Soil Type Research Articles

Dynamic Analysis of Soil-Structure Interaction in Earthquake-Prone Areas

This study used a thorough experimental method to examine the dynamic interaction between soil and structures in earthquake-prone locations. The study challenge concentrated on how different soil types and configurations influence the diversity of structural reactions under seismic loading conditions. The research utilized a mixed methods approach, which involved quantitatively analyzing soil parameters and assessing structure dynamics. The methods employed included the creation of scaled replicas depicting common architectural structures situated on various soil types, including sandy, clayey, and mixed compositions. We used high-precision sensors to record ground motion characteristics such as Acceleration, velocity, and Displacement. The data was then evaluated using statistical methods such as ANOVA and regression analysis. The results revealed substantial differences in the structural reaction based on the type of soil and the parameters of the structure. Structures built on sandy soils saw greater peak accelerations (up to 0.170 g) but smaller displacements. On the other hand, structures on clayey soils had moderate accelerations (up to 0.140 g) but had bigger inter-story drifts. The varied soil layers, ranging from 1.500 Hz to 1.780 Hz, influenced the natural frequencies of the buildings. The damping ratios ranged from 5.000% to 7.800%, indicating that structural damping effectively reduces seismic forces. The results emphasized the critical importance of the interaction between soil and structures in seismic design and the necessity for customized engineering solutions based on the individual soil conditions at the site. Suggested measures include improving methods for soil characterization, optimizing structural dynamics using cutting-edge dampening technologies, and upgrading seismic design codes to enhance the ability of structures to withstand earthquakes in places prone to seismic activity.

Impact of climate changes on agroresources of Ukrainian Polissia based on geospatial data

Aim. To determine the patterns of the climate change impact on the transformation of agricultural production and the ecosystem of Ukrainian Polissia in terms of time and space. Methods. Satellite and statistical data for the last 40 years (1982–2022) were used. The mean temperature for the vegetation period was defined by the sum of radiation temperatures of the terrestrial surface, calculated using the data of the infrared range (10.3–11.3; 11.4–12.4 μm) of the high-precision AVHRR radiometer of artificial meteorological Earth's satellites, NOAA, and the precipitation dynamics – using the data of ERA5 ECMWF/Copernicus Climate Change Service. The impact of climate change on the vegetation state and phenological parameters, including the beginning, end, and duration of the vegetation season, was determined by the normalized difference vegetation index (NDVI), obtained using the data of the infrared (0.72–1.1 μm) and red (0.58–0.68 μm) ranges of the AVHRR radiometer on the website of STAR NESDIS NOAA. Crop yields and the dynamics of sown areas were determined by the data from the State Statistics Service of Ukraine. The information about the dynamics of the forest cover was obtained using the Global Forest Watch satellite data. To evaluate the impact of climate change on Ukraine's forests, the investigation was conducted on burnt forest areas, using the MCD64A1 6.1 index, developed on the basis of the MODIS satellite data. Results. According to the satellite data, the radiation temperature of the terrestrial surface during the growing period increased by 2.2 ºС on average in the territory of Ukrainian Polissia over the last 40 years. There is a regional difference in the temperature regime observed in the direction from west to east. In the territory of western Polissia, the increase in the temperature of the terrestrial surface in recent decades was within the range of 1.2–1.6, and in the central and eastern parts – within 2.3–2.9 ºС. Due to the warming, the duration of the growing period was extended by 21–35 days, mostly because of earlier spring onset. There is a descending trend in the average annual precipitation amount down to 20–30 mm, which is especially notable for central and eastern Polissia. The warming was the reason for the introduction of the crops, new for this region, into the structure of sown areas, especially corn and sunflower, which had a generally positive effect on the vegetation state by the NDVI index, which increased from 0.30 in 1982–1992 to 0.36 in 2012–2022 on average. The crop yield increased accordingly, and according to the statistical data for the recent years, amounted to: corn – 7.0–9.5 t/ha, winter wheat – 4.5–5.0, and sunflower – 1.5–2.0 t/ha, which is close to the level of their yield on chornozem. At the same time, due to climate change and the transformation of agricultural activity, there has been a higher risk of deterioration in the ecological state of typical Polissia landscapes, droughts, and soil degradation. According to the results of the analysis of twenty-two years of the dynamics in forest fires, the largest areas of burnt forests were registered in 2012 (694.30 sq.km), 2015 (1,078.81 sq.km), and 2020 (776.27 sq.km), which demonstrated the increase in fires during the recent decade along with the tendency towards longer fire hazard period. Conclusions. The increase in the temperature of the terrestrial surface of the Ukrainian Polissia during the growing period and the lengthening of the growing period created the conditions for corn and sunflower to be introduced into the arable areas, which had a positive impact on the vegetation state index, NDVI. As a result of these transformations both in the sown area of these crops and their yield, Polissia is becoming a new grain-oil belt of Ukraine. Concurrently, there are higher risks associated with maintaining high performance of agroecosystems and the increase in the risks for soil degradation processes, the deterioration of the ecological state of wetlands and forests, as well as drying-out of small rivers and lakes. Balancing the high yield of modern agroecosystems and safe nature management requires systemic measures in adapting the agricultural activity and nature management to new climatic conditions, which requires implementing the management of soil, water, and bio-resources, achieving optimal parameters of fertility for mineral and peaty-swampy soils. Reconstructing current land reclamation systems to optimize water regimes for the agricultural lands and protect typical Polissia ecosystem is needed.

Determination of Organic Carbon Content of the Soils within the Greenhouses Built on Pyroclastic Deposits in Isparta Settlement Area

Soil organic carbon (SOC) is an important indication of soil health and helps to sustain soil fertility. As a result, determining its composition and the factors that influence it is critical for long-term soil nutrient management, especially in controlled conditions such as greenhouses. This study utilizes machine learning to classify SOC content in greenhouses built on pyroclastic deposits in the Isparta region. A dataset of 276 samples and eight variables—clay (%), silt (%), sand (%), soil electrical conductivity (EC), pH, elevation, slope, and aspect—were used to model SOC values. SOC content was classified into five classifications: very low (2.3%). In this study, five machine learning models—Logistic Regression (LR), K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF)—were evaluated using cross-validation to determine their classification accuracy, precision, recall, F-score, and ROC area. Random Forest (RF) and Decision Tree (DT) outperformed the other models, with RF achieving the highest overall accuracy (76.4%), precision (77.3%), and AUC (0.904), followed by DT at 75.4% and AUC of 0.874. This study shows the practicality of machine learning models in categorizing SOC content, highlighting their importance for long-term soil health and fertility control in greenhouse conditions. To improve model efficacy, future studies should include more auxiliary variables, such as soil physical and chemical qualities and lithological data, as well as a wider range of soil types.

Large deformation simulation of uprooting of trees with complex root system architectures using material point method with embedded truss elements

Abstract Background and aims Urban trees in coastal cities like Hong Kong may suffer from an uprooting failure when subjected to extreme winds. A proper numerical model for tree uprooting simulation can help to select tree species or soil types that better resist uprooting failure. However, modeling tree uprooting is challenging as it is a cross-disciplinary problem involving complex root system architectures (RSAs) and large deformation of both roots and soils. This study aims to develop a hybrid numerical model that combines truss elements and material point method (MPM) to simulate the entire large-deformation uprooting process of trees with complex RSAs. Methods The tree uprooting model is developed by coupling truss elements in finite element method (FEM) with MPM. Laboratory pull-out tests using artificial roots and real root cuttings are adopted to validate the developed model. A comparative study is performed to investigate the difference between using complex and simplified RSAs in tree uprooting simulations. Results The developed model provides consistent predictions of peak load, critical displacement and failure mode when compared with results from laboratory tests. Moreover, the comparative study shows that the uprooting resistance obtained with a complex RSA is higher than that with a simplified RSA. The difference varies with the soil and root mechanical properties. Conclusion The developed hybrid model offers a novel way for simulating an entire tree uprooting process involving large deformations and complex RSAs. The study shows that using a simplified RSA to approximate the complex RSA might result in misleading failure modes.

Impact of Paddy Field Expansion on Ecosystem Services and Associated Trade-Offs and Synergies in Sanjiang Plain

In recent decades, the integrity and security of the ecosystem in the Sanjiang Plain have faced severe challenges due to land reclamation. Understanding the impact of paddy field expansion on regional ecosystem services (ESs), as well as revealing the trade-offs and synergies (TOS) between these services to achieve optimal resource allocation, has become an urgent issue to address. This study employs the InVEST model to map the spatial and temporal dynamics of five key ESs, while the Optimal Parameter Geodetector (OPGD) identifies primary drivers of these changes. Correlation analysis and Geographically Weighted Regression (GWR) reveal intricate TOS among ESs at multiple scales. Additionally, the Partial Least Squares-Structural Equation Model (PLS-SEM) elucidates the direct impacts of paddy field expansion on ESs. The main findings include the following: (1) The paddy field area in the Sanjiang Plain increased from 5775 km2 to 18,773.41 km2 from 1990 to 2020, an increase of 12,998.41 km2 in 40 years. And the area of other land use types has generally decreased. (2) Overall, ESs showed a recovery trend, with carbon storage (CS) and habitat quality (HQ) initially decreasing but later improving, and consistent increases were observed in soil conservation, water yield (WY), and food production (FP). Paddy fields, drylands, forests, and wetlands were the main ES providers, with soil type, topography, and NDVI emerging as the main influencing factors. (3) Distinct correlations among ESs, where CS shows synergies with HQ and SC, while trade-offs are noted between CS and both WY and FP. These TOS demonstrate significant spatial heterogeneity and scale effects across subregions. (4) Paddy field expansion enhances regional SC, WY, and FP, but negatively affects CS and HQ. These insights offer a scientific basis for harmonizing agricultural development with ecological conservation, enriching our understanding of ES interrelationships, and guiding sustainable ecosystem management and policymaking.

Realtime estimation of average sand grain diameter and sand bed height and mass for a trailing suction hopper dredger.

A Trailing Suction Hopper Dredger (TSHD) in the sailing process, excavating seabed sediment with the drag head and pumping it through the pipeline to the spoil hopper sedimentation. The spoil hopper sedimentation process, as a critical factor affecting the loading yield and efficiency of a dredger, is susceptible to the influence of different average sand grain diameter . However, the soil type tends to change continuously during the loading process, making it difficult to obtain the by measurement or calculation. In this paper, combined with the existing simplified one-dimensional sedimentation model and simulated loading data, the Bootstrap Particle Filter (BPF), Gaussian Particle Swarm Optimized Particle Filter (GPSO-PF), Assisted Particle Filter (APF), Continuous-Discrete Feedback Particle Filter based on the constant feedback gain approximation (CD-FPF-CG) and the Galerkin method feedback gain approximation (CD-FPF-GL) are applied in the numerical simulations for online estimation of important variables such as the average sand grain diameter , the sand bed height and mass , respectively. The simulations results show that the CD-FPF-CG has a higher numerical accuracy and efficiency than the BPF, GPSO-PF, APF and CD-FPF-GL. Therefore, the CD-FPF-CG is used to estimate the above important variables for the actual vessel and the initial value of the average sand grain diameter for the CD-FPF-CG is determined via Simulated Annealing Multiple Population Genetic Algorithm (SAMPGA).

Antioxidant Compound of Curcuma mangga Val. with Variation in Rhizome Parts and Soil Types

The scientific name of Curcuma mangga Val. (CM), that is commonly known as temu mangga, contains polyphenols, categorized as antioxidant compounds. These antioxidant compounds can neutralize free radicals. The study aims to determine the influence of rhizome parts and soil types on the antioxidant properties of CM. The research stages include sorting, peeling, washing, blanching, drying, and compositional analysis (antioxidant activity, total phenolic, flavonoid, andtannin). The study utilized a Completely Randomized Design (CRD) with rhizome parts (main, 1 tiller) and soil types (clay, lime, and sand) as variables. Both rhizome part and soil type have significant effects on the antioxidant activity and antioxidant compounds of CM. The chosen CM, specifically the main rhizome with clay soil type, exhibits an antioxidant activity of 82.50% RSA, total phenolic of 647.50 mg GAE/100 g db, flavonoids of 620.2 mg QE/100 g db (dry basis), andtannins of 167.07 mg CE/100 g db.

The Origin and Geography of Brown Forest Soils

Brown soils, Brown forest soils, Burozems or Cambisols have been studied for more than 100 years, and to this day, their nature, origin and process organization remain controversial. In addition, issues of their geography are quite controversial, especially in such a large country as Russia. A brief review of the literature on the morphological diversity features of the genesis and origin of brown soils in the various geographical locations of Eurasia is given. It was shown that the genesis of brown soils is not as closely related to the type of forest vegetation as previously thought, although, at the same time, the vast majority of brown soils are forest soils. Depending on the geographic situation and local climatic and geogenic conditions, Brown forest soils have related subtypes among adjacent soil types in different natural zones. Thus, in the polar zone, they are close to Entic Podzols, in the subtropics to Cinamonic soil, and in the forest-steppe, they replace zonal Retisols in positions with a relatively less contrasting and even climate. Being to a certain extent intrazonal soils, brown soils are combined with other more intrazonal soils—Rendzinas—and form the so-called Burozem-Rendzinas on uplands, composed of carbonate rocks in various natural zones. The article is illustrated with original photographs of Brown forest soils from various natural zones, taken by the author during numerous expeditions. It has been established that Burozems combine the characteristics of intrazonal soil, which is inherent in all natural zones, and have elements of zonal soils, as well as adjacent intrazonal soils in invariant combinations of soil-forming factors. From this, two conclusions can follow about their further classification fate: a more thorough justification for an independent soil type or a classification of structural metamorphism and in situ transformation of minerals among various existing zonal soil types.

Precipitation Patterns and Their Role in Modulating Nitrous Oxide Emissions from Arid Desert Soil

Nitrous oxide (N2O) ranks as the third most significant greenhouse gas, capable of depleting the ozone layer and posing threats to terrestrial ecosystems. Climate change alters precipitation variability, notably in terms of frequency and magnitude. However, the implications of precipitation variability on N2O emissions and the underlying mechanisms remain inadequately understood. In this study, employing laboratory incubation methods on three representative sandy soil types (sandy soil, shrub soil, and crust soil), we examined the impacts of diverse precipitation levels (5 mm and 10 mm) and frequencies (7 days and 14 days) on N2O emissions from these soil types. This study aims to clarify the complex connections between soil N2O emission fluxes and soil physicochemical properties in the soil environment. Our findings reveal that the N2O emission flux exhibits heightened responsiveness to 5 mm precipitation events and a 14-day precipitation frequency, and compared to other treatments, the 5 mm precipitation and 14-day precipitation frequency treatment resulted in a 20% increase in cumulative nitrous oxide emissions. Consequently, cumulative N2O emissions were notably elevated under the 5 mm precipitation and 14-day precipitation frequency treatments compared to the other experimental conditions. The N2O emission flux in sandy soil displayed a positive correlation with available phosphorus (AP) and a negative correlation with pH, primarily attributed to the exceedingly low AP content in sandy soil. In shrub soil, the soil N2O emission flux exhibited a significant positive correlation with NH4+-N and a negative correlation with NO3−-N. Conversely, no significant correlations were observed between soil N2O emission flux and soil physicochemical properties in crust soil, underscoring the importance of considering plant–soil microbial interactions. Our findings suggest that soil nitrous oxide emissions in arid and semi-arid regions will be particularly responsive to small and frequent rainfall events as precipitation patterns change in the future, primarily due to their soil physicochemical characteristics.

Response of Typical Shrubs Growth and Soil Nutrients to Graphene Addition in Impoverished Land of the Ulan Buh Desert

Graphene can promote plant growth and improve soil conditions, but its effectiveness in enhancing infertile soils in arid regions remains unclear. This study selected three typical shrubs from the Ulan Buh Desert Nitraria tangutorum, Xanthoceras sorbifolium, and Amygdalus mongolica as research subjects. Five graphene addition levels were set: 0 mg/L (C0), 25 mg/L (C1), 50 mg/L (C2), 100 mg/L (C3), and 200 mg/L (C4).A pot experiment was conducted in June 2023 to investigate the effects of graphene addition on shrub growth and soil nutrients. The results showed that the optimal graphene addition levels for A. mongolica, X. sorbifolium, and N. tangutorum were C2, C2, and C3, respectively. Compared with the control, the total biomass of the different shrubs increased by 185.31%, 50.86%, and 161.10%, respectively. However, when the graphene addition exceeded the optimal level, shrub biomass showed a decreasing trend with increasing graphene concentration. Total shrub biomass was positively correlated with soil available nitrogen and potassium, while redundancy analysis indicated that soil organic matter was the primary factor influencing shrub growth. This suggests that graphene promotes shrub growth by affecting soil organic matter and available nutrients. Therefore, graphene addition can enhance soil fertility in barren lands in arid regions and significantly promote shrub growth. However, due to soil leaching effects, this growth-promoting effect may decrease over time.

Evaluating Wheat Cultivation Potential in Ethiopia Under the Current and Future Climate Change Scenarios

Land suitability analyses are crucial for identifying sustainable areas for agricultural crops and developing appropriate land use strategies. Thus, the present study aims to analyze the current and future land suitability for wheat (Triticum aestivum L.) cultivation in Ethiopia. Twelve variables including soil properties, climate variables, and topographic characteristics were used in the evaluation of land suitability. Statistical methods such as Rotated Empirical Orthogonal Functions (REOF), Coefficient of Variation (CV), correlation, and parametric and non-parametric trend analyses were used to analyze the spatiotemporal variability in current and future climate data and identified significant patterns of variability. For future projections of land suitability and climate, this study employed climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) framework, downscaled using regional climate model version 4.7 (RegCM4.7) under two different Shared Socioeconomic Pathway (SSP) climate scenarios: SSP1 (a lower emission scenario) and SSP5 (a higher emission scenario). Under the current condition, during March, April, and May (MAM), 53.4% of the country was suitable for wheat cultivation while 44.4% was not suitable. In 2050, non-suitable areas for wheat cultivation are expected to increase by 1% and 6.9% during MAM under SSP1 and SSP5 climate scenarios, respectively. Our findings highlight that areas currently suitable for wheat may face challenges in the future due to altered temperature and precipitation patterns, potentially leading to shifts in suitable areas or reduced productivity. This study also found that the suitability of land for wheat cultivation was determined by rainfall amount, temperature, soil type, soil pH, soil organic carbon content, soil nitrogen content, and elevation. This research underscores the critical importance of integrating spatiotemporal climate variability with future projections to comprehensively assess wheat suitability. By elucidating the implications of climate change on wheat cultivation, this study lays the groundwork for developing effective adaptation strategies and actionable recommendations to enhance management practices. The findings support the county’s commitment to refining agricultural land use strategies, increasing wheat production through suitability predictions, and advancing self-sufficiency in wheat production. Additionally, these insights can empower Ethiopia’s agricultural extension services to guide farmers in cultivating wheat in areas identified as highly and moderately suitable, thereby bolstering production in a changing climate.

Risk for nitrogen leaching after application of solid manure in autumn differs between manure types

Manure application performed in autumn requires regulation due to the risk of nitrogen (N) leaching during winter. On the other hand, application of manure in spring can pose some practical problems depending on the risk for N immobilization and the difficulty in ploughing heavy clay soils during this time of year. The risk for leaching is likely to differ between different soil texture and manure characteristics. In this study, we sought to estimate the risk for nitrogen leaching depending on the carbon/nitrogen ratio (C/N) of the manure, time for manure application, and soil type. We combined 3-year lysimeter experiments with 2-year field plot experiments and laboratory soil incubations and compared results with those from an empirical model. We compared effects of manure application on two soils (silty clay and loamy sand) and solid manures with different representing C/N ratios. In incubations, only manure with a C/N-ratio below 14 contributed with significant amounts of leachable N during the first months after application. In the lysimeter study, N leaching was unaffected by the timing of the application of the manure with C/N-ratio 18. However, regarding manure with C/N-ratio 10, N leaching was elevated with 10–15 kg N per ha after manure application in October compared to November and March on both soil types. The mineral N analyses from soil profiles in the field experiments showed a similar pattern, however, the increase was higher on the loamy sand compared to the silty clay. The ammonia emissions did not differ between manure types, but were on average 24% of applied NH4-N after application in October when air temperature was on average 12°C compared to only 3% of applied NH4-N in November and March when air temperature was on average 5°C. Similar to lysimeter results, the modelled N leaching was higher the earlier the manure application occurred in autumn. However, the model also predicted increased leaching for the manure with a high C/N-ratio, and a smaller effect on leaching on clay soil. Considering this, the model calculations overestimated the leaching effects from manure with a high C/N-ratio and underestimated the leaching effects on clay soil.

Adoption of soil conservation practices by mandarin (Citrus reticulata B.) farmers in Gulmi, Nepal

Mandarin has a tremendous potential for export and increased income for farmers of Nepal. However, in the recent years, soil degradation and erosion are the major challenges faced by the citrus enterprises especially in the hilly region of Nepal. The declining status of production and productivity cannot be checked without the transfer of site-specific and commodity-based knowledge and skills to the corresponding farmers. A study was carried out in 2023 to examine the soil conservation practices and status of technology adoption among the mandarin farmers. A total of 80 households from three wards of Dhurkot rural municipality of Gulmi district were selected on purpose for the study. Data were collected through interviews, key informant interviews, and focus group discussion, using semi-structured questionnaire, then the descriptive analysis was done using MS Excel and SPSS (Version 23.0). The results revealed that mainly three types of soil were presented in the study areas viz. luvisols, cambisols and sandy gravel, which are highly prone to soil erosion. The average area under mandarin cultivation was reported to be 0.74 hectare, with an estimated productivity of 7.6 metric tons per hectare. Approximately 95% of the respondents were familiar with soil degradation and its consequences in mandarin production. Accordingly, 96.2% of the respondents had adopted some forms of soil conservation practices like sod culture (40%), minimum tillage (36.2%), liming (40%), terracing and cover cropping (95%) and integrated plant nutrient system (31.2%), alongside the traditional stone bunds and mulching. The findings suggested that an increased participation in trainings and contact with extension agents has a significant influence on the importance of capacity building of the farmers regarding sustainable soil conservation technology, innovative cultivation practices, and ensuring frequent extension services to the farmers. Implementing these measures is expected to enable mandarin farmers in Nepal to check annual losses of soil fertility due to soil erosion and landslides, thereby contributing to commercialization of citrus.

Sustainable Development Strategies and Good Agricultural Practices for Enhancing Agricultural Productivity: Insights and Applicability in Developing Contexts—The Case of Angola

In general, agricultural productivity in Angola is low due to the limited awareness among stakeholders regarding sustainable development strategies (DSs) and good agricultural practices (GAPs) that could be adjusted to local crops, soil types, and climatic conditions. A structured approach was followed to develop a systematic literature review (SLR) that can address this gap by examining how DSs and GAPs may be adapted for Angola’s context to encourage sustainable agricultural development. Key steps included the selection and exclusion of literature from primary scientific databases based on specific screening indicators such as the publication date, language, relevance to DSs and GAPs, and geographic focus on developing or developed nations with comparable agricultural challenges. The initial search resulted in 11,392 articles, of which 4257 met the primary selection criteria. After further screening for relevance and availability, 98 articles were shortlisted, and 15 studies were ultimately included for in-depth analysis. This strict screening process ensured the inclusion of studies most applicable to Angola’s agricultural context. The key research findings indicate that certain DSs and GAPs have high adaptability potential for Angola. The findings emphasise practices such as drip irrigation and inorganic fertilisation, which are widely implemented in both developed and developing countries due to their efficiency in resource-limited environments. Additional strategies, such as water management systems, organic composting, and agroforestry practices, demonstrate significant potential to enhance soil fertility, water efficiency, and crop resilience against climate variability. By identifying these practices and strategies, this study provides a basic framework for policymakers in Angola to develop targeted implementation guidelines, fostering sustainable agricultural growth and resilience in the face of climatic challenges. Thus, this review contributes to the scientific and practical understanding of sustainable agriculture in developing countries, offering critical insights that support Angola’s efforts to achieve greater self-sufficiency and economic stability through sustainable agricultural practices.

Characterization and Classification of Soils of Chamba Block of Tehri Garhwal District of Uttarakhand, India: A Case Study from Lesser Himalayas

In the present study, an attempt was made to characterize and classify the soils occurring on different topography in the Chamba block of Tehri Garhwal district of Uttarakhand. A detailed soil survey was carried out by simple random sampling and studying master profiles using Landscape Ecological Unit’s map on 1:10000 scale to study the soils. The high-resolution remote sensing data product derived from the IRS-R2, specifically the LISS-IV data and GIS approaches were used. Nine representative pedons (covering all the soil types) were studied for their morphological, physical and chemical properties. These soils were very shallow to deep, dark grayish brown to dark brown/dark yellowish brown, brown to dark yellowish brown, dark grayish brown to olive brown and very dark grayish brown to dark yellowish brown in colour. Structure of the surface soils varied from sub-angular blocky to disturbed to single grain.Soil texture varied fromsandy loam to sandy loam, sandy loam to loam, loamy sand to sand and loam to clay loam in texture, strongly acidic to acidic (<5.5-6.5) and neutral (6.5-7.5) in reaction. The electric conductivity exhibited a range from 0.17 to 1.83 dS m-1 within surface horizons and from 0.02 to 0.80 dS m-1 within the sub-surface horizons, accompanied by organic carbon content categorized as medium (0.50-0.75%) to high (>0.75%). The exchangeable cations, specifically Ca2+, Mg2+, Na+, and K+, demonstrated variability ranging from 4.90 to 10.40, 1.30 to 4.00, 0.39 to 1.01, and 0.44 to 1.27 cmol p+kg-1, respectively, in surface horizons. Base saturation (BS) varied from 80 to 92% in surface horizons and from 68 to 91% in the sub-surface horizons. The cation exchange capacity (CEC) varied between 8.6 to 19.9 cmol p+kg-1 in surface horizons and from 2.7 to 17.2 cmol p+kg-1 in the sub-surface horizons. The soils were classified within the Entisols and Inceptisols orders. To ensure sustainable agricultural production within these soils, it is imperative to implement appropriate management strategies to mitigate the impacts of soil degradation.

Crop Yield Prediction Using Machine Learning

Machine learning plays a key role in helping farmers and decision-makers predict crop yields, assisting them in choosing which crops to grow and how to manage them throughout the growing season. To better understand the effectiveness of different machine learning methods, we conducted a systematic literature review. From six electronic databases, we initially gathered 567 relevant studies and, after applying our selection criteria, narrowed it down to 50 studies for in-depth analysis. We focused on identifying the commonly used algorithms and features in these studies. The analysis revealed that temperature, rainfall, and soil type are the most frequently used features for crop prediction, while Artificial Neural Networks (ANN) are the most applied machine learning models. In addition, we expanded our investigation to include studies specifically using deep learning techniques. We reviewed 30 papers in this category and found that Convolutional Neural Networks (CNN) are the most popular choice. Other widely used deep learning algorithms include Long Short-Term Memory (LSTM) networks and Deep Neural Networks (DNN). Overall, our findings offer insights into the prevalent approaches and highlight opportunities for future research in crop yield prediction using both machine learning and deep learning techniques.

Soil quality index to access the impacts of long‐term vinasse application in sugarcane areas

AbstractSoil quality index (SQI) helps quantify management practices impacts on the soil, providing information for producers in decision‐making. Through evaluation in sugarcane areas, soil indicators were used to develop SQI to access and quantify the impacts of long‐term vinasse application on the soil. The treatments consisted of two soil types: clayey (490 g kg−1 clay) and sandy (80 g kg−1 clay) and two conditions: with (70 m3 ha−1 year−1) and without vinasse application for 10 years. Soil samples were collected in the 0‐ to 10‐cm, 10‐ to 20‐cm, and 20‐ to 30‐cm layers in each treatment. Four soil functions were developed to calculate SQI: root environment quality (REQ), air/water ratio (AWR), soil chemical quality (SCQ), and soil tolerance to erosion (STE). Twelve soil indicators related to soil fertility and aggregation/structure were used. The long‐term vinasse application increased water storage (32%–58% of soil porosity), sum of bases (11–19 mmolc dm−3) and aggregate stability index (41% vs. 78%) compared to without vinasse treatment in sandy soil. In the clayey soil, vinasse increased (p < 0.05) the REQ, SCQ, and STE functions by 10%, 14%, and 13%, respectively, besides not affecting AWR. The long‐term application of vinasse promoted greater benefits, proportionally, in the sandy soil, with increments (p < 0.05) of 30% in AWR, 25% in SCQ, and 27% in STE. According to the SQI, long‐term vinasse application increased the capacity of the clay soil to perform its functions by 8%, while it increased to the sandy soil was 22%.

CO₂ sequestration and soil improvement in enhanced rock weathering: A review from an experimental perspective

AbstractEnhanced rock weathering (ERW) is an emerging negative emission technology (NET) with significant potential for mitigating climate change and improving soil health through the accelerated chemical weathering of silicate minerals. This study adopts a critical research approach to review existing ERW experiments, focusing on the mechanisms of soil improvement and CO₂ sequestration, as well as the economic costs and environmental risks associated with its large‐scale implementation. The results demonstrate that while ERW effectively enhances soil pH and provides essential nutrients for crops, its CO₂ sequestration capacity is highly dependent on variables such as soil type, rock type, application rate, and particle size. Furthermore, the economic feasibility of ERW is challenged by high costs related to mining, grinding, and transportation, and environmental risks posed by the release of heavy metals like Ni and Cr during the weathering process. Notably, significant discrepancies exist between laboratory experiments and field applications, highlighting the need for extensive in‐situ monitoring and adjustment of ERW practices. This study underscores the importance of optimizing ERW strategies to maximize CO₂ sequestration while minimizing environmental impacts. Future research should focus on long‐term field experiments, understanding secondary mineral formation, and refining the application techniques to enhance the overall efficiency and sustainability of ERW. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.

Land use management solutions in response to climate change: Case study in the central coastal areas of Vietnam

Abstract Vietnam is highly susceptible to climate change, which has significantly affected its agricultural production. Therefore, sustainable land use that adapts to climate change is a crucial research topic. This study was conducted in Loc Ha district, Ha Tinh province in central Vietnam, an area particularly vulnerable to climate change. The results indicate an increasing trend in temperature and rainfall, with flooding being the primary impact of climate change on agriculture, while drought has a moderate impact. This study assessed the suitability of land in the Loc Ha district to facilitate land use planning in line with climate change conditions until 2035. The land suitability analysis in Loc Ha district reveals that the district has 12 soil types across 8 soil groups, divided into 55 land units with varying characteristics. Adapting land use management to the climate change situation is an effective solution for agricultural development in the research area and across Vietnam in the future.

Granular Soils and Contaminant Modeling in Tailing Dams

The granular soils of tailings, encompassing clay, gravel, sand, and silt, play a pivotal role in the behavior and stability of tailings dams. Different types of granular soils significantly influence the tailings material’s strength, compressibility, and permeability. This study highlights the importance of understanding the relationship between soil types and contaminant properties when analyzing solute transport through numerical modeling. Consequently, various soil types were incorporated into the initial tailings dam model to simulate contaminant transport based on solute transport analysis. The findings underscored the essential role of granular soils in contaminant dispersion within tailings dams. Finer particles, such as clay and silt, demonstrated higher adsorption capacities, which slow contaminant movement. In contrast, coarser materials, like sand and gravel, enable faster transport, increasing the potential for rapid dispersion.