Sciences (SPSS) was utilized in establishing the relationships between TGRD with underlying geological formations and soil types as well as in the development of the model. The developed model was tested by predicting the TGRD value over different combinations of soil types and geological formations, and it was found to fit in well with more than 80% degree of accuracy which is within the acceptable limit. The developed model in this study, may help in establishing the background radioactivity levels in a terrestrial environment that can be used to evaluate any changes that may arise as a result of any release due to both natural and or human activities in a certain area. [ABSTRACT FROM AUTHOR]

The same rainfall can cause different degrees of water stress depending on soil type, so the production response shown by plants can be different. This study is essential for growers, especially in predicting oil palm production based on water deficit for each soil type. The study was conducted on oil palm plantations in Central Kalimantan, Indonesia, with four soil types in 1,446.15 ha (40 blocks). The source of data collected from oil palm plantations included bunch number, average bunch weight, rainfall, and soil physical and chemical properties for the last 15 years (2007 - 2021). This experimental study used a two-stage cluster sampling method. The results showed that the best productivity, bunch number, and average bunch weight were found on Ultisols. The four soil types tested showed the same annual production distribution dynamic, but the response rate from each soil type showed differences. Entisols and Spodosols were more prone to drought stress due to water deficit than Ultisols and Histosols because of the differences in soil texture. Water deficit causes a decrease in oil palm productivity by 5 - 22% in the first year (Ultisols 12 - 22%; Entisols 12 - 22%; Spodosols 7 - 19%; Histosols 5 - 15%) and 1 - 8% in the second year (Ultisols 3 - 7%; Entisols 2 - 4%; Spodosols 5 - 8%; Histosols 1 - 5%) compared to previous years production. A decrease in oil palm productivity occurs at 3 - 5 months (bunch failure phase), 1 year (abortion sensitive phase), and 2 - 2.5 years (sex differentiation phase) after a water deficit appears.

According to the “Regulations on the implementation of state monitoring of lands”, approved by the Decree of the Government of the Russian Federation of November 28, 2002 No. 846, information is collected on the state of lands in the Russian Federation, processed and stored. Continuous monitoring of the use of lands is carried out on the basis of their intended purpose and permitted use, analysis and assessment of the qualitative state of land, taking into account the impact of natural and anthropogenic factors. Land monitoring is carried out by the federal executive authorities, the executive authorities of the constituent entities of the Russian Federation and local governments in accordance within their powers [1]. But, the ongoing monitoring does not provide the proper result for monitoring land plots and crop rotation fields as a production resource and is not carried out according to a number of parameters characterizing soil fertility that are essential for agricultural production. The specificity of accounting for agricultural lands as a natural resource used as the main means of production in agriculture requires different approaches and a wider list of indicators of the state of such lands and their fertility [2; 3]. In this regard, studies have been carried out to monitor agricultural lands and analyze the current state of the use of agricultural lands for effective agricultural production, and on its basis a comprehensive assessment of the ecological state of agricultural landscapes of the Republic of Adygea has been carried out. The authors have analyzed the state of agricultural lands at the present stage and identified possible ways of rational use of available crop lands. Factors limiting the placement of agricultural crops in specific areas of the republic and the reasons that reduce their productivity and product quality have also been established.

Subsoiling has been widely used all over the world as an important operation method of no-tillage farming. For energy-saving and life-extension, the tillage resistance and wear-corrosion of subsoilers have attracted wide attention. In this study, the tillage resistance, soil disturbance, wear and corrosion of subsoiler with S-T-SK-2# biomimetic structures (S means subsoiler; T means tine; SK means shank; 2#, h/s=0.57, h=5 mm and α=45°.) and self-healing coating under two seasons, two locations with different soil properties (black loam and clay soil) and subsoiling speeds (2 km/h and 3.6 km/h) were investigated. The soil moisture content and compactness affected the tillage resistance and wear-corrosion. The tillage resistance and degree of corrosion on all subsoilers were much larger in clay soil than that in black loam soil. Compared with S-T-SK-2#, the tillage reduction rate of C-S-T-SK-2# (S-T-SK-2# with self-healing coating) was up to 14.32% in clay soil under the speed of 2 km/h. The significance tests of regression equation results showed that subsoiler type and soil properties had a significant impact on soil disturbance coefficient, swelling of total soil layer, bulkiness of the plough pan. It is of a guiding significance for the analysis of soil disturbance. Synergism mechanism of subsoiler coupling with biomimetic structures and self-healing coating was analyzed in following. It depicted the guiding effect of biomimetic structure and the shield function of self-healing coating, resulting in anticorrosion and wear resistance of subsoiler. [ABSTRACT FROM AUTHOR]

Rhizosphere microbes have an extremely close relationship with plants and the study on the relationship between rhizosphere microorganisms and their influencing factors is conducive to the protection of vegetation and the maintenance of biodiversity. Here we investigated how plant species, slope positions and soil types affect the rhizosphere microbial community. Slope positions and soil types were collected from northern tropical karst and non-karst seasonal rainforests. The results indicated that soil types played a predominant role in the development of rhizosphere microbial communities (28.3% of separate contribution rate), more than plant species identity (10.9% of separate contribution rate) and slope position (3.5% of separate contribution rate). Notably, environmental factors closely related to soil properties were the major influence factors that controlling the rhizosphere bacterial community structure in the northern tropical seasonal rainforest, especially pH. Additionally, plant species also influenced the rhizosphere bacterial community. In low nitrogen content soil environments, rhizosphere biomarkers of dominant plant species were often nitrogen- fixing strains. It suggested that plants might have a selective adaptation mechanism to rhizosphere microorganisms to obtain the advantages of nutrient supply. Overall, soil types exerted the biggest influence on rhizosphere microbial community structure, followed by plant species and finally slope positions. [ABSTRACT FROM AUTHOR]

Terrestrial gamma radiation dose (TGRD) rates were measured in situ from different locations in Katsina State, Nigeria, using a portable radiation survey metre based on geological formations and soil types. The measured TGRD rates ranged from 45 to 271 nGyh–1 with an average value of 116 ± 1 nGyh–1. Geological formation (silicified sheared rock) and soil type (lithosols and ferruginous crusts and ferruginous tropical soils) appeared to have the highest mean TGRD values of 163 and 134 nGyh–1 with sandstone geological formation and alluvial and hydromorphic soils having the lowest TGRD with values of 80 and 61 nGyh–1, respectively. One way ANOVA results shows that the tested null hypothesis was rejected. Thus, indicating that there exists a strong relationship between the various geological formations, soil types with the measured TGRD values based on the alternate hypothesis. Human health hazard indices like annual effective dose equivalent (AEDE), lifetime outdoor annual equivalent dose, and relative excess lifetime outdoor cancer risk associated with the mean TGRD of the study area were also calculated and found to be 0.711, 9.955 mSv, and 5.79 × 10–4, respectively. These values were higher than the world average values but favourable compared with the safety limits recommended by ICRP. [ABSTRACT FROM AUTHOR]

Quinoa is a resilient high-yielding pseudo cereal, gaining attention because of its high nutritional value, strong growth potent ial, and tremendous source of essential amino acids, micronutrients, vitamins, phenolic compounds, and minerals. The main aim of this investigation was to find the best suitable soil type for maximizing the growth and yield of Quinoa. The pot study was undertaken at the Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore, during the Kharif 2022 season. Eight soil samples (clay loam soils of wetlands of TNAU, sandy loam soils of eastern block of TNAU, sandy loam soils of Mettupalayam, sandy clay loam soils of 36 B eastern block of TNAU, sandy clay loam soils of 37 B eastern block of TNAU, clay loam soils of Ooty, sandy clay loam soils of Govindanaickenpalayam and sandy clay loam soils of Annur) were collected round Coimbatore in Tamil Nadu and tested in a complete randomized design with three replications. The pot study results revealed that growth parameters viz. Plant height (81.5 cm), number of leaves plant-1 (164.8), leaf area (317.7 cm²), number of branches plant-1 (38.0) and dry matter production (22.78 g) were significantly higher in the clay loam soils of Ooty than all other soil types. Similarly, yield attributes such as the number of panicles plant-1 (21.7), panicle length (13.08 cm), number of grains panicle-1 (3050) and grain yield plant-1 (9.60 g) of Quinoa were also higher in the same clay loam soils followed by that in sandy clay loam soils of Govindanaickenpalayam. Red soils of Mettupalayam had shown the lowest growth, yield and yield attributes of Quinoa. Based on the above results, it was concluded that the clay loam soil of Ooty was the best suited for cultivating Quinoa crops. [ABSTRACT FROM AUTHOR]

Eggplant cultivation displays versatility across various soil types. However, nutrient depletion, a result of excessive chemical fertilizer utilization, presents a growing concern. The integration of green manure into agricultural practices, catering to diverse soil types, can remediate this nutrient loss. The purpose of this study was to investigate eggplant growth and yield responses to differing green manure quantities across varying soil types. Employing a factorial experimental method, this research was structured in a completely randomized design (CRD). Two independent variables were evaluated: green manure dosage, with three levels (30 g/plant (D1), 60 g/plant (D2), 90 g/plant (D3)), and soil type, also classified into three categories: Latosol (T1), Grumusol (T2), and Regosol (T3). Data interpretation was conducted using analysis of variance, followed by the Tukey test, each executed at α = 5% significance level. Outcomes indicated a notable interaction between green manure dosage and soil type concerning the leaf area and root fresh weight parameters. The optimal combination emerged as a 30 g/plant green manure dosage applied to Regosol soil type. Notably, individual treatments exerted divergent effects on eggplant growth parameters, though no significant impact on eggplant yield parameters was observed. This research underscores the interplay between green manure usage and soil type in cultivating eggplants, adding value to sustainable agricultural practices.

IntroductionSoil type plays a major role in nutrient dynamics and soil water which impacts crop growth and yield. The influence of soil characteristics on crop growth is usually evaluated through field experimentation (in the short term) and through crop-soil modelling (in the long-term). However, there has been limited research which has looked at the effect of model structural uncertainty of model outputs in different soil types.MethodsTo analyze the impact of soil inputs on model structural uncertainty, we developed eight model structures (a combination of two crop models, two soil water models and two irrigation models) within the Agricultural Production Systems sIMulator (APSIM) across three soil types (Ferralsols, Alisols and Chernozems). By decomposing the mean proportion of variance and simulated values of the model outputs (yield, irrigation, drainage, nitrogen leaching and partial gross margin) we identified the influence of soil type on the magnitude of model structural uncertainty.ResultsFor all soil types, crop model was the most significant source of structural uncertainty, contributing >60% to variability for most modelled variables, except irrigation demand which was dominated by the choice of irrigation model applied. Relative to first order interactions, there were minimal (

Rising global demand for palm oil has created environmental pressures related to deforestation, burning, and peat exploitation, which in turn drives increased greenhouse gas (GHG) emissions. GHG emissions in oil palm (OP) production are known to vary spatially. However, temporal changes across contrasting management and soil types, are less well studied. This paper quantifies spatiotemporal GHG emissions across contrasting regions, management types, and soil types for the period 1990–2019 to assess the potential for reducing emission. The study focusses on Indonesia, as the biggest producer of OP, and in particular on the North Sumatra and Riau provinces, where OP is intensively produced. GHG inventories in 5 year time steps were constructed to investigate the change in drivers of emissions using spatial data, resampled to a 500 m grid. Total GHG emissions were found to have increased in both regions due to expanding OP production. However, results show a reduction in emissions flux from 1.98 to 1.15 Ton C _eq . ha ^−1 yr ^−1 in North Sumatra and 9.63–2.67 Ton C _eq . ha ^−1 yr ^−1 in Riau over the study period. This reduced flux was linked to the decreased deforestation and burning activities, together with increased biomass increment from lower carbon stock area conversion to OP. In both provinces, smallholder plantations emitted fewer emissions than industrial ones, and production on organic soils resulted in consistently higher emissions than on mineral soils. In North Sumatra, emissions under all management and soil types were found to decrease. In Riau, however, GHG emissions on organic soils regardless of management types, remained high. Our findings emphasise that potential for low-emissions OP production is attainable by reducing emissions per unit area through an improved understanding of GHG emissions spatiotemporal variability and their drivers. These contribute to reinforcing ongoing government regulations and guiding the industry towards low-emission OP productions.

Equivalent lateral forces are used in earthquake engineering to build structures that can survive seismic shocks. Considering seismic waves affect how the Earth moves, buildings in India’s seismically active areas must be built to withstand earthquakes. This study examines how multistorey reinforced concrete building frames function seismically while taking into account different soil types, loading scenarios, and seismic Zones IV. For a twelve-storey skyscraper, the analysis includes earthquake reaction storey displacement. This study looks into how soil changes in seismic zone IV affect buildings’ responses, as well as how seismic zones themselves affect them. The building’s natural time periods were evaluated using both response spectrum analysis and time history analysis methods. These results provide insightful information about the complex interaction between soil type and seismic zone, Member stresses and maximum displacement are calculated using static and dynamic analysis. In India’s seismically active region, the necessity for earthquake-resistant structures is highlighted by seismic waves that alter the motion of the earth. Response spectrum analysis combines modal responses via techniques including SRSS, CQC, and ABS, taking into account a variety of response modes. This study compares earthquake loads using various soil types in Zone IV to evaluate building performance during earthquakes. This project’s primary goal is to analyse a multistorey building’s seismic response. Staad Pro Software does load calculations in order to analyse the entire structure. Staad-Pro analysis employs the Limit State create approach, which complies with the Indian Standard Code of Practice.

Hand weeding is a common method of weed control on vegetable farms, especially in developing countries. It requires considerable physical labour and is a significant economic burden, yet comparative studies on hand weeding tools are rare. We evaluated the agronomic, ergonomic and economic performance of four hand weeding tools (and unweeded control) at two sites and two weed ages. Agronomic efficiency was evaluated based on the reduction in weed load from pre-weeding to post-weeding, economic efficiency based on the time taken to weed, and ergonomic efficiency based on heart rate and energy expenditure of the tool operator. Among the tools, the chipping hoe provided higher weed control efficiency than the rotating hoe and combined tool, and showed a lower average heart rate and workload than the combined tool. Ergonomic performance was superior in loam soil compared with clay. The light-weight chipping hoe provided better weed control than heavier tools while also reducing the workload of the weeder. Tools did not differ in economic performance, but the cost was 50% higher with late weeding. Viable hand weeding strategies require the optimization of tools for ergonomic performance and careful attention to timing of operations, thus benefiting economic performance.

This study assessed organic matter, N, P, and K contents in three soil types after the application of biochars and organic fertilizers for two years. The experiment was arranged in a nested design with two factors. Three types of biochar and two types of organic fertilizer were used singly or in combination on three soil types. Among the treatments, the application of tobacco processing waste biochar on Inceptisol and rice husk biochar plus manure on Entisol resulted in the highest soil organic matter and total nitrogen contents. The highest phosphorus content was observed from rice husk biochar treatment on Inceptisol and from rice husk biochar+manure treatment on Entisol and Litosol. The highest K content in Inceptisol and Litosol occurred with each biochar treated rice husk biochar+manure treatment. The highest K content in Inceptisol and Litosol was observed in each tobacco waste biochar+compost treatment and in compost treatment only, respectively.

Soil acidification has become a major global issue, and it is important to study the causes and mechanisms of soil pH changes. This study detected soil pH changes in data collected from 1162 papers published during 1996–2000 and 2016–2020 in China, and it discussed the influencing factors on soil pH changes using Geodetector. The results showed that 58.4% of the collected data pairs were significantly acidified. Alfisols, desert soils, primarosols, semi-aqueous soils and aqueous soils were significantly acidified, while other types of soil did not change significantly. Soil pH on construction land decreased in units of 0.39 and on cultivated land decreased by 0.12, but soil pH changes in forest land and grassland were not significant. Nitrogen deposition, the amount of precipitation, sulphur deposition, temperature and vegetation planted in the soil had a great effect on soil acidification. This study provided a scientific reference for clarifying soil pH changes and made suggestions for subsequent soil remediation. [ABSTRACT FROM AUTHOR]

Ashes produced during on-farm burning of crop residues are mixed in soil before sowing next crop and studies suggest that they can enhance adsorption of pesticides in soil. Enhanced adsorption of pesticides in soil can reduce their availability for degradation and pest/weed control. Therefore, present study evaluated effect of sugarcane trash ash (STA) on degradation of atrazine (used to control annual grasses and many broad-leaved weeds) and fipronil (used for control of early shoot borer and termites) in three sugarcane growing soils and bioavailability of atrazine. Three sugarcane-growing soils (silty clay loam, sandy clay loam and loam) were used to study effect of 0.1 and 0.2% STA on atrazine and fipronil degradation in laboratory incubated soils. Field study for effect of STA on atrazine degradation was performed in silty clay loam soil. Effect of STA on atrazine bioavailability was assayed using its effect on mustard seed germination. Pesticides and their metabolites were quantified using high-performance liquid chromatography (HPLC)/ gas–liquid chromatography (GLC)/ liquid chromatography-mass spectroscopy (LC–MS/MS). Under laboratory condition 0.2% STA doubled atrazine half-life (t1/2) in sandy clay loam, increased t1/2 by 40% in silty clay loam, while no significant effect was observed in loam soil. The STA did not affect fipronil degradation in all three soils. Metabolites, hydroxyatrazine and deethylatrazine (atrazine) and sulfide, sulfone, amide and desulfinyl (fipronil) were detected in soil samples; but their spectrum and quantities varied with the soil type. The t1/2 of atrazine under field condition was 3.61, 2.73 and 2.86 days in control, 0.1% and 0.2% STA-mixed silty clay loam, respectively. The STA reduced atrazine availability suggesting that higher amount of herbicide will be needs for the desired effect in STA-mixed soils. This study has relevance in assessing fate and bioavailability of atrazine and fipronil in sugarcane soils where trash is burnt year after year and mixed in soils. The STA mixing might have cumulative effect due to regular burning of trash. [ABSTRACT FROM AUTHOR]

This paper is a result of many years of field and laboratory research of the soils in Pčinja river basin, North Macedonia, spread out on 237.640,71 ha ranging from 191 to 1664 m above the sea level in order to gain a better understanding of the productive capacities of the soils and measures for their improvement. The catchment area of Pčinja River is a spatial area that extends in two states in the of the Republic of North Macedonia and the part of the Republic of Serbia, whose boundaries are naturally clearly defined. Soil samples were taken by spade and one composite sample was prepared for each sampling site, each containing about 3 kg of soil. Before sieving the samples were air dried. In laboratory, the following analyses have been carried out on the soil samples: hygroscopic moisture, mechanical composition, pH of the soil solution, humus content and total nitrogen, content of carbonates. The mechanical composition and chemical properties of the soils have been determined by standard methods. This area is very heterogeneous, with numerous relief forms, with different expositions and inclinations, and with great differences of altitude. Additionally, there are several geological formations of a very heterogeneous petrographic-mineralogical composition and climate-vegetation zones. Long-term effects of human involvement should also be noted. The vast diversity of the factors required for soil formation in this area is the reason for the formation of many different soil types as well as the lower taxonomic units. These types of soils are characterized by different properties (chemical, physical, and physical-mechanical, productive). Therefore, they have varied effects on agricultural production. There are 9 different soil types and 18 complexes of more than two land types distributed in the Pčinja River basin together with a considerable amount of subtypes, varieties and forms. The most represented with the largest area are: Vertisol, Fluvisol, Fluvisol (Colluvial Soils) and Cambisol. [ABSTRACT FROM AUTHOR]

This study employs spatial interpolation techniques based on extensive geotechnical sub-soil data to develop geotechnical zonation maps for the district of Sargodha, Pakistan. The sub-soil data was extracted from 170 geotechnical investigation reports that contained soil type, standard penetration (N-value), and groundwater depth (exploring a depth of up to 15 m). Two spatial interpolation techniques were employed: (1) inverse distance weighting (IDW) and (2) kriging. IDW technique was used in ArcGIS-10.5 to develop zonation maps of N-values and soil type at various depths, while the kriging method was adopted to generate contours for the groundwater table (GWT) in Surfer 18. The outcomes revealed that subjected region was split into three major zones established on N-values (i.e., zone 1 (1–5), zone 2 (6–10), and zone 3(> 10)) and four subzones generated on soil types. The silty clay is prevalent up to 3 m, followed by sandy soil up to 15 m deep. Empirical correlations of N-values with depth have been proposed with R 2 = 0.99 and RMSD = 0.51, enabling rapid assessment of stiffness and strength characteristics of subsoils during preliminary planning and feasibility studies of different projects. The GWT contour plots showed that the depth of GWT in zone 1 varies between 2.5 and 3.25 m, 0.75 and 4.5 m in zone 2, and 1.75 and 4.0 m in zone 3. Furthermore, the correlation coefficient to forecast N-values is about 95%, 97% for soil type, and 86% for GWT. It is anticipated that these maps will be a helpful resource for engineers and planners in their attempts to achieve improved land-use planning and to determine necessary remedial action. [ABSTRACT FROM AUTHOR]

Numerical studies for considering soil-structure interaction (SSI) are widely used to provide a better understanding of the seismic behavior of structures. The outcomes of these numerical studies are strongly depending on the input parameters. Back to the literature, for modelling different types of soil, there are convenient procedures whereby a single value of the Poisson's ratio is estimated for each type of soil; however, a range limitation between 0.10 and 0.40 is possible, and then other required parameters are determined utilizing the tables of the international seismic codes and the equations of the literature. In this article, a comprehensive parametric study was carried out with the aim of evaluating influences of the Poisson’s ratio on the seismic behavior of structures, and sixteen values of Poisson’s ratios were interpolated between 0.11 and 0.41 in order to examine all possible trails. For achieving this goal, a 4-story steel structure was analyzed on four different soil types (soft, stiff, very dense, and rock soils) under the El Centro acceleration record. The results in terms of time history top displacement and base shears have been discussed. [ABSTRACT FROM AUTHOR]

SOC storage (SOCS) plays a vital role in global climate change. Understanding the spatial pattern and features of soil organic carbon (SOC) and its influencing factors is important for increasing SOC fixation. However, few studies exist on the organic carbon reserves of farmland on a regional scale. This study revealed the SOCD and SOCS values and distribution using Hubei Province as a sampling region. The results demonstrated that the spatial distributions of farmland system carbon storage and density were uneven, and the spatial heterogeneity was related to geography, cultivated area, and soil type. The SOCD ranged from 0.559 to 10.613 kg/m2, with an average of 3.3710 ± 0.0337 kg/m2, and the soil carbon reserve of the farmland system was ~17.81 Tg. The SOCD varied with topography and soil type: in mountainous cultivated land, it was generally higher than that in hilly land and in the plains. However, the plain cultivated areas contained the highest carbon reserves. Within the farmland system, paddy soil, the dominant soil type, exhibited higher SOCD and larger SOC storage capacity. Soil types with the same physicochemical properties exhibited different organic carbon storage capacity in different geomorphic and regional environments. Specifically, paddy soil was found to have higher SOCD and SOCS than the other soil types, and its soil carbon storage capacity was high; the SOC reserves of wheat-rice tillage were the largest among the main tillage methods. Boosting the soil carbon sink requires fundamental improvement in soil properties by improving soil texture, using conservation tillage to increase soil organic matter, and reducing unnecessary human interference. [ABSTRACT FROM AUTHOR]

Differences in soil properties and among plant species may play an important role in the effectiveness of residual and freshly applied phosphorus fertilizers. However, a limited number of experimental results are available on this subject. Pot experiments were carried out with soils from 9 sites of the National Long-term Fertilization Trials, varying in their main characteristics, such as pH, soil texture, organic matter content and P status. Soil samples were taken after 20 years from the unfertilized control and from plots annually fertilized with 200 kg P2O5.ha-1. Effects of long-term fertilization as well as that of freshly applied phosphorus were studied in the experiments. Perennial ryegrass (Lolium perenne L.) was used as test plant. The objective of the present study was to develop quantitative relationships between selected soil parameters and the phosphorus retention characteristics of the experimental soils. Amounts of P removed by plants during 5 cuts were correlated with DM production of plants as well as with the phosphorus amounts extracted at pH 3.7 by ammonium lactate-acetic acid, AL-P mg.kg-1 soil. Phosphorus nutrient balance was calculated from the results to evaluate either P supply or retention characteristics of experimental soils. Results of the experiments were computed by stepwise regression analyses using the STATGRAPHICS program package. Soil parameters involved in the study were: humus content, pH values (ranging from 3.9 to 7.4), clay mineralogy, total P contents of soils, P rates applied for 20 years, freshly applied P in the pot experiment. Based on the results of regression analyses, the importance of soil parameters was evaluated. It was established that several soil parameters significantly influenced the phosphorus retention of soils. Regression coefficients (R²) ranged between 0.619 and 0.285 (n = 86). Long-term effects of P application, higher pH values and humus content had a favourable influence on the P retention of experimental soils. On the other hand, increasing phosphorus retention could be attributed to higher CEC, vermiculite content as well as to increasing rates of freshly applied phosphorus. It was found that long-term effects of P applications on the P supplying power of soils were related also to the increasing N and K rates, providing a balanced nutrient supply in soils. Our results may help the broader understanding of phosphorus retention and fixation characteristics under various soil conditions. [ABSTRACT FROM AUTHOR]

The main goal of the research is to develop a system of agro-ecological land zoning to improve the adaptive landscape system of land management and land use, based on the analysis of long-term data in agricultural production for farms of various forms of ownership in the city of Maikop and the Maikop region, and the project of basic elements of the ALSLM of the Republic of Adygea. To achieve this goal, materials have been collected on the structure of sown areas of farms, gross harvests of crop products, the livestock industry, the use of chemicals, land management and nature management. The article analyzes the geomorphological features, agro-climatic, hydrological resources and parameters, soil-forming and underlying rocks, soil cover and vegetation of the landscapes of the foothill zone of the Republic of Adygea. A comparative assessment of the quality of lands in farms has been carried out, soil bonitet scores calculated for fertility and favorable factors in the system of environmental monitoring. Technological properties of agricultural lands have been assessed. Five nature management territorial complexes (NMTCs) have been identified and maps of the main landscapes have been compiled. The degree of their correspondence to agricultural activities has been revealed on the basis of the analysis of the agro-ecological potential of landscapes. The factors limiting their placement in specific areas of the foothill zone of the Republic and the reasons that reduce their productivity and product quality have been established. In general, according to the principle of economic feasibility, the considered territories of the city of Maikop and the Maikop district of the Republic of Adygea, which are included in the zone of intensive agriculture, are quite suitable for growing both grain crops and for the development of vegetable growing, horticulture (traditional and intensive), viticulture.

[Display omitted] • A modeling approach was developed to study nitrogen attenuation with travel distances. • Both vertical and horizontal distances along nitrogen transport paths were studied. • Three nitrogen attenuation rates (vertical, horizontal, and total) were studied. • Empirical equations were obtained to quantify the three nitrogen attenuation rates. • The equations are highly practical since they only require saturated hydraulic conductivity. Onsite Sewage Treatment and Disposal Systems (OSTDS) used for domestic wastewater treatment are a source of nitrogen (ammonium and nitrate) contamination to groundwater and surface water. One way to manage the contamination is to establish setback distances for nitrogen attenuation through nitrification and denitrification reactions within the setback distances. Determining the setback distances requires investigating nitrogen attenuation as a function of distance from OSTDS. While field investigations have been conducted, there have been few modeling investigations. Using an ArcGIS-based Nitrogen Load Estimation Toolkit, this study simulates nitrogen attenuation for over 20,000 OSTDS at five study areas across Florida, where a third of households are served by OSTDS. Different from conventional studies that only consider the horizontal distances (between an OSTDS and a surface water body that receives OSTDS effluents), this study also considers the vertical distances (between an OSTDS drainfield and water table beneath the drainfield) to account for the nitrogen reactive transport processes in the vadose zones and groundwater aquifers, making the assessment of nitrogen attenuation more comprehensive. Modeling results yield the following three empirical but quantitative relations: (1) vertical attenuation rate as a function of vertical distance and saturated hydraulic conductivity (K s) available in the Soil Survey Geographic Database, (2) horizontal attenuation rate as a function of horizontal distance and K s , (3) total attenuation rate as a multiplication of the vertical and horizontal attenuation rates. These relations can be used to determine nitrogen attenuation within vertical and horizontal distances to OSTDS for practical management of OSTDS nitrogen contamination. [ABSTRACT FROM AUTHOR]

Reducing antibiotic levels in soil ecosystems is vital to curb the dissemination of antimicrobial resistance genes (ARGs) and mitigate global health threats. However, gaps persist in understanding how antibiotic resistome can be suppressed during antibiotic degradation. Herein, we investigate the efficacy of a biochar biofilm incorporating antibiotics-degrading bacterial strain (Arthrobacter sp. D2) to mitigate antibiotic resistome in non-manured and manure-amended soils with sulfadiazine (SDZ) and trimethoprim (TMP) contamination. Results show that biofilm enhanced SDZ degradation by 83.0% within three days and increased TMP attenuation by 55.4% over 60 days in non-manured soils. In the non-manured black soil, the relative abundance of ARGs increased initially after biofilm inoculation. However, by day 30, it decreased by 20.5% compared to the controls. Moreover, after 7 days, biofilm reduced TMP by 38.5% in manured soils and decreased the total ARG abundance by 19.0%. Thus, while SDZ degradation did not increase sulfonamide resistance genes, TMP dissipation led to a proliferation of insertion sequences and related TMP resistance genes. This study underscores the importance of antibiotic degradation in reducing related ARGs while cautioning against the potential proliferation and various ARGs transfer by resistant microorganisms. [Display omitted] • Biochar biofilm (BB) reduced the antibacterial stress exerted on soil microbiota. • BB enhanced the dissipation of sulfadiazine and trimethoprim in non-manured soils. • BB promoted the proliferation of non-resistant bacteria in manured soils. • Sulfadiazine degradation did not result in an increase in related resistance genes. • Trimethoprim decrease correlated with the increase of related ARGs and insertion sequences. [ABSTRACT FROM AUTHOR]

Comammox Nitrospira (CMX) is a no vel discovered "one-step" nitrifying microorganism, and the understanding of its niche specialization and response to agricultural practices in intensive ecosystems is still in its infancy. In this study, we investigated the effect of CMX community activated by nitrogen (N) inputs and soil types on two long-term maize N fertilizer experiments in the main maize-producing areas of North China (calcareous fluvo-aquic soil) and Southwest China (acidic purple soil). CMX includes clade A and clade B, with clade B detected only in the purple soil. The results indicated that the abundance and alpha diversity of CMX in the purple soil were higher than those in fluvo-aquic soil. Greater network complexity and enhanced cooperation have led to a broader ecological niche for CMX in acidic purple soils, but not in fluvo-aquic soil. The clade A community were affected mainly by soil organic carbon (C), N contents in fluvo-aquic soil, while pH and the ratio of C:N were the primary factors for CMX in purple soil. Moreover, the alpha diversity and niche breadth of clade A in fluvo-aquic soil and clade B in the purple soil increased under optimal N application (148 kg N ha−1 for fluvo-aquic soil,180 kg N ha−1 for purple soil). Overall, these findings provide new insights into the adaptation mechanisms of CMX communities under distinct agricultural soil conditions and offers microbial perspective of optimizing N fertilizer management strategies. It refines our understanding of the microbial-soil nutrient cycling processes, promoting the development of future microbe-driven soil management strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Land-use systems (LUSs) and soil types (STs) are strongly related to factors that influence soil degradation and carbon (C) loss. However, the way in which land use and soil type affects the soil organic C (SOC) pools, and soil aggregation in the Sanjiang Plain, has not been thoroughly investigated. Therefore, this study aimed to investigate soil physic–ochemical properties, soil aggregates, and C management index (CMI) in three different LUSs (grassland, dryland, and paddy field) under two STs (meadow soil and albic soil) of the Sanjiang Plain in northeast China. A total of 60 composite soil samples were collected for laboratory analyses. The results were as follows: soil properties were affected by LUS and ST, especially soil chemical properties; ST had no significant effect on soil aggregates but significantly affected its SOC content, while LUS had a significant effect on soil aggregates (p < 0.01), except for small macro-aggregates (2–0.25 mm); the mean weight diameter (MWD) and SOC in meadow soil was significantly different under different land uses, with grassland being the highest and dryland the lowest. However, there was no significant difference in albic soil. The heterogeneity of grassland, dryland, and paddy field showed that different LUSs had particular effects on SOC and its active components because LUS had significant effects on C pool index (CPI) and CMI, but ST and its interaction had no significant effects on CPI and CMI. Overall, the results showed that LUS was an important factor affecting CMI in the Sanjiang Plain, rather than ST, and the paddy field CMI was optimal in the Sanjiang Plain.

Soil, a significant natural resource, plays a crucial role in supporting various ecosystems and serves as the foundation of Pakistan’s economy due to its primary use in agriculture. Hence, timely monitoring of soil type and salinity is essential. However, traditional methods for identifying soil types and detecting salinity are time-consuming, requiring expert intervention and extensive laboratory experiments. The objective of this study is to propose a model that leverages MODIS Terra data to identify soil types and detect soil salinity. To achieve this, 195 soil samples were collected from Lahore, Kot Addu, and Kohat, dating from October 2022 to November 2022. Simultaneously, spectral data of the same regions were obtained to spatially map soil types and salinity of bare land. The spectral reflectance of band values, salinity indices, and vegetation indices were utilized to classify the soil types and predict soil salinity. To perform the classification and regression tasks, the study employed three popular techniques in the research community: Random Forest (RF), Ada Boost (AB), and Gradient Boosting (GB), along with Decision Tree (DT), K-Nearest Neighbor (KNN), and Extra Tree (ET). A 70–30 test train validation split was used for the implementation of these techniques. The efficacy of the multi-class classification models for soil types was evaluated using accuracy, precision, recall, and f1-score. On the other hand, the regression models’ performances were evaluated and compared using R-squared (R2), Mean Squared Error (MSE), Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE). The results demonstrated that Random Forest outperformed other methods for both predicting soil types (accuracy = 65.38, precision = 0.60, recall = 0.57, and f1-score = 0.57) and predicting salinity (R2 = 0.90, MAE = 0.56, MSE = 0.98, RMSE = 0.97). Finally, the study designed a web portal to enable real-time prediction of soil types and salinity using these models. This web portal can be utilized by farmers and decision-makers to make informed decisions regarding soil, crop cultivation, and agricultural planning.

In this study, we have proposed a new classification method for determining different soil classes based on three machine learning approaches, namely: support vector classification (SVC), multilayer perceptron (MLP), and random forest (RF) models. For the development of models, we have used a database of 4888 soil samples obtained from Vietnam projects. In the model’s study, 15 soil properties factors (variables) have been selected as input parameters for classifying soil samples into 5 soil classes: lean clay (CL), elastic silt (MH), fat clay (CH), clayey sand (SC), and silt (ML). To evaluate and analyze the results quantitatively and qualitatively, various methods such as learning curve (time and number of training samples), confusion matrix, and several statistical metrics such as precision, recall, accuracy, and F1-score were used. Results indicated that performance of all the three models (average accuracy score = 0.968) is good but of the SVC model (accuracy score = 0.984) is best in accurate classification of soils. [ABSTRACT FROM AUTHOR]

Weed control is needed to avoid competition in early rice growth. A weed control method is waterlogging. The study aimed to investigate the effect of waterlogging on weed seed germination and growth in lowland rice. This research was arranged in a completely randomized design (CRD) factorial and three replications. The first factor was waterlogging, which consisted of three levels: without waterlogging, 1-15 days after planting (DAP), and 1-30 DAP. The second factor was focused on two different soil types: latosol soil (LS) and regosol soil (RS). The results showed that waterlogging could inhibit seed germination of weed in RS but not in LS. In this study, waterlogging of 1-30 DAP inhibited weed dry weight higher than 1-15 DAP in both soil types. Waterlogging of 1-30 DAP decreased the weed dry weight by 87.2% in LS and 97.3% in RS than without waterlogging. Waterlogging could change the summed dominance ratio (SDR) of weed species. The research findings show that the waterlogging period of 1-30 DAP effectively inhibits the weed seed germination and growth in RS, but in LS could extend. We recommend that waterlogging period of 1-30 DAP can be applied for weed control in lowland rice. [ABSTRACT FROM AUTHOR]

In geotechnical engineering classification of soils is an important accept because to provide guidance about soils based on their experimental analysis. The classification of system can be done in various ways because one should not rely on empirical information for solving the problems. These soil types are classified based on their behavioural conditions and based on generalized information provided by the scientists, engineers and resource persons. Classification of soil type by visiting particular location is difficult so remote sensing images are used. The most widely used remote sensing method for classification of soils is hyperspectral image (HSI) technology. To classify HSI different soft computing techniques are applied and compared algorithms with their accuracies to know the best algorithm for classification of soil types. [ABSTRACT FROM AUTHOR]

Since hunger and malnutrition are affecting billions of people, the effect of cropping seasons, soil types and climatic conditions (temperature and precipitation) on yield, iron (Fe), zinc (Zn) and amino acids content in grains of hybrid maize (Zea mays), at smallholder farms in Eastern Uganda, was examined. Thirty-six (36) on-farm experiments under maize–bean intercropping with NPK fertilizer were established across three soil types (Petric Plinthosols, Lixic Ferralsols and Vertisols) and growing conditions (seasons, temperature and rainfall). We found significant differences in the grain yield between seasons, but not between soil types. Fe (mean of 22.48 mg/kg) in maize–grains significantly correlated with Zn (mean of 23.21 mg/kg), soil pH, soil organic matter and total nitrogen. Grain amino acid concentrations differed significantly between the seasons and across soil types. Precipitation and temperature did not significantly influence grain-yield nor grain Fe and Zn contents. For two seasons, the hybrid maize variety did not perform better than other varieties in the regions. Thus, a critical finding is that improved varieties of maize is not enough to facilitate increased Fe and Zn uptake nor amino acids content in their grains to desired levels. Hence, a diet dominated by maize will not supply sufficient micronutrients (Fe and Zn) to meet the human dietary requirements in this region. [ABSTRACT FROM AUTHOR]

This study investigated phosphorous (P) sorption characteristics under lime rates, and validated them under field conditions. Soil samples from nitisols and luvisols were taken, mixed with lime(tha−1) at[0,0], [5.25, 3.75], [10.5, 7.5] and [15.75, 11.25], respectively, and incubated for 30 days. It was equilibrated with KH2PO4 at 0, 10, 20, 30, 40, and 50 mgPL−1. The data were tested with Freundlich and Langmuir models. External P requirement (EPR) and changes in chemical properties were evaluated. The field validation on wheat involved rates of P (0, 8.2, 16.4, 24.6, 32.9, and 41.1 kg ha−1) and lime (0, 650, and 1300 kgha−1) in a randomized complete block design with three replications. Freundlich was found the best-fitted model. Freundlich coefficient (Kf) ranged from 212 to 45 mgPkg−1 (nitisols) whereas it was 112.7 to 16.29 mgPkg−1 (luvisols). EPR (kgPha−1) without and the highest lime rate were: nitisols (142.5 and 52.32 kgPha−1) and luvisols (124.84 and 25.94 kgPha−1). Liming reduced EPR by 63.3% (nitisols) and 79.3% (luvisols). Liming increased soil pH from [4.55 to 6.60 in the nitisols, and 5.33 to 6.51 in luvisols]; exchangeable acidity (cmol(+)kg−1) 3.84 to 0.01 nitisols, and 0.72–0.05 luvisols, and available P (mg/kg) 3.2–6.32 nitisol, and 2.74–8.72 luvisols. Furthermore, applying 32.9 kgPha−1 x 1300 kgha−1 lime resulted in grain yield (4345.2 kgha−1) that was 449% more than the untreated crop (791.3 kgha−1). The validation result suggested higher P than blanket P recommendation. It also justifies that excess P or lime alone cannot be a complete solution for P management and increased yield. [ABSTRACT FROM AUTHOR]

Acid-volatile sulfides (AVS) are strongly associated with the bioavailability of some divalent metals such as cadmium, copper, lead, nickel and zinc. However, the global spatial variability of AVS for aquatic systems is unknown. The specific goals of this study were to: (1) summarize all available AVS monitoring data from all types of freshwater and saltwater waterbodies (streams/creeks, rivers, lakes/ponds/reservoirs and estuarine/marine areas) and (2) compare AVS concentrations from these various types of waterbodies considering both soil type classification and biomes. AVS measurements were reported from 21 different countries. A total of 17 different soil types were reported for all waterbody types and both podzols and luvisols were found in all waterbody types. Nine different biomes were sampled for all waterbody types. The temperate broadleaf and mixed forest biome was sampled for AVS in all waterbody types. Mean AVS concentrations ranged from 0.01 to 503 µmoles/g for 140 different waterbody types and the 90th centile for all these waterbodies was 49.4 µmoles/g. A ranking of waterbody type means from low to high AVS measurements showed the lowest mean value was reported for streams/creeks (5.12 µmoles/g; range from 0.1 to 39.8 µmoles/g) followed by lakes/ponds/reservoirs (11.3 µmoles/g; range from 0.79 to 127 µmoles/g); estuarine/marine areas (27.2 µmoles/g; range from 0.06 to 503 µmoles/g) and rivers (27.7 µmoles/g; range from 1.13 to 197 µmoles/g). The data provided in this study are compelling as it showed that the high variability of AVS measurements within each waterbody type as well as the variability of AVS within specific locations were often multiple orders of magnitude differences for concentration ranges. Therefore, a comprehensive spatial and temporal scale sampling of AVS in concert with divalent metals analysis is critical to avoid possible errors when evaluating the potential ecological risk of divalent metals in sediment. [ABSTRACT FROM AUTHOR]

With 22 taxa reported from the country so far, Epipactis is the most species-rich orchid genus in Hungary. Many of them are rare, threatened species. To protect endangered species effectively, it is crucial to explore their ecology. Our work aimed to select and examine factors that are influencing the distribution of Epipactis species. Our data collection (2014–2018) was carried out in the Keszthely Hills, in the northeastern part of the Zala Hills and the Southern Bakony Mountains. We assigned ecologically relevant data from databases of local forestries, terrain models and geological maps to each occurrence. We examined the factors that result in the best differentiation between the studied species. At 1,261 localities, a total of 5,223 individuals of 15 taxa were found. We found three factors (tree species composition of the forest, genetic soil type, bedrock type) that significantly influenced the distribution of Epipactis species. Our results can help understand the distribution patterns of these species and allow for more effective, targeted protection of their potential habitats on a regional level. [ABSTRACT FROM AUTHOR]

The incorporation of organic materials derived from plant biomass into various soils is an effective strategy for increasing soil organic carbon (SOC). The comparative effect of organic material forms and soil types on carbon (C) sequestration has received little attention. On a C equivalent basis, wheat straw, wheat straw‐biochar, tobacco straw, and tobacco straw‐biochar were added to different soil types such as acidic, saline, and calcareous and incubated for 180 days. The structural characteristics of SOC, humic substance (HS) contents, and enzyme activities were investigated, and it was discovered that the C content of crop straws and biochar was primarily fixed in the form of humin (HU) in all soil types. Furthermore, biochar application did not increase humic acid (HA), whereas crop straws treatments did. Between HU and SOC, there was a significant positive correlation. SOC Aryl C was increased by biochar treatments, whereas phenolic C and O‐alkyl C were increased by straw treatments. Aromatic C correlated positively with SOC concentration, whereas polyphenol oxidase activity correlated positively with O‐alkyl C. The activity of polyphenol oxidase influenced the ormation of O‐alkyl C significantly. The majority of SOC functional groups and enzyme activities were found to have significant relationships with HS contents (p value <0.05). These findings suggest that both soil types and organic materials influence HS and functional groups of SOC, with organic materials having a stronger influence on microbial activity than soil types. Biochar can be used for a wide range of soils to not only store more recalcitrant C but also make SOC more hydrophobic. [ABSTRACT FROM AUTHOR]

We sought to identify counties in the northeastern United States where the incidence of infant botulism (IB) is elevated compared to the nationwide incidence and to assess associations with soil type at the case residence. IB cases were identified through the distribution of the orphan drug Human Botulism Immune Globulin Intravenous for treatment of IB by state and national surveillance systems and were subsequently confirmed by laboratory testing. IB incidence by county was calculated as the number of IB cases divided by the number of live births in the county from 2000 to 2019. Cases were spatially mapped and assigned to soil types using the US Department of Agriculture's online soils database. Possible association with soil type was evaluated with the Chi-squared test. We identified a rectangular area consisting of 17 contiguous counties in Delaware, Maryland, New Jersey, New York, and Pennsylvania, approximately 80 km by 250 km, in which the 20-year incidence of IB was nearly seven times greater than that of the remaining counties in those five states. Within this area, case residences were strongly associated with certain soil types ( P ≤ 0.003). From 2000 to 2019, IB occurred with disproportionate incidence in a rectangular area encompassing the lower Delaware and Raritan River Valley and parts of five adjacent states. Further investigation of the soils in counties from this area could assess whether C. botulinum is more prevalent in certain soil types and whether isolation of C. botulinum is more common in counties with higher IB incidence., Importance: Infant botulism occurs more frequently in 17 counties within and adjacent to the Delaware and Raritan River watersheds. This study should alert physicians and pediatricians in the area to the higher likelihood of encountering cases of this otherwise rare disease that manifests with constipation, poor feeding, loss of head control, weak suck/cry, generalized weakness, and descending bilateral paralysis., Competing Interests: The authors declare no conflict of interest.