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Environment

利用光谱减法改进土壤有机质的红外光谱表征

Published: January 10, 2019
doi:
10.3791/57464
, ,
1Department of Crop Sciences,University of Illinois Urbana-Champaign, 2Department of Land, Air and Water Resources,University of California Davis, 3Central Great Plains Resources Management Research,USDA ARS

Summary

som 是许多土壤功能和过程的基础, 但 ftir 光谱对其特性的表征往往受到矿物干扰的挑战。该方法利用经验资料, 利用经验资料, 减去土壤光谱中的矿物干扰, 提高了 fsir 光谱分析的效用。

Abstract

土壤有机质 (som) 是许多土壤过程和功能的基础。傅里叶变换红外光谱检测构成土壤有机成分的红外活性有机键。然而, 土壤有机质含量相对较低 (通常 < 按质量划分为 5%), 矿物和有机官能团在中红外 (mir) 区域 (4, 000-400 cm-1) 中吸收重叠,因此主要土壤的有机质含量很大。矿物吸收, 具有挑战性, 甚至阻止解释 som 表征的光谱。光谱减法是一种对光谱的事后数学处理, 它可以通过数学去除矿物吸收物, 减少矿物干扰, 提高与有机官能团相对应的光谱区域的分辨率。这就需要一个富矿参考光谱, 可以通过删除 som 为给定的土壤样本获得经验。从土壤样品的原始 (未经处理的) 光谱中减去富矿参考光谱, 以产生代表 som 吸收率的光谱。常见的 som 去除方法包括高温燃烧 (“灰化”) 和化学氧化。som 去除方法的选择有两个考虑因素: (1) som 去除量, (2) 矿物参考光谱中的吸收伪影, 从而产生减法谱。这些潜在的问题可以而且应该被识别和量化, 以避免对 som 有机官能团组成的光谱进行错误或有偏见的解释。在 som 去除后, 生成的富矿样品用于收集矿物参考光谱。根据实验目标和样本特征, 有几种执行减法的策略, 最显著的是减法系数的确定。由此产生的减法谱需要根据上述方法进行仔细的解释。对于许多含有大量矿物成分的土壤和其他环境样品, 减法在改善 ftir 对有机物成分的光谱表征方面具有很强的潜力。

Introduction

土壤有机质 (som) 是大多数土壤样本中质量较小的成分, 但与土壤功能的多种特性和过程有关, 如养分循环和碳固存1。表征 som 的组成是将 som 的形成和周转与其在土壤功能2、3 中的作用联系起来的几种方法之一。描述 som 成分的一种方法是傅里叶变换红外光谱 (ftir), 它提供了对土壤和其他环境样品 (如羧基 c-o、脂肪族 c-h) 中构成有机物的功能基团的检测4. 然而, ftir 光谱在揭示 som 官能团成分方面的效用受到大多数土壤 (通常 > 95% 质量) 的主要矿物成分的挑战, 因为这些土壤具有很强的无机吸收性, 这也是挑战的原因。严重限制有机吸收的检测和解释。

光谱减法为改善土壤样品中有机物的 ftir 光谱表征提供了一种途径。从土壤光谱中减去矿物吸收, 可用于在 som 成分分析中提高感兴趣的有机功能基团的吸收率

(图 1)。

与标准 ftir 光谱 (即土壤光谱) 相比, 光谱减法的优点包括:

(i) 与正常土壤光谱相比, 有机吸收带的分辨率和解释得到改进。虽然可以通过假设由于有机官能团的不同而导致土壤光谱中的有机带的相对差异来解释土壤光谱中的有机带, 但这限制了对具有相同矿物学和相对较高 som 的样品的比较。含量, 并可能不太敏感的有机带的变化, 即使那些被认为是相对无矿物质的 (例如脂肪性 c-h 拉伸)5

(二) 分析高 som 样品或富含有机物质的提取物或馏分以外的土壤

(三) 突出从中观到场尺度的实验处理引起的变化6

光谱减法在 som ftir 分析中的其他应用包括补充结构和分子特征 (例如, 核磁共振光谱、质谱)5、7, 识别通过萃取或破坏性分馏去除 som 的组合物 8, 并为法医目的对 som 组合物进行指纹识别 9。该方法适用于土壤以外的各种矿物-有机混合物, 包括沉积物10、泥炭11和煤炭12、13。

通过去除有机物以获得矿物参考光谱的实例, 证明了光谱减法在改善 fsom ftir 光谱表征方面的潜力, 然后利用这些矿物参考光谱, 执行和评估理想和非理想光谱减法。本演示的重点是在中红外区域采集的漫反射红外傅立叶变换 (drift) 光谱 (mir, 4, 4, 400 厘米-1), 因为这是分析土壤样本的一种普遍方法4。

获得富矿参考光谱的 som 去除的两种示例方法是 (i) 高温燃烧 (“灰化”) 和 (二) 使用稀次氯酸钠 (naocl) 进行化学氧化。需要注意的是, 这些都是常用的 som 删除方法的示例, 而不是规范性建议。其他 som 去除方法可减少矿物伪影和/或提高去除率 (例如, 低温灰化)14。高温灰化是最初用于获得矿物富集参考光谱以进行减法的方法之一, 最初用于从土壤 (如溶解的有机物、垃圾)中获得的富 om 样品。 16其次是其在散装土壤样品中的应用 17,18。用于去除 som的化学氧化示例是基于 anderson 19 描述的 naocl 氧化方法。这最初是作为在 x 射线衍射 (xrd) 分析之前去除土壤样品中有机物的预处理而开发的, 并被研究为对 som 稳定20敏感的潜在化学分馏,21. 使用 naocl 进行高温去除和化学氧化都可能产生土壤特有的伪影, 并对光谱解释有限制, 在选择 som去除14的方法时应考虑到这一点,22岁

Protocol

1. 准备未经处理的钻井技术和 som 去除土壤 使用不锈钢网 (“细土分数”) 将土壤筛 < 2 毫米。注: 本演示采用了两种质地相似的土壤, 但 som 总含量相差近 3倍 (表 1)。 2. 化学氧化去除 som: 氯化钠的例子 在溶液中向下添加 1m hcl, 同时与 ph 计混合和测量, 将 ph 值为 6% w/v 调整到 ph 9.5。注: 大多数商业漂白剂 (如clorox) 适用于质量和浓度 (通?…

Representative Results

som 去除方法对减法光谱的解释具有实际和理论意义。例如, 高温灰化引起的矿物变化可能表现为峰的损失或外观, 也可以表现为矿物参考光谱中的转移或扩大峰。这些光谱伪影很容易发生在与有机带重叠的区域, 为1600-900 厘米-1,22妥协的解释的有机带。图 2显示了高温灰化 (≥550°c) 后矿物带的常见变化, 包括在 3700-36600 cm-1 时?…

Discussion

删除 som 的方法有两个考虑因素: 1) 删除 som 的数量, 以及 2) 由此产生的矿物参考光谱中的吸收伪影。幸运的是, 有可能—-可以说是必要的—-确定和处理这些问题, 以避免从产生的减法谱对 som 成分进行有偏见的解释。理想情况下, 光谱减法将采用仅有矿物的参考光谱, 以产生 “纯” som 的光谱。在现实中, 所产生的减法谱显示出与 som 相对应的吸收率, 相对于原始 (未经处理的) 土壤谱增强。这是?…

Disclosures

The authors have nothing to disclose.

Acknowledgements

我们赞赏 randy southard 博士关于 naocl 氧化的指导, 以及与 fungai f. n. d. mukome 博士就光谱减法进行的各种讨论。

Materials

Nicolet iS50 spectrometer Thermo Fisher Scientific 912A0760 infrared spectrometer used to collect spectra
EasiDiff Pike Technologies 042-1040 high throughput sample holder
OMNIC Thermo Fisher Scientific INQSOF018 software used to perform subtractions
6% v/v sodium hypochlorite Clorox n/a generic store-bought bleach for oxidative removal of soil organic matter
Type 47900 Furnace VWR International 30609-748 muffle furnace for ashing soils to removal soil organic matter
VWR Gooch Crucibles, Porcelain  VWR International 89038-038 crucibles for ashing
VWR Tube 50 mL Sterile CS500  VWR International 89004-364 for sodium hypochlorite
Forced air oven VWR International 89511-414 for drying soils after oxidation and water washes
VersaStar pH meter Fisher Scientific 13 645 573 for measuring pH of oxidation solution
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Tags

Infrared SpectroscopySoil Organic MatterMineral InterferenceSpectral SubtractionOrganic Carbon QualityWind ErosionSoil CarbonSodium HypochloriteOxidationCentrifugationOven DryingTotal Organic CarbonCombustion Gas Chromatography

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Margenot, A. J., Parikh, S. J., Calderón, F. J. Improving Infrared Spectroscopy Characterization of Soil Organic Matter with Spectral Subtractions. J. Vis. Exp. (143), e57464, doi:10.3791/57464 (2019).
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