Near infrared spectroscopy techniques for soil contamination assessment in the Nile Delta

Heavy metals concentration is considered one of the factors directly affecting soil and crop quality and, thus, human health. The objective of the current work was to critically examine the suitability of Vis- NIR (350–2500 nm) measurements for calibration procedures and methods to predict contaminated soil. 25 different sites were selected adjacent to drain Bahr El-Baqar east of Nile Delta. Spectroradiometer ASD was used to measure the spectral reflectance profile of each soil site. The concentrations of three heavy metals (Cr, Mn and Cu) were determined in the studied samples. Stepwise multiple linear regression (SMLR) was used to construct calibration models subjected to the independent validation. The obtained regression models were of good quality (R² = 0.82, 0.75, and 0.65 for Cr, Mn, and Cu, respectively). Thus, Visible and Nearinfrared (Vis-NIR) reflection spectroscopy is cost- and time-effective procedure that can be used as an alternative to the traditional methods of determination of heavy metals in soils.     

Near infrared reflectance spectroscopy (NIRS) could be used for characterization of soil nematode community

Studying soil nematofauna provides useful information on soil status and functioning but requires high taxonomic expertise. Near infrared reflectance (NIR) spectroscopy (NIRS) has been reported to allow fast and inexpensive determination of numerous soil attributes. Thus the present study aimed at assessing the potential of NIRS for determining the abundance and diversity of soil nematodes in a set of 103 clayey topsoil samples collected in 2005 and 2006 from agricultural soils in the highlands of Madagascar.The morphological characterization of soil nematofauna involved extraction through elutriation then counting under binoculars and identification at family or genus level using microscopy, on ca. 150-g fresh soil samples. Taxa were assigned to five trophic groups, namely bacterial feeders, fungal feeders, obligate plant feeders, facultative plant feeders, and omnivores and predators (together). In addition, four ecological indexes were calculated: the Enrichment index, Structure index, Maturity index, and Plant parasitic index.Oven-dried (40 °C) < 2-mm sieved 5-g soil subsamples were scanned in the NIR range (1100-2500 nm), then spectra were fitted to nematofauna data using partial least square regression. Depending on the sample set considered (year 2005, year 2006, or both years), NIRS prediction of total nematode abundance was accurate (ratio of standard deviation to standard error of cross validation, i.e. RPD ≥ 2) or acceptable (RPD ≥ 1.6). Predictions were accurate, acceptable, or quasi-acceptable (RPD ≥ 1.4) for several of the six most abundant taxa, and to a larger extent, for most trophic groups (except facultative plant feeders); but they could not be made for taxa present in a small number of samples or at low abundance. By contrast, NIRS prediction of relative abundances (in proportion of total abundance) was poor in general, as was also the prediction of ecological indexes (except for the 2006 set). On the whole, these results were less accurate than NIRS predictions of soil attributes often reported in the literature. However, though not very accurate, NIRS predictions were worthwhile considering the labor-intensity of the morphological characterization. Most of all, NIRS analyses were carried out on subsamples that were probably too small (5 g) to allow representative sampling of nematofauna. Using larger samples for NIRS (e.g. 100 g) would likely result in more accurate predictions, and is therefore recommended. Scanning un-dried samples could also help improve prediction accuracy, as morphological characterization was carried out on samples not dried after sampling.Examining wavelengths that contributed most to NIRS predictions, and chemical groups they have been assigned to, suggested that NIRS predictions regarding nematofauna depended on constituents of both nematodes and preys’ food. Predictions were thus based on both nematofauna and soil organic properties reflected by nematofauna.     

红外光谱在土壤学中的应用

红外光谱技术在土壤学中已得到较广泛的应用,它能够综合地反映土壤体系的物质组成及其相互作用,为研究土壤中物质循环及其作用过程提供了新的手段。本文回顾了近年来红外光谱技术在土壤学中的应用,包括透射光谱在土壤定性分析中的应用,并重点介绍红外反射光谱与化学计量学相结合的光谱建模技术发展情况及其在土壤定量分析中的应用。同时本文探讨了基于光声效应的红外光声光谱技术,红外光声光谱非常适合用于土壤这种复杂、非透明体系的研究,能够克服传统透射和反射光谱中存在的缺陷,测定快速方便,并具有较高的灵敏度和测量精确度,具有很大的应用潜力。     

Determination of bulk density of soil clod by saturation

A method for the bulk density determination on soil clod is described. Clods are oven-dried, weighed and equilibrated over water saturated sand columns. Total volume of the clod is computed from the volume of its components - solid, and air. Air volume is calculated from the increase in weight of the dry clod on saturation.     

Relationship between particle density and soil bulk chemical composition

Purpose

An analytical database containing XRF chemical analyses and real density measurements of unconsolidated sediments of the Padania Plain (Northern Italy) has been used to understand the relationship that exists between the soil particle density (ρ_s) and their bulk chemical composition.

Materials and methods

Using a linear regression, we built an equation able to link the particle density with the soil elemental composition.

Results and discussion

Positive correlations were found between ρ_s and SiO₂, MgO, CaO and Na₂O and negative correlations with K₂O, TiO₂, Al₂O₃, Fe₂O₃ and LOI, reflecting the presence in the soils of quartz and feldspars/mineral clays respectively.

Conclusions

Our equation is very useful because it helps to know the density properties of a soil when it is not possible to measure ρ_s with a pycnometer. On the other hand, by knowing the ρ_s, it is possible to have a quite precise knowledge about the chemistry of the studied soils.

     

Estimating forest soil bulk density using boosted regression modelling

Soil bulk density (ρ) is an important physical property, but its measurement is frequently lacking in soil surveys due to the time‐consuming nature of making the measurement. As a result pedotransfer functions (PTFs) have been developed to predict ρ from other more easily available soil properties. These functions are generally derived from regression methods that aim to fit a single model. In this study, we use a technique called Generalized Boosted Regression Modelling (GBM; Ridgeway, 2006 ) which combines two algorithms: regression trees and boosting. We built two models and compared their predictive performance with published PTFs. All the functions were fitted based on the French forest soil dataset for the European demonstration Biosoil project. The two GBM models were Model G3 which involved the three most frequent quantitative predictors used to estimate soil bulk density (organic carbon, clay and silt), and Model G10, which included ten qualitative and quantitative input variables such as parent material or tree species. Based on the full dataset, Models G3 and G10 gave R² values of 0.45 and 0.86, respectively. Model G3 did not significantly outperform the best published model. Even when fitted from an external dataset, it explained only 29% of the variation of ρ with a root mean square error of 0.244 g/cm³. In contrast, the more complex Model G10 outperformed the other models during external validation, with a R² of 0.67 and a predictive deviation of ±0.168 g/cm³. The variation in forest soil bulk densities was mainly explained by five input variables: organic carbon content, tree species, the coarse fragment content, parent material and sampling depth.     

土壤容重对土壤物理性状和小麦生长的影响

以黑土和白浆土为试材 ,进行筒栽试验 .结果表明 ,适宜小麦生长的容重范围分别为 1 .1 5～1 .3 0 g/cm3和 0 .9～ 1 .0 5g/cm3.     

容重对土壤水分入渗能力影响模拟试验

通过人工改变土壤颗粒级配,配制典型砂壤、中壤、黏壤,并设置不同容重水平,用土柱积水入渗模拟了土壤容重对其入渗能力的影响,为土壤改良和促进天然降水转化利用提供理论依据。结果表明,容重对土壤入渗能力有较大影响。试验土壤入渗能力随容重增大递减,3种典型土壤稳定入渗速率与容重均呈对数负相关,砂壤120 min累积入渗量与容重呈幂函数负相关,中壤、黏壤则呈线性负相关。考斯加科夫入渗模型中,表征初始入渗速率的参数随容重增大递减,表征入渗能力衰减速度的参数则随容重增大递增,说明土壤初始入渗能力随容重增大递减,入渗能力衰减速度随容重增大递增。     

Building and testing conceptual and empirical models for predicting soil bulk density

The development of pedotransfer functions offers a potential means of alleviating cost and labour burdens associated with bulk‐density determinations. As a means of incorporating a priori knowledge into the model‐building process, we propose a conceptual model for predicting soil bulk density from other more regularly measured properties. The model considers soil bulk density to be a function of soil mineral packing structures (ρ_m) and soil structure (Δρ). Bulk‐density maxima were found for soils with approximately 80% sand. Bulk densities were also observed to increase with depth, suggesting the influence of over‐burden pressure. Residuals from the ρ_m model, hereby known as Δρ, correlated with organic carbon. All models were trained using Australian soil data, with limits set at bulk densities between 0.7 and 1.8 g cm^?3 and containing organic carbon levels below 12%. Performance of the conceptual model (r² = 0.49) was found to be comparable with a multiple linear regression model (r² = 0.49) and outperformed models developed using an artificial neural network (r² = 0.47) and a regression tree (r² = 0.43). Further development of the conceptual model should allow the inclusion of soil morphological data to improve bulk‐density predictions.     

Comparison of clod and core methods for determination of soil bulk density

Abstract

An interagency forest monitoring program has been initiated on a systematic network of forested plots often accessible only by foot traffic along a compass line. Extensive site classification and physiochemistry data are being collected for vegetation and soil indicators of forest health. In order to select a suitable technique for obtaining an estimate of mineral soil bulk density, conventional clod and core methods were compared across a wide range of forest soils within the Coastal Plain of southeastern Virginia. Replicate soil clods and cores were collected from two to four horizons within each of six pedons representing different soil series. Following analysis, the sample data were used to evaluate main and interaction effects due to differences in the method, series, horizon, and texture effects. Differences between the clod and core data were highly significant on average (P < 0.001) as were all of the main effects. Both methods exhibited high precision (average CV < 5%) within the individual horizons sampled. The two data sets were highly correlated (r = 0.98), and the regression equation used to predict clod bulk density with data from the core method is: Clod BD = (1.011 x Core BD) + 0.068; standard errors of ±0.042 and ±0.048 for the slope and intercept, respectively. From an operational standpoint, the core method appears to have many advantages over the clod method for sampling in remote locations.     

体积置换法直接测量土壤质量含水率及土壤容重

土壤含水率直接测量是相关研究和应用的基础,在土壤力学、作物栽培、农田灌溉、生态环境等研究和实践中十分重要。该文提出了一种与传统烘干称质量法相当的体积置换法直接测量土壤质量含水率及土壤容重。该方法在假设一定土壤颗粒密度的前提下,用一定体积的标准取样环刀取得土样后,通过向待测量土体补充水分使土壤达到饱和,用一定体积的水置换土壤中的充气空隙,直到土样达到饱和状态;再通过测量得到的初始/原始土样质量、饱和后土壤的质量以及已知土壤颗粒密度和水密度,计算得到被置换的充气空隙的体积,进而由此计算得到土壤质量含水率和土壤容重。采用3种不同土壤,即陕西杨凌黏黄土、北京粉壤土和江西黏红土,分别预配制成7种不同初始土壤体积含水率,含水率约为:风干土(含水率2%～3%)、5%、10%、15%、25%、30%和饱和含水率,以及3种不同土壤容重:1.25、1.35和1.45g/cm3进行室内试验。用类似的土样,采用传统方法烘干土样8、12、24、48h后,测量确定土壤的质量含水率,通过延长烘干时间测得数据表明,传统方法烘干8h所测得的质量含水率仍有1%～3.2%的含水率误差。最终试验结果表明体积置换方法测得的土壤含水率比传统烘干土样8h所测得的结果大2%～3%,比烘干土样48h所测得的结果大1%左右。体积置换方法测量操作过程简单,耗时较少,节约能源,测量结果具有较高精度。     

Soil condition classification using infrared spectroscopy: A proposition for assessment of soil condition along a tropical forest-cropland chronosequence

Soil fertility depletion in smallholder agricultural systems in sub-Saharan Africa presents a formidable challenge both for food production and environmental sustainability. A critical constraint to managing soils in sub-Saharan Africa is poor targeting of soil management interventions. This is partly due to lack of diagnostic tools for screening soil condition that would lead to a robust and repeatable spatially explicit case definition of poor soil condition. The objectives of this study were to: (i) evaluate the ability of near infrared spectroscopy to detect changes in soil properties across a forest-cropland chronosequence; and (ii) develop a heuristic scheme for the application of infrared spectroscopy as a tool for case definition and diagnostic screening of soil condition for agricultural and environmental management. Soil reflectance was measured for 582 topsoil samples collected from forest-cropland chronosequence age classes namely; forest, recently converted, RC (17 years) and historically converted, HC (ca.70 years). 130 randomly selected samples were used to calibrate soil properties to soil reflectance using partial least-squares regression (PLSR). 64 randomly selected samples were withheld for validation. A proportional odds logistic model was applied to chronosequence age classes and 10 principal components of spectral reflectance to determine three soil condition classes namely; “good”, “average” and “poor” for 194 samples. Discriminant analysis was applied to classify the remaining 388 “unknown” samples into soil condition classes using the 194 samples as a training set. Validation r² values were: total C, 0.91; total N, 0.90; effective cation exchange capacity (ECEC), 0.90; exchangeable Ca, 0.85; clay content, 0.77; silt content, 0.77 exchangeable Mg, 0.76; soil pH, 0.72; and K, 0.64. A spectral based definition of “good”, “average” and “poor” soil condition classes provided a basis for an explicitly quantitative case definition of poor or degraded soils. Estimates of probabilities of membership of a sample in a spectral soil condition class presents an approach for probabilistic risk-based assessments of soil condition over large spatial scales. The study concludes that reflectance spectroscopy is rapid and offers the possibility for major efficiency and cost saving, permitting spectral case definition to define poor or degraded soils, leading to better targeting of management interventions.     

容重对土壤水分蓄持能力影响模拟试验研究

通过人工改变土壤颗粒级配,并设置不同容重水平,测定土壤水分特征参数,研究了容重对土壤水分蓄持能力的定量影响。结果表明:(1)容重对土壤水分特征曲线、比水容量有较大影响,试验土壤各吸力段水分蓄持能力均随容重增大递减,比水容量也随容重增大递减。(2)容重对试验土壤饱和含水量、田间持水量、凋萎系数有较大影响,此3个水分参数均随容重增大递减。饱和含水量与容重呈幂函数负相关关系,田间持水量及凋萎系数均与容重呈指数负相关关系。(3)容重对试验土壤有效水、易效水、迟效水含量有较大影响,此3水分参数均随容重增大递减,分别与容重呈指数、幂函数、对数负相关关系。     

土壤容重测定用分段式原状取土器的设计

为了提高土壤容重测定中土样采集的效率和精准性,将环刀法和原状取土管法结合,进行了分段式原状取土器的研制.该分段式原状取土器主要由取土装置和土样分离装置等组成.与经典环刀法试验对比表明,分段式原状取土器可有效保证所取土样的原状度,并能提高取土效率4～8倍.     

Shear strength of surface soil as affected by soil bulk density and soil water content

This paper proposes a new method to measure the soil strength parameters at soil surface in order to explain the processes of soil erosion and sealing formation. To simulate the interlocks between aggregates or particles within top 2 mm of the soil, a piece of sandpaper (30 particles cm⁻²) was stuck on the bottom face of a plastic box of diameter of 6.8 cm with stiffening glue and used as shear media. The soil strength for the soils from sandy loam to clayey loam was measured with penetrometer and the new shear device at soil surface at different bulk density and soil water content. The normal stresses of 2, 5, 8, 10 and 20 hPa were applied for the new shear device. The results indicated that significant effect of bulk density on soil strength was detected in most cases though the difference in bulk density was small, ranging from 0.01 to 0.09 g cm⁻³. It was also indicated that the measurement with the new shear device at soil surface was reproducible. The changes in soil shear strength parameters due to changes in bulk density and soil moisture were explainable with the Mohr–Coulomb’s failure equation and the principles of the effective stress for the unsaturated soils. The implications of the method were later discussed.     

The calibration of a high resolution gamma-ray transmission system for measuring soil bulk density and an assessment of its field performance

The calibration of a high resolution gamma-ray density probe and a simple experiment comparing the probe with an earlier, lower resolution version are described. An assessment is made of the performance of the probe in three experiments investigating compaction by tractor wheels, two of which were in the field and the third in an indoor soil tank. A linear calibration relationship was obtained, although the addition of a quadratic term improved the fit of the curve slightly. The probe was found to be much more accurate than the earlier version within 100 mm of the soil surface where treatment effects were largest and most numerous in the field experiments, and thin layers of high density could be detected. Over the 15 month period of the experiments, the stability of the system was found to be satisfactory.     

Near infrared spectroscopy for determination of various physical,chemical and biochemical properties in Mediterranean soils

The potential of near infrared (NIR) reflectance spectroscopy to predict various physical, chemical and biochemical properties in Mediterranean soils from SE Spain was evaluated. Soil samples (n = 393) were obtained by sampling 13 locations during three years (2003–2005 period). These samples had a wide range of soil characteristics due to variations in land use, vegetation cover and specific climatic conditions. Biochemical properties also included microbial biomarkers based on phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r²) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r² > 0.90 and RPD > 3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram-positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81 < r² < 0.90 and 2.5 < RPD < 3) were obtained for exchangeable calcium and magnesium, water soluble carbon, water holding capacity and urease activity. Resultant models for protozoa and fungi were not accurate enough to satisfactorily estimate these variables, only permitting approximate predictions (0.66 < r² < 0.80 and 2.0 < RPD < 2.5). Electrical conductivity, pH, exchangeable phosphorus and sodium, metabolic quotient and Gram-negative bacteria were poorly predicted (r² < 0.66 and RPD < 2). Thus, the results obtained in this study reflect that NIR reflectance spectroscopy could be used as a rapid, inexpensive and non-destructive technique to predict some physical, chemical and biochemical soil properties for Mediterranean soils, including variables related to the composition of the soil microbial community composition.     

Critical soil bulk density and strength for pea seedling root growth as related to other soil factors

Bulk density and soil strength are two major soil physical factors affecting root growth of pea seedlings. This study was conducted to determine the influence of soil texture, organic carbon content and water content on critical bulk density and strength. Soil from the plough layer (PL) and beneath the sub-soil (SUB) was used. By soil packing and adjusting the water content between 30% and 100% of field water capacity (FWC) a wide range of bulk density (1.3–1.7 Mg m⁻³) and strength (0.24–6.66 MPa) were obtained. Pea (Pisum sativum L.) was grown in the packed cores of 100 cm³ for 72 h at 20°C. Regression models were developed to explain root growth in terms of bulk density, soil strength, silt and clay (<60 μm) content, organic carbon, and water content. The regression curve of root growth as a function of soil strength showed that 40% of maximum root length can be regarded as an indicator of very poor root growth. By substituting this value into the root growth equations we calculated a critical bulk density and strength in terms of fraction<60 μm, organic carbon percentage and water content. The values of critical bulk density in both layers and of critical soil strength in the sub-soil increased with a decreasing content of fraction<60 μm. Irrespective of fraction<60 μm content, the critical bulk density and strength decreased as soil water content decreased. Critical soil strength was more sensitive than critical bulk density to changes in fraction<60 μm content and water content. This study provides data and a method for predicting critical bulk density and soil strength in relation to other soil properties for pea seedling root growth.