李家岗下蜀黄土剖面的反射光谱研究

采用色度学方法,系统研究了下蜀黄土典型剖面的反射光谱特征。结合磁化率、微量元素Ｒｂ、Ｓｒ的含量和比值,讨论了色度参数的古气候意义,初步把下蜀黄土形成以来的古气候划分为３个波动旋回。下蜀黄土和黄土高原色度参数的对比,揭示了长江中下游地区更强的化学风化作用和成壤强度。     

新书《土壤红外光声光谱原理及应用》介绍

中国科学院南京土壤研究所杜昌文著的《土壤红外光声光谱原理及应用》一书已于2012年5月由科学出版社出版。全书41.0万字,318页,每册定价88元,共分五章。土壤分析是土壤学研究中的常规性工作,现代农业对土壤信息的需求量十分巨大,传统的化学分析方法很难适应海量的土壤数据获取(土壤数字化),而仪器分析的方法则为海量土壤信息的获取提供了可能。     

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。     

土壤剖面的反射光谱研究

研究表明，土壤反射光谱包含有丰富的土壤信息，可从中获取有机质含量、氧化铁含量、质地、主导粘土矿物类型等多种有用信息。本文以不同地区的土壤剖面为例，解读它们的反射光谱，以获得土壤形成特征的某些信息，为在土壤研究中进一步应用反射光谱提供有益的探索。     

土壤的多角度偏振反射光谱研究

在利用多波段、多时相、高光谱的遥感数据来提高遥感对地物的识别能力的同时[1] ,人们注意到角度信息在遥感图像识别和分类中起到的影响和贡献[2 ] ,即地物在2π空间上的三维光谱特征。在早期的遥感,主要采取垂直收集对地观测数据。根据不同的地物具有不同的吸收、反射和发射电     

水稻冠层光谱反射特征及其与叶面积指数关系研究

在水稻试验小区,通过人为控制的方法造成施N水平的差异,对水稻整个生长期内冠层光谱进行了比较系统、密集的测定,并测定了水稻几个重要生育期的叶面积指数。结果表明:随着施N水平的提高,水稻冠层光谱在各生育期呈现出一定的规律性,在近红外部分(760 ~ 1220 nm),冠层光谱反射率随着施N水平的提高而升高,而在可见光部分(460 ~ 710 nm),水稻冠层的光谱反射率反而逐渐降低。冠层光谱经差异显著性检验发现:水稻灌浆期以前,对施N水平最为敏感的波段是绿光(560 ~ 610 nm)和近红外(710 ~ 760 nm)部分;转换为归一化植被指数(NDVI)以后,差异最显著的是 (R760 - R560) / (R760 R560)。对叶面积指数与冠层光谱反射率的相关分析结果表明:在水稻抽穗期以前,叶面积与冠层光谱反射率相关性较差;而抽穗期以后,二者有较好的相关性。     

不同傅里叶变换红外光谱法研究土壤光谱特征的比较与应用

为了将傅里叶变换红外光谱技术更好地应用于土壤中官能团的定量分析,通过比较3种不同傅里叶变换技术下土壤特征吸收峰的差异,来选取最佳的光谱技术应用于土壤的相关研究。采用透射(T-FTIR)、衰减全反射(ATR-FTIR)和漫反射(DR-FTIR)3种光谱技术分别对有机物(苯甲酸、硬脂酸)和土壤(辽东栎)进行了分析。并将辽东栎和草地土壤样品按不同比例混合,使用T-FTIR和DR-FTIR对混合土样进行光谱测定,用于定量分析研究。结果表明:(1)有机物样品在3种光谱技术中均出现特征吸收峰,苯甲酸在1 600～1 400 cm^-1出现苯环C=C骨架特征峰,硬脂酸在2 900～2 800 cm^-1显现甲基的特征峰。有机物中羧酸-COOH内羰基-C=O在1 720～1 680 cm^-1出现伸缩振动吸收峰,羟基-OH分别在1 430～1 410 cm^-1,940～930 cm^-1附近出现面内和面外弯曲振动吸收峰。有机物在T-FTIR技术中需要用溴化钾(KBr)对其稀释。(2)辽东栎土壤样品在T-FTIR和DR-FTIR技术测试中发现,其土壤谱图中有较多有效特征吸收峰,土壤样品在T-FTIR技术中也需要用KBr进行稀释并使样品均匀的分布在锭片中; 而ATR-FTIR技术测试中仅出现个别有效特征吸收峰,不利于对土壤谱图鉴别与进一步分析。(3)辽东栎和草地土壤样品按不同比例混合的测试结果表明:T-FTIR和DR-FTIR技术测试中质量分数与峰面积比呈正相关,线性拟合分别为R²=0.70和R²=0.88。土壤在3种不同红外技术中,DR-FTIR光谱具有较好的土壤特征吸收峰,对土壤样品可以不用KBr稀释。测试步骤简单易操作,可用于土壤样品定量分析研究。     

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。     

基于红外衰减全反射光谱的温室土壤盐分特征研究

与传统的露地耕作土壤不同,温室土壤在耕作过程中受较多的人为调控,但在调控的过程中产生了多种问题,如大量施肥导致的土壤盐渍化[1]。因此,研究如何表征温室土壤的离子特征并预测温室土壤的发展是当前设施农业发展所面临的重要问题。常规农化分析只从不同的角度分析温室土壤的特征,很难实现整体上的综合表征。红外光谱能够综合反应土壤的理化性质,在温室土壤研究中有具有明显的特点。常规的透射光谱在研究土壤时存在制样时间长和难以定量的缺点,而衰减全反射红外光谱(ATR-FTIR)则可克服这一缺点,结合化学计量学的方法,能够实现土壤的定性与定量分析[2,3]。红外光谱包含大量化学键信息,在分析时需进行合理的降维,抽取     

应用红外光声光谱技术及支持向量机模型测定土壤有机质含量

快速测定土壤有机质含量对作物生产和土壤肥力评价具有重要意义,红外光声光谱技术的应用为土壤有机质快速测定提供了可能。本研究以江苏省南京市溧水区水稻土土样为材料,探究了红外光声光谱技术在有机质测定中的应用。采用主成分分析、偏最小二乘和独立成分分析,分别提取了土壤光谱的主成分、偏最小二乘潜变量和独立成分,并以提取的信息输入支持向量机,从而构建了三种支持向量机校正模型。同时,偏最小二乘也被用于建立校正模型,作为支持向量机模型的对照。预测结果表明,基于独立成分的支持向量机模型效果最好,预测相关系数R2、均方根误差RMSEP和实际测量值的标准差与光谱模型预测值标准差的比值即RPD值分别为0.808、0.575和2.28。F检验表明,该模型显著优于基于主成分的支持向量机模型,但与基于偏最小二乘潜变量的支持向量机模型,以及经典偏最小二乘模型没有显著差异。t检验表明,各校正模型对有机质的预测结果与化学测定结果没有显著差异。因此,红外光声光谱技术为土壤有机质的快速测定提供了新的技术手段。     

饲料中肉骨粉含量的近红外反射光谱检测方法

收集28份鸡饲料,31份猪饲料,25份牛饲料和肉骨粉7份,在饲料中掺入不同比例(0.5%～6.0%)的肉骨粉,制成分析样本.采用偏最小二乘(PLS)法,分别对光谱进行散射校正、平滑、一阶导数和二阶导数预处理,建立了鸡饲料、猪饲料和牛饲料中肉骨粉含量的近红外定量分析模型.利用验证集样本对定标模型进行了检验,鸡饲料、猪饲料和牛饲料中肉骨粉含量的真值与预测值之间的决定系数分别为0.9694、0.9846和0.9788;标准差分别为0.279、0.252和0.287;相对分析误差分别为5.663、6.865和5.889.结果表明,利用近红外光谱法测定饲料中的肉骨粉含量具有较高的预测精度.     

Influence of simulated rainfall on physical properties of a conventionally tilled loess soil

Rainfall simulations were conducted on a loess derived silt loam soil (Henan province, P.R. China) under conventional tillage. This tillage practice is widespread and involves the turning of the plough layer and the wheat stubble in July (primary tillage), followed by a secondary tillage operation in October. Soil samples were collected and in situ measurements were done before each rainfall simulation in order to analyse soil physical properties after successive simulated rainfall events. The purpose of this study was to determine rainfall induced changes in saturated hydraulic conductivity, bulk density, penetration resistance, water retention and soil erodibility. The results only showed significant differences in soil bulk density and erodibility when applying successive rainfall events. Penetration resistance and water retention (at matric potentials ≤ − 3 kPa) were not significantly affected and soil surface sealing was not observed. This was also confirmed by the infiltration measurements, where no significant differences in saturated hydraulic conductivity were found. From a soil conservation point of view, this study indicated that the primary tillage operation (i.e. ploughing at the beginning of July) is rather disadvantageous: the saturated hydraulic conductivity is not significantly affected, but the soil erodibility is considerably higher in comparison to a consolidated soil. Furthermore, the beneficial effects of the wheat stubble on soil and water conservation are lost by the tillage operation.     

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.     

Soil properties and soil water conditions in the yangjuangou catchment of the chinese loess plateau

Soil properties and soil water conditions were assessed for different land use (forest, arable land, grassland) on a silty Calcaric Regosol in the Yangjuangou Catchment of the Chinese Loess Plateau. The loess here is unimodal, poorly sorted with abundant coarse silt, has very low dry bulk density (1.11?–?1.38?g cm^???3) and little organic carbon content (1.6?–?3.7?g kg^???1). The soils are hydrophilic, have high porosity (0.5?–?0.55 cm^3?cm^???3), unsaturated hydraulic conductivity, and plant available water content (0.34?–?0.4 cm^3?cm^???3). Soil properties are quite uniform in space. Land use had no significant effects on soil properties and soil water conditions.     

土壤颗粒分布参数模型对黄土性土壤的适应性研究

土壤颗粒组成是土壤最基本的物理性质之一,其分布曲线可用来估算土壤的水力学性质,然而对于土壤颗粒分布曲线的完整表达需要借助于参数模型,对于不同类型的土壤,参数模型的拟合效果不尽相同.为了选择能够较好描述黄土性土壤颗粒分布状况的参数模型,该文采用了3个指标--相关系数(R),均方根误差(RMSE)和Akaike信息准则(AIC)值,对3类共10个参数模型(单参数模型2个,二参数模型6个,三参数模型2个)在黄土性土壤上的适应性进行了评价(共828个土壤颗粒分析资料).结果表明:简化的三参数Fredlund模型对黄土性土壤颗粒分布的拟合效果最好,且受质地影响较小,二参数Weibull模型次之,单参数的Jaky模型效果最差.三参数Fredlund模型是估算黄土性土壤颗粒组成的最适宜的模型.     

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.     

黄土高原塿土覆盖层与黏化层的土壤水文效应

黄土高原(土娄)土在《中国土壤系统分类(修订方案)》中属土垫旱耕人为土类的相应亚类,其土壤水分状况是诊断表层所属人为表层类堆垫表层(覆盖层)和诊断表下层(黏化层)的重要诊断特征。以土壤持水性能、蒸发性能和水分移动性能为切入点,对(土娄)土覆盖层和黏化层的土壤水文效应进行研究论证,以期对土垫旱耕人为土类及其亚类的诊断层与诊断特征获取更深层的认识。     

宇宙射线土壤水分观测方法在黄土高原草地植被的应用

宇宙射线土壤水分观测系统(COSMOS)是一种测量直径达600 m以上表层土壤平均含水量的新型土壤水分测量仪器。在黄土高原一片草地植被上测试COSMOS仪器测量土壤水分的效果,并与烘干法及Hydra ProbeⅡ土壤湿度传感器测量结果进行比较。结果表明,COSMOS测量结果与烘干法结果一致性好;与Hydra ProbeⅡ点尺度测量结果存在不同时间段的差别,暗示了黄土高原土壤水分空间变异性及其时间变化。COSMOS仪器能够很好地测量黄土高原破碎表面观测范围内表层平均土壤含水量,并为研究土壤含水量的空间变异性提供了潜在工具。