基于激光衍射的土壤粒径测定法的评价与校正

为比较与评价激光法与吸管法测定土壤粒径分布的准确性,该文采用激光法与吸管法测定了23组来自中国13个不同省份或自治区土壤样本的粒径分布,将激光法与传统吸管法的测定结果进行比较,并在此基础上对激光法测定参数进行了修正。结果表明:1)与吸管法相比,激光衍射法低估土壤样品中的黏粒含量,其相对误差为36.33%;高估粉粒含量,其相对误差为36.51%;2)对吸管法与激光衍射法的实测结果进行线性关系分析表明,其中黏粒与粉粒的线性关系较好,决定系数分别为0.91,0.90;3)经过模型转换后,基于激光衍射法的土壤粒径分布结果的相对误差明显降低:黏、粉的相对误差分别降低至16.25%、12.83%,说明激光衍射法可以用于大规模不同类型的土壤粒径分析。该研究可为土壤系统化和规范化的对比研究以及建立基于激光衍射技术的土壤质地划分标准提供依据。     

Soil particle size range correction for improved calibration relationship between the laser-diffraction method and sieve-pipette method

Particle size fraction(clay, silt, and sand) is an important characteristic that influences several soil functions. The laser-diffraction method(LDM) provides a fast and cost-effective measurement of particle size distribution, but the results usually differ from those obtained by the traditional sieve-pipette method(SPM). This difference can persist even when calibration is applied between the two methods. This partly relates to the different size ranges of particles measured by the two methods as a result of different operational principles, i.e., particle sedimentation according to Stokes’ Law vs. Mie theory for laser beam scattering. The objective of this study was to identify particle size ranges of LDM equivalent to those measured by SPM and evaluate whether new calibration models based on size range correction can be used to improve LDM-estimated particle size fractions, using 51 soil samples with various texture collected from five soil orders in New Zealand. Particle size distribution was determined using both LDM and SPM. Compared with SPM, original data from LDM underestimated the clay fraction(< 2 μm), overestimated the silt fraction(2–53 μm), but provided a good estimation of the sand fraction(53–2 000 μm).Results from three statistical indices, including Pearson’s correlation coefficient, slope, and Lin’s concordance correlation coefficient, showed that the size ranges of < 2 and 2–53 μm defined by SPM corresponded with the < 5 and 5–53 μm size ranges by LDM, respectively. Compared with the traditional calibration(based on the same particle size ranges), new calibration models(based on the corrected size ranges of these two methods) improved the estimation of clay and silt contents by LDM. Compared with soil-specific models(i.e., different models were developed for different soils), a universal model may be more parsimonious for estimating particle size fractions if the samples to be assessed represent multiple soil orders.     

Methodological aspects of determining soil particle‐size distribution using the laser diffraction method

This paper presents the influence of selected methodological aspects on the results of particle‐size distribution (PSD) as measured by the laser diffraction method (LDM). The investigations were carried out using the Mastersizer 2000 with Hydro MU attachment (Malvern Ltd., UK). It was found that for the investigated soils: (1) optimal speed of pump and stirrer was 2500 rpm, (2) optimal measurement time was ≈ 1 min, (3) there are two, practically equivalent methods for soil‐sample dispersion: chemical (with the use of a solution of sodium hexametaphosphate) or physical (by means of ultrasound application for 4 min at a maximum power of 35W), (4) one must not use the chemical and physical dispersing methods simultaneously, because this can lead to aggregation (not dispersion) of soil particles, (5) the Fraunhofer theory (physical models) can be used to convert scattered‐light data to PSD. In the case of the Mie theory, the best results were obtained for a refractive index (RI) in the range of 1.5–1.6 and an absorption index (AI) of 1.0. It was also found that most of the discussed parameters depend on design of the measuring device and on the type and volume of the investigated suspensions. It is necessary, therefore, to explain how the data was obtained every time and to specify the details in the methodological part of the paper.     

激光粒度仪与吸管法测定土壤机械组成的比较研究——以不同退化程度栗钙土为例

激光粒度仪法作为测量土壤机械组成的新型方法,具有操作简单、速度快的优势,但其适用性与可靠性尚未达成广泛共识。为探究激光粒度仪测定土壤机械组成的准确性与适用性,采集7种退化程度共21份栗钙土土样,使用激光粒度仪与吸管法测定土样机械组成并对比分析。结果显示:激光法测定结果黏粒偏小,而砂粒、粉粒偏大,且随粒径减小误差增大。将两种测定结果进行回归分析,发现砂粒与粉粒转换模型拟合效果理想,黏粒拟合效果差。建立质地三角图发现两种方法得到的质地差异较大,采用转换后数据分析质地,发现质地接近、正确率高,转换效果好。通过扫描电镜对土粒形态观察,发现标准流程不同分散方法下土粒形状与数量均有差异,推测分散方法会影响土壤机械组成的测定结果。激光粒度仪的适用性据测定对象的不同而有差异,对黏粒精度要求高的情况下不宜使用该法,而其他情况下需要对测定结果进行数据转换。     

Revisiting the particle‐size distribution of soils: comparison of different methods and sample pre‐treatments

The choice of analytical method and sample pretreatment has significant consequences for the shape of particle‐size distribution (PSD) frequency curves, and therefore for the evaluation of soil textural parameters. Here, the comparison of several granulometric methods based on different physical principles is presented: wet sieving (WS), based on gravity and the mechanical force of water, was combined with pipette (PP) sedimentation/settling velocity, Micromeritics SediGraph (MS) sedimentation/x‐ray attenuation and Coulter Counter (CC) electroresistance particle counting. The Malvern Mastersizer (MM), an instrument based on laser diffraction, was used without WS. Twelve typical temperate‐region soil types were chosen for this study on the basis of their mineral composition, organic matter content, conductivity and magnetic susceptibility. The modalities of PSD frequency curves obtained by different methods were compared. The results showed considerably larger clay‐fraction contents determined with the sedimentation techniques, PP and MS, than that obtained by CC or MM. Statistical correlation and regression models were used to compare the fractions of clay, silt and sand obtained with different methods. Linear correlations were found in almost all cases, except those comparing clay fractions obtained by CC with those obtained by MM, PP and MS methods. These correlations were non‐linear. The observed difference was attributed to the presence of aggregates and/or magnetic properties of soil particles. However, more data are needed to verify this hypothesis. The implications of sample pre‐treatment with dispersant and hydrogen peroxide (H₂O₂) were evaluated by the MS and CC techniques and observed by the scanning electron microscope. H₂O₂ was found to be an efficient disaggregating agent. The use of dispersant resulted in the increased amount of the clay fraction measured by the MS method.     

激光衍射法测定土壤粒径分布的研究进展

常见的土壤粒径分布测试手段有筛分法、沉降法(包括吸管法和密度计法)、激光衍射法等。近年来,由于激光衍射法分析土壤粒径分布具有操作简单、效率高、测试样品用量小、适合批量样品测定的特点,其在土壤粒径分布的测定中得到越来越广泛的应用。本文介绍了激光衍射法测定土壤粒径分布的基本原理和分析方法,综述了该技术在测定土壤粒径分析方面的国内外研究进展,重点分析了激光衍射法测定土壤粒径分布的影响因素,并对激光衍射法测定土壤粒径分布的应用前景进行了展望。研究表明,激光衍射法通过转换方程可以获得精确的结果。在保证足够大的样本量、土壤样本包含多种质地类型,且完善的前处理条件下,可以建立稳定的、适用于大范围预测的模型。激光衍射法测定土壤粒径分布虽然受到一些因素的影响,例如前处理方法、仪器设置以及样品用量等,但是激光粒度仪为粒度测定提供了高效快速的技术手段,为精准农业和数字农业的发展提供了先进的技术支撑。     

激光法与湿筛－吸管法测定土壤颗粒组成的转换及质地确定

湿筛-吸管法是测定土壤颗粒组成(PSD)的传统方法,而激光法则是新兴的土壤颗粒测定方法,为了明确二者测定数据间的转换关系,应用两种方法分别测定了中国6个主要土纲的265个土壤样品。结果表明,激光法测定的土壤黏粒含量明显地小于湿筛-吸管法测定的数据,激光法测定的土壤粉粒含量明显地大于湿筛-吸管法测定的数据,而对于土壤砂粒含量的测定结果二者互有高低。两种方法测定的黏粒、粉粒和砂粒间均分别具有很好的相关性,甚至按照美国的7级分类标准,每个粒度级别在两种方法间均具有很好的相关性。按照激光法和吸管法测定数据间的转换关系式得出了用激光法测定数据的砂土、壤土和黏土质地划分界限,从而能够应用激光法测定的数据直接进行质地划分,这对于推动激光法在土壤学中的进一步应用和推动土壤科学的发展均具有重要意义。     

The implications of sample preparation on the particle size distribution of soil

Particle size distribution (PSD) is among basic parameters in soil and sediment characterization and provides essential information in sedimentological and environmental studies. The problem with the PSD determination is that for any given sample the result depends not only on the method used but also on the sample pre‐treatment, making them seldom comparable. In this study, the PSD of seven non‐treated and pre‐treated soil samples were determined by four granulometric methods (pipette, sedigraph, particle counter and laser diffraction analysis). Samples were subjected to pre‐treatments commonly used in sample preparation for the PSD determination, i.e., addition of dispersant (sodium metaphosphate) and removal of the organic matter (with hydrogen peroxide). The total organic carbon (TOC) analysis was used to estimate the content of organic matter before and after its removal. The effect of different pre‐treatments was evaluated based on the PSD variations and the changes in the specific surface area (SSA) of the samples. The results highlighted differences in the PSD curves of samples depending on the granulometric method and pre‐treatment applied. The most pronounced difference was the higher amount of clay fraction determined by settling techniques. The role of hydrogen peroxide in disruption of aggregates was evident in the increase in the SSA as well as the share of fine fraction determined by all four techniques, while sodium metaphosphate made no modifications of the SSA but acted in favour of prolonging settling of clay particles and increasing its content obtained by settling techniques.     

激光衍射法和吸管法分析黏性富铁土颗粒粒径分布的比较

激光衍射技术(Laser diffraction technique,简称LD法)近年来被认为是一种有效的分析土壤颗粒粒径分布(Particle size distribution,PSD)的手段。为检验LD法在黏粒含量高的富铁土上应用的可行性,用LD法和传统的吸管法实测了6个黏性富铁土剖面(黏粒含量>40%)不同层次土样的PSD数据,比较发现:LD法能够提供更多颗粒粒径级别,尤其是黏粒部分(<2μm)的PSD信息,且分析耗时短,效率高。但是LD法与吸管法测定的不同粒级土壤颗粒的含量存在一定的差异。两种方法相比,激光衍射法"低估"黏粒和"高估"粉粒,或者沉降法"高估"了黏粒和"低估"了粉粒。虽然在黏性富铁土的黏粒部分未发现两种方法的线性关系,但粉粒和砂粒分别存在显著的线性相关。供试土壤黏粒含量高且分布范围窄是导致上述差异的主要原因。经过模型转换后,LD法和吸管法PSD实测数据之间的误差明显降低,这说明LD法可以用于黏性土壤的PSD分析。但是LD法PSD测定结果尚不能直接用于目前基于沉降法的土壤质地三角图,需要一定的数据转换。应该尽快通过对各类代表性土壤进行系统化和规范化的对比研究,提高LD技术的可靠性和实用性,建立起基于LD技术的新的土壤质地三角图,以便进一步深化其在土壤科学上的应用。     

Transferability of continuous‐ and class‐pedotransfer functions to predict water retention properties of semiarid Syrian soils

Hydraulic properties of soils, particularly water retention, are key for appropriate management of semiarid soils. Very few pedotransfer functions (PTF s) have been developed to predict these properties for soils of Mediterranean regions, where data are particularly scarce. We investigated the transferability of PTF s to semiarid soils. The quality of the prediction was compared to that for soils originating from temperate regions for which most PTF s were developed. We used two soil data sets: one from the Paris basin (French data set, n  = 30) and a Syrian data set (n  = 30). Soil samples were collected in winter when the water content was near field capacity. Composition and water content of the samples were determined at seven water potentials. Continuous‐ and class‐PTF s developed using different predictors were tested using the two data sets and their performance compared to those developed using artificial neural networks (ANN ). The best performance and transferability of the PTF s for both data sets used soil water content at field capacity as predictor after stratification by texture. The quality of prediction was similar to that for ANN ‐PTF s. Continuous‐ and class‐PTF s may be transferable to other countries with performances that vary according to their ability to account for variation in soil composition and structure. Taking into account predictors of composition (particle size distribution, texture, organic carbon content) and structure (bulk density, porosity, field capacity) did not lead to a better performance or the best transferability potential.     

Determination of soil texture: Comparison of the sedimentation method and the laser‐diffraction analysis

Laser‐diffraction analysis (LDA) is a rapid automated method achieving highly resolved frequency distributions of particle sizes. Recently, LDA has come into use in environmental sciences. However, in the size range of silt and clay deviations from the particle‐size analysis with the standard pipette method, which is regarded as the reference method for soil‐texture classification, have been reported. Therefore, this study concentrates (1) on the verification of systematic relations between both methods using a series of soils of Lower Saxony (Germany) and (2) on the general applicability of the laser‐diffraction method to soil‐texture classification as well as (3) texture‐based estimates of air capacity, available field capacity, and permanent wilting point. The comparison of LDA with the pipette method demonstrated highly significant linear correlations in each of the particle‐size fractions from clay to coarse silt. The slope of regressions ranged from 0.4 with fine silt to 3.1 with clay. If the clay content derived from LDA was applied to texture classification, the resulting textural classes differed from the standard textural classes, except for purely sandy samples with a clay content of <5%. However, the linear‐regression model enabled an approach of the LDA‐based clay content to values produced with the standard pipette method. Using this transformation, a texture classification became practicable in many cases, but, despite of a high significance level between LDA and pipette method, still led to wrong textural classes in several cases. A comparison with regression models from other regions in Europe showed both similarities and discrepancies, even for similar substrates. Hence, the laser‐diffraction analysis cannot be used for the texture classification of soil samples without verification by the standard pipette method.     

土壤颗粒粒径分布质量分形维数和体积分形维数的对比

用激光衍射法(LD法)和吸管法实测了60个富铁土土样的颗粒粒径分布(PSD)数据,在此基础上分别计算了颗粒的质量分形维数Dm和体积分形维数Dv。结果发现:由于LD法"低估"了黏粒部分,因此Dv相对低于Dm;由于Dv和Dm之间呈现出了一定的正相关性(p<0.001),且Dv与其实测黏粒之间呈一定的正相关性,因此Dv在一定程度上也能够用于表征土壤的某些基本属性;LD法可以对粒径进行更多的分级,但不同的粒径分级会对Dv产生影响,对粒径的再细分会导致Dv略微降低。     

Estimation of soil water retention function based on asymmetry between particle‐ and pore‐size distributions

By examining the symmetry between the distributions of particle‐size (PSD) and pore‐size (POD) in a soil, as hypothesized by early pore‐solid fractal (PSF) models, we found significant discrepancies in fractal dimensions between the PSD and the water retention curve (WRC) of a soil. Therefore, we developed an asymmetry‐based PSF model to estimate better the WRC directly from the PSD data of a soil. To do so, we adopted the concept of a microscopic arrangement of different‐sized particles to address such asymmetry, and evaluated the performance of the modified PSF model on five soil textural classes (coarse‐, moderately coarse‐, medium‐, moderately fine‐ and fine‐textured soils) using experimental PSD and WRC data from the UNSODA database (159 undisturbed soils for model calibration and 70 undisturbed soils for model validation). The fit of the symmetry‐based PSF model to the calibration dataset showed that the fractal dimension of the WRC (D_p) was slightly larger than that of cumulative mass distribution of particles (D_s) for most soils. The asymmetry‐based PSF model performed better than the symmetry‐based PSF model. In addition, the asymmetry‐based PSF model reduced the tendency to under estimate soil water content for a given matric head and the performance of the asymmetry‐based model was consistent irrespective of soil texture, indicating that the adoption of asymmetry between the PSD and the POD was adequate in predicting the WRC of a porous, particulate system such as soil.     

CHARACTERIZING VARIATIONS IN SOIL PARTICLE‐SIZE DISTRIBUTION ALONG A GRASS–DESERT SHRUB TRANSITION IN THE ORDOS PLATEAU OF INNER MONGOLIA,CHINA

The application of fractal geometry to describe soil degradation and dynamics is becoming a useful tool for better understanding of the performance of soil systems. In this study, four different land cover types, which represent a sequence of grass–desert shrub transition and a gradient of desertification, were selected, and soils at depths of 0–10, 10–20 and 20–40 cm were sampled in the Ordos Plateau of Inner Mongolia, PR China. The fractal theory was used to analyse the soil particle‐size distribution (PSD) and its variations. The results showed that (i) vegetation conversion and desertification significantly changed the soil PSD. During the desertification process, soil coarse fractions that ranged from 250 to 100 µm significantly increased, whereas fine fractions lower than 50 µm significantly decreased (p < 0·01); (ii) fractal model of the accumulative volume particle‐size distribution is appropriate, and fractal dimensions (D_m) of soil PSD significantly decreased along the sequence of grass–desert shrub transition; (iii) D_m is more sensitive to the desertification process, and therefore, we suggest D_m other than soil texture and soil organic carbon as a reliable parameter to reflect the soil environment change induced by desertification. Copyright © 2011 John Wiley & Sons, Ltd.     

绿洲农田土壤粒径分布特征及其影响因素分析──以策勒绿洲为例

以塔里木盆地南缘策勒绿洲为例,重点探讨了绿洲农田土壤粒径分布特征及其主要影响因素。基于2008年9月对策勒绿洲范围内农田表层土壤粒度测定数据,首先通过土壤粒径分布体积分形维数分析,表明绿洲农田土壤粒径分布差异性显著,并根据分析结果提出假设,认为农田利用年限及空间位置的不同是土壤粒径分布产生差异性的主要因素;其次利用排序方法对影响因素的贡献率进行定量分析,并与分维值结果进行相互验证。研究结果表明在影响土壤粒径分布差异性方面,利用年限为主导因素,其相对贡献率达67%。因此,保证农田长期合理的耕作管理方式将有助于土壤粒径分布属性的稳定及改善。     

Improvement in estimation of soil water retention using fractal parameters and multiobjective group method of data handling

Soil water retention characteristic is required for modeling of water and substance movement in unsaturated soils and need to be estimated using indirect methods. Point pedotransfer functions (PTFs) for prediction of soil water content at matric suctions of 1, 5, 25, 50, and 1500 kPa were developed and validated using a data-set of 148 soil samples from Hamedan and Guilan provinces, Iran, by multiobjective group method of data handling (mGMDH). In addition to textural and structural properties, fractal parameters of the power-law fractal models for both particles and aggregates distributions were also included as predictors. Their inclusion significantly improved the PTFs’ accuracy and reliability. The aggregate size distribution fractal parameters ranked next to the particle size distribution (PSD) in terms of prediction accuracy. The mGMDH-derived PTFs were significantly more reliable than those by artificial neural networks but their accuracies were practically the same. Similarity between the fractal behavior of particle and void size distributions may contribute to the improvement of the derived PTFs using PSD fractal parameters. It means that both distributions of the pore and particle size represent the fractal behavior and can be described by fractal models.     

Performance of pedotransfer functions in predicting soil water characteristics of soils in Norway

Abstract

Pedotransfer functions (PTFs), predicting the soil water retention curve (SWRC) from basic soil physical properties, need to be validated on arable soils in Norway. In this study we compared the performance of PTFs developed by Riley (1996), Rawls and Brakensiek (1989), Vereecken et al. (1989), Wösten et al. (1999) and Schaap et al. (2001). We compared SWRCs calculated using textural composition, organic matter content (SOM) and bulk density as input to these PTFs to pairs of measured water content and matric potential. The measured SWRCs and PTF input data were from 540 soil horizons on agricultural land in Norway. We used various statistical indicators to evaluate the PTFs, including an integrated index by Donatelli et al. (2004). The Riley PTFs showed good overall performance. The soil specific version of Riley is preferred over the layer specific, as the latter may introduce a negative change in water content with increasing matric potential (h). Among the parameter PTFs, Wösten's continuous PTF showed the overall best performance, closely followed by Rawls&B and Vereecken. The ANN-based continuous PTF of Schaap showed poorer performance than its regression based counterparts. Systematic errors related to both particle size and SOM caused the class PTFs to perform poorly; these PTFs do not use SOM as input, and are therefore inappropriate for soils in Norway, being highly variable in SOM. The PTF performance showed little difference between soil groups. Water contents in the dry range of the SWRC were generally better predicted than water contents in the wet range. Pedotransfer functions that included both SOM and measured bulk density as input, i.e. Wösten, Vereecken and Rawls&B, performed best in the wet range.     

Impact of protein surface denaturation on droplet flocculation in hexadecane oil-in-water emulsions stabilized by beta-lactoglobulin

The influence of globular protein denaturation after adsorption to the surface of hydrocarbon droplets on flocculation in oil-in-water emulsions was examined. n-Hexadecane oil-in-water emulsions (pH 7.0) stabilized by beta-lactoglobulin (1-wt % beta-Lg) were prepared by high-pressure valve homogenization. NaCl (0-150 mM) was added to these emulsions immediately after homogenization, and the evolution of the mean particle diameter (d) and particle size distribution (PSD) was measured by laser diffraction during storage at 30 degrees C for 48 h. No change in d or PSD was observed in the absence of added salt, which indicated that these emulsions were stable to flocculation. When 150 mM NaCl was added to emulsions immediately after homogenization, d increased rapidly during the following few hours until it reached a plateau value, while the PSD changed from monomodal to bimodal. Addition of N-ethylmaleimide, a sulfhydryl blocking agent, to the emulsions immediately after homogenization prevented (at 20 mM NaCl) or appreciably retarded (at 150 mM NaCl) droplet flocculation. These data suggests that protein unfolding occurred at the droplet interface, which increased the hydrophobic attraction and disulfide bond formation between droplets. In the absence of added salt, the electrostatic repulsion between droplets was sufficient to prevent flocculation, but in the presence of sufficient salt, the attractive interactions dominated, and flocculation occurred.     

Milling—A Further Parameter Affecting the Rapid Visco Analyser (RVA) Profile

Rapid Visco Analyser (RVA) profiles were recorded for raw maize grits and two extruded nonexpanded pellets based on wheat and maize. Large differences were found between the profiles obtained when an impeller mill was used to prepare the samples compared with a disk mill. The differences were related to differences in particle properties of the ground products (particle‐size distribution, particle shape, and protein content). Generally, milling the samples with the impeller mill resulted in greater starch conversion than with a disk mill. For raw maize grits, this was shown by X‐ray diffraction, differential scanning calorimetry (DSC), and alkaline viscosity measurements. Several other laboratory mills were tested and all produced particulates with a sieve range of 125–212 μm that had substantially differing RVA profiles. Cooling the sample during milling did not nullify the milling effects. All the laboratory mills produced <20% of the particulates of the size range required for the RVA analysis. The mill used for sample preparation can exert a significant effect on the RVA for both raw and processed cereal samples, even if measurements are made on a defined sieve fraction.     

Validation of water sorption‐based clay prediction models for calcareous soils

Soil particle size distribution (PSD), particularly the active clay fraction, mediates soil engineering, agronomic and environmental functions. The tedious and costly nature of traditional methods of determining PSD prompted the development of water sorption‐based models for determining the clay fraction. The applicability of such models to semi‐arid soils with significant amounts of calcium carbonate and/or gypsum is unknown. The objective of this study was to validate three water sorption‐based clay prediction models for 30 calcareous soils from Iran and identify the effect of CaCO₃ on prediction accuracy. The soils had clay content ranging from 9 to 61% and CaCO₃ from 24 to 97%. The three water sorption models considered showed a reasonably fair prediction of the clay content from water sorption at 28% relative humidity (RMSE and ME values ranging from 10.6 to 12.1 and −8.1 to −4.2, respectively). The model that considers hysteresis had better prediction accuracy than the other two that do not. Moreover, the prediction errors of all three models arose from under‐prediction of the clay content. The amount of hygroscopic water scaled by clay content decreased with increasing CaCO₃ content. The low organic carbon content of the soils and the low fraction of low‐activity clay minerals like kaolinite suggested that the clay content under‐predictions were due to large CaCO₃ contents. Thus, for such water‐sorption based models to work accurately for calcareous soils, a correction factor that considers the reduction of water content due to large CaCO₃ content should be included.