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Soil acidification is a natural phenomenon that human activity can accelerate or manage. Acid soils limit plant growth by reducing nutrient availability and causing aluminum toxicity, significantly reducing crop production. Liming has proven efficient for increasing crop yield on acidic soils. Knowledge is required on the effect of liming on the soil pH dynamics to find the suitable material, application rate, timing, and method. The objective of this study was to develop a prediction model of soil pH temporal variations after lime application using data from the literature. A database was built from research results extracted from 16 scientific papers that provided data on soil acidity changes over time under different liming treatments. Machine learning (ML) was used to predict soil pH dynamics from eight predictive parameters: rate of application, time since application, neutralizing value (CCE), grind fineness (D50), pH measurement depth, soil acidity (pH prior to liming), the type of solution used for pH measurement (water or CaCl 2) and the soil:solution ratio used to measure pH. Since soil pH fluctuates with seasons, all pH values were expressed as difference between the actual pH value and that of an unlimed control (ΔpH). The Random Forest (RF) algorithm was tested to predict ΔpH over time. On testing, we obtained an R2 between measured and predicted ΔpH values of 0.881 and an RMSE of 0.230. These results are excellent, considering the heterogeneity in soils, liming materials, and pedoclimatic conditions found in the 16 papers. The primary factors influencing ΔpH, ranked by their impact are application rate, time elapsed post-application, and lime characteristics including its grind fineness and neutralizing value. • Random Forest robustly predicts soil pH change over time following lime application. • The predictors are: rate, neutralizing value, particle size, depth, and initial pH. • The model predicts that, on average, lime increases soil pH for 82 weeks. • Machine learning models are promising tools in managing liming practices. [ABSTRACT FROM AUTHOR]

Continued mining operations have resulted in substantial soil degradation, necessitating the effective restoration of ecological functions in soils. Accurate and rapid measurement of soil organic matter (SOM) is essential for boosting soil fertility, supporting ecological restoration, and facilitating effective environmental management. Combining visible to near-infrared spectroscopy with machine learning algorithms is a promising technique for quantitative analysis of SOM. Firstly, the paper utilized a spectral pre-processing method that integrates fractional order differentiation transformation (FOD) and optimal band combination (OBC) algorithm. OBC algorithm was used to construct six three-band spectral indices to obtain optimal spectral combination parameters. Then, the HOVD-TELM model was constructed based on the hybrid model of two-hidden-layer extreme learning machine and Harris hawk optimizer. The opposition-based learning, vertical crossover operator and disruption operator were added to prevent the model from converging prematurely. The experimental results showed that: (1) compared with the pre-processing methods such as integer order differentiation and two-band spectral index, the FOD and OBC methods used in this paper obtained more ideal spectral pre-processing effects. (2) compared with models such as Partial least square regression and Extreme gradient boosting, the HOVD-TELM model proposed in this paper obtained the optimal prediction performance, with the minimum RMSE of 6.7874 g·kg−1 and the maximum R2 of 0.9209, indicating good prediction reliability. In summary, this paper proposed a fast and accurate method for detecting soil organic matter content and improves the estimation accuracy of SOM content. [Display omitted] • A method for rapid and accurate detection of soil organic matter content. • The method is based on visible to near-infrared spectroscopy and machine learning. • High quality spectral features are extracted by pre-processing methods. • We proposed an improved machine learning model. [ABSTRACT FROM AUTHOR]

Measuring soil structure stability has always been a challenge, and various approaches have been proposed, mainly related to measuring soil aggregate stability upon wetting. This paper presents a rapid and cost-effective tool for evaluating soil structural stability named ASTAVIT, which stands for Aggregate STability Assessment using VIdeo Tests. The ASTAVIT principle involves visually monitoring the spreading of aggregates. This has already been implemented in the SLAKES smartphone application (now renamed Moulder), which simplifies the measurement of soil aggregates with minimal equipment. The aim of this work was to develop a robust, adaptable, and representative enough method that can be widely used in soil science laboratories. The protocol has been modified to use a 3D-printed plate, which source file is provided with this paper, to record the immersion of up to 96 individual aggregates in water. The increase in the projected area of the aggregates during slaking is tracked using image recognition software, ImageJ. The final stability index is determined based on this area increase. Soil structural stability can be assessed within an hour using a procedure that involves placing aggregates on a plate, filming, and analyzing. This method provides an objective evaluation of soil stability in a timely manner. The amount of soil used per test is similar to that used in Le Bissonnais tests (ISO 10930), ensuring representative results. The ASTAVIT index demonstrates expected behaviors of aggregate stability, as evidenced by its correlation with other soil characteristics and its ability to differentiate between soils that have undergone different tillage practices. An indicative classification of the ASTAVIT index into four categories of soil stability, similar to the Le Bissonnais tests, is proposed. ASTAVIT is expected to facilitate a broader implementation of structural stability studies. • This paper describes an alternative method for measuring aggregate stability. • The evaluation is based on changes in the visual area of the slaking aggregates. • The method is low labor and high throughput. • It uses a custom 3D printed support and LED illumination. • The FAST method effectively discriminates between cropland and grassland. [ABSTRACT FROM AUTHOR]

Accurate soil type maps provide an important basis for agricultural decision-making and land degradation control. In soil classification studies, the various environmental covariates are often selected based on the soil-forming framework. Since the mapping area and available observation data are limited, meteorological and vegetation cover factors have not been fully developed, and their role in soil classification needs to be evaluated. In addition, whether deep learning has out-performance in soil classification remains to be tested. The aim of this paper is to evaluate the accuracy of deep learning modelling techniques in classifying soil type using different combinations of input variables, and evaluate the importance of soil-forming variables in soil type classification. Therefore, we collected commonly used environmental covariates in Northeast China (NEC), including multiple meteorological factors and adopted a satellite-based biophysical model (Boreal Ecosystem Productivity Simulator, BEPS) to enrich vegetation cover factors. Next, four modeling strategies were developed: the soil-forming factors of soil and relief were considered as traditional environmental covariates (T), as well as combined with meteorologic variables (T + C), vegetation cover variables (T + V) and all available environmental covariates (T + C + V). Then, the effectiveness of different modeling strategies for soil classification was explored with convolutional neural network (CNN) model and multi-layer random forest (MRF) model based on soil separability. Finally, a 30 m resolution soil type map was established. The results demonstrated that both MRF and CNN can achieve high accuracy soil classification, while the CNN model performs better. The descending order of classification accuracy based on different modeling strategies of the CNN model is shown as T + C + V: 91.08%, T + V: 88.84%, T + C: 86.82%, and T: 83.96%. Meanwhile, the separability of different soil-forming factors for soil classification is soil properties, vegetation cover, temporal variation, meteorologic and relief in descending order. For Castanozems and Brown soils, MRF has higher classification accuracy, while CNN has better performance in Meadow soils and Fluvo-aquic soils. The methodology proposed in this paper aims to achieve high accuracy soil classification, provide an approach to understand the importance of soil-forming factors for the region, as well as for different soil types, and provide references for facilitating the interpretation of misclassified areas. Our results are accurate in the core areas, and therefore, this work facilitates researchers to be able to focus more on areas where different soil types intersect, thus significantly improves efficiency and saves resources, and promises to be a useful tool for future soil surveys. • Clarify the role of meteorological and vegetation cover factors for improving soil classification accuracy. • Validate the potential of multi-layer random forest (MRF) and convolutional neural network (CNN) in digital soil mapping. • Estimate vegetation cover information at 30-m resolution utilizing a satellite-based biophysical model. • Temperature, net primary productivity and precipitation are the three most important variables for soil classification. [ABSTRACT FROM AUTHOR]

It is often assumed that a homogeneous distribution of soil properties occurs in the topsoil layer, but the vertical variation of soil properties in cultivated soils would mainly depend on the tillage system. In remote sensing, for example, only information strictly limited to the soil surface is accessible, although the interest of the user communities would concern the topsoil rootzone, i.e. until a depth of 30–40 cm. The present study provides an analysis of data collected from studies in which the vertical variation of the main soil properties was reported for four types of tillage systems: i) deep inversion ploughing (DP); ii) subsoiling (SUB); iii) minimum tillage (MT) and no-tillage (NT). To the best of our knowledge, a review about the effects of different tillage systems on soil vertical variation seems to be lacking in the current literature. A keyword-based search followed by a two-stage manual selection provided a total of 43 papers with data sets suitable for the analysis. The soil data, extracted by these papers, were standardized to avoid different measurement units and different site-specific baselines. This method allowed to obtain the soil data extracted by different papers worldwide, comparable to study the vertical gradient. A gradient of soil organic carbon (SOC) was reported in all the 43 selected papers, whereas total nitrogen (TN) in 20 papers, therefore reliable global models of vertical variation could be obtained for these properties. Linear models of SOC vertical variation were obtained for MT and SUB, whereas second order polynomial functions were calculated for DP and NT. The full cross-validation of the models provided R2 higher than 0.8 and errors (RMSE) from 1.55 to 3.23 g.kg−1, with similar efficiency for SOC and TN. Predictive models of vertical variation of C/N ratio and bulk density (BD) were also carried out, whereas data of pH, CEC, and textural fractions were found only in few papers and modelling was not possible. The models proposed by this analytical review might be employed to extend the estimation of surface soil properties to the whole topsoil layer of cultivated soil, according to the adopted tillage method. In addition, the results of the paper highlighted the impact of tillage system on the vertical gradient of SOC, TN, and BD, allowing a better quantification of the carbon and nitrogen stock in agricultural soils. • Predictive models for remote sensing are strictly limited to the soil surface. • Rootzone volume is commonly the layer of interest in most agronomic applications. • Tillage typologies influence the vertical gradients of soil features. • Inversion tillage tend to homogenize the soil features within A horizon. • Surface features can be extended to the A horizon according to the tillage type. [ABSTRACT FROM AUTHOR]

Soil structure is a dynamic property which controls a wide range of soil functions and is closely linked with soil carbon content. The carbon contents of agricultural soils are subject to several ongoing trends, including declining carbon stocks and attempts to increase the soil carbon reserves. In this study, we aimed to quantify how organic soil amendments, which have been shown to reduce long-term nutrient loads from agricultural fields, can impact soil structure. The structural impacts of a large one-time addition (8 tons carbon per hectare, three different soil amendments) of pulp and paper mill side stream sludges to a boreal clay soil were explored quantitatively in aggregate (X-ray microtomography, sample size 1–2 mm), core (water retention measurements, sample size 195 cm3) and column (macropores ≥80 µm, sample size ∼ 20 dm3) scales. Our results showed no micrometer-scale structural changes within soil aggregates despite the large number (25 aggregate per treatment) of imaged samples. However, the organic soil amendments had a statistically significant impact on the macroporosity. The macroporosity was on average 20–27 % higher compared to the control samples and visible even five years after the application of the amendments. Such change in soil structure improves soil aeration and fast infiltration of water during wet periods and extreme rain events and may thereby also reduce erosion risk by decreasing surface runoff. The increased microporosity was visible only in the column scale. No statistically significant differences were observed in the fraction of large pores in core scale water retention measurements. Probing the soil structural changes in macropore regime by X-ray tomography or developing sub-micron scale analysis methods are recommended approaches to improve our understanding of clay soil's structural changes induced by organic soil amendments. • The effect of a large single dose of organic matter on soil structure was studied. • Soil structure was investigated from aggregate to column scale. • 100 aggregates imaged with X-ray tomography. • Differences in intra-aggregate porosity were not found. • Only macropores (≥80 µm) were affected by the organic soil amendments. [ABSTRACT FROM AUTHOR]

Organic materials are integral to the soil carbon cycle in agricultural ecosystems, yet their specific impacts on soil organic carbon (SOC) and microbial diversity are not fully understood. In this study, we analyzed 188 data pairs from 57 published papers to assess the effects of various organic materials on SOC composition and microbial diversity across different farmlands. Our findings indicate that the addition of organic materials consistently enhances SOC composition and promotes both bacterial and fungal diversity. Notably, the particulate organic carbon (POC) fraction exhibited the most significant increase (42.35%), suggesting that POC is the primary pathway for organic carbon accumulation. Our analysis also identified the type of organic material as the leading factor influencing soil active carbon fractions and microbial diversity, with compost emerging as the most effective material for boosting soil carbon sequestration and microbial richness. Interestingly, while both dissolved organic carbon (DOC) and microbial biomass carbon (MBC) increased with organic material addition, a negative correlation between these two components was observed. This study advances our understanding of the complex interactions between organic materials, SOC components, and microbial diversity, providing valuable insights for the development of sustainable soil management practices aimed at enhancing soil carbon storage and agroecosystem health. [Display omitted] • Organic material enhanced active SOC components and microbial diversity. • Material type is a key determinant of soil carbon composition. • The main factor of SOC increase was the accumulation of POC. • MBC has a potential competition with DOC. [ABSTRACT FROM AUTHOR]

The Visual Evaluation of Soil Structure (VESS) method has been used frequently to evaluate the structural quality of soils from various parts of the planet, under different edaphoclimatic conditions and cultivation practices. In this context, this paper hypothesised that VESS is sensitive enough to detect differences between structural quality (Sq) scores of VESS from soils with different textural classes, submitted to distinct management and cultivation practices, under contrasting climates. To test this hypothesis, a systematic review and meta-analysis of global scope were conducted, with the objective of compiling and analysing all indexed scientific papers that utilised the method. Exclusion criteria were adopted with the intention of eliminating papers that did not meet the selection criteria for the meta-analysis, however, these papers were used in the systematic review. A sensitivity analysis was performed prior to the meta-analysis in order to evaluate the heterogeneity in the data set, thus increasing the scientific validity of the overall analysis. The results obtained through the systematic review showed that the number of studies using VESS has grown in recent years, not only in temperate regions, but also under diverse soil conditions and cropping systems in subtropical and tropical regions. The meta-analysis showed that temperate soils presented lower Sq scores compared to those observed in tropical and subtropical soils, whereas higher Sq scores were observed in clayey/silty soils compared to sandy soils, regardless of climate zone. Our findings also revealed that Sq scores differences induced by soil management and cropping systems were not detected by the meta-analysis. Thus, the VESS is an on-farm, practical and reliable tool for evaluating the structural quality of soils globally. [ABSTRACT FROM AUTHOR]

Highlights • Automated optical methodologies can provide in depth analysis of particle size and shape. • Lased diffraction is in better agreement with automated optical methodologies than sedimentation methods are. • A comparative study shows that traditional techniques present limitation for particle size analysis. • Confirmation of the offset between sedimentation and laser. Abstract For many years papers have been published showing differences between sedimentation-based methods against laser diffraction. Differences were found especially in the fine texture ranges and regression equations were presented to convert data obtained between different methods. In this paper we aimed at understanding which method is closer to an independent measurement of particle size. We selected a new, automated image analysis technique as a reference method. Since with this new method each individual particle is photographed, its pixels counted and its shape analysed, we assumed this method as the reference method against which test the accuracy of sedimentation methods and laser diffraction. Comparison showed that laser diffraction was in better agreement with the independent optical methods, indicating that the sedimentation methods tend to largely overestimate the finer fractions of the distribution. Considering the results presented in this research, and the methodological disadvantages of sedimentation methods, we propose to employ laser diffraction as a standard method for particle size analysis in soils. [ABSTRACT FROM AUTHOR]

The bionic design of soil-engaging components has recently received much attention in conservation tillage and is extremely important for reducing tillage resistance and increasing implement passability in wet-adhesive rice paddy soil. In this paper, to reduce adhesion and resistance of rotary tillage in wet-adhesive soil, a novel imitating pangolin scale structure is first proposed, and the bionic non-smooth surface parameters affecting the soil adhesion effect is clarified. Afterwards, based on the JKR attached Bonding contact model, an accurate discrete element interaction model of the designed rotary tillage blade -wet adhesive soil is established, and the effect of spindle speed, bump size and bump distance on the tillage resistance and soil disturbance is analyzed using the proposed model. Finally, the proposed imitating pangolin scale structure is optimized to improve the anti-adhesive and drag reduction properties using response surface method, furthermore, the corresponding model validation experiments and field tests are also conducted. Results reveal that the relative errors between the simulated and experimental values of the bionic blade rotary torque and soil adhesion mass are only respectively 4.4 % and 8.3 %. In addition, the optimal parameter combinations of anti-adhesion and drag reduction are also determined: the spindle speed is 180 rpm, the bump width is 10.6 mm and the bump distance is 17.9 mm, respectively, at the time, the effect of soil breaking of the designed blade is reduced by 9.95 % compared to that of the traditional blades but the effect of anti-adhesion and drag reduction is improved by 18.81 %. [Display omitted] • An adhesive breakable soil model is proposed and calibrated. • A non-smooth surface of the blade imitating the pangolin scale structure is designed. • A discrete element model of wet adhesive soil-rotary tillage blade is established. • Response surface method is used to determine the optimal structure and working parameters. • The effect of soil adhesion on the tillage performance of soil-touching components is investigated. [ABSTRACT FROM AUTHOR]

Soil Water Retention Curve (SWRC) provides crucial information for understanding soil moisture retention, essential for agriculture, hydrology, engineering and environmental science applications. Many SWRC fitting models in the literature are based on empirical equations without a direct physical meaning. However, SWRC data is physically related to the soil's porous structure and its interactions with the wetting fluid. Hence, the curve's behavior reflects the porous complexity. Non-physical model equations might even be able to fit the data to be used in several applications; however, the search for physically fitting models representing the SWRC data as a smooth continuous distribution function can reflect new insights and information about this heterogeneous porous media. In this regard, the well-established physically-based Kosugi model is based on the assumption of lognormal pore size distributions. However, a general approach for any modality and distribution shape could be interesting. This paper proposes applying the mathematical method known as " Inverse Laplace Transform " (ILT) to fit the Soil Water Retention Curve using a weighted superposition of exponential decays. This multi-exponential approach involves working with two physically related parameters, the amplitude and its respective characteristic matric potential, which are physically interpreted as the amount of pores that empty at that suction head. The ILT-EXP method proposed was implemented in Python software to fit the curves, and it is now available in an online web app. The evaluation of the ILT-EXP model to fit SWRC data is discussed, presenting its potential to estimate soil pore size distribution of multimodal samples. One advantage of ILT-EXP over other multimodal models is that it does not need to know how many modal components are present in the SWRC data, being automatically determined by the method. Finally, a statistical fitting comparison of 439 SWRC data, with six other classical models is discussed. The results indicate that fitting with the ILT-EXP model demonstrates strong potential, making it a powerful method for handling multimodal curves. This approach represents a novel and robust method for estimating a smooth, continuous soil pore size distribution. [Display omitted] • Inverse Laplace Transform was used to fit the soil water retention curve as a sum of exponential decays. • The ILT-EXP model allows a reliable estimation of multimodal soil pore distribution (PSD). • An online WebApp was developed to perform the ILT-EXP and other classical methods in SWRC data. [ABSTRACT FROM AUTHOR]

This article presents a review of the equipment used in the process of determining the mechanical strength of soil, in particular with regards to the vertical loads applied. Here, devices incorporating the bevameter approach, i.e. medium and large-scale testers, are discussed. The bevameter technique is described in detail, along with the most common mathematical models relating to the vertical pressure applied to the soil and its compaction. The paper also highlights important phenomena for this type of experiment, such as the scale effect, wall effect, multipass effect, and slip sinkage effect. The article presents the reasons for which plate testers are currently the most commonly used tester type for soil penetration tests for the purpose of terramechanics, including the Next Generation NATO Reference Mobility Model that is currently under development. Investigations towards the influence of the penetration rate on soil penetration are also addressed. Furthermore, the authors also present a selection of their own results of currently ongoing research on the subject of potential influence of the plate grouser on plate sinkage. The results already obtained have made it possible to identify phenomena that are not taken into account in the current research methods, in turn resulting in the development of an innovative plate tester for investigating the sinkage of the running gear components of machines and vehicles in fragmented media. • Bevameters show a number of significant advantages over penetrometers. • Bevameters will be the leading soil testing method in the new NATO mobility model. • There are reasonable minimum dimensions for both tester plate and soil bin. • The grouser of the tester plate can also influence the soil penetration process. • Taking from already conducted bevameter tests can improve research pace. [ABSTRACT FROM AUTHOR]

Reliable assessment of soil mechanical parameters causes many problems due to its random nature, and therefore the literature on the subject provides many techniques in this area. The article presents an analysis of the state of the art in the field of process analogues (testers) for identifying soil compaction under external loads that are generated, for example, by the running gear components of off-road machinery and vehicles. A classification of these testers into three main groups is proposed: small-size (penetrometers), medium-size (plate testers), and large-size (chassis components). The cone index approach for small-scale testers is described in detail in the paper. Consequently, the bevameter approach, which is used for medium- and large-scale testers, is described in Part 2 of this pair of articles. The main application of penetrometers in terramechanics, which is to determine the mobility of off-road vehicles, mostly qualitatively, is highlighted, with a description of the most important mobility metrics, also in the context of the NATO Reference Mobility Model, also being presented. An overview of the devices is presented, with the tester area, applied pressure levels, types of soil tested, and field of use also being discussed. The analyses include static and dynamic testers. The pair of articles also presents the main issues with penetrometer testing, and the reasons for which bevameters are the most commonly used tester for determining quantitative soil parameters for the purpose of terramechanics. • Penetrometers are basic testers for evaluating the mobility of off-road vehicles. • Various tester shapes are used with cone penetrometers being the most common ones. • There are methods for dynamic and impact soil testing incorporating penetrometers. • Taking from already conducted penetration tests can improve research pace. [ABSTRACT FROM AUTHOR]

Simple analytical solutions for one-dimensional unsaturated soil water infiltration are important for estimating soil hydraulic properties and optimizing irrigation practices. In this paper, we propose a method based on the functional extremal problem of the Richards equation to simulate the vertical infiltration of one-dimensional unsaturated soil water under constant flux. This method used the Brooks-Corey model to present the functional extremal problem and obtain the functional extremal solution of the Richards equation using the Euler-Lagrange and the integral median theorem. Hydrus-1D was used to obtain the numerical data of one-dimensional vertical infiltration with a constant flux of 0.0001–0.001 (cm·min−1). By comparing the analytical results of the functional extremal solution with the numerical data, we derived the relationships between the infiltration characteristics (soil water content profile, cumulative infiltration, and infiltration time) and the major parameters (soil hydraulic parameters, constant flux q i , and vertical wetting front depth z f). The comparison results of the high fluxes conditions showed that the functional solution accurately described the one-dimensional vertical infiltration in soils with the absolute air-entry suction h d ≥ 10 cm under a constant flux at the upper boundary. • Analytical solution of 1-D vertical infiltration with the flux boundary was proposed. • Expressions of infiltration characteristics were obtained by hydraulic parameters. • Numerical data of Hydrus-1D were used to adjust and validate the analytical solution. • The solution can be used for simulating infiltration of constant rainfall intensity. [ABSTRACT FROM AUTHOR]

Roughness is an important physical property of soil surface, and the estimation of soil surface roughness (SSR) has widely applications in the working performance evaluation and parameter control of agricultural machinery. This paper analyzed the influence of SSR on the reflection characteristics of ultrasonic beam and the subsequent changes in the receiver output voltage signal. Then, taking the peak output voltage V max , median value time interval T m , single-cycle voltage integral E r and peak time interval T p of the received voltage signal as inputs, an SSR estimation model based on adaptive neuro-fuzzy inference system (ANFIS) was established. The experimental results showed that the average estimation error was less than 18% with the measurement distance in 40 – 45 cm. The proposed method is different from laser scanning, depth camera and other non-contact measurement methods to obtain a 3D shape of the soil surface through the point cloud information, but directly estimates the SSR according to the reflection characteristics of the ultrasonic beam. Therefore, it is convenient and efficient, and the measurement component is mainly an ultrasonic sensor. The measurement principle determines that it has a good anti-interference performance to the ambient light intensity, dust and machine vibration, and can well meet the real-time requirements. • A soil surface roughness estimation method using an ultrasonic sensor was proposed. • Influence of SSR changes on the reflected ultrasonic beam was analyzed. • Characteristic parameters of reflected ultrasonic beam related to SSR were determined. • SSR estimation model was established based on ANFIS. • Calibration tests were carried out to verify the SSR estimation accuracy. [ABSTRACT FROM AUTHOR]

The global temperature has been increasing over the years due to climate change that, directly or indirectly, affects water and energy consumptions in the agriculture sector. The application of mulching practices reduces soil evaporation, conserves soil moisture, suppresses weed growth, controls soil structure and temperature, influences soil micro-organisms, and is aesthetically pleasing. This study has reviewed 189 published research papers, which described the effects of various mulching materials and methods on soil and environment that influence crop productivity. This paper describes the extent of influence of different mulching materials and methods on the hydrothermal environment of soils. It is imperative to know the processes that control soil environments under various mulching conditions and the effects of mulching materials on crop yield, productivity and water use efficiency. These issues of mulching are the prime concerns of this review study. Plastic mulching materials have a greater importance than the organic ones to control soil environment and increase crop yield. But, the organic mulching materials are inexpensive and environment friendly. The selection of an appropriate mulching material is, however, guided by crop type, crop management practices and climatic conditions. Future research is needed on the effects of low-cost biodegradable mulching materials on microclimate modifications, soil biota, soil fertility, crop growth and crop yields. [ABSTRACT FROM AUTHOR]

Soil structure is a key attribute of soil quality and health that significantly impacts water infiltration. Structure can be significantly altered by natural or anthropogenic drivers including soil management practices and can in turn impact soil infiltration. Those changes in soil structure are often complex to quantify and can lead to conflicting impacts on water infiltration into soils. Here, we present a narrative systematic review (SR) of the impacts of soil structure on water infiltration. Based on inclusion and exclusion criteria, as well as defined methods for literature search and data extraction, our systematic review led to a total of 153 papers divided into two sets: experimental (131) and theoretical (22) papers. That implied a significant number of in-situ and field experiments that were conducted to assess the impacts of soil structure on water infiltration under the influence of different land uses and soil practices. Analysis of the metadata extracted from the collected papers revealed significant impacts of soil structure on water infiltration. Those effects were further attributed to land use and management, where we demonstrate the impact of three unique categories: soil amendments, crop management and tillage. Furthermore, significant correlations were established between infiltration rate and soil structural properties, with R2 values ranging from 0.51 to 0.80 and for saturated hydraulic conductivity and soil structural properties, with R2 values ranging from 0.21 to 0.78. Finally, our review highlighted the significant absence of and the need for theoretical frameworks studying the impacts of soil structure on water infiltration. • Review revealed significant impacts of soil structure on infiltration capacity. • Effects attributed to landuse management: soil amendments, crop management and tillage. • Significant correlations established between soil infiltration capacity and structure. • Significant need for theoretical frameworks studying structure and infiltration. [ABSTRACT FROM AUTHOR]

This paper describes the long-term effects of practicing ten years reduced tillage on crop yields in a conventional and organic farming system context. Data were collected from the BASIS field experiment, which was established in the Netherlands in 2009 to investigate the effects of reduced tillage on crop yield and soil properties in a controlled traffic farming system on a sandy loam soil. The experiment is unique in its focus on root crops grown on ridges, planted crops and small seeded crops, including cash crops such as potato (Solanum tuberosum), carrot (Daucus carota subsp. Sativus), onion (Allium cepa) and sugar beet (Beta vulgaris). The objective of the present paper was to analyse the long-term effects of reduced tillage on the marketable yields of these crops, grown in a conventional (4-year rotation) and organic farming system (6-year rotation). Tillage treatments were conventional deep inversion tillage (CT, mouldboard plough, 23–25 cm depth), reduced tillage with sub-soiling (RTS, chisel plough, 18–20 cm depth), and reduced tillage without sub-soiling (RT). Our key finding is that the two reduced tillage systems, over a 10-year period, provided similar or even higher marketable yields than conventional tillage, for 12 (RTS) and 11 (RT) of the 13 crops grown. Reduced tillage resulted in lower yields in two crops: carrot (−13.4% in RTS and −15.2% in RT) and cabbage (−5.2% in RT). In both cases, yield losses could be partly related to negative effects of crop residues from the preceding cover crop. Our results provide evidence that yield levels of crops grown in RT in our experiment can generally compete with crop yields in ploughed systems. However, crop residue management and seedbed preparation remain a challenge in reduced tillage systems, requiring further attention in research and dissemination. • 10 year field trial of reduced tillage (RT) effect on crop yield on sandy loam soil. • 13 crops studied in an organic and conventional farming system. • Overall marketable crop yield was similar in RT vs deep inversion tillage. • Marketable carrot yield was significantly lower in RT vs deep inversion tillage. [ABSTRACT FROM AUTHOR]

Soil quality is defined here as the capacity of soil to have biological function, to sustain plant and animal production, to maintain or enhance water and air quality and to support human health and habitation. There are different soil quality assessment models based on diverse methods and data, but none of the models can fully meet all purposes. The selection of an appropriate soil classification model therefore becomes an important aspect in soil quality assessment. This paper presents a new comprehensive support vector machine-based classification model for classification of urban soil quality and then uses that model to assess the soil quality of Taiyuan relative to Chinese environmental quality standards and regional background values. The results indicated that the support vector machine-based soil quality model combined soil heavy metal contamination and soil fertility data satisfactorily, with an accuracy of 98.3333%. The soil quality of Taiyuan was subsequently divided into five classes (IA, IB, IC, IIA and IIB). Fifty percent of all samples were classified as class IB, indicating that soil quality within the study area was good. This paper shows that a comprehensive support vector machine-based classification model is feasible and reliable for soil quality assessment. Furthermore, the assessment presented could provide references for related ecological problems. [ABSTRACT FROM AUTHOR]

Soil erosion and accompanying sediment issues have a significant impact on environmental sustainability. However, there is not currently a clear understanding of the relationship between soil erosion and sediment sources at the catchment scale, which has led some researchers to regard areas with severe soil erosion as the main sediment source. This view does not apply in all circumstances. • This paper uses 137Cs to study the average annual erosion rate of different land use types. The results show that the erosion rates of woodland, sparse woodland and farmland areas were 400, 1756, and 2771 t·km−2·a−1, respectively, multiplied by the corresponding area. Surface soil erosion levels in the catchments of the three types accounted for 11%, 26% and 25%, respectively, and the total accounted for 62% when the gully bank accounted for 38%. • Fingerprinting technique results show that the relative source contributions of woodland, farmland, sparse woodland and gully bank areas to sediment at the small catchment outlet were 4%, 10%, 48% and 38%, respectively. The results reveal that the detachment process of soil and the transport process of sediment with runoff were internally related and independent of each other. • By comparing on-site erosion rates with downstream source contributions, we have a clearer understanding of soil erosion and subsequent sediment transport process in the agroforestry catchment in mountainous areas. We emphasize the importance of governance and management in areas with severe soil erosion, mainly targeting types such as hillslope framland. In addition, sparse woodland and gully banks should be given more attention, as they account for a large proportion of sediment in the downstream catchment. • Soil erosion using 137Cs based on multiple reference inventories. • Combine on-site erosion by 137Cs with sediment sources by fingerprinting. • Clearer understanding of soil erosion and sediment transport process. [ABSTRACT FROM AUTHOR]

Understanding the role of organic amendments on soil potassium (K) distribution characteristics in Chinese paddy fields, we conduct a meta-analysis to explore the effect of organic amendment under different climatic and management practices. The meta-analysis consisted of 376 published papers from which 1294 paired observations were collected to evaluate the response of exchangeable K (EK) to different organic amendments in Chinese paddy soils. The results showed that EK concentration presented great variations (coefficient of variation: 44.5 %) and followed a decreasing trend from North to South and West to East, while higher EK concentration was detected in Northeast China, in 2020 s. Compared to the 2000s, the soil EK concentration in the 2020s significantly increased for the Northeast, Southwest, and East China. The highest EK concentrations were observed in Northeast (164 mg kg−1) and lowest values were observed in South China (71 mg kg−1). In case of organic amendments soil EK significantly increased compared to chemical fertilizers (CF), whereas the total K showed no significant differences in CF plus manure (CFM). The effects of organic amendments on soil K concentration revealed significant difference under various soil textures, cropping systems, and organic material types. The boosted regression trees analysis confirmed that the difference in K input for CF and CFM, and available phosphorus (AP) for straw combined with CF were the most influential variables on the variation of soil EK concentration. The structural equation modeling illustrated that organic amendments can directly and indirectly affect soil EK variation through increased K input and the regulation of crop K uptake and soil properties (total nitrogen and AP), respectively. These findings indicate that the organic amendments presented great potential for solving paddy soil K deficiency, as well as the types of organic material and soil properties should be carefully considered for greatest K use efficiency and lowest resource waste. • Clarified the distribution of exchangeable K (EK) concentration in Chinese paddy soil. • Quantified the change of soil EK in response to chemical and organic amendments. • Illustrated the main driving factors and path effects on increase soil EK content. • Manure and straw are conducive to increasing EK supply and reserves, respectively. • Rice straw combine with green manure is preferential for increase EK in South China. [ABSTRACT FROM AUTHOR]

Abstract: The paper deals with the determination of the tractor wheel load during tillage. Forces acting between tractor and implement significantly change the load of driving wheels. Mathematical description of simple model fails due to impossibility of determination these forces between the tractor and implement. The article describes the multi-body model used for calculation of resultant force and torque acting from the implement on a tractor as well as the forces acting between the wheels and the soil. Paper also shows the results of verification of calculations based on experimental measurements carried out in the laboratory and tests performed under the field conditions. [Copyright &y& Elsevier]

• Limited resource accessibility reduces crop productivity on compacted soil. • Plants grown on compacted soil are exposed to a multi-stress environment. • A plant eco-physiological perspective is needed to develop mitigation strategies. • Improving tolerance to specific stresses through breeding enhances crop performance. • Restoring specific soil properties facilitates root growth and resource accessibility. Soil compaction constitutes a major threat to the fertility of arable soils and food security. The aim of this paper is to highlight the need and opportunities for plant eco-physiological approaches to identify strategies to recover crop yields after soil compaction. Reduced productivity on compacted soil primarily results from decreased root elongation rates and thus limited accessibility to water and nutrients. Hence, strategies to recover productivity after compaction must address plant eco-physiological phenomena that underlie low root system expansion rates. In compacted soil, root growth is decreased due to high soil penetration resistance and due to low oxygen concentration in soil air caused by reduced fluid transport capability. Thus, plant roots are exposed to a multi-stress environment, which needs to be addressed directly when aiming to recover productivity after compaction in the long-term. Here, we discuss possibilities to increase root growth in order to enhance resource accessibility and recover crop productivity on compacted soil. Yield recovery can be achieved through breeding of novel cultivars and targeted soil management approaches. On the one hand, the tolerance of plants to the different soil physical stresses can be enhanced by selecting for specific root traits that facilitate root growth in compacted soil. Soil management approaches that improve specific physical properties of compacted soil on the other hand can facilitate root growth in compacted soil. Since plant roots are major drivers of soil structure dynamics, increasing root growth in compacted soil may not only mitigate crop productivity losses but also recover soil structure. [ABSTRACT FROM AUTHOR]

• The performance of on-line vis-NIR for estimating soil organic carbon was evaluated. • Predictions for three datasets single field, UK with spiking, and UK were compared. • Random forest (RF) regression and spiking technique were used. • The best results obtained with the spiked UK dataset. Accurate on-line visible and near infrared (vis-NIR) spectroscopy prediction of soil organic carbon (OC) is essential for food security and environmental management. This paper aims at using on-line vis-NIR spectra coupled with random forest (RF) modelling approach for the prediction of soil organic carbon (OC), comparing between single field (SF), non-spiked UK multiple-field (NSUK) and spiked UK multiple-field (SUK) calibration models. Fresh soil samples collected from 6 fields in the UK (including two target fields) were scanned with a fibre-type vis-NIR spectrophotometer (tec5 Technology for Spectroscopy, Germany), with a spectral range of 305–2200 nm. After dividing spectra into calibration and independent validation sets, RF was run on the calibration set to develop calibration models for OC for the three studied datasets. Results showed that the model prediction performance depends on the dataset used and varies between fields. Less accurate prediction performance was obtained for the on-line prediction compared to laboratory (samples scanned in the laboratory under non-mobile measurement) prediction, and for non-spiked models compared to spiked models. The best model performance in both laboratory and on-line predictions was obtained when samples from the SF were spiked into the UK samples, with coefficients of determination (R2) values of 0.80 to 0.84 and 0.74 to 0.75, root mean square error of prediction (RMSEP) values of 0.14% and 0.17 to 0.18%, and ratio of prediction deviation (RPD) values of 2.30 to 2.5 and 1.98 to 2.04, respectively. Therefore, these results suggest that RF modelling approach when coupled with spiking provides high prediction performance of OC under both non-mobile laboratory and on-line field scanning conditions. [ABSTRACT FROM AUTHOR]

• Arable soil N 2 O emission is correlated with the temperature, chemical soil properties. • N 2 O fluxes from the forest soil are correlated with atmospheric temperature. • Denitrification is an important source of N 2 O in arable soils. • Nitrification is a key source of N 2 O-N emission from forest soils. • Management of forests is an effective way to mitigate the N 2 O emissions from the soil. The paper presents the relts of a study aimed at assessing N 2 O-N emissions from arable and forest soils under the climate conditions of Central Poland. Measurements were conducted during the 2012 growing season. N 2 O-N emissions from the soil were measured in situ by infrared spectroscopy using a portable Alpha FTIR spectrometer (Bruker). The measured N 2 O-N fluxes showed a high variability over the study period, with fluxes from the arable soil treated with fertilizer (0.08–21.60, median 5.31, mean 7.08 μg N 2 O-N m−2 h-1) tending to exceed those from the forest soil (0.00–18.78, median 3.35, mean 4.54 μg N 2 O-N m−2 h-1). N 2 O-N fluxes from the arable soil were correlated stronger with the atmospheric temperature and soil moisture than with the soil NO 3 --N content. The N 2 O-N fluxes from the forest soil were positively correlated with atmospheric temperature only. The relationship between the N 2 O-N emission from the arable soil and soil NH 4 +-N content was marked by negative correlation. Based on the measured N 2 O-N flux and its relationship with environmental factors (especially the negative correlation between N 2 O-N flux and NH 4 +-N content) it can be hypothesized that denitrification is an important source of N 2 O-N in arable soils of Central Poland, even when the soil water-filled pore space (WFPS) during the growing season is below 40%. However, in such soil moisture conditions the N 2 O-N fluxes from the arable soils are relatively low. The very low soil NO 3 --N content throughout almost the entire growing season suggests that nitrification may be the main process producing N 2 O-N in the forest soil characterized a low soil pH. The study results indicate that conservation and sustainable management of forests constitute an effective way to mitigate the N 2 O-N emissions from the soil. Given the non-zero emission from the forest soils, we postulate a review of the algorithms employed for the approximation of the regional N 2 O-N emissions to properly reflect the impact of afforestation on the regional N 2 O-N emission. [ABSTRACT FROM AUTHOR]

Highlights • Slope stability was analysed after 8 years of plantation. • The root system of plantation can improve the stability of slope compared with bare land. • The R. pseudoacacia roots provided additional cohesion more than other plant did. • Our results provide some insight into a pre-requisite to control slope stability in unstable regions. Abstract Vegetation is widely used for reinforcing slopes, and thus controlling shallow landslides, because plant root systems can increase soil shear strength by anchoring soil layers and modifying hydrological characteristics. However, limited information is available regarding the vertical variation of soil reinforcement by roots at the slope scale, and how slope stability is influenced, especially in plantation areas. In this paper we examine the biomechanical effects on slope stability of the roots of Populus tomentosa, Robinia pseudoacacia and Olea europaea in a geohazard-prone region in China. Root density, variation in root area ratio (RAR) with depth, root tensile strength and root peak tensile force are measured, along with calculating the contribution of root cohesion to the factor of safety. The Wu-Waldron model and fiber bundle model are used to estimate static stress and dynamic stress adherence of plant roots to soil during debris flows and landslides, and a two-dimensional finite element model is used to calculate the increase in the factor of safety caused by additional root cohesion. The results show that RAR is higher for P. tomentosa than for R. pseudoacacia and O. europaea. The vertical soil profile of R. pseudoacacia roots has the highest soil water content (7.06%). The additional cohesion provided by R. pseudoacacia roots (10.35–15.12 kPa) is greater than that provided by P. tomentosa roots (6.19–10.26 kPa) and O. europaea roots (2.31–5.06 kPa). The stable area is also larger on a slope planted with R. pseudoacacia compared with the other two species. Young growth roots (8 years) are shown to affect the distribution of soil water and are limited by soil water in the semi-humid region. R. pseudoacacia roots provide significant additional cohesion by both static and dynamic stress for slope stability. This study aims to increase current understanding of the biomechanical properties of plantation species roots and their efficacy in soil reinforcement. [ABSTRACT FROM AUTHOR]

Highlights • The 4 per 1000 target is equivalent to 3.4 GtC per year over 0–40 cm soil depth. • Soil and forest C sequestration could help early anthropogenic CO2 emissions offset. • Improved agronomic practices result in SOC increases that can exceed 0.4% per year. • A 0.4% top soil C increase can lead to yearly grain yield increases (average: 1.3%). • SOC sequestration requires nutrients; from N biofixation or fertilizer recycling. Abstract At the 21st session of the United Nations Framework Convention on Climate Change (UNFCCC, COP21), a voluntary action plan, the '4 per 1000 Initiative: Soils for Food Security and Climate' was proposed under the Agenda for Action. The Initiative underlines the role of soil organic matter (SOM) in addressing the three-fold challenge of food and nutritional security, adaptation to climate change and mitigation of human-induced greenhouse gases (GHGs) emissions. It sets an ambitious aspirational target of a 4 per 1000 (i.e. 0.4%) rate of annual increase in global soil organic carbon (SOC) stocks, with a focus on agricultural lands where farmers would ensure the carbon stewardship of soils, like they manage day-to-day multipurpose production systems in a changing environment. In this paper, the opportunities and challenges for the 4 per 1000 initiative are discussed. We show that the 4 per 1000 target, calculated relative to global top soil SOC stocks, is consistent with literature estimates of the technical potential for SOC sequestration, though the achievable potential is likely to be substantially lower given socio-economic constraints. We calculate that land-based negative emissions from additional SOC sequestration could significantly contribute to reducing the anthropogenic CO 2 equivalent emission gap identified from Nationally Determined Contributions pledged by countries to stabilize global warming levels below 2 °C or even 1.5 °C under the Paris agreement on climate. The 4 per 1000 target could be implemented by taking into account differentiated SOC stock baselines, reversing the current trend of huge soil CO 2 losses, e.g. from agriculture encroaching peatland soils. We further discuss the potential benefits of SOC stewardship for both degraded and healthy soils along contrasting spatial scales (field, farm, landscape and country) and temporal (year to century) horizons. Last, we present some of the implications relative to non-CO 2 GHGs emissions, water and nutrients use as well as co-benefits for crop yields and climate change adaptation. We underline the considerable challenges associated with the non-permanence of SOC stocks and show how the rates of adoption and the duration of improved soil management practices could alter the global impacts of practices under the 4 per 1000 initiative. We conclude that the 4 per 1000 initiative has potential to support multiple sustainable development goals (SDGs) of the 2030 Agenda. It can be regarded as no-regret since increasing SOC in agricultural soils will contribute to food security benefits that will enhance resilience to climate change. However, social, economic and environmental safeguards will be needed to ensure an equitable and sustainable implementation of the 4 per 1000 target. [ABSTRACT FROM AUTHOR]

Highlights • Soil pores between 10 and 100 μm support microbial activity on aggregate exterior. • Interior aggregate microbial density is not affected by interior pore structure. • X-ray micro-CT plus SEM can delineate soil pore structure and microbial distribution. • Non-destructive plus traditional measurements help elucidate aggregate protection of SOC. Abstract Limitations of traditional measurement methods have impeded progress in understanding the role of soil aggregation in protecting soil organic carbon (SOC) from decomposition by soil microbes living in pore spaces. In this paper, we used the Scanning Electronic Microscope (SEM) and X-ray micro Computed Tomography (micro-CT) to study the relationships of the aggregate pore structure and microbial distribution in the interior and exterior of soil aggregates, and thereby gained an insight into protection of carbon within macroaggregates of an undisturbed Mollisol in northeastern China. There were close relationships between soil pore structure and distribution of soil microbes and soil organic carbon (SOC), but they were different on the exterior and interior of soil aggregate. On the exterior of macroaggregates, there were negative relationships between soil porosities, the number of pores and SOC, especially for soil pores in the 10–30 μm and 30–100 μm classes, indicating these two pore sizes are unlikely to help sequester C. In contrast, there was a positive correlation between soil pores > 100 μm and SOC. Furthermore, soil pore structure had no impact on soil microbial biomass and density or on SOC contents in the interior of soil aggregates. This study provides a new method by combining SEM with micro-CT technology for linking soil structure and soil microbial properties with C sequestration and SOC changes. [ABSTRACT FROM AUTHOR]

Highlights • A review of the gamma ray attenuation method in soil science is presented. • An historical overview of the technique use is showed. • Basic equations utilized to evaluate soil properties are demonstrated. • Applications of the technique to measure soil properties are discussed. • Possible future research direction is covered. Abstract The gamma ray attenuation method (GAM) has been used with success in soil science since the fifties of the last century. Several soil properties can be measured directly or indirectly in a fast, non-destructive and accurate way using GAM. This review paper has as main objectives to discuss briefly the first uses of GAM in the soil sciences, to revise the main equations utilized for measuring soil properties, to show some applications to highlight the potential of the technique and to point out possible future studies with GAM. [ABSTRACT FROM AUTHOR]

Highlights • PSD can be used to quantitatively describe different soil textures. • The fractal characteristics of soil PSD between the sloping farmland and other land-use types are analyzed. • There were clear differences between the D V and D q of soil PSD in different land-use types. • The fine particles loss is important cause of coarsening and increased inhomogeneity of the sloping farmland. • The results provide a soil fractal index for the degradation of soil properties in landscapes prone to soil erosion. Abstract Soil particle composition is one of the main physical properties of soil that affects soil fertility, and the fractal dimension of soil particle size distribution (PSD) can be used to quantitatively evaluate the particle composition of different soils. The single fractal dimension of soil PSD can quantitatively characterize the roughness of the soil particle, and the multifractal dimension of soil PSD can quantitatively characterize the inhomogeneous property of soil particle composition. Sloping farmland is widely distributed in hilly areas of China that are subject to the most serious soil erosion, and the loss of soil will lead to changes in soil particle composition and soil physical properties. Previous studies have not been used to evaluate the heterogeneity of soil PSD between sloping farmland and other land use types by the multifractal method. In order to quantitatively assess the differences in soil properties between the slope land and other types of land use, this paper takes four types of land use (sloping farmland, shrub-grass sloping land, terraced farmland, and oak forestland) in the warm-temperate granite mountainous areas in eastern central China as research objects. A laser particle size analyzer and soil fractal model were applied to compare the soil PSD of different land-use types and their corresponding single fractal dimension (D v ) and generalized fractal dimension (D q ). The results showed that there were clear differences between the D V and D q of soil PSD in different land-use types. The D v of the soil PSD increased as follows: sloping farmland < level terraced land < shrub-grass sloping land < oak forestland, indicating that the soil particle composition coarseness was highest in sloping farmland and lowest in the oak forestland. The sequence of characteristic parameters of D q (capacity dimension, D 0 ; information dimension, D 1 ; and correlation dimension D 2 ) was as follows: sloping farmland < level terraced land < shrub-grass sloping land < oak forestland, indicating that the inhomogeneity of soil particle composition was the highest in sloping farmland, and lowest in oak forestland. The D v , D 0 , D 1 , and D 2 of the soil PSD were significantly positively correlated to the content of clay and silt particles, and were significantly and negatively correlated to the content of sand particles, indicating that the fewer clay particles and silt in the soil or the higher the proportion of sand, the higher the coarseness and the inhomogeneity of soil particle composition. This study showed that the soil coarseness and the inhomogeneity of the sloping farmland soil particle composition are significantly greater than those of other land-use types. The mass loss of the soil fine particles (clay and silt particles) is an important cause of coarsening and increased inhomogeneity of the sloping farmland. This study provides a soil fractal index for quantitative assessment of soil texture and the degradation of soil properties in landscapes prone to soil erosion such as sloping farmland. [ABSTRACT FROM AUTHOR]

Abstract: Tillage might be unnecessary for crop production, but no practical mechanised system can avoid field traffic, usually by wheels. Wheels can cause soil damage, but this can be limited to a small proportion of field area by restricting all heavy wheels to permanent traffic lanes. Widespread adoption of controlled traffic in Australia, and permanent raised beds in Mexico has demonstrated the effectiveness and practicability of Controlled Traffic Farming (CTF) systems in very different cropping environments. This paper considers the system impact of wheel traffic on productivity and sustainability of mechanised cropping, citing comparisons between CTF and conventional “random traffic” cropping systems where possible. Evidence of the extent and effects of wheeling on soil structure is summarised in terms of hydrology and crop performance. Soil erosion and broader environmental effects are considered briefly. Tillage and traffic effects on greenhouse gas emissions from cropping are discussed, including emissions from fuel, herbicide and fertiliser inputs. Soil emissions are considered in some detail, citing evidence from soil compaction studies, and where emissions have been monitored from wheeled and non-wheeled soil. Outcomes have been encapsulated in a spreadsheet comparison of emissions from cropping systems using tillage with random traffic, no-till with random traffic and CTF no-till. Using data from extensive grain production systems in Australia this indicates that CTF could provide a major reduction in cropping emissions. CTF can improve productivity, and all measures of sustainability; it also overcomes some important constraints to the adoption of conservation agriculture. As precise guidance becomes progressively cheaper, machine system width compatibility remains the only major impediment to a significant improvement in food security and the environmental footprint of cropping. Width compatibility is simple in principle, but complex in practice, and will occur only with the active engagement of the farm machinery industry. The paper urges ISTRO to join with regional farmer CTF groups to draw attention to this issue and provide a forum for the development of compatibility standards. [Copyright &y& Elsevier]

Abstract: Investigations on soil compaction focused mainly on effects on soil physical parameters and on plant growth. Nevertheless, a substantial number of papers deal with effects of soil compaction on soil organisms (soil fauna, soil microorganisms) and biologically driven processes in soils (e.g., macropore formation, respiration rates, N-mineralisation). In view of soil and soil functions protection, there is an essential need to identify soil compaction threshold values with respect to soil biota and soil biological processes. No such values are currently available. Thus the aim of our study was to evaluate literature on the effects of soil compaction mainly in agricultural soils on soil organisms and soil biological processes (e.g., respiration, nitrification); to identify relevant parameters which are helpful for assessing soil compaction from the soil biological point of view; and to find out whether threshold values of soil structure parameters proposed by soil physicists correspond to harmful impacts on soil organisms and biological processes in soils. Our literature review showed that due to the high variability of experimental situations and conditions in the evaluated papers, especially in papers describing field investigations, no general effect of soil compaction was found. Negative and positive effects occurred with slight compaction as well as with strong compaction. A verification of the thresholds published to date for soil compaction was not possible based on the data evaluated. However, the fact that above an effective bulk density of 1.7gcm−3, only negative effects on microbial biomass and C-mineralisation were found confirms this value, proposed by soil physicists, also from the soil biological point of view. In order to provide a scientifically meaningful data base for the assessment of soil compaction, effects on soil biodiversity, related functions and processes, we recommend considering the following site and soil properties as essentials: land use, climate, soil type, texture, bulk density; soil organic matter content; pH value; soil moisture (water content/water tension); pore volume; macroporosity and air and/or water conductivity. [Copyright &y& Elsevier]

Abstract: Rainfall simulation is a widely used method for soil erosion studies on agricultural land. Major problem of this experimental research method is the comparability between different simulators due to differences in simulated rainfall. Therefore the purpose of this study is to characterize the rainfall produced by a rainfall simulator which was widely used during the last decades. Four different calibration methods were used to assess the drop size distribution: (1) Indication Paper, (2) Plaster Micro Plot, (3) Joss–Waldvogel Disdrometer and (4) Laser Distrometer (Thies). Additionally, the latter one was used to measure drop fall velocity in combination with drop diameter. The spatial rainfall distribution pattern on the plot was measured with 100 rainfall gauges. The spatial rainfall distribution pattern clearly shows a heterogeneity, which is caused by the used nozzle configuration. Considerable differences in drop-size distribution can be observed depending on the used measurement technique. Laser Disdrometer and Plaster Micro Plot cover the whole produced drop size spectrum ranging from <0.5mm to >3.0mm, whereas Indication Paper as well as the Joss–Waldvogel Disdrometer primarily show drops smaller than 2.0mm. Characterisation of rainfall is therefore strongly dependent on the used method and if different methods are used, may lead to contradictory results. The volume drop size distribution reflected by the Laser Distrometer is very similar to that one produced by rain with an intensity of 40mmh−1. Nevertheless, with maximum velocities above 10ms−1 small drops are by far too fast and large drops with velocities dominantly below 5ms−1 are too slow compared to natural rainfall. As an overall result, the simulator can be characterised as suitable for runoff and infiltration measurements, but with constraints due to the low reproducibility of the spatial rain distribution. As a consequence of the produced drop spectrum and fall velocity the erosion quantities may be underestimated systematically. For this, methodological development has to be focussed on homogeneous spatial rainfall distributions and on increasing the amount of large drops with higher fall velocities. [Copyright &y& Elsevier]

Abstract: Improved agricultural productivity using conservation farming (CF) systems based on non-inversion tillage methods, have predominantly originated from farming systems in sub-humid to humid regions where water is not a key limiting factor for crop growth. This paper presents evidence of increased yields and improved water productivity using conservation farming in semi-arid and dry sub-humid locations in Ethiopia, Kenya, Tanzania and Zambia. Results are based on on-farm farmer and research managed experiments during the period 1999–2003. Grain yield of maize (Zea mays L.) and tef (Eragrostis Tef (Zucc)) from conventional (inversion) tillage are compared with CF with and without fertilizer. Rain water productivity (WPrain) is assessed for the locations, treatments and seasons. Results indicate significantly higher yields (p <0.05) for CF+ fertilizer treatments over conventional treatments in most locations, increasing from 1.2 to 2tha−1 with 20–120% for maize. For tef in Ethiopian locations, the yield gains nearly doubled from 0.5–0.7 to 1.1tha−1 for “best bet” CF+ fertilizer. WPrain improved for CF+ fertilizer treatments with WP gains of 4500–6500m3 rainwater per t maize grain yield in the lower yield range from 0 to 2.5tha−1. This is explained by the large current unproductive water losses in the on-farm water balance. There was a tendency of improved WPrain in drier locations, which can be explained by the water harvesting effect obtained in the CF treatments. The experiences from East and Southern Africa presented in this paper indicate that for smallholder farmers in savannah agro-ecosystems, conservation farming first and foremost constitutes a water harvesting strategy. It is thus a non-inversion tillage strategy for in situ moisture conservation, rather than solely aimed at minimum tillage with mulch cover. Challenges for the future adoption of CF in sub-Saharan Africa include how to improve farmer awareness of CF benefits, and how to efficiently incorporate green manure/cover crops and manage weeds. [Copyright &y& Elsevier]

Abstract: Soil tillage and its interaction with climate change are widely discussed as a measure fostering carbon sequestration. To determine possible carbon sinks in agriculture, it is necessary to study carbon sequestration potentials in relation to agricultural management. The aim of this paper is to evaluate the soil carbon sequestration potential of a site in north-eastern Switzerland under different tillage systems. The study was performed as a long-term (19-year) trial on an Orthic Luvisol (sandy loam) with a mean annual air temperature of 8.4°C and a long-term precipitation mean of 1183mm. The soil organic carbon (SOC) concentration was determined five times during the study period, with the paper focussing mainly on the year 2006. The main objective was to quantify the influence of mouldboard ploughing (PL), shallow tillage (ST), no-tillage (NT) practices, and grassland (GL) on soil organic carbon content, the latter''s different fractions (labile, intermediate, and stable), and its distribution by depth. In calculating the SOC content of the whole soil profile, we included a correction factor accounting for variations in bulk density (equivalent soil mass). The total SOC stock at a depth of 0–40cm was 65MgCha−1, and although higher under GL, did not differ significantly between PL, ST, and NT. SOC concentrations per soil layer were significantly greater for NT and ST (0–10cm) than for PL, which had greater SOC concentrations than NT and ST at 20–30cm depth. Both SOC concentrations and stocks (0–20cm) were largest under GL. In all treatments, most of the carbon was found in the intermediate carbon fraction. There was no significant difference in any of the three SOC fractions between NT and ST, although there was between ST and PL. A sharp decrease in C-concentrations was observed in the first 7 years after the transition from grassland to arable land, with a new equilibrium of the carbon concentration in the 0–40cm layer being reached 12 years later, with no significant difference between the tillage treatments. Overall, the results indicate that effects of tillage on soil carbon are small in moist, cold-temperate soils, challenging conversion into no-till as a measure for sequestering C. [Copyright &y& Elsevier]

Abstract: Efficient mechanisation is a major factor underlying the high productivity and low cost of most Australian crop production systems. Efficiency has generally been associated with greater work rates, achieved by using equipment of greater power and weight. This trend has continued until very recently, despite a reduction in tillage for weed control. Scientists have warned of erosion and soil structural degradation caused by tillage and traffic, but tillage, rather than field traffic was seen as the major problem, and reduction of tillage as the solution. Reduced tillage has provided major benefits, but adoption has occurred slowly and sustained zero tillage is still rare, except in controlled traffic farming systems. The first part of this paper presents research evidence of the direct cost, practical impact and long-term effects of wheel traffic on cropped soil. Direct cost is associated with the energy requirements of disturbing wheeled soil. Practical impact occurs as a result of the lost opportunities and additional operations associated with wheel ruts. Long-term productivity and environmental impact occur because wheel traffic reduces plant available water and increases runoff and erosion. In controlled traffic all equipment wheels are restricted to compacted permanent traffic lanes, so that soil in the crop beds and traffic lanes can be managed respectively for optimum cropping and optimum trafficability. Controlled traffic farming recognizes the symbiosis between controlled traffic and zero tillage in providing opportunities for more productive and sustainable farming of soil uncompromised by wheel effects. The beneficial effects of controlled traffic have been demonstrated in widely different soils and mechanisation systems (e.g. Australia and China), and it has been vigorously advocated in both the USA and Europe, but large-scale adoption has been rare. The second part of this paper discusses cropping system response to controlled traffic farming, and the program which led to large-scale adoption in Australia. This happened first in extensive grain production, but adoption has since occurred in many Australian farming systems, supported by the availability of high-precision field guidance systems and a greater range of compatible equipment. Controlled traffic farming reduces soil degradation and the energy requirements of cropping. It is also more productive, and its practicality and economic viability have been clearly demonstrated in enthusiastic farmer adoption, and the formation of an Australian Controlled Traffic Farming Association. [Copyright &y& Elsevier]

Abstract: The paper deals with the quantitative characterization of small-scale random roughness on agricultural bare soils which controls many of the hydraulic and erosion processes on the field scale. More precisely, our aim is to analyse the adequacy of a stereo photogrammetry system to obtain accurate estimation of this random roughness by means of statistical parameters and to detect soil surface roughness changes due to rainfall. The work presented in this paper is based on a set of digital elevation models (DEMs) of actual agricultural bare soils obtained by stereo photogrammetry. The considered field surfaces correspond to various tillage practices (conventional seedbed, chisel and conventional ploughing) and are watered by simulated rainfalls in order to get various patterns. The stereo photogrammetry process is carefully analysed; the effects of the correlation window size are taken into consideration in order to propose optimized DEM reconstructions. Classical roughness parameters such as root mean square of the heights, correlation length and tortuosity are estimated on the DEMs of the database and results concerning the effect of the DEM size on the obtained accuracy are presented for each roughness parameter. The tortuosity comes out to be a relevant roughness estimator able to quantify the roughness evolution during rain, even with important degradation of the soil. Finally to study the evolution of roughness with rainfall thoroughly, we introduced two positional tortuosity values computed independently over the areas of rigdes and interrows of the DEM. The obtained values clearly show that the rainfalls do not decrease homogeneously the soil small-scale roughness: the interrows areas are much more smoothed by the rain than the ridges areas do. The study presented shows that stereo photogrammetry provide DEMs that enable accurate studies of the geometrical properties of soils that can definitely be of use for hydraulic and erosion studies. [Copyright &y& Elsevier]

Abstract: Ephemeral gully erosion is an important soil erosion process on the Inner-Mongolia Plateau in North China, and although its damage is very intense, little research on the area has been published. In this paper, a global positioning system (GPS) is used to measure the morphology of ephemeral gullies in a small catchment, the Inner-Mongolia Autonomous Region. First, this paper presents the characteristics of ephemeral gullies and soil loss due to ephemeral gully erosion. The network of ephemeral gullies takes on the shapes of tree branches, and there are 16 hole-ephemeral gullies in the middle of the ephemeral gullies. An average gully length of about 19.6mha−1 and an average soil loss of 8.8m3 ha−1 due to ephemeral gully erosion were measured. Second, soil erosion influences crop production in cropland and combinations of vegetation in fallow. The difference between vegetation in the middle of ephemeral gullies and in other places is very obvious. Third, this paper discusses hole-ephemeral gullies that are holes locating in the middle of ephemeral gullies whose widths and depths are more than 0.5m () for the first time. The relationship between local hill slope gradient S (mm−1) and upslope contributing area A (ha) can be expressed as S =0.064A −0.375 and may be a key indicator for determining the position of existing hole-ephemeral gully heads and for predicting where hole-ephemeral gullies could form in the small watershed on the Inner-Mongolian Plateau. [Copyright &y& Elsevier]

Abstract: Measurement of the in situ cone penetration resistance (PR) is the only easily available and direct measurement of the actual in situ soil strength. Soil strength varies frequently due to changes in soil moisture conditions, which affects trafficability of soils quite unexpectedly. To generalize the information obtained from penetration resistance data, two of the authors [Hartge, K.H., Bachmann, J., 2004. In situ evaluation of the soil consolidation state by using penetration resistance data. J. Plant Nutr. Soil Sci. 167, 304–308] proposed a simple site specific analysis for the interpretation of the depth-dependent penetration resistance characteristics. In this paper, results of comparison of PR data with independently measured vane shear (VS) data were used to assure the plausibility of this approach for deeply developed non-layered soil. The focus of this paper is to prove the validity of the underlying basic assumption that the horizontal stress component begin to dominate the vertically measured penetration resistance and can further be used to characterize the intensity of agricultural landuse systems with respect to the compaction status of the soil. The procedure applied consists in assigning PR-values to the principal stress (σ x) as a function of depth normalized by the PR-value of the greatest accessible depth, which is limited by the length of the probe. PR data were measured on three pasture sites after clearing the secondary virgin forest 12, 50 and 150 years ago. Results show that the duration of cattle grazing could significantly be detected by using either PR data or VS data. These results confirm the general feasibility of this simple experimental approach to evaluate the compaction state of soil from easy obtainable PR data. [Copyright &y& Elsevier]

Crop–pasture rotations (CPR) are unusual around the world but have been the predominant cropping system in Uruguay since the 1960s. Uruguay has a temperate sub-humid climate, 80% of its landscape (16 Mha) is climax grasslands C3 and C4 species. Beef, wool, and dairy are the main commodities. Crops occupy a portion of the remaining 20% land area, primarily on Argiudolls and Vertisols, rotated with seeded grass and legume pastures. Continuous cropping (CC) with conventional tillage (CT) has proven unsustainable due to decreased soil productivity. Seeded pasture periods increased soil productivity. CPR adoption created less variable inter-annual economic results, but soil degradation remained a major concern during the crop cycle using CT. Farmers and technicians became interested in no-till (NT) to reduce erosion and production cost. Currently, approximately 52% of crop producing farms and 25% of dairy farms have adopted NT. This paper synthesizes research results (mainly from long-term experiments) contrasting CC versus CPR with CT (1960–1990) and NT (from 1990). Soil erosion was reduced more than six times with NT in CC, and almost three times in CPR compared with CC using CT; but combining the use of CPR and NT resulted in the same low erosion rate as under natural pasture. The transition from CT to NT is not always easy. The time between herbicide application to pasture and planting of the first crop of the rotation crop cycle with NT is a critical transition factor to optimize N and water availability, and soil tilth. Chiseling or paraplowing can alleviate plow-pans inherited by NT from previous CT; but higher soil strength at the soil surface under NT contributes to better forage utilization under grazing. Soil organic carbon (SOC) content in CC decreased with CT, and was maintained with NT only if grain was harvested. In CC systems with harvested forage, SOC decreased even with NT. CPR with NT maintained or increased the original SOC content. The paper concludes with a discussion on the relative sustainability of CC versus CPR with NT. Both are sustainable from the soil quality and productivity standpoints. But compared with CC, CPR is a more economically and climatically buffered system, due to higher diversity. Also, CPR systems are more environmentally sustainable since fuel and agrochemicals usage is reduced approximately 50%. [Copyright &y& Elsevier]

The papers in this special issue present results of the European Union (EU) concerted action “Experiences with the impact of subsoil compaction on soil crop growth and environment and ways to prevent subsoil compaction”. The results and conclusions of earlier research on subsoil compaction are memorized and it is emphasized that the conclusions are still sound: high axle load traffic on soils of high moisture content causes deep and persistent subsoil compaction. The concerted action on subsoil compaction in the EU and an almost identical concerted action on subsoil compaction in central and eastern Europe are briefly introduced. This special issue presents a selection of papers of the concluding workshop of the concerted action on subsoil compaction in the EU. It includes three papers on modeling the impact of subsoil compaction on crop growth, water availability to plants and environmental aspects; three papers on modeling of subsoil compaction by heavy machinery; four papers on measurement of soil mechanical and physical properties in relation to subsoil compaction and four papers on methods to determine the risk of subsoil compaction and to identify prevention strategies. The trends in agriculture in relation to subsoil compaction are discussed. A positive trend is that policy makers in the EU and worldwide recognize soil as a vital and largely non-renewable resource increasingly under pressure. A negative trend is that wheel loads in agriculture are still increasing causing severe damage to subsoils. The conclusion is that European subsoils are more threatened than ever in history. Manufactures, agricultural engineers and soil scientists should collaborate and research should be initiated to solve this problem and find solutions. Subsoil compaction should be made recognized by all people involved from farmer to policy maker. Therefore an assessment of the existence and seriousness of subsoil compaction throughout Europe should be initiated. [Copyright &y& Elsevier]

Various soil indicators can be chosen for soil health assessment. The important indicators representing overall soil health need to be carefully selected to reduce the cost and time involved in sampling and testing, which can be achieved by establishing a minimum data set (MDS). The objective of this paper was to identify the indicators that are important for assessing soil health in northeast Mississippi and establish an MDS. Values for chemical, physical and biological indicators obtained from three treatments (no-fertilized control, no-organic fertilizer and poultry litter) in five different field experiments were used to screen MDS. The methodology followed a combination of principal component analysis (PCA), cluster analysis and expert's opinion (EO) method. Results showed that the correlation between the MDS and total data set (TDS) was high (R2 =0.94). The chosen MDS included four chemical indicators (pH, organic carbon, total nitrogen and Mehlich-3 phosphorus), three physical indicators (bulk density, water-stable aggregate stability, available water capacity), and two soil biological indicators (dehydrogenase activity, heterotrophic plate count). When the selected chemical MDS was applied to all treatments of the five experiments, the MDS and TDS data fitted well (R2 =0.81), indicating that the soil indicators included in the MDS were the most important for soil health in this study. In conclusion, an MDS for soil health assessment was established for the experiments in northeast Mississippi. The results can provide fundamental guidance for researchers, growers, and stakeholders to evaluate soil health and optimize soil management. • Minimum data set (MDS) representing soil health was determined in Mississippi. • The selected nine indicators are enough to assess overall soil health status. • Poultry litter (PL) is more effective in improving soil health than cover crops under no-till. • Soil health differences were accurately depicted by chemical MDS under PL application. [ABSTRACT FROM AUTHOR]

This paper aims to create supervised classification models of the soil water potential based on hyperspectral data of Polish mineral soils (104 samples) from the Visible and Near-InfraRed (VNIR) and Short-Wave InfraRed (SWIR) range and selected soil physico-chemical properties, such as organic carbon content, or fraction of sand, silt, and clay. Soil water content regression models were also created, which took into account the soil water potential ranging from 98.1 J∙m-3 to 1554249 J∙m-3. Several machine learning algorithms were tested to create models of the soil water potential and the soil water content. It occurred that reflectance characteristics of the soils exhibit a high correlation with soil moisture. Gaussian Processes (GP) model was most suitable for the estimation of the soil water content, regardless if input data contained pure reflectance spectra (R=0.82), or if they were supplemented with selected physico-chemical soil properties and soil water potential (R=0.94). No improvement of the models' accuracies was noticed when only the selected soil physical and chemical properties were included as inputs, which suggested that the soil surface spectral data contained in themselves information, which strictly belonged to specific soil physico-chemical properties. Among classification models of the soil water potential, the LOG method had the highest percentage of correctly classified cases. More than 65% of all cases were correctly classified if the spectral data, moisture, and other properties of the tested material were included, and more than 54% when the independent variables did not include soil moisture. The majority of misclassified cases were by one class. The greatest accuracy was achieved for the two extreme values of pF (0 and 4.2), while the worst one was for pF2.2 and pF2.7. • Hyperspectral imaging is useful for the investigation of soil retention properties. • Spectral reflectance of the soils exhibits a high correlation, up to R= 0.94, with soil moisture. • Soil water potential (SWP) models classified correctly up to 65% of cases. • The best method for SWP classification is the Logistic Linear Regression (LOG). [ABSTRACT FROM AUTHOR]

Plant roots can increase soil shearing resistance directly by mechanical reinforcing. The 2D crack pattern of the surface soil near the plant were observed experimentally, and it was found that the soil cracking near the plant roots was inhibited, which may be due to the influence of the plant roots. This paper focuses on the mechanical reinforcement of soil by plant roots and investigates the development rule and formation mechanism of desiccation cracking under the influence of plant roots. A numerical model describing the process of desiccation cracking of soils in the presence of root systems, which is based on a lattice of Hooke springs model, was combined with a non-stationary random field characterized by a trend term and a random fluctuation term. The root density distribution function was introduced to describe the root distribution, and an exponential function of critical strain and root density was constructed to obtain the trend of critical strain distribution of the root systems (the root systems of a single plant). The random fluctuation term was generated by the conditional simulation technique. Minkowski densities (i.e., area density, length density and Euler number density) were adopted to quantify the crack patterns. Parameters of the model were calibrated and verified by the field experimental results, and its precision was evaluated. The effect of most input parameters (include the new parameters maximum critical strain value h c and the lateral distribution radius of RDDF r m) on the model output was analyzed. The results show that in the validation process the coefficients of determination R 2 for the Minkowski densities is between 0.749 and 0.948. Root mean square error is between 0.000 2–0.120 9. BIAS is between 0.049 5–0.139 0, and the consistency index is between 0.908 and 0.987. The model is effective in predicting the formation and development of cracks in farmland soils under the influence of the root systems. The model produces the dynamic development of the desiccation cracking network of farmland soils under the influence of the root systems. The simulation results provide ample indication of the reinforcing effect of the root systems on the soil and the limiting effect of the root systems on desiccation cracking. • The critical strain non-stationary random field of soil with roots was reproduced. • A model of soil desiccation cracking under the influence of root systems was developed. • Field experiments were conducted to validate the reliability of the proposed model. • Numerical simulations and model sensitivity analysis were conducted. [ABSTRACT FROM AUTHOR]

The intensification of arable agriculture has resulted in an increase in vehicle wheel load and the intensity of field operations, which has increased the risk and incidence of degradation in physical properties of the uncultivated subsoil layer. Biopores generated by the long-term, repeated use of specific cover crops within an arable rotation has been suggested as an approach to improve subsoil physical properties. Therefore, this paper aimed to determine the impact of long-term repeated cover cropping and the interaction of rotation treatments with different cultivation approaches on subsoil physical properties. Data was collected at the NIAB 'Sustainable Trial for Arable Rotations' long-term, rotation and cultivation field experiment established in 2006. Rotation treatments comprised a brassica cover crop alternated annually with winter wheat (ALTCC) compared to continuous winter wheat (CWW). Cultivation treatments comprised PLOUGH (250 mm depth), and non-inversion cultivation at 250 mm (DEEP) and 100 mm (SHALLOW) depths. Penetration resistance and volumetric soil moisture were collected at bi-monthly intervals during the 2018/19 growing season. Undisturbed soil cores were collected for laboratory analyses of soil water retention, water stable aggregates, root morphology digital scanning and biomass, and X-ray computed tomography (CT). Results showed that treatment ALTCC combined with SHALLOW, resulted in lower penetration resistance and increased moisture in the subsoil. This increased subsoil moisture persisted later into the season compared to the control. SHALLOW increased subsoil water retention, improved subsoil root morphology and increased subsoil porosity. Benefits from treatment ALTCC were not observed where combined with higher intensity, deeper cultivation. Overall, the combination of treatments ALTCC with SHALLOW, produced significant benefits to subsoil physical properties. • Repeated cover cropping with low intensity cultivation improved subsoil properties. • 100 mm non-inversion cultivation improved root morphology. • Benefits of repeated cover cropping negated by high intensity, deeper cultivation. [ABSTRACT FROM AUTHOR]

Complete and coherent soil profile information is important for studying soil morphological characteristics, vertical variation patterns of soil physicochemical properties, and identifying soil types. However, traditional soil survey methods use a limited number of discrete sample points at different depths as a data source to explore the correlation between soil depth and soil properties. Due to the variability of soil properties at vertical depth, there is a strong uncertainty in the conclusions drawn from the limited sample points. With the development of near-Earth remote sensing technology, the near-Earth hyperspectral imaging system can acquire hyperspectral images of soil profiles and characterize the fine texture differences and spectral variations of soil with continuous spectral curves and images, which is useful for inversion of soil properties. Soil organic carbon (SOC) is one of the important physicochemical properties to identify the genetic horizon, therefore, this paper explored the ability of visible–near-infrared (Vis-NIR) hyperspectral imaging spectroscopy to predict SOC in soil monoliths. The dataset contained five soil monoliths retrieved from the upper Yellow River, China. A random forest (RF) model was developed for predicting organic carbon, and the organic carbon content in the genetic horizon was used to establish a depth function to obtain the continuous content variation with the depth. These differences with and without depth function modeling, and the effect of three equal-spacing sampling schemes (1, 5, and 10 cm) on the depth function and the accuracy differences in five spectral statistics of the maximum (max), mean, median, mode, and minimum (min) within the image region of interest (ROI) were compared. The results indicated that (1) the depth function under the 1-cm sampling scheme predicted organic carbon the best, (2) the mode of the spectra within the ROI could yield a comparable or even a higher accuracy than that obtained with the mean, and (3) imaging spectroscopy could be used to visualize the distribution of organic carbon on soil profiles with relatively uniform morphology. These results indicated that imaging spectroscopy could be used for predicting organic carbon in undisturbed soil profiles. • Hyperspectral imaging was used to map soil organic carbon in soil profiles. • The depth function yielded optimal accuracy for predicting organic carbon, with R2 of 0.92 and RMSE of 0.73 g/kg. • The depth function under the 1-cm sampling scheme predicted organic carbon the best. • The mode of the spectra within the ROI could yield higher accuracy. [ABSTRACT FROM AUTHOR]

• A novel equipment was developed to evaluate in-situ soil root bonding strength. • The equipment is also capable of recording ambient time and condition data. • Four different vegetation species were investigated and compared. • Soil phase properties significantly effect on in-situ soil root bonding strength. • Ranunculus acris showed the highest uproot strength among the investigated species. Research shows that construction of seawalls controls soil erosion along the coastal lines but scouring at the bottom deteriorates water clarity and causes algae growth. An environmentally friendly, sustainable solution such as controlled cultivation of plants has potential to perform better in such cases. Studies already show that plant roots' tensile strength has direct influence on soil shear strength. However, the tensile strength tests performed in the lab cannot represent the exact ambient condition. This paper describes the development of a novel, effortless approach to carry and assemble an In-situ Smart Testing Apparatus (ISTA) that evaluates Soil Root Bonding Strength (SRBS) by pulling vegetation with roots out of the soil and measures and records the pulling strength along with the vertical displacement that takes place during the uprooting process. Another aspect of the equipment includes in-situ tensile testing capability of plant roots. In addition to those, the controlling program of the equipment stores other parameters like test date and time along with the latitude, longitude, humidity, and temperature of test location in the same file. This paper includes the initial study conducted on four different naturally grown species (Ranunculus acris , Stenotaphrum secundatum , Paspalum urvillei , and Rhynchospora mixta) using the developed ISTA near a pond at the Agricultural Department at Louisiana Tech University. Different forces required to uproot the investigated plants indicate that SRBS could be stimulated by the types and arrangements of roots inside subsoil. The obtained results reveals a strong effect of plant types and soil phase properties (soil bulk density, moisture content, air content, and pore space) on SRBS in the form of pulling force and displacement. The ISTA, thus, has significant potential to measure, store and distribute the real time data that can aid relevant professionals in preventing soil erosion and ensuring sustainable coastal ecosystems. [ABSTRACT FROM AUTHOR]