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1.
Visible near-infrared (vis-NIR) and portable X-ray fluorescence (pXRF) spectrometers have been increasingly utilized for predicting soil properties worldwide. However, only a few studies have focused on splitting the predictive models by horizons to evaluate prediction performance and systematically compare prediction performance for A, B, and combined A+B horizons. Therefore, we investigated the performance of pXRF and vis-NIR spectra, as individual or combined, for predicting the clay, silt, sand, total carbon (TC), and pH of soils developed in loess, and compared their prediction performance for A, B, and A+B horizons. Soil samples (176 in A horizon and 172 in B horizon) were taken from Mollisols and Alfisols in 136 pedons in Wisconsin, USA and analyzed for clay, silt, sand, pH, and TC. The pXRF and vis-NIR spectrometers were used to measure the pXRF and vis-NIR soil spectra. Data were separated into calibration (n=244, 70%) and validation (n=104, 30%) datasets. The Savitzky-Golay filter was applied to preprocess the pXRF and vis-NIR spectra, and the first 10 principal components (PCs) were selected through principal component analysis (PCA). Five types of predictor, i.e., PCs from vis-NIR spectra, pXRF of beams at 0-40 and 0-10 keV (XRF40 and XRF10, respectively) spectra, combined XRF40 and XRF10 (XRF40+XRF10) spectra, and combined XRF40, XRF10, and vis-NIR (XRF40+XRF10+vis-NIR) spectra, were compared for predicting soil properties using a machine learning algorithm (Cubist model). A multiple linear regression (MLR) model was applied to predict clay, silt, sand, pH, and TC using pXRF elements. The results suggested that pXRF spectra had better prediction performance for clay, silt, and sand, whereas vis-NIR spectra produced better TC and pH predictions. The best prediction performance for sand (R2=0.97), silt (R2=0.95), and clay (R2=0.84) was achieved using vis-NIR+XRF40+XRF10 spectra in B horizon, whereas the best prediction performance for TC (R2=0.93) and pH (R2=0.79) was achieved using vis-NIR+XRF40+XRF10 spectra in A+B horizon. For all soil properties, the best MLR model had a lower prediction accuracy than the Cubist model. It was concluded that pXRF and vis-NIR spectra can be successfully applied for predicting clay, silt, sand, pH, and TC with high accuracy for soils developed in loess, and that spectral models should be developed for different horizons to achieve high prediction accuracy.  相似文献   

2.
Many factors can influence the results obtained by portable X-ray fluorescence analysis (pXRF). The effect of soil organic matter on pXRF results is not satisfactory understood. Thus, we conducted this study to verify the effect of organic matter removal on oxide determination by pXRF in Oxisols. To obtain soil material with different organic matter contents and maintaining the same elemental composition from soil minerals, six contrasting Oxisols were heated in a muffle furnace for 30 min at the following temperatures (°C): 100; 200; 300; 400; 500 and 600. After heating, the soil samples were scanned using a pXRF Bruker® S1 Titan LE model (Dual Soil mode) for 60 s and the contents of SiO2, Al2O3, Fe2O3, TiO2, P2O5, and MnO were recorded. The soil organic matter presence underestimated the pXRF results for lightest oxides (Si and Al) compared to heaviest oxides (Fe, Ti, and Mn). These oxides are important for tropical soils classification and for many soil-related studies and pXRF technology has been a useful tool for soil chemical characterization. Our findings contribute to more suitable use of pXRF highlighting the possible effect of organic matter.  相似文献   

3.
The role of mounds of the fungus-growing termite Macrotermes bellicosus (Smeathman) in nutrient recycling in a highly weathered and nutrient-depleted tropical red earth (Ultisol) of the Nigerian savanna was examined by measuring stored amounts of selected nutrients and estimating their rates of turnover via the mounds. A study plot (4?ha) with a representative termite population density (1.5?mounds?ha?1) and size (3.7?±?0.4?m in height, 2.4?±?0.2?m in basal diameter) of M. bellicosus mounds was selected. The mounds were found to contain soil mass of 9249?±?2371?kg?ha?1, composed of 7502?±?1934?kg?ha?1 of mound wall and 1747?±?440?kg?ha?1 of nest body. Significant nutrient enrichment, compared to the neighboring topmost soil (Ap1 horizon: 0–16?cm), was observed in the nest body for total nitrogen (N) and exchangeable calcium (Ca), magnesium (Mg) and potassium (K), and in the mound wall for exchangeable K only. In contrast, available (Bray-1) phosphorus (P) content was found to be lower in both the mound wall and the nest body than in the adjacent topmost soil horizon. Consequently, the mounds formed by M. bellicosus contained 1.71?±?0.62?kg?ha?1 of total N, 0.004?±?0.003?kg?ha?1 of available P, 3.23?±?0.81?kg?ha?1 of exchangeable Ca, 1.11?±?0.22?kg?ha?1 of exchangeable Mg and 0.79?±?0.21?kg?ha?1 of exchangeable K. However, with the exception of exchangeable K (1.2%), these nutrients amounted to less than 0.5% of those found in the topmost soil horizon. The soil nutrient turnover rate via M. bellicosus mounds was indeed limited, being estimated at 1.72?kg?ha?1 for organic carbon (C), 0.15?kg?ha?1 for total N, 0.0004?kg?ha?1 for available P, 0.15?kg?ha?1 for exchangeable Ca, 0.05?kg?ha?1 for exchangeable Mg, and 0.06?kg?ha?1 for exchangeable K per annum. These findings suggest that the mounds of M. bellicosus, while being enriched with some nutrients to create hot spots of soil nutrients in the vicinity of the mounds, are not a significant reservoir of soil nutrients and are therefore of minor importance for nutrient cycling at the ecosystem scale in the tropical savanna.  相似文献   

4.
The aim of the current study was to identify major soil and leaf factors accounting for low natural rubber (NR, Hevea brasiliensis) productivity on tropical acid Acrisols in Vietnam. Twenty NR plots were measured with NR productivity, leaf factors (N, P, K, Ca, Mg, Mn, Cu, Fe, and Zn), soil factors (pH, particle size distribution, total C, N, P, K, exchangeable K, Ca, Mg, Al, Mn, Fe, Zn, available P). Cluster analysis showed that NR productivity could be separated into three clusters with low (23.2), medium (38.2), and high (61.3 g tree?1 harvest?1) yield. High-yield cluster had higher leaf P concentration and soil pH, while low-yield cluster had higher leaf Mn, soil exchangeable Al, and Mn concentration. Simple and multiple linear regression analysis applied with backward elimination procedure suggested that leaf and soil toxic concentration may be responsible for low NR productivity in the study soil.  相似文献   

5.
The plant minimal exchangeable K (EPl,min) defines the lower accessible limit of the most available pool of soil K to plants. It is also an index of long‐term K reserve in soils. However, its estimation by the classical method of exhaustion cropping is laborious. This study aimed at comparing EPl,min values obtained by the exhaustion cropping method with EPl,min values estimated by an alternative approach based on the cationic exchange capacity (CEC) of the infinitely high selective sites for K (i.e., always saturated with K) in the K‐Ca exchange (EK‐Ca,min). A set of 45 soil samples, corresponding to the various fertilization K treatments of 15 long‐term K fertilization trials, was used in this study. The selected soil samples presented a wide range of texture, CEC, and exchangeable K. The plant minimal exchangeable K was found more or less independent of the K treatment, whereas EK‐Ca,min increased when the soil exchangeable K content increased. The plant minimal exchangeable K was systematically lower than EK‐Ca,min, showing that EK‐Ca,min is at least partially available to the plant. Hence, EK‐Ca,min is not a surrogate of EPl,min. Conversely, the plant minimal exchangeable K was strongly, positively correlated to soil CEC (measured at soil pH; r2 = 0.90***). This soil property can consequently be used as a proxy of EPl,min.  相似文献   

6.
Purpose

Soil pollution indices are an effective tool in the computation of metal contamination in soil. They monitor soil quality and ensure future sustainability in agricultural systems. However, calculating a soil pollution index requires laboratory measurements of multiple soil heavy metals, which increases the cost and complexity of evaluating soil heavy metal pollution. Visible and near-infrared spectroscopy (VNIR, 350–2500 nm) has been widely used in predicting soil properties due to its advantages of a rapid analysis, non-destructiveness, and a low cost.

Methods

In this study, we evaluated the ability of the VNIR to predict soil heavy metals (As, Cu, Pb, Zn, and Cr) and two commonly used soil pollution indices (Nemerow integrated pollution index, NIPI; potential ecological risk index, RI). Three nonlinear machine learning techniques, including cubist regression tree (Cubist), Gaussian process regression (GPR), and support vector machine (SVM), were compared with partial least squares regression (PLSR) to determine the most suitable model for predicting the soil heavy metals and pollution indices.

Results

The results showed that the nonlinear machine learning models performed significantly better than the PLSR model in most cases. Overall, the SVM model showed a higher prediction accuracy and a stronger generalization for Zn (R2V?=?0.95, RMSEV?=?6.75 mg kg?1), Cu (R2V?=?0.95, RMSEV?=?8.04 mg kg?1), Cr (R2V?=?0.90, RMSEV?=?6.57 mg kg?1), Pb (R2V?=?0.86, RMSEV?=?4.14 mg kg?1), NIPI (R2V?=?0.93, RMSEV?=?0.31), and RI (R2V?=?0.90, RMSEV 3.88). In addition, the research results proved that the high prediction accuracy of the three heavy metal elements Cu, Pb, and Zn and their significant positive correlations with the soil pollution indices were the reason for the accurate prediction of NIPI and RI.

Conclusion

Using VNIR to obtain soil pollution indices quickly and accurately is of great significance for the comprehensive evaluation, prevention, and control of soil heavy metal pollution.

  相似文献   

7.
Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO2 contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.  相似文献   

8.
Abstract

This study was aimed at characterizing the effects of the activity of termites of the genus Nasutitermes on the physico‐chemical properties of the acid sandy soils of southern Nigeria. Selected morphological properties of the termite mounds were measured in the field. Outside portions of the termite mound and surface (0–15 cm) soil were collected and analyzed for some physical and chemical properties. Results obtained showed a density of 112 mounds ha‐1 with average height of 0.85 m. There were significantly higher proportions of clay, silt, and organic carbon, and higher pH, exchangeable potassium (K), calcium (Ca), magnesium (Mg), available phosphorus (P), effective cation exchange capacity and base saturation in the mounds of the Nasutitermes than in the surrounding topsoil. Mounds of Nasutitermes termites, if returned to the soil, could improve the properties of the soil in areas where termites occur in large numbers.  相似文献   

9.
Effects of soil type and nitrogen (N) fertilizer–application rates on the nutrient composition of grapevine (Vitis vinifera L. cv. Riesling) leaves during a growing cycle were compared with the composition of the resulting grape juice. Grapevines were planted in 75 L containers that had been installed in a vineyard and filled with three different vineyard soils (loess, shell lime, and Keuper). Four typical levels of N fertilizer (40, 80, 120, and 160 kg N ha–1) were applied. Elemental composition of mature leaves sampled seven times during the growing cycle as well as of the extracted grape juice was analyzed. The time of sampling affected all measured elements (C, N, Ca, K, P, Mg, S, Fe, Zn, Mn, and B) in the leaves. Nitrogen‐fertilizer rate affected the concentrations of all elements except Ca and Mg, while the soil type had significant effects on elemental composition of the leaves with the exception of N, B, and Ca. Soil type had a significant effect on K, S, Mn, and B in the grape juice. Increasing rates of N fertilizer increased C concentration in the grape juice significantly and affected its elemental composition similar to the effects in leaves. This may be explained with the role of leaves as the source for supplying the grapes during ripening via phloem transport. Cluster analysis for the elemental composition of soils, leaves, and grape juice revealed no consistent relationships indicating that other soil characteristics in addition to the mineral concentration influence the elemental composition of grapevine leaves and grape juice.  相似文献   

10.
Purpose

Copper (Cu) is the earliest anthropogenic metal pollutant, but knowledge of Cu soil concentrations at ancient metalworking sites is limited. The objective of this work was to examine the ability of portable X-ray fluorescence to quantify Cu in soils at such sites.

Materials and methods

Using a Bruker Tracer III-SD pXRF, we examine factory “scan” settings versus simple instrument parameter changes (a reduction in energy settings from 40 to 12 kV) to target analysis for Cu. We apply these to a set of uncontaminated samples (n?=?18, <?92 mg Cu kg?1) from Central Thailand and compare results to standard wet chemistry analysis (aqua regia digestion and ICP-OES analysis). We then apply the optimized method to a set of highly contaminated samples (n?=?86, <?14,200 mg Cu kg?1) from a known ancient smelting site.

Results and discussion

We demonstrate that simple changes to factory recommended “scan” settings can double the sensitivity of Cu determination via pXRF (“optimized limit of determination” of 19.3 mg kg?1 versus an initial value of 39.4 mg kg?1) and dramatically improve the accuracy of analysis. Changes to other results for other elements are variable and depend on concentration ranges, soil matrix effects, and pXRF response for the individual element. We demonstrate that pXRF can accurately determine Cu across a wide concentration range and identify grossly contaminated soil samples.

Conclusions

We conclude that pXRF is a useful tool to rapidly screen and analyse samples at remote sites and can be applied to ancient metalworking sites. Simple optimization of the pXRF settings greatly improves accuracy and is essential in determining comparative background concentrations and “unaffected” areas. Application to other elements requires further element and matrix specific optimization.

  相似文献   

11.
Accurate soil testing procedures contribute to agricultural development of Mozambique. The Mehlich 3 (M-3) procedure has not been evaluated for Mozambican soils despite its wide applicability. Results showed M-3 solution could extract exchangeable calcium (Ca), magnesium (Mg), and potassium (K) as well as 1 M ammonium acetate (NH4OAc), while M-3 was not appropriate for extraction of exchangeable sodium (Na). M-3 was an alternative procedure to Bray-I for available phosphorus (P) extraction. Although M-3 extracted 1.6 times more P than Bray-I, determination coefficient between the two procedures showed significantly high value. P content in M-3 extracts can determine using inductively coupled plasma spectrophotometers (ICP) to maximize the merits of M-3. In conclusion, M-3 is applicable for determination of exchangeable Ca, Mg, K, and available P, in a single determination using ICP, and should contribute to development of effective and accurate soil diagnosis in Mozambique.  相似文献   

12.
The production and composition of leaf litter, soil acidity, exchangeable nutrients, and the amount and distribution of soil organic matter were analyzed in a broad‐leaved mixed forest on loess over limestone in Central Germany. The study aimed at determining the current variability of surface‐soil acidification and nutrient status, and at identifying and evaluating the main factors that contributed to the variability of these soil properties along a gradient of decreasing predominance of European beech (Fagus sylvatica L.) and increasing tree‐species diversity. Analyses were carried out in (1) mature monospecific stands with a predominance of beech (DL 1), (2) mature stands dominated by three deciduous‐tree species (DL 2: beech, ash [Fraxinus excelsior L.], lime [Tilia cordata Mill. and/or T. platyphyllos Scop.]), and (3) mature stands dominated by five deciduous‐tree species (DL 3: beech, ash, lime, hornbeam [Carpinus betulus L.], maple [Acer pseudoplatanus L. and/or A. platanoides L.]). The production of leaf litter was similar in all stands (3.2 to 3.9 Mg dry matter ha–1 y–1) but the total quantity of Ca and Mg deposited on the soil surface by leaf litter increased with increasing tree‐species diversity and decreasing abundance of beech (47 to 88 kg Ca ha–1 y–1; 3.8 to 7.9 kg Mg ha–1 y–1). The soil pH(H2O) and base saturation (BS) measured at three soil depths down to 30 cm (0–10 cm, 10–20 cm, 20–30 cm) were lower in stands dominated by beech (pH = 4.2 to 4.4, BS = 15% to 20%) than in mixed stands (pH = 5.1 to 6.5, BS = 80% to 100%). The quantities of exchangeable Al and Mn increased with decreasing pH and were highest beneath beech. Total stocks of exchangeable Ca (0–30 cm) were 12 to 15 times larger in mixed stands (6660 to 9650 kg ha–1) than in beech stands (620 kg ha–1). Similar results were found for stocks of exchangeable Mg that were 4 to 13 times larger in mixed stands (270 to 864 kg ha–1) than in beech stands (66 kg ha–1). Subsoil clay content and differences in litter composition were identified as important factors that contributed to the observed variability of soil acidification and stocks of exchangeable Ca and Mg. Organic‐C accumulation in the humus layer was highest in beech stands (0.81 kg m–2) and lowest in stands with the highest level of tree‐species diversity and the lowest abundance of beech (0.27 kg m–2). The results suggest that redistribution of nutrients via leaf litter has a high potential to increase BS in these loess‐derived surface soils that are underlain by limestone. Species‐related differences of the intensity of soil–tree cation cycling can thus influence the rate of soil acidification and the stocks and distribution of nutrients.  相似文献   

13.
Rapid soil testing and soil quality assessment are essential to address soil degradation and low farm incomes in smallholder farms. With the objective of testing diffuse reflectance spectroscopy (DRS) to rapidly assess soil chemical properties, nutrient content and a soil quality index (SQI), samples of surface soil were collected from 1113 smallholder farms in seven districts in Bundelkhand region of Uttar Pradesh, India. A minimum dataset (MDS) approach was followed to estimate SQI using the three chemical parameters of soil pH, electrical conductivity (EC) and soil organic carbon (SOC), and 11 different soil nutrients. Principal component and correlation analyses showed that soil pH, SOC content and three available nutrients − copper (Cu), iron (Fe) and sulphur (S) − may constitute the MDS. Estimated SQI values showed strong positive correlation with crop yields. Results of chemometric modelling showed that the DRS approach could yield the coefficient of determination (R2) values in the validation datasets ranging from 0.79 to 0.94 for exchangeable calcium (Ca) followed by 0.67–0.88 for exchangeable potassium (K), 0.52–0.86 for SOC and 0.53–0.81 for available boron (B) content. Except in one district, the DRS approach could be used to estimate SQI values with R2 values in the range of 0.63–0.81; an R2 value of 0.71 was obtained in the pooled dataset. We also estimated the three-tier soil test crop response (STCR) ratings to compare DRS and wet chemistry soil testing approaches. Similar STCR ratings were obtained for both these approaches in more than 86% of the samples. Parameters for which both the methods yielded similar ratings in more than 80% of the samples were EC (>98%), pH and exchangeable Ca (>81%) and available B (>89%). With similar ratings, these results suggest that the DRS approach may safely be used for farmers' fields, replacing the traditional wet analysis approach of soil testing.  相似文献   

14.
The development of accurate calibration models for selected soil properties is a crucial prerequisite for successful implementation of visible and near infrared (Vis‐NIR) spectroscopy for soil analysis. This paper compares the performance of calibration models developed for individual farms with that of general models valid for three farms in three European countries. Fresh soil samples collected from farms in the Czech Republic, Germany and Denmark were scanned with a fibre‐type Vis‐NIR spectrophotometer. After dividing spectra into calibration (70%) and validation (30%) sets, spectra in the calibration set were subjected to partial least squares regression (PLSR) with leave‐one‐out cross‐validation to establish calibration models of soil properties. Except for the Czech Republic farm, individual farm models provided successful calibration for total carbon (TC), total nitrogen (TN) and organic carbon (OC), with coefficients of determination (R2) of 0.85–0.93 and 0.74–0.96 and residual prediction deviations (RPD) of 2.61–3.96 and 2.00–4.95 for the cross‐validation and independent validation respectively. General calibration models gave improved prediction accuracies compared with models of farms in the Czech Republic and Germany, which was attributed to larger ranges in the variation of soil properties in general models compared with those in individual farm models. The results revealed that larger standard deviations (SDs) and wider variation ranges have resulted in larger R2 and RPD, but also larger root mean square errors of prediction (RMSEP). Therefore, a compromise solution, which also results in small RMSEP values, should be found when selecting soil samples for Vis‐NIR calibration to cover a wide variation range.  相似文献   

15.
Tundra soils (except for the soils of barren circles) in the moderately and extremely continental tundra areas are characterized by the pronounced surface accumulation of humic substances. The humate-fulvate nature of humus is typical of the upper horizons of surface eluvial-gley soils, gley soils, and raw-humus mountainous brown soils; the C ha/C fa ratio in them varies from 0.5 to 0.91. The fulvate-humate nature of humus (C ha/C fa = 1.27–1.50) is typical of cryozems and sandy podburs. The first and the third fractions of humic substances (hs 1 and hs 3) predominate in the composition of humus. The coefficients of correlation (R) between the major parameters of soil humus and the physicochemical characteristics of tundra soils have been calculated. These coefficients between the contents of C org, C ha, C fa, C ha1, and C ha3 and the total acidity are equal to 0.73, 0.76, 0.72, 0.85, and 0.67, respectively; for the exchangeable Mg2+, their values are equal to 0.66, 0.88, 0.85, 0.74, and 0.90, respectively; and for the exchangeable Ca2+, 0.55, 0.47, 0.39, 0.41, and 0.61, respectively (p < 0.05). The composition of exchangeable cations and the total acidity specify the conditions of fractionation of humic substances in the studied soils. The differentiation of the qualitative composition of humus in the profiles of tundra soils is well pronounced and is mainly controlled by the distribution of clay and fine silt particles.  相似文献   

16.
Three wheat categories with different biomass production were studied on tropical Inceptisols in Rwanda. Growth parameters such as number of tillers per square meter, average plant height, and shoot and root biomass were determined, and elemental concentrations of roots and leaves measured. In order to identify reasons for inhibited wheat growth soil parameters such as pH, exchangeable cations, Corg and Ntot were determined. As aluminum toxicity was suspected on the acid soils, aluminum fractionation was carried out in water extracts of the soil samples using 8-hydroxyquinoline. Growth parameters correlated well with exchangeable aluminum and with soil pH. These findings, along with root morphology, indicated aluminum toxicity at the low productivity plots. Aluminum fractionation results strengthened this hypothesis, but did not give much additional information. The reasons for this are discussed. Simultaneously, the elemental concentrations of the leaves suggested Ca, Mg and P deficiencies.  相似文献   

17.
Abstract

An understanding of how soil solution ionic strength (Is) and major cation activities influence crop growth is often limited by the extensive measurements required to characterize ionic composition and subsequent speciation exercises. Easily measured solution and soil attributes need to be identified that can predict these important solution parameters. Soil and soil solution chemical properties of four Ultisols in the Coastal Plain and Piedmont of North Carolina were used to develop models to predict ionic strength and solution cation attributes. GEOCHEM‐PC‐predicted Is was linearly related to electrical conductivity (EC) across soils (r2=0.92), confirming that Is for soil solutions with complex composition can be estimated from their electrical conductivity. Models of the form lnMs=a+blnEC+clnME, or modifications thereof, were developed for predicting solution aluminum (Al), calcium (Ca), magnesium (Mg), and postassium (K) levels (Ms) from a knowledge of EC and either soil exchangeable cation #OPME) or cation saturation (MSATE) attributes. For each cation, total and free solution concentration and activity in absolute and saturation terms were investigated. The best models explained, at most, 68% of the variability associated with total solution Al concentration (Als‐T) or 74% when Als ‐T was expressed as a percent of major solution cations. Greater than 85% of the variability associated with solution Ca and Mg could also be accounted for, but only 67% of the variability associated with solution K could be explained. Including soil pH and interaction terms (MExEC, MExpH, and ECxpH) in models improved the relationship for total Al concentration (R2=0.87) and solution Ca parameters (R2 ≥0.93), but not for solution Mg and K indices. None of the models could account for >30% of the variability associated with free concentration and activity of Al3+, suggesting that the prediction of these parameters for a particular Al species could not be made from a knowledge of soil pH, solution EC, and ME or MSATE data.  相似文献   

18.
Abstract

Soil cation exchange capacity (CEC) measurements are important criteria for soil fertility management, vaste disposal on soils, and soil taxonomy. The objective of this research was to compare CEC values for arable Ultisols from the humid region of the United States as determined by procedures varying widely in their chemical conditions during measurement. Exchangeable cation quantities determined in the course of two of the CEC procedures were also evaluated. The six procedures evaluated were: (1) summation of N NH4OAc (pH 7.0) exchangeable Ca, Mg, K, and Na plus BaCl2 ‐ TEA (pH 8.0) exchangeable acidity; (2) N Ca(OAc)2 (pH 7.0) saturation with Mg(OAc)2 (pH 7.0) displacement of Ca2+; (3) N NH4OAc (pH 7.0) saturation with NaCl displacement of NH4 +; (4) N MgCl2 saturation with N KCl displacement of Mg2+; (5) compulsive exchange of Mg2+ for Ba2+; and (6) summation of N NH4OAc (pH 7.0) exchangeable Ca, Mg, K, and Na plus N KCl exchangeable AJ. The unbuffered procedures reflect the pH dependent CEC component to a greater degree than the buffered methods. The compulsive exchange and the summation of N NH4OAc exchangeable cations plus N KCl exchangeable Al procedures gave CEC estimates of the same magnitude that reflect differences in soil pH and texture. The buffered procedures, particularly the summation of N NH4OAc exchangeable cations plus BaCl2 ‐ TEA (pH 8.0) exchangeable acidity, indicated inflated CEC values for these acid Ultisols that are seldom limed above pH 6.5. Exchangeable soil Ca and Mg levels determined from extraction with 0.1 M BaCl2 were consistently greater than values for the N NH4Oac (pH 7.0) extractions. The Ba2+ ion is apparently a more efficient displacing agent than the NH4 + ion. Also, the potential for dissolving unreacted limestone is greater for the Ba2 + procedures than in the NH4 + extraction.  相似文献   

19.
Carbonatite originating from the Lillebukt Alkaline Complex at Stjernøy in Northern Norway possesses favorable lime and potassium (K) fertilizer characteristics. However, enrichments of barium (Ba) and strontium (Sr) in carbonatite may cause an undesired uptake by plants when applied to agroecosystems. A field survey was carried out to compare concentrations of Ba, Sr, and macronutrients in indigenous plants growing in mineral soil developed on a bedrock of apatite–biotite–carbonatite (high in Ba and Sr) and of apatite–hornblende–pyroxenite (low in Ba and Sr) at Stjernøy. Samples of soil and vegetation were collected from three sites, two on carbonatite bedrock and one on pyroxenite bedrock. Ammonium lactate (AL)‐extracted soil samples and nitric acid microwave‐digested samples of soil, grasses, dwarf shrubs, and herbs were analyzed for element concentration using ICP‐MS and ICP‐OES. Concentrations of magnesium (Mg) and calcium (Ca) in both soil (AL) and plants were equal to or higher compared to values commonly reported. A high transfer of phosphorus (P) from soil to plants indicates that the apatite‐P is available to plants, particularly in pyroxenite soil. The non‐exchangeable K reservoir in the soil made a significant contribution to the elevated K transfer from soil to plant. Total concentrations of Ba and Sr in surface soil exhibited a high spatial variation ranging from 490 to 5,300 mg Ba kg?1 and from 320 to 1,300 mg Sr kg?1. The transfer of AL‐extractable elements from soil to plants increased in the order Ba < Sr < Ca < Mg < K, hence reflecting the chemical binding strength of these elements. Concentrations of Ba and Sr were low in grasses (≈ 20 mg kg?1), intermediate in dwarf shrubs and highest in herbs. Plant species and their affinity for Ca seemed more important in explaining the uptake of Ba and Sr than the soil concentration of these elements. The leguminous plant species Vicia cracca acted as an accumulator of both Ba (1.800 mg kg?1) and Sr (2.300 mg kg?1).  相似文献   

20.
Soil erosion has serious off-site impacts caused by increased mobilization of sediment and delivery to water bodies causing siltation and pollution. To evaluate factors influencing soil erodibility at a proposed dam site, 21 soil samples collected were characterized. The soils were analyzed for soil organic carbon (SOC), exchangeable bases, exchangeable acidity, pH, electrical conductivities, mean weight diameter and soil particles’ size distribution. Cation exchange capacity, exchangeable sodium percentage, sodium adsorption ratio, dispersion ratio (DR), clay flocculation index (CFI), clay dispersion ratio (CDR) and Ca:Mg ratio were then calculated. Soil erodibility (K-factor) estimates were determined using SOC content and surface soil properties. Soil loss rates by splashing were determined under rainfall simulations at 360?mmh?1 rainfall intensity. Soil loss was correlated to the measured chemical and physical soil properties. There were variations in soil form properties and erodibility indices showing influence on soil loss. The average soil erodibility and SOC values were 0.0734?t?MJ?1?mm?1 and 0.81%, respectively. SOC decreased with depth and soil loss increased with a decrease in SOC content. SOC significantly influenced soil loss, CDR, CFI and DR (P??1. Addition of organic matter stabilize the soils against erosion.  相似文献   

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