土壤微团聚体中矿物-有机复合体特征

以国家肥力网湖南祁阳红壤长期定位试验站的长期施有机肥和长期施化肥的土壤为研究对象,采用干筛法获得土壤微团聚体。利用同步辐射红外显微成像法研究土壤微团聚体中黏土矿物和有机官能团的原位分布图谱及其相关性。结果表明:土壤中黏土矿物(3 620 cm-1)和大分子有机物(脂肪,2 920 cm-1;蛋白质,1 650 cm-1;多糖,1 080 cm-1)呈高度异质性的分布规律。其中,黏土矿物和多糖有较为相似的分布模式;而黏土矿物和脂肪、蛋白类物质则呈现差异较大的分布模式。与长期施化肥处理的土壤微团聚体相比,长期施有机肥处理的土壤微团聚体中黏土矿物和大分子有机物呈现更高的分散性。此外,施有机肥和化肥处理土壤微团聚体样品中黏土矿物与有机官能团的决定系数(R2)均为:黏土矿物-脂肪黏土矿物-多糖黏土矿物-蛋白质,表明土壤微团聚体中黏土矿物和大分子有机物的亲和性有差异,且该差异不受长期施肥处理的影响。同步辐射微区域红外谱进一步表明,从土壤微团聚体外部到内部,黏土矿物的特征峰和大分子有机物的特征峰强度均逐渐增加。     

Improved analysis and modelling of soil diffuse reflectance spectra using wavelets

Diffuse reflectance spectroscopy using visible (vis), near‐infrared (NIR) and mid‐infrared (mid‐IR) energy can be a powerful tool to assess and monitor soil quality and function. Mathematical pre‐processing techniques and multivariate calibrations are commonly used to develop spectroscopic models to predict soil properties. These models contain many predictor variables that are collinear and redundant by nature. Partial least squares regression (PLSR) is often used for their analysis. Wavelets can be used to smooth signals and to reduce large data sets to parsimonious representations for more efficient data storage, computation and transmission. Our aim was to investigate their potential for the analyses of soil diffuse reflectance spectra. Specifically we wished to: (i) show how wavelets can be used to represent the multi‐scale nature of soil diffuse reflectance spectra, (ii) produce parsimonious representations of the spectra using selected wavelet coefficients and (iii) improve the regression analysis for prediction of soil organic carbon (SOC) and clay content. We decomposed soil vis‐NIR and mid‐IR spectra using the discrete wavelet transform (DWT) using a Daubechies’s wavelet with two vanishing moments. A multiresolution analysis (MRA) revealed their multi‐scale nature. The MRA identified local features in the spectra that contain information on soil composition. We illustrated a technique for the selection of wavelet coefficients, which were used to produce parsimonious multivariate calibrations for SOC and clay content. Both vis‐NIR and mid‐IR data were reduced to less than 7% of their original size. The selected coefficients were also back‐transformed. Multivariate calibrations were performed by PLSR, multiple linear regression (MLR) and MLR with quadratic polynomials (MLR‐QP) using the spectra, all wavelet coefficients, the selected coefficients and their back transformations. Calibrations by MLR‐QP using the selected wavelet coefficients produced the best predictions of SOC and clay content. MLR‐QP accounted for any nonlinearity in the data. Transforming soil spectra into the wavelet domain and producing a smaller representation of the data improved the efficiency of the calibrations. The models were computed with reduced, parsimonious data sets using simpler regressions.     

接种蚯蚓与添加有机物料对茶园土壤结构的影响

蚯蚓通过取食、排泄、分泌黏液、挖掘洞穴等活动,可显著改善土壤结构,提高土壤肥力.为探究蚯蚓与有机物料不同配施方式对茶园土壤肥力的调控效果与机理,设计5个处理组:不施肥(CK),不施肥+蚯蚓(BE),菜籽饼+蚯蚓(CE),茶树修剪物+蚯蚓(JE),生物质炭+蚯蚓(TE),分别进行室内模拟实验.结果显示,与不施肥(CK)相...     

Proximal soil sensing of soil texture and organic matter with a prototype portable mid‐infrared spectrometer

Recent advances in semiconductor technologies have given rise to the development of mid‐infrared (mid‐IR) spectrometers that are compact, relatively inexpensive, robust and suitable for in situ proximal soil sensing. The objectives of this research were to evaluate a prototype portable mid‐IR spectrometer for direct measurements of soil reflectance and to model the spectra to predict sand, clay and soil organic matter (SOM) contents under a range of field soil water conditions. Soil samples were collected from 23 locations at different depths in four agricultural fields to represent a range of soil textures, from sands to clay loams. The particle size distribution and SOM content of 48 soil samples were measured in the laboratory by conventional analytical methods. In addition to air‐dry soil, each sample was wetted with two different amounts of water before the spectroscopic measurements were made. The prototype spectrometer was used to measure reflectance (R) in the range between 1811 and 898 cm^?1 (approximately 5522 to 11 136 nm). The spectroscopic measurements were recorded randomly and in triplicate, resulting in a total of 432 reflectance spectra (48 samples × three soil water contents × three replicates). The spectra were transformed to log₁₀ (1/R) and mean centred for the multivariate statistical analyses. The 48 samples were split randomly into a calibration set (70%) and a validation set (30%). A partial least squares regression (PLSR) was used to develop spectroscopic calibrations to predict sand, clay and SOM contents. Results show that the portable spectrometer can be used with PLSR to predict clay and sand contents of either wet or dry soil samples with a root mean square error (RMSE) of around 10%. Predictions of SOM content resulted in RMSE values that ranged between 0.76 and 2.24%.     

黄土的红外反射光谱与红外光声光谱特征及其差异研究

红外光谱法作为一种新的研究手段已经广泛应用于土壤分析,由其检测区域和手段的不同又可分为多种光谱类 型。本研究以第四纪黄土为例,系统地比较了近红外区和中红外区反射光谱和光声光谱的吸收特征及其差异。结果表明,中红外光谱比近红外光谱的信息更为丰富,且中红外光谱与样品中物质的特征吸收关系更加密切,从而更有利于土壤定性与定量分析。土壤的反射光谱和光声光谱表现出了明显不同的特征,在近红外区,反射光谱和光声光谱吸收明显不同,而在中红外区,反射光谱和光声光谱具有相对应的吸收,但相对吸收强度明显不同,且吸收峰的位置也发生改变,尤其在1 000 ~ 2 000 cm-1谱区,反射光谱相互干扰很强,而光声光谱的吸收特征更为明显。在黄土的分类鉴别上,反射光谱优于光声光谱。红外反射光谱和光声光谱在不同波段下具有不同的吸收灵敏度,在土壤定性与定量分析中各自都将具有其明显的优势。     

Characterization of fungal melanins and soil humic acids by chemical analysis and infrared spectroscopy

Summary Humic acids from two Brazilian topsoils under savanna grassland and five soil fungal melanins were characterized by elemental, functional group and infrared analysis. C, N, total acidity, COOH, and phenolic OH contents were within the ranges reported for several other fungal melanins and soil humic acids. Compared with the soil humic acids, the infrared spectra of the fungal melanins showed greater detail, indicative of higher aliphaticity. They were similar to the type III infrared spectra of humic acids, which are characteristically high in proteinaceous material and polysaccharides. The infrared spectra of the humic acids from the two Brazilian soils studied were classified as type I, which includes most soil humic acids. Notwithstanding the greater detail, in some areas the fungal melanin spectra were similar to those reported for other fungal melanins and humic acids of different origins. The probable contribution of the melanic fungi to the formation of soil humic polymers is discussed.     

基于红外光声光谱的蒙脱石-黄原糖复合体界面层特征研究

黏土矿物-有机物复合体在土壤中具有重要的作用,而土壤黏土矿物-多糖复合体是黏土矿物-有机物复合体形成的前体,有利于复合体的形成和转化,但其具体的作用机制尚不清楚。本研究制备了蒙脱石-黄原糖模型复合体,采用X-衍射分析了复合体的结构信息,并利用傅里叶转换红外光声光谱原位逐层扫描功能,探测了蒙脱石-黄原糖复合体表面下不同深度的光谱信息。结果表明,蒙脱石与黄原糖的相互作用主要发生在蒙脱石的表面,并形成表面界面层;该界面层具有明显的红外光声光谱特征,所形成的复合体有更强的持水能力,且表层与亚表层的光谱信息明显不同;红外光声光谱逐层分析表明,蒙脱石-黄原糖复合体界面层厚度大约在2.05～6.47μm之间。本结果为揭示复杂的矿物-有机物复合体形成过程及其影响因素提供了定量依据。     

Using soil knowledge for the evaluation of mid‐infrared diffuse reflectance spectroscopy for predicting soil physical and mechanical properties

Mid‐infrared diffuse reflectance spectroscopy can provide rapid, cheap and relatively accurate predictions for a number of soil properties. Most studies have found that it is possible to estimate chemical properties that are related to surface and solid material composition. This paper focuses on prediction of physical and mechanical properties, with emphasis on the elucidation of possible mechanisms of prediction. Soil physical properties that are based on pore‐space relationships such as bulk density, water retention and hydraulic conductivity cannot be predicted well using MIR spectroscopy. Hydraulic conductivity was measured using a tension‐disc permeameter, excluding the macropore effect, but MIR spectroscopy did not give a good prediction. Properties based on the soil solid composition and surfaces such as clay content and shrink‐swell potential can be predicted reasonably well. Macro‐aggregate stability in water can be predicted reasonably as it has a strong correlation with carbon content in the soil. We found that most of the physical and mechanical properties can be related back to the fundamental soil properties such as clay content, carbon content, cation exchange capacity and bulk density. These connections have been explored previously in pedotransfer functions studies. The concept of a spectral soil inference system is reiterated: linking the spectra to basic soil properties and connecting basic soil properties to other functional soil properties via pedotransfer functions.     

反射光谱估算滨海土壤黏粒含量

探明反射光谱估算土壤黏粒含量的成因是实现黏粒含量测定、提高估算精度的基础。该文以江苏省滨海平原的150个土壤样品为研究对象,将测得的原始光谱数据进行平滑、一阶导数、连续统去除和倒数等数据变换,采用逐步多元线性回归(stepwise multiple linear regression,SMLR)和偏最小二乘回归(partial least squares regression,PLSR)方法估算黏粒含量,并在此基础上分析建模的影响波段,探讨反射光谱估算土壤黏粒含量的成因。结果表明,连续统去除光谱数据的SMLR分析估算精度最高,建模集和验证集决定系数分别为0.941和0.750。360~900、1 800~2 490 nm是黏粒含量的重要建模影响波段,该建模影响波段主要包括铁离子(410 nm附近)、土壤有机质(500~800 nm)、层状硅酸盐中的结晶水(1 900 nm附近)、绿泥石和蛭石等黏土矿物(2 325 nm)的吸收特征波段;PLSR分析表明,1 400 nm附近回归系数出现的双峰特征源于高岭石的双峰吸收。黏粒中的黏土矿物、黏粒对铁离子的吸附特性以及黏粒与有机质的高度相关性是实现反射光谱估算滨海土壤黏粒含量的原因。     

苏北滨海土壤碳酸钙含量反射光谱估算研究

土壤属性的快速、精确测定是实现现代精细农业的基础。本研究分析了江苏省北部滨海土壤的属性特征以及碳酸钙的可见-近红外反射光谱特征,探讨利用可见-近红外光谱估算滨海土壤碳酸钙含量的可行性,比较不同光谱反射率数据集、不同预处理方法以及不同建模方法定量反演的优劣。结果表明:(1)苏北滨海土壤有机质含量较低、碳酸钙含量较高,其光谱曲线在2 340 nm处有较明显的碳酸钙吸收特征;(2)滨海土壤碳酸钙含量与土壤的可见-近红外波段反射率呈正相关,且碳酸钙含量高低对于土壤的近红外波段反射率的影响高于可见光波段;(3)可见-近红外反射光谱可用于估算滨海土壤碳酸钙含量。就建模结果而言,381~2 459 nm波段反射光谱数据集、log(1/R)预处理、偏最小二乘回归三者结合的效果比较理想。     

Predicting soil properties from the Australian soil visible–near infrared spectroscopic database

There are reflectance spectra in the visible and near infrared wavelengths from some 20 000 archived samples of soil in Australia. Their particular forms depend on absorbances at specific wavelengths characteristic of components in the soil such as water, iron oxides, clay minerals and carbon compounds, and so one might expect to be able to predict soil properties from the spectra. We tested a tree‐based technique for the prediction of 24 soil properties. A tree is first constructed by the definition of rules that separate the data into fairly homogeneous groups for any given property on both the absorptions at specified wavelengths and other, categoric, variables. Then within each group the property is predicted from the absorptions at those wavelengths by ordinary least‐squares regression. The spectroscopic predictions of the soil properties were compared with actual values in a subset of sample data separated from the whole data for validation. The criteria of success that we used were the root mean squared error (RMSE) to measure the inaccuracy of our predictions, the mean error (ME) to measure their bias and the standard deviation of the error (SDE) to measure their imprecision. We also used the ratio of performance to deviation (RPD), which is the ratio of the standard deviation of the observed values to the RMSE of the predictions; the larger it is the better does the technique perform. We found good predictions (RPD>2) for clay and total sand content, for total organic carbon and total nitrogen, pH, cation exchange capacity, and exchangeable calcium, magnesium and sodium. Several other properties were moderately well predicted (1.5 ≤ RPD < 2); they included air‐dry water content, volumetric water content at field capacity and wilting point, bulk density, the contents of silt, fine sand and coarse sand, total and exchangeable potassium, total phosphorus and extractable iron. Properties that were poorly predicted (RPD < 1.5) include the carbon‐to‐nitrogen ratio, available phosphorus and exchangeable acidity. We conclude that even though the predictions are less accurate than direct measurements, the spectra are cheap yet valuable sources of information for predicting values of individual soil properties when large numbers of analyses are needed, for example, for soil mapping.     

Sample preparation and selection for qualitative and quantitative analyses of soil organic carbon with mid‐infrared reflectance spectroscopy

Mid‐infrared spectroscopy (MIRS) is a well‐established analytical tool for qualitative and quantitative analysis of soil samples. However, effects of soil sample grinding procedures on the prediction accuracy of MIR models and on qualitative spectral information have not been well investigated and, in consequence, not standardized up to now. Further, the effects of soil sample selection on the accuracy of MIR prediction models has not been quantified yet. This study investigated these effects by using 180 well‐characterized soil samples that were ground for different times (0, 2 or 4 minutes) and then used for MIR measurements. To study the impact of sample preparation, soil spectra were subjected to principal component analyses (PCA), multiple regression and partial least square (PLS) analysis. The results indicate that the prediction accuracy of MIR models for soil organic carbon (SOC) and pH and the qualitative spectral information were better overall for lightly ground (2 minutes) soil samples compared with intensively (4 minutes) or unground soil samples. Whereas the grinding procedure did not show any effect on spectra of clay minerals, spectral information for quartz and for SOC was modified. Even though it is difficult to recommend a global standardized soil sample grinding procedure for MIR measurements because of different mill types available within laboratories, we highly recommend using an internally standardized grinding procedure. Moreover, we show that neither land use nor soil sampling depth influences the prediction of the SOC content. However, sand and clay content substantially affect the score vectors used by the PLS algorithm to predict the SOC content. Thus, we recommend using soil samples similar in texture for more precise SOC calibration models for MIR spectroscopy.     

Discrimination of Australian soil horizons and classes from their visible–near infrared spectra

A soil's reflectance spectrum in the visible and near infrared is rich in information. It is an integrative property of the soil that measures its colour, the abundance of iron oxides, clay minerals and carbonates, the amount of water and organic matter and its particle size. We explored the merit of discriminating between soil horizons, of which we had 13 654 samples, and soil orders from the Australian Soil Classification, of which we had samples from 1697 profiles with designated horizons, by analysing quantitatively their diffuse reflectance spectra in the visible‐near infrared (vis–NIR) range (350–2500 nm). We re‐sampled the spectra to 10‐nm intervals and converted them to logarithms of deviations from their convex hulls. We then transformed them to canonical variates, which we display as scatter diagrams in low‐order canonical planes. The minerals, colour and organic constituents thought to be responsible for their discrimination are identified. Each spectrum was re‐examined and allocated to the group whose centroid was nearest in the canonical space. Topsoil horizons (A, A2 and transitional AB and AC horizons) were distinguishable from subsoils (B, C and transitional BC horizons). Vertosols, Ferrosols, Podosols (Podzols), Organosols, Calcarosols, Rudosols, Sodosols, Hydrosols, Kandosols and Kurosols were in general well separated from other soil orders and were assigned to their own orders such that 80% or more were correctly allocated. These orders possess characteristics that are easily distinguished by vis–NIR spectroscopy. Re‐allocations to other orders were interpretable and could be related to identifying features of the ASC classification. Our results show that spectra distinguish soil horizons and soil type. They suggest that vis–NIR spectroscopy could make an important contribution to the definition and identification of classes in an effective system of soil classification.     

基于近红外光谱和正交信号-偏最小二乘法对土壤的分类

不同质地的土壤,由于蓄水能力和土壤颗粒大小的不同使得其光谱特性不同,这为采用近红外光谱技术对土壤质地进行判别分析提供了依据。该研究利用正交信号校正(OSC)方法可以获得与浓度有关的谱图信息这一优势,将其与偏最小二乘方法(PLS)结合,采用近红外光谱技术对不同质地的土壤:砂土、壤土、黏土进行判别分析。结果表明:建模样本的相关系数可达0.965,采用该模型对其余45个样本分别进行了预测,三种土壤预测样本的判别正确率分别为:93.3%,86.6%和86.6%。说明OSC方法可以提取谱图中的微弱的质地信息,实现土壤质地的快速鉴别分析。     

Fertilization effects on organic matter in physically fractionated soils as studied by 13C NMR: Results from two long-term field experiments

^l3C–nuclear magnetic resonance (NMR) spectra taken using magic–angle spinning (MAS), cross polarization (CP) and with total suppression of side bands (TOSS) are reported for soils from two long–term field experiments. One set of soils was from the Broadbalk Experiment at Rothamsted, UK (monoculture of winter wheat since 1843) and the other was from the Lermarken site of the Askov Long–Term Experiment on Animal Manure and Mineral Fertilizers (arable rotation since 1894). At both sites soil samples were taken from three fertilizer treatments: nil, inorganic fertilizers, animal manure. Spectra were obtained from whole soil samples and from the size fractions clay (<2 μrn), silt (2–20 μm) and, in some cases, sand (20–2000 μm). Comparison of the total strengths of the ¹³C–NMR signal for each size separate in relation to its total organic C content shows that clay, particularly, contains large percentages of C not detected by NMR because of the large magnetic susceptibilities of the soil minerals. It is proposed that the observed signals come from the more labile pools of soil organic matter (SOM), on the presumption that these pools are less closely associated with soil minerals and iron oxides and are likely to be less protected from microbial or enzymic decomposition. For both Rothamsted and Askov, functional groups in the 45–110 ppm region (N– and O–alkyls) dominate in the spectra for whole soils, with aromatics (110–160 ppm) and alkyls (0–45 ppm) signals being the next prominent. In the Askov whole soil samples ¹³C–NMR revealed no differences between nil, inorganic fertilizer and animal manure treatments but in the Rothamsted whole soil there were some small differences. Clay and silt fractions from Askov contain more alkyls and less aromatics than those from Rothamsted. For both sites clay in enriched in alkyls and depleted in aromatics relative to silt. Clay from Askov, but not Rothamsted, contains more N–alkyls (45–65 ppm) and less acetals (90–110 ppm) than silt. O–alkyls (65–90 ppm) account for more than 20% of the total signal in clay and silt from both sites. Fertilization regimes have not significantly affected the chemical composition of SOM associated with clay– and silt–sized fractions in the soils at either site. We conclude that the chemical composition of SOM is determined primarily by the interaction between the organisms responsible for decomposition and the mineral soil matrix rather than the nature of substrate input.     

Organo-clay formulation of acetochlor for reduced movement in soil.

This study aimed to design ecologically acceptable formulations of acetochlor by adsorbing it on montmorillonite exchanged by a small organic cation, phenyltrimethylammonium (PTMA). Adsorption of acetochlor on the clay mineral exchanged with different organic cations and its release from these complexes were determined by GC and modeled by Langmuir equation. Interactions between acetochlor molecules and the exchanged organic cation on the clay surface were studied by Fourier transform infrared spectroscopy. Leaching of acetochlor in soil was determined by a bioassay using a column technique and Setaria viridis as a test plant. The adsorbed amounts of acetochlor on montmorillonite exchanged by PTMA at a loading of 0.5 mmol/g of clay were higher than at a loading up to the cation-exchange capacity, i.e., 0.8 mmol/g, and were higher than obtained by using a clay mineral exchanged by other organic cations. Preloading montmorillonite by PTMA at 0.5 mmol/g yielded maximal shifts of the infrared peaks of the herbicide. The above formulation of acetochlor yielded slow release in water and showed improved weed control in field and greenhouse experiments in comparison with the commercial formulation. The PTMA-clay formulation of acetochlor maintained herbicidal activity in the topsoil and yielded the most significant reduction in herbicide leaching and persistence under field conditions. The application of this formulation can minimize the risk to groundwater and can reduce the applied rates.     

南极Fildes半岛成土过程中不同时期的岩石风化趋势

From the view of energy state of material,this paper introduces a concept a concept of weathering potential in carrying out quantitative calculation of the relevant products at different stages of rock-weathering and primary soil-forming processes,elaborates respectively on weathering degree in the bio-weathering layer of rocks and during the formation of soil material and clay,and evaluats the further tendency of weathering in the above-mentioned stages.The authors have discovered that the scales of weathering potential of the materials increase successively in the three stages,which indicates that the products in the above-mentioned three stages must have undergone stronger and stronger weathering in the primitive forming process of soil in Fildes Peninsula,Antarctic.But,Because of relatively weak chemical weathering,it is reasonable that there are much more skeleton grains and little clay in priamry soils in this region.Meanwhile the authors have also verified that the weathering potential of crde rock determines to some extent decrease in the products‘ weathering potential in the different stages in primary soil-forming,thereby plays an important role in the genesis and development of the primary soil in the studied area.     

青海省东部山区旱作农田土壤团聚体特征研究

比较了青海省东部山区垂直梯度分布的三种旱作农田土壤(黑钙土、栗钙土、灰钙土),在0~60 cm土层的不同粒级土壤风干团聚体和水稳性团聚体含量间的差异,并结合其它土壤质量指标(有机质、粘粒)对不同土壤结构和抗侵蚀能力进行了综合评价。结果表明,>0.25mm风干团聚体、>0.25mm水稳性团聚体含量和土壤有机质含量与土壤类型间有密切关系。均表现为黑钙土>栗钙土>灰钙土。黑钙土和栗钙土的土壤有机质含量与>0.25mm水稳性团聚体间存在显著正相关关系(P<0.05),灰钙土则无明显相关性;三种土壤粘粒含量与>0.25mm风干团聚体和0.25mm水稳性团聚体含量间无明显相关性。各项指标综合比较,三种土壤抗侵蚀能力大小为:黑钙土>栗钙土>灰钙土。     

The over-estimation of clay and the under-estimation of pores in soil thin sections

The amounts of clay visible in four thin sections from paleosol horizons (clay contents 9–32%) were measured by point counting. These sections were used as references for visual estimates, without point counting, of the amounts of clay in 14 further sections. The measurements and estimates were recorded on pore-free and gravel-free bases so they could be related to gravimetric analyses. Amounts of clay measured and estimated by area in these thin sections were between 1.6 and 3.1 times those determined gravimetrically. The reasons for these differences are discussed. Firstly, clay in soil thin sections contains much pore space beyond the resolution of the optical microscope and has an apparent density dependent on the amount of submicroscopic pore space. An edge effect also causes over-estimation of clay in soil thin sections and under-estimation of visible pore space. Components (clay, mineral grains, pores) are usually sloped at their borders with each other within the standard 25–30 μm (three-dimensional) thin sections. Clay, for instance, may overcap a pore at its border, hiding some pore space. The need for true two-dimensional images of soil pore patterns in image analysis is indicated. A nomogram has been constructed, using apparent density, to allow estimation of clay in thin sections of soils with any clay content. Coarse/fine ratios can be determined more accurately and estimates of clay can also be recalculated to provide illuvial to total clay ratios that are more meaningful. It is recommended that the micromorphological identification criterion for the argillic horizon be reassessed and that 4% illuvial to total clay in a soil thin section be adopted as the diagnostic cut-off.     

Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements

Reflectance spectroscopy provides an alternate method to classical physical and chemical laboratory soil analysis for estimation of a large range of key soil properties. Techniques including classical chemometrics approaches and specific absorption features studies have been developed for deriving estimates of soil characteristics from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance measurements. This paper examines the performances of two distinct methods for clay and calcium carbonate (CaCO₃) content estimation (two key soil properties for erosion prediction) by VNIR/SWIR spectroscopy: i) the Continuum Removal (CR) has been used to correlate spectral absorption bands centred at 2206 and 2341 nm with clay and CaCO₃ concentrations and ii) the partial least-squares regression (PLSR) method with leave-one-out cross-validation, which is a classical chemometrics technique, has been used to predict clay and CaCO₃ concentrations from VNIR/SWIR full spectra. We tried to respond to the question “should we use all bands in the 400-2500 nm range or should we focus our analysis on selected spectral absorption bands to determine soil properties from reflectance data?” In this paper, the CR and PLSR methods were applied to VNIR/SWIR laboratory and airborne HYMAP reflectance measurements collected over the La Peyne Valley area in southern France.This study shows that the performance of both techniques is dependent on the spectral feature for the soil property of interest and on the level data acquisition (lab or airborne) face to the instrument specifications. When airborne HYMAP reflectance measurements are used, the PLSR technique performs better than the CR approach. As well, when the soil property of interest has no well-identified spectral feature, which is the case of clay, the PLSR technique performs better than the CR approach. In this last situation, PLSR is able to find surrogate spectral features that retain satisfactory estimations of the studied soil properties. However, parts of these spectral features remain difficult to explain or relate to area-specific correlations between soil properties, which means that extrapolation to larger pedological contexts must be envisaged with care. In the near future, VNIR/SWIR airborne hyperspectral data processed by the PLSR technique will allow for accurate mapping of clay and CaCO₃ contents, which will contribute significantly to the digital mapping of soil properties.