Laser Grain-Size Determination in Soil Genetic Studies 1. Practical Problems

Buurman, P.; Pape, Th.; Muggler, Cristine Carole

doi:10.1097/00010694-199703000-00007

Cited by 161 publications

(106 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Samples and standards were matrix matched and all analyses were performed in triplicates. Moreover, organic carbon (OC) was measured by combusting samples from which carbonates were removed using 1 N HCl in a NCS Analyzer Flash 2000 (Thermo Scientific, Massachusetts, USA) and the clay content was determined with the hydrometer method (Buurman et al 1997;Kooistra et al 2001).…”

Section: Methodsmentioning

confidence: 99%

Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features

Gholizadeh¹,

Borůvka²,

Saberioon³

et al. 2015

Soil Water Res.

147

View full text Add to dashboard Cite

Gholizadeh A., Borůvka L., Saberioon M.M., Kozák J., Vašát R., Němeček K. (2015): Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features. Soil & Water Res., 10: 218-227.The lands near mining industries in the Czech Republic are subjected to soil pollution with heavy metals. Excessive heavy metal concentrations in soils not only dramatically impact the soil quality, but also due to their persistent nature and indefinite biological half-lives, potentially toxic metals can accumulate in the food chain and can eventually endanger human health. Monitoring and spatial information of these elements require a large number of samples and cumbersome and time-consuming laboratory measurements. A faster method has been developed based on a multivariate calibration procedure using support vector machine regression (SVMR) with cross-validation, to establish a relationship between reflectance spectra in the visible-near infrared (Vis-NIR) region and concentration of Mn, Cu, Cd, Zn, and Pb in soil. Spectral preprocessing methods, first and second derivatives (FD and SD), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR) were employed after smoothing with Savitzky-Golay to improve the robustness and performance of the calibration models. According to the criteria of maximal coefficient of determination (R 2 cv ) and minimal root mean square error of prediction in cross-validation (RMSEP cv ), the SVMR algorithm with FD preprocessing was determined as the best method for predicting Cu, Mn, Pb, and Zn concentration, whereas the SVMR model with CR preprocessing was chosen as the final method for predicting Cd. Overall, this study indicated that the Vis-NIR reflectance spectroscopy technique combined with a continuously enriched soil spectral library as well as a suitable preprocessing method could be a nondestructive alternative for monitoring of the soil environment. The future possibilities of multivariate calibration and preprocessing with real-time remote sensing data have to be explored.

show abstract

Section: Methodsmentioning

confidence: 99%

Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features

Gholizadeh¹,

Borůvka²,

Saberioon³

et al. 2015

Soil Water Res.

147

View full text Add to dashboard Cite

show abstract

“…The fragments were grouped in six classes (0.04-2, 2-5, 5-20, 20-50, 50-100, and 100-250 µm). The suspensions with densities higher than those given by the instrument's specifications were diluted with tap water following Buurman et al (1997). The calculation model uses Fraunhofer, the «polarization intensity differential of scattered light» (PIDS) and Mie theory.…”

Section: Methodsmentioning

confidence: 99%

“…Pojasok and Kay (1990) measured the dispersible clay in the same soil sample where WSA was determined in order to save time and perform both measurements at the same energy input level. Fragment size distribution and micro-aggregation may be easily quantified by laser-ray diffraction (Cooper et al, 1984;Buurman et al, 1997). This technique was used by Muggler et al (1997) to study aggregation in Brazilian Oxisols, and by Westerhof et al (1999) to determine the changes in grain size distribution of these soils upon stirring and wetting.…”

Section: Introductionmentioning

confidence: 99%

Macro- and micro-aggregate stability of soils determined by a combination of wet-sieving and laser-ray diffraction

Amezketa

Aragüés

Carranza³

et al. 2003

Span. j. agric. res.

View full text Add to dashboard Cite

Soil structural stability affects the profitability and sustainability of agricultural systems. Different-sized structural units have different stability mechanisms and respond differently to such external factors as rain, wind, irrigation and management. A comprehensive analysis of the soils structural stability requires its characterization at the macroand micro-aggregate scales. We determined the aggregate stability of 36 soils at the macro-aggregate scale using wetsieving methods and of 20 soils at the micro-aggregate scale using laser-ray diffraction techniques. All the tests gave consistent estimates of aggregate stability. Most soils were homogeneous and quite stable at the macro-aggregate level as determined by the «water stable aggregate» parameter, but differed significantly among them and were quite unstable at the micro-aggregate level as determined by the «mean weight diameter of micro-aggregates» parameter. Slaking induced by the fast wetting of aggregates was the main destabilizing mechanism in these soils (88% of the soils had slaking stability index values < 0.5), whereas most soils were quite tolerant to the mechanical shaking of aggregates (89% of the soils had stirring stability index values > 0.5). The combination of the macro-and micro-aggregate stability tests is a consistent way for describing the structural stability of the studied soils.Key words: soil structural stability, wetting, stirring, aggregate-breakdown, slaking stability index, stirring stability index. ResumenDeterminación de la estabilidad de macro-y micro-agregados del suelo mediante una combinación de técnicas de tamizado en húmedo y difracción de rayos láser La estabilidad estructural del suelo afecta a la rentabilidad y sostenibilidad de los agrosistemas. Los agregados de distintos tamaños son estabilizados por mecanismos diferentes, y responden de forma diferente frente a la lluvia, el viento, el riego y otras prácticas agronómicas. Un análisis completo de la estabilidad estructural de los suelos requiere su caracterización a nivel de macro-y micro-agregados. En este trabajo se ha determinado la estabilidad de macroagregados de 36 suelos mediante métodos de tamizado en húmedo, y la estabilidad de microagregados de 20 suelos mediante técnicas de difracción de rayos láser. Todos los ensayos estimaron de forma consistente la estabilidad de agregados. La mayoría de los suelos se comportaron homogéneamente y de forma bastante estable al nivel de macroagregados, de acuerdo con los valores del parámetro «agregados estables en agua», mientras que se comportaron de forma muy diferente y muy inestable al nivel de microagregados, de acuerdo a los valores del parámetro «diámetro medio ponderado de los microagregados». La desagregación inducida por la humectación rápida de los agregados (slaking) fue el mecanismo más desestabilizador en estos suelos (el 88% de los suelos presentó índices de estabilidad frente a slaking < 0,5), mientras que la mayoría de los suelos fueron bastante estables frente a la agitación mecánica de lo...

show abstract

“…These comparisons have previously been made by Beuselinck et al (1998) and Buurman et al (1997, who showed that both the strength and the form of the relationships between methods depends on the type of sediment or soil analyzed.…”

Section: Evaluation Of the Laser Diffraction Particle Size Analysis Mmentioning

confidence: 99%

Sedimentary aggregates in the Peoria Loess of Nebraska, USA

Mason

Jacobs

Greene³

et al. 2003

CATENA

View full text Add to dashboard Cite

Loess grain size data used to infer transport direction or wind strength are generally derived from vigorously disaggregated samples. However, these data may not adequately represent the effective particle size distribution during loess transport, if the transported dust contained aggregates of finegrained material. Thin sections of minimally altered C and BC horizons in the late Pleistocene Peoria Loess of Nebraska, USA, indicate the presence of aggregates with diameters of 30 -1000 Am. The larger aggregates (>250 Am) are unlikely to have been transported, and are interpreted as the result of soil faunal activity and other pedogenic processes after deposition. Aggregates smaller than 250 Am could have a similar origin, but laser diffraction particle size analysis suggests that many are sedimentary particles. Comparison of minimally and fully dispersed particle size distributions from each sampling site was used to estimate the modal diameter of aggregates. The aggregate modal diameter becomes finer with decreasing loess thickness, representing increasing distance from the source. A similar trend was observed in the modal diameter of fully dispersed particle size distributions, which represents the mode of sand and silt transported as individual grains. We interpret both trends as the result of sorting during transport, supporting the interpretation that many of the aggregates were transported rather than formed in place. Aggregate content appears to increase with distance from the source, explaining a much more rapid downwind increase in clay content than would be expected if clay were transported as particles smaller than 2 Am diameter. this loess were transported as primary particles, were thoroughly exposed to sunlight and are potentially well suited for luminescence dating. D

show abstract

Laser Grain-Size Determination in Soil Genetic Studies 1. Practical Problems

Cited by 161 publications

References 4 publications

Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features

Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features

Macro- and micro-aggregate stability of soils determined by a combination of wet-sieving and laser-ray diffraction

Sedimentary aggregates in the Peoria Loess of Nebraska, USA

Contact Info

Product

Resources

About