A Summary of Research Progress on Bioavailability Assessment Method of Selenium in Soil and Its Influencing Factors
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摘要:
硒是人体必需的微量元素之一。土壤-植物体系是人体摄入硒的主要途径，但尚缺乏准确评价土壤中硒生物有效性的通用方法，且影响因素也复杂多样, 这些问题制约了富硒土地资源的利用。本文通过追踪近年来国内外研究成果，系统地总结及比较了化学提取法、梯度扩散薄膜法、区域尺度硒生物有效性评价方法的优缺点。传统的化学提取法如单一提取和顺序提取在一定程度上能够表征土壤中生物有效性硒，但提取过程中存在影响因素多和提取不完全等问题。梯度扩散薄膜技术(DGT)能够模拟植物的根系吸收过程，相比顺序提取能更好地表征硒的生物有效性，但由于复杂的自然体系和不同元素结合相的差异，野外原位表征技术上仍存在难度。通过大规模的农作物-根系土样本，建立土壤-农作物硒元素评价模型，模型参数为影响土壤硒有效性的理化指标(如土壤酸碱度、有机质含量、土壤硒总量等)，能较好地预测区域尺度上硒生物有效性。本文还总结了影响植物吸收土壤中硒的因素如地形、土壤类型、硒的存在形态、土壤理化性质、植物种类、土壤老化等，认为地形和土壤类型、硒的存在形态、酸碱度和有机质是影响有效硒的主要因素，植物种类与土壤老化为次要因素。完善DGT等原位分析检测技术、改进元素形态分析方法是未来发展的重要方向。
要点(1) 化学提取法和梯度扩散薄膜技术在表征硒生物有效性上仍存在不足。
(2) 区域尺度土壤硒的生物有效性评价模型预测的成功率较高。
(3) 成土母质及土壤理化性质是影响植物吸收土壤硒的主要因素。
HIGHLIGHTS(1) The chemical extraction method and DGT technology are limited in accessing the bioavailability of soil selenium.
(2) The soil selenium bioavailability assessment models are acceptable at the regional scale prediction.
(3) Soil parent materials and soil physicochemical properties play a significant role in determining the uptake of soil selenium by plants.
Abstract: Selenium (Se) is a trace element that plays a crucial role in human health. It has antioxidant, anti-cancer and anti-viral properties and is essential for a healthy body. The level of Se in the human body is largely dependent on daily dietary intake, which is in turn influenced by the amount of Se that enters the food chain from the soil. The global distribution of Se in soil is uneven, with a large difference in concentrations ranging mainly between 0.01-2.0mg/kg. The average abundance of Se in the Earth's crust is 0.07mg/kg, but in some Se-enriched areas, it can reach up to 1200mg/kg. The chemical behavior of Se in soils is complex and diverse, involving processes such as adsorption-desorption, precipitation-dissolution, oxidation-reduction, methylation-demethylation and complexation reactions, each of which affects the bioavailable Se and is influenced and conditioned by factors such as soil pH, soil organic matter, metal oxides, clay and microorganisms. Roots are the primary site for most plants to absorb Se, which is then transported, metabolized, and accumulated. Plants can directly absorb Se from the soil, including Se that exists in the form of free ions, carbonate-bound Se, and Se adsorbed on the surfaces of clay and humus in soil solutions. However, selenite and selenate can be reduced to solid, insoluble Se(0) and metal-Se precipitates that are not bioavailable in locally anaerobic areas (such as soil aggregates) or used by bacteria as terminal electron acceptors.Previous researchers have conducted a lot of work on chemical extraction methods, but there are still problems, such as insufficient extraction specificity and Se form transformation during the extraction process. Hence, an accurate approach for predicting the amount of soil Se that can be absorbed by plants is essential. However there are no clear paths for the choices of assessment methods and influencing factors of soil Se bioavailability. These problems have restricted the utilization of Se-enriched land resources. Thus, providing a scientific basis for the development and utilization of Se-enriched land resources is the goal here by summarizing the main assessment methods and dominant factors on soil Se bioavailability.Determining the activity of Se in soils comprehensively requires considering the complicated and varied effects of natural conditions on its bioavailability, which can be studied through characterization methods and identification of influencing factors. Therefore, it is of practical importance and a challenge to accurately determine the form of Se in soils and assess its bioavailability. Current methods for characterizing the bioavailability of soil Se include the traditional chemical extraction methods (single extraction and sequential extraction) and the emerging Diffusive Gradients in Thin films (DGT) technique. Chemical extraction is a process that involves separating a specific component or substance from a mixture using a solvent or a chemical reagent. The extraction method depends on the physical and chemical properties of the substance being extracted and the nature of the mixture. The general steps involved in a chemical extraction method are: choosing the appropriate solvent or chemical reagent that can selectively dissolve the desired substance while leaving the unwanted components behind, mixing the mixture and the solvent/reagent together to allow the selective extraction of the desired substance, separating the extracted substance from the mixture using various techniques such as filtration, centrifugation, or evaporation, and purifying and isolating the extracted substance by further chemical or physical methods if necessary. The DGT technique is an effective environmental chemistry method used for identifying elements and compounds in various aqueous environments, including natural waters, sediments, and soils. This technique is particularly useful for detecting bioavailable trace elements, and it can be applied for in-situ detection. The DGT technique involves using a specially-designed passive sampler that comprises a binding gel, a diffusive gel, and a membrane filter. The element or compound of interest passes through the membrane filter and diffusive gel before being assimilated by the binding gel in a rate-controlled manner. Subsequently, the binding gel is analyzed post-deployment, enabling the determination of the time-weighted-average bulk solution concentration of the element or compound via a simple equation.The advantages and limitations of chemical extraction methods, DGT technique and bioavailability assessment models of Se at a regional scale are compared. Traditional chemical extraction procedures such as single extraction or sequential extraction can be used to characterize the bioavailability of Se in the soil, to a certain extent. Still, the extraction process has many limits and incomplete extraction problems. The DGT method can be used to simulate the root uptake process of plants and can better characterize the bioavailability of Se compared to sequential extraction. One of the major advantages of the DGT technique is its ability to provide accurate and reliable results, even at low concentrations. Additionally, this technique is non-destructive and can be used in-situ, making it suitable for real-time monitoring of environmental conditions. However, there are also some limitations associated with the DGT technique. For instance, the binding gel used in this method may not be specific to the target element or compound, leading to the possibility of cross-reactivity with other substances. Additionally, the technique may be influenced by factors such as temperature, pH, and ionic strength, which could affect the accuracy of the results. Using large-scale crop-root soil samples, a soil-crop Se assessment model was developed with parameters of physicochemical indicators (e.g. soil pH, soil organic matter, soil Se, etc.), which can better predict Se bioavailability on a regional scale.Some major and minor influencing factors affecting the uptake of Se in soil by plants are discussed. In short, topography and soil type, Se species, pH and organic matter are the main factors affecting bioavailable Se, with plant species and soil aging as secondary factors.In brief, the main limitations of the characterization methods for the bioavailability of different forms of Se are: a single extraction method can be affected by soil properties, soil/solution ratio, extraction time, the pH value of the extraction agent, and other factors. Sequential extraction methods have problems with incomplete extraction, dilution of the extract, and Se loss during centrifugation and filtration. These traditional methods cannot be used to reflect the dynamic processes of the solid-phase soil-solution-root system. DGT technology is a method that disturbs the equilibrium between soil solution and solid phase, simulating the dynamic process of Se uptake by roots, and has advantages in assessing bioavailability. However, it is still questionable whether it can be used to fully predict the replenishment dynamics of Se in field soil. The main factors affecting the bioavailability of soil Se are: (1) Topographical factors such as altitude, slope, and terrain wetness index, which have some influence on soil Se content; there are large differences in organic matter, iron/aluminum hydroxides, and pH among different soil types, which can be controlled to affect Se migration and bioavailability; (2) Soluble and exchangeable Se are more easily absorbed by plants, and selenate with better mobility is easier to absorb, transport, and metabolize in plants than selenite; (3) Increasing soil pH can generally improve Se bioavailability, but this is not the case in organic-enriched soils. Currently, there is no universally applicable method for evaluating soil Se bioavailability, as it is influenced by many factors such as topography, soil type, and soil physicochemical properties. This makes it difficult to compare and verify different results. Improving in-situ DGT analysis technology and modifying the analysis of Se forms are important technical means for accurately evaluating soil Se bioavailability and are also important directions for future development.
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Keywords:
- selenium /
- soil /
- bioavailability /
- influencing factors /
- chemical speciation /
- assessment method
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花岗质岩岩石是地球大陆地壳有别于其他行星的重要标志，且与大量的岩浆-热液矿床在时空和成因上密切相关[1-3]，有关花岗质岩石的形成与演化一直是地质学者研究的热点。花岗质岩石主要矿物组成比较简单，一般由长石、云母和石英组成，但有关其岩石起源与演化一系列问题一直存在激烈的争议。绝大多数情况下，人们大多借助元素和同位素地球化学来限定花岗质岩石成因，如以往常采用全岩的Sr、Nd、Pb等放射成因同位素来进行示踪，遗憾的是这些同位素在很多情况下难以对花岗质岩浆的形成与演化提供明确的制约[4-5]。这是因为全岩同位素示踪存在三个方面的局限性：①岩浆在侵位过程当中如果发生了多次岩浆改造(Modification)，如岩浆混合、围岩同化混染和结晶分异等，Sr-Nd同位素测定值代表的是均一化后某一个时间点(snapshot)的信息，无疑会隐藏许多岩浆来源的信息[6]；②全岩放射成因同位素能够较合理地监测到古老地壳和软流圈地幔物质，但很难监测到年轻物质的具体混入量，因为后者的放射成因子体同位素难以准确测量，而且年轻的幔源岩石或者岛弧火山岩在参与花岗岩形成之前如果遭受热液蚀变，Sr同位素只有少量变化，而Nd和Pb同位素没有变化[4]，故难以准确地判断其源岩性质；③使用全岩放射成因同位素分析问题时，我们通常假定岩石中各矿物相具有相同的来源并且保持同位素平衡，但近年来人们发现一些矿物与其寄主岩石在同位素组成上可以存在很大差别[7]。因此，仅借助全岩放射成因同位素来示踪岩浆来源，许多详细的岩浆来源信息及源岩性质变化细节不能被有效地揭露出来，况且与成矿有关的花岗质岩石常普遍遭受不同程度的热液蚀变，这就给用全岩化学成分限定岩浆起源与形成过程带来了更大难度。
为了攻克这个难题，越来越多的研究者试图利用花岗岩中矿物的元素和同位素来揭示岩石成因和演化过程，但由于侵入岩缓慢的冷却过程，亚固相线下大部分矿物的化学成分得到重新平衡，许多详细的岩石成因信息已经丢失[8]。而副矿物具有难熔、惰性和化学性质稳定等特征，一般不易受后期热事件的影响[8-9]，即使在特定的条件下发生改变，也能通过结构及成分有效地辨别出来[10-12]。同时，副矿物中含有岩石中大部分高场强元素和稀土元素，这些元素和相关同位素在副矿物中扩散速率缓慢，其结晶过程随着岩浆物理化学条件的改变而表现出不同的结构与地球化学特征，甚至能保存元素和同位素环带，被视为岩浆来源和演化过程的监测器，最大限度地保留了岩浆来源与演化过程的地球化学指纹[12-13]。近年来，随着激光剥蚀电感耦合等离子体质谱(LA-ICP-MS)和激光剥蚀多接收等离子体质谱(LA-MC-ICP-MS)等微区原位分析技术的快速发展和日趋成熟，使得对副矿物进行原位成分测定、获得高精度微量元素和同位素组成得以实现，极大地促进了副矿物在岩石成因中的应用[13-14]。如Bruand等[13]通过对副矿物锆石、磷灰石和榍石进行了原位氧同位素分析，识别出古老花岗岩受后期变质作用的影响，而全岩分析无法揭示出来。越来越多的研究表明，副矿物榍石[CaTi(SiO4)O]微区原位元素和Nd同位素组成，也能够详细揭示岩浆来源和岩浆变化的细节，可显著提高岩浆作用过程的空间分辨率，是探讨岩浆来源与岩石成因的新的有效手段，避免了利用全岩分析为我们探讨花岗岩类成因带来的困扰[15-17, 14]。
湘南构造岩浆带是华南地区花岗质岩浆活动的重要组成部分，发育有多个高钾钙碱性花岗闪长质小岩体，如水口山、宝山和铜山岭等，这些闪长质小岩体主要形成于155~160Ma[18-19]，在时空和成因上与铜铅锌多金属成矿密切相关，普遍遭受了不同程度的热液蚀变作用[19-21]。以往基于全岩元素和Sr-Nd-Pb同位素分析，先后提出壳-幔混合成因、残留体再造及中下地壳脱水熔融等多种不同成因模型[22-23]，有关这些花岗闪长质岩体的源区特征及岩浆性质一直存在非常大的争议。本文以铜山岭岩体为对象，在详细的野外和镜下观察基础上，采用电子探针(EPMA)、激光剥蚀等离子体质谱(LA-ICP-MS)技术对暗色包体和花岗闪长岩两种岩石类型中榍石的主量、微量元素进行原位分析，采用激光剥蚀多接收等离子体质谱(LA-MC-ICP-MS)技术分析两类样品中榍石的原位Nd同位素组成，准确限定花岗闪长质岩石形成的源区特征和岩浆物理化学性质，为深入理解该地区花岗闪长质岩石成因及其大规模铜铅锌多金属成矿机制提供重要支撑。
1. 地质背景
湘南位于华夏地块和扬子地块的结合部位，其东为华夏地块，西为扬子地块，是一个极富特色的铜铅锌多金属成矿密集区(图 1a)[24-25]。该地区主要出露的地层为古生界灰岩、碎屑岩[26]。岩浆作用强烈，花岗闪长质小岩体成带状密集分布，区域上自北向南分布的水口山、宝山、铜山岭是该地区铜铅锌多金属成矿有关的花岗闪长质小岩体的典型代表。
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图 1 (a)湘南地区地质简图和(b)铜山岭岩体分布图(据文献Wang等[24]和卢友月等[25]修改)。湘东南的花岗闪长质侵入体位于华夏和扬子地块的结合部位，铜山岭岩体位于湘东南的南部，由Ⅰ、Ⅱ、Ⅲ等3个小岩体组成，本次研究的样品采自Ⅰ号岩体Figure 1. (a)The simplified geological map of southern Hunan Province and (b) the distribution of the Tongshanling granitic pluton (modified from Wang, et al.[24] and Lu, et al.[25]). Granodioritic pluton in southeast Hunan Province (South China) emplaced at the junction between Cathaysia and Yangtze bocks. The Tongshanling pluton is located in the south of southeast Hunan Province, and is composed of three small plutons Ⅰ, Ⅱ and Ⅲ. The studied samples were collected from No.Ⅰ pluton.铜山岭岩体位于湘东南地区南部，由Ⅰ、Ⅱ、Ⅲ三个小岩体组成，近东西向分布，总面积12km2(图 1b)。该岩体侵入于寒武纪浅变质岩、泥盆纪海相碳酸盐岩夹碎屑岩地层中，形成年龄为159±1Ma[18]。岩体周边分布一系列铜铅锌多金属矿床(点)，自北向南有铜山岭矽卡岩型-热液脉型铜多金属矿床、江永矽卡岩型银铅锌矿床、桥头铺矽卡岩型铜钼多金属矿床(图 1b)。前人通过年代学、同位素(S、Pb、C)及流体包裹体研究，大多认为这些矿床与铜山岭岩体在时空和成因上密切相关[21, 25, 27-28]。
2. 实验部分
2.1 实验样品
本次研究的所有样品均采自铜山岭Ⅰ号岩体，岩性主要为角闪石黑云母花岗闪长岩(图 2a)，主要矿物组成为角闪石、黑云母、长石和石英，角闪石一般呈棕色和浅绿色(图 2)，局部可见有明显的蚀变特征。岩体中发育有大量的铁镁质暗色包体如图 2b所示。主要由角闪石和黑云母等暗色矿物组成。
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图 2 铜山岭岩体岩性特征和暗色包体照片及榍石透射光和背散射电子图像。铜山岭岩体中的花岗闪长岩主要由角闪石、长石、石英和黑云母组成。榍石在反射光和背散射电子图像中没有显示出明显的成分环带a—花岗闪长岩的主要矿物组合；b—花岗闪长岩中暗色包体；c—代表性花岗闪长岩镜下照片；d—角闪石镜下特征；e—透射光下榍石照片；f—榍石的背散射电子图像。Figure 2. Characteristics of mafic microgranular enclave and hosted granodiorite, and photomicrographs of accessory mineral titanite.a—The major mineral assemblages of granodiorite; b—The mafic microgranular enclave hosted by granodiorite; c—Photomicrograph of the representative granodiorite; d—Photomicrograph of amphibole; e—Photomicrograph of titanite under transmission light; f—Black scatter electric image of titanite. The granodiorites are mainly composed of amphibole, feldspar, quartz, and biotite. Accessory mineral titanite grains in the MME and host granodiorite of the Tongshanling granitic pluton show little or no intra-grain concentric zoning in transmission and BSE images.本文对花岗闪长岩和暗色包体样品进行粉碎后采用电磁法分选榍石，将分选的榍石颗粒制成环氧树脂靶，然后对榍石进行抛光处理，之后对榍石进行透反射光和背散射照相(图 2中e，f)，检查榍石的内部结构，选择无裂痕、无微小矿物包裹体和表面平整的区域进行激光原位分析。
2.2 分析方法
2.2.1 榍石主量元素分析
榍石主量元素利用EPMA进行分析，在中国科学院地球化学研究所矿床地球化学国家重点实验室完成，仪器型号为日本电子生产的JXA8530F-plus型场发射电子探针。仪器工作条件为：加速电压25kV，加速电流10nA，束斑5μm。采用自然界和人工合成国际标样对榍石中元素进行校正，用Kaersutite角闪石国际标样校正榍石的Na、K、Mg、Al、Si、Ca、Mn和Fe等元素的含量，磷灰石和金红石标样分别用来校正榍石中F和Ti的含量。元素特征峰测试时间为10s，背景测试时间为5s，所有测试数据均进行了ZAF校正处理。
2.2.2 榍石原位微量元素分析
榍石微量元素分析实验在中国科学院地球化学研究所矿床地球化学国家重点实验室利用LA-ICP-MS完成。激光剥蚀系统为GeoLasPro 193nm ArF准分子激光器，电感耦合等离子体质谱为Agilent 7900。激光剥蚀过程中采用氦气为载气，氩气为补偿气，并加入少量氮气提高灵敏度，三者在进入ICP之前通过一个T形接头混合。样品仓为标配的剥蚀池，其中加入树脂制作的模具来获得一个较小体积的取样空间，以降低记忆效应，提高冲洗效率。分析过程中，激光工作参数频率为5Hz，能量密度5J/cm2，束斑44μm，分析点靠近电子探针点的位置，每个样品的总测试时间为90s，采集背景信号15s，样品剥蚀时间60s，冲洗管路和样品池时间15s。在测试之前用美国地调局研制的硅酸盐玻璃NIST610对ICP-MS性能进行优化，使仪器达到最佳的灵敏度和电离效率(U/Th≈1)、尽可能小的氧化物产率(ThO/Th < 0.3%)和低的背景值。微量元素含量校正、仪器灵敏度漂移校正等都采用ICPMSDateCal软件处理，以对应点电子探针获得的Ca含量作为内标，标准物质NIST610和NIST612玻璃作为外标进行数据校正，微量元素分析的准确度优于10%。
2.2.3 榍石原位Sm-Nd同位素分析
榍石Sm-Nd同位素分析实验在中国科学院地球化学研究所矿床地球化学国家重点实验室利用LA-MC-ICP-MS完成。激光剥蚀系统是澳大利亚瑞索公司生产的RESOlution-155 ArF193-nm，多接收电感耦合等离子体质谱仪是英国Nu公司生产的Nu Plasma Ⅲ。分析过程中，激光的束斑72μm，剥蚀频率6Hz，能量密度6J/cm2。使用144Sm/147Sm=0.205484和146Nd/144Nd=0.7129分别校正Sm同位素和Nd同位素的质量歧视[29]。利用144Sm/149Sm=0.22332校正144Sm对144Nd的同质异位数干扰[30]。榍石标样BLR-1作为外标校正147Sm/144Nd的质量歧视和元素分馏。实验测得的4个监控标样MAD、Otter Lake、LAP和SAP的143Nd/144Nd比值分别为0.511352±0.000008、0.511956±0.000008、0.511355±0.000015、0.511011±0.000007，与相应样品的143Nd/144Nd参考值在误差范围内基本一致(MAD：0.511322±0.000053、Otter Lake：0.512940±0.000009、LAP：0.512352±0.000024、SAP：0.511007±0.000030)[17]。
3. 榍石微区原位元素和同位素分析结果
3.1 榍石主量和微量元素特征
表 1 铜山岭花岗闪长岩和暗色包体中榍石电子探针分析数据Table 1. Representative EPMA data of titanite in granodiorite and mafic microgranular enclave of the Tongshanling pluton元素/分析点 暗色包体(%) 花岗闪长岩(%) TSL4-1 TSL4-2 TSL4-3 TSL4-4 TSL4-5 TSL5-1 TSL5-2 TSL5-3 TSL5-4 TSL5-5 TSL5-6 Na2O 0.014 0.013 - 0.056 0.009 - - 0.003 - - - K2O 0.009 0.004 0.001 0.006 0.008 - - - - - - F 1.45 0.48 1.45 1.69 1.23 1.84 0.255 1.57 1.10 1.09 1.07 MgO - 0.003 0.001 - 0.005 0.031 0.001 0.017 - - 0.002 Al2O3 3.62 2.70 3.60 4.14 3.31 5.61 1.81 4.68 3.03 3.37 2.48 SiO2 31.7 31.4 31.2 31.3 30.7 31.3 31.1 31.4 31.6 31.0 31.6 Cl 0.017 - 0.008 0.012 0.002 0.005 - - 0.007 - 0.004 CaO 29.4 29.3 30.0 29.9 29.4 29.9 29.6 29.0 29.6 29.5 29.4 TiO2 33.9 35.7 35.1 33.7 34.0 30.6 38.2 32.9 35.0 34.2 36.8 MnO 0.059 0.043 0.024 0.045 0.061 0.028 0.044 0.053 0.066 0.024 0.027 FeO 0.220 0.356 0.366 0.190 0.184 0.465 0.378 0.191 0.606 0.456 0.432 总计 100 99.9 102 101 98.9 99.7 101 99.8 101 99.7 102 以O=5计算的阳离子个数(afpu) Na 0.001 0.001 - 0.003 0.001 - - - - - - Mg - - - - - 0.001 - 0.001 - - - Al 0.069 0.052 0.068 0.078 0.064 0.107 0.034 0.089 0.057 0.065 0.047 Si 1.021 1.020 0.996 1.004 1.008 1.013 1.001 1.015 1.016 1.010 1.007 Ca 1.013 1.020 1.026 1.025 1.032 1.038 1.020 1.002 1.020 1.030 1.006 Ti 0.822 0.872 0.841 0.812 0.840 0.745 0.925 0.800 0.847 0.839 0.883 Mn 0.002 0.001 0.001 0.001 0.002 0.001 0.001 0.001 0.002 0.001 0.001 Fe 0.006 0.010 0.010 0.005 0.005 0.013 0.010 0.005 0.016 0.012 0.012 F 0.008 0.003 0.008 0.009 0.007 0.010 0.001 0.008 0.006 0.006 0.006 F和Cl 0.001 - - 0.001 - - - - - - - Al+Fe 0.075 0.061 0.078 0.083 0.069 0.120 0.044 0.094 0.074 0.077 0.058 注：“-”代表低于检测限，下同。 表 2 铜山岭花岗闪长岩和暗色包体中榍石原位微量元素组成Table 2. Trace element compositions of titanite in granodiorite and mafic microgranular enclave of the Tongshanling pluton元素/分析点 暗色包体(μg/g) 花岗闪长岩(μg/g) TSL4-1 TSL4-2 TSL4-3 TSL4-4 TSL4-5 TSL5-1 TSL5-2 TSL5-3 TSL5-4 TSL5-5 TSL5-6 Li 0.431 0.565 0.141 0.264 0.050 1.17 - 0.082 0.260 0.942 - V 1461 571 610 1317 701 781 553 643 687 795 717 Ni 0.178 0.560 0.417 0.032 0.619 0.042 0.185 0.431 - 0.338 - Cu 0.532 0.510 0.589 0.329 0.761 0.648 0.596 0.265 0.357 0.347 0.651 Zn 2.22 2.36 3.49 1.91 2.59 1.76 1.02 2.94 1.15 2.21 1.31 Ga 8.27 6.41 6.58 7.61 6.31 3.56 3.88 7.71 7.68 2.23 6.38 As 0.776 2.36 0.632 0.365 2.66 7.54 1.51 2.63 3.80 3.25 0.796 Rb 0.063 0.742 0.088 - 0.003 0.242 0.051 0.033 0.137 0.087 0.099 Sr 4.66 6.61 6.16 4.74 6.29 7.23 7.51 6.22 7.62 11.3 6.42 Y 270 74.0 131 32.4 90.9 118 872 333 1706 74.9 906 Zr 16.5 143 26.8 59.4 486 11.1 154 190 536 474 67.0 Nb 384 584 354 306 1489 650 625 1069 1455 1217 963 Sn 861 4116 3960 1353 6594 90 1162 3503 1233 829 651 Cs 0.112 0.320 0.038 0.039 0.004 0.317 0.002 0.005 0.044 0.110 0.011 Ba 0.093 0.342 0.055 0.108 0.053 1.323 - 0.080 0.033 1.263 0.048 La 5.33 9.87 8.07 4.19 5.92 16.5 4.37 14.1 15.8 15.7 2.75 Ce 24.8 43.1 48.4 16.6 21.5 63.9 43.2 73.9 98.1 51.4 25.7 Pr 5.45 6.39 9.19 2.58 3.91 11.9 15.5 15.8 27.0 7.02 9.56 Nd 37.6 29.6 49.9 13.1 24.9 69.8 135.2 97.8 214 32.6 86.8 Sm 19.8 7.79 13.2 4.95 10.7 22.2 86.8 35.8 135 26.4 68.5 Eu 8.94 10.9 13.4 5.71 15.7 10.2 46.0 17.4 32.5 28.8 20.3 Gd 29.7 9.59 16.2 5.09 13.8 22.6 118 42.2 192 25.9 108 Tb 5.95 1.58 2.85 0.84 2.18 3.50 21.7 7.20 37.03 1.42 21.3 Dy 42.7 10.5 19.8 5.3 13.3 20.1 143 47.5 259 9.8 151 Ho 9.84 2.45 4.44 1.12 3.05 4.20 30.2 10.9 55.4 2.14 31.2 Er 29.0 7.2 13.5 3.3 9.0 11.0 85.5 33.9 166.4 6.5 89.3 Tm 4.63 1.18 2.21 0.51 1.40 1.58 13.73 5.69 26.6 1.12 13.6 Yb 32.1 10.3 17.2 3.5 9.8 10.1 103 47.5 206 10.8 100 Lu 4.52 1.97 3.38 0.52 1.29 1.49 17.3 9.48 33.0 1.91 14.1 Hf 0.639 5.09 0.849 2.10 19.0 0.387 7.36 6.77 21.0 16.4 2.13 Ta 28.4 52.1 34.0 24.7 109.5 56.0 56.2 85.7 104.8 91.0 80.3 W 10.2 167 50.5 13.3 173 11.1 3.24 609 366 144 6.15 Pb 0.495 1.386 0.502 0.280 1.14 5.52 0.540 1.43 1.39 1.68 0.427 Th 2.13 3.76 1.44 6.40 2.52 2.35 5.04 63.5 62.0 6.92 2.41 U 17.2 52.8 16.9 18.2 19.8 4.39 18.0 262 205 45.4 10.1 ΣREE 258 152 222 67 136 269 864 459 1498 187 742 LaN/YbN 0.12 0.69 0.34 0.85 0.43 1.17 0.03 0.21 0.06 1.04 0.02 T(℃) 762 878 786 828 956 743 883 895 963 954 834 Eu/Eu* 1.13 3.86 2.80 3.48 3.94 1.39 1.39 1.37 0.62 1.10 0.72 Ce/Ce* 1.13 1.33 1.38 1.24 1.09 1.12 1.29 1.22 1.17 1.20 1.23 Zr/Hf 25.9 28.1 31.5 28.3 25.6 28.7 21.0 28.0 25.5 29.0 31.4 Nb/Ta 13.5 11.2 10.4 12.4 13.6 11.6 11.1 12.5 13.9 13.4 12.0 Y/Ho 27.4 30.2 29.6 28.8 29.8 28.0 28.9 30.7 30.8 35.0 29.0 分析结果显示，铜山花岗闪长岩及暗色包体中榍石的主量元素变化范围基本一致，SiO2为31.0%~31.7%，Al2O3为1.81%~5.61%，CaO为29.0%~30.0%，TiO2为30.6%~38.2%，FeO为0.184%~0.606%，F为0.48%~1.84%。对榍石原位微量元素分析显示，单个样品的微量元素含量变化范围不大，没有明显的成分环带。两类样品中榍石的稀土元素总量变化范围较大，为67~1498μg/g，但二者稀土配分模式存在一定差别(图 3)[31]，暗色包体中榍石具有微弱的重稀土富集，LaN/YbN比值为0.12~0.85，具有明显的Eu正异常，Eu/Eu*值为1.13~3.94；而花岗闪长岩中榍石稀土配分模式变化较大，Eu正异常变小，部分分析点显示出负异常，Eu/Eu*值为0.62~1.39。两类样品中榍石的微量元素对Zr/Hf、Nb/Ta、Y/Ho比值变化范围较小(表 2)，Zr/Hf比值为21.0~31.5，Nb/Ta比值为10.4~13.9，Y/Ho比值为27.4~35.0。
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图 3 铜山岭榍石稀土元素配分模式图，暗色包体中榍石的稀土含量低于花岗闪长岩中榍石的稀土含量并具有明显的正Eu异常，而花岗闪长岩中的榍石显示出弱的正Eu或者负Eu异常。球粒陨石标准化数据据Sun和McDonough[31]Figure 3. Chondrite-normalized REE patterns for titanite from the Tongshanling granitic pluton. Titanite from MME is characterized by Eu positive anomaly. The titanite from granodiorite has REE content higher than those from MME and shows weak positive or negative Eu anomaly on REE pattern. It is indicate that the granitic melts of the Tongshanling are characterized by high oxygen fugacity (The chondrite values are from Sun and McDonough[31]).3.2 榍石Sm-Nd同位素特征
3个样品中榍石的微区原位Sm-Nd同位素分析结果见表 3。单颗粒榍石的Sm-Nd同位素组成非常均一，暗色包体中榍石的147Sm/144Nd比值为0.2399~0.4026，144Nd/143Nd变化范围为0.512321~0.512675，εNd(t)值为-3.5~-8.9，平均值为-7.2±2.4。花岗闪长岩中榍石147Sm/144Nd比值为0.2850~1.4020，144Nd/143Nd变化范围为0.512269~0.513399，εNd(t)值为-5.4~-9.9，平均值为-6.9±2.4。花岗闪长岩中榍石的Sm-Nd同位素比值变化范围略大于暗色包体中榍石的Sm-Nd同位素比值，但两者的初始Nd同位素组成非常相似(图 4)。
表 3 榍石原位Sm-Nd同位素组成Table 3. In-situ Sm-Nd isotope compositions in titanite from granodiorite and mafic microgranular enclave of the Tongshanling pluton暗色包体分析点 147Sm/144Nd 2σ 143Nd/144Nd 2σ εNd(t) 2σ fSm/Nd 2σ T4TNd07 0.3415 0.0099 0.512337 0.000442 -8.9 0.6 0.736 0.050 T4TNd09 0.3894 0.0010 0.512392 0.000095 -8.8 1.9 0.980 0.005 T4TNd10 0.4026 0.0026 0.512675 0.000057 -3.5 1.1 1.047 0.013 T4TNd11 0.2416 0.0048 0.512321 0.000283 -7.1 1.5 0.228 0.024 T4TNd12 0.2399 0.0072 0.512504 0.000744 -3.5 1.5 0.220 0.037 T4TNd13 0.2626 0.0018 0.512346 0.000509 -7.0 0.9 0.335 0.009 花岗闪长岩分析点 147Sm/144Nd 2σ 143Nd/144Nd 2σ εNd(t) 2σ fSm/Nd 2σ T3TNd01 1.4020 0.0098 0.513399 0.000267 -9.9 1.2 6.127 0.050 T5TNd01 0.4059 0.0026 0.512580 0.000166 -5.4 1.2 1.063 0.013 T5TNd02 0.5917 0.0046 0.512761 0.000140 -5.7 0.7 2.008 0.023 T5TNd05 0.3743 0.0047 0.512404 0.000270 -8.2 1.3 0.903 0.024 T3TNd03 0.2850 0.0048 0.512269 0.000693 -9.0 3.5 0.449 0.024 ![]()
图 4 铜山岭花岗闪长岩和暗色包体中榍石Sm-Nd同位素组成，暗色包体和花岗闪长岩中的榍石具有相似的初始Nd同位素组成a—榍石147Sm/144Nd与143Nd/144Nd相关图；b—榍石147Sm/144Nd与εNd(t)相关图；c—榍石εNd(t)加权平均值；d—榍石εNd(t)柱状图。Figure 4. The Sm-Nd isotope compositions of titanite from the Tongshanling granitic pluton. All titanite grains have coincident negative initial Nd isotopic compositions.(a) Plot of 147Sm/144Nd against 143Nd/144Nd for titanite; (b) Plot of 147Sm/144Nd against εNd(t) for titanite; (c) Weighted mean εNd value(t) for titanite; (d) Histogram of εNd(t) value for titanite. Titanite from MME has homogenous Nd isotope compositions. Their present 144Nd/143Nd ranges from 0.512321 to 0.512675, corresponding to εNd(t) value from -3.5 to -8.9 with an average of -7.2±2.4 (N=6). Titanite from granodiorite overall have 144Nd/143Nd ratio ranging from 0.512269 to 0.513399. Their time-corrected initial εNd(t) value vary between -5.4 and -9.9 with an average of -6.9±2.4 (N=5). All titanite grains have negative initial Nd isotopic compositions.4. 榍石地球化学特征对岩石成因的指示
4.1 榍石形成条件及其对岩浆性质的约束
副矿物榍石主量元素通常存在较大的差异，且含有较高的稀土元素和高场强元素，常被应用于判别榍石成因进而揭示寄主岩石的形成条件。因此，元素在榍石晶格位的替代方式得到了地质学者的广泛关注[32]。铜山岭花岗闪长岩及其中暗色包体中榍石普遍含有Al、Fe和F等元素，具有相似的元素变化趋势，Al+Fe与Ti具有明显的负相关关系(图 5a)，暗示Al和Fe主要通过替代八面体位置上的Ti进入榍石，具体的替代方式是(Al，Fe3+)+(F，OH)=Ti4++O2-。然而，在Al+Fe和F的关系图中，Al和Fe超过了(Al，Fe3+)+(F，OH)=Ti4++O2-理论替换线(图 5b)，说明还有额外的Al通过替换进入榍石晶格。铜山岭花岗闪长岩及暗色包体中榍石具有较高的REE含量，很可能还发生了Al+Fe+REE一起替换了Ti位和Ca位，替代方式是(Al，Fe3+)+REE=Ti4++O2-。因此，榍石中微量元素可能同时通过上述两种替代方式进入其晶格中。
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图 5 铜山岭榍石主量元素(a，b)和微量元素比值(c，d，e，f)相关图。榍石中主微量元素受离子半径和电荷控制，不受热液活动的影响，能反映初始岩浆的信息a—Ti和Al+Fe相关图；b—F和Al+Fe相关图；c—Zr/Hf比值和Nb/Ta比值相关图；d—Zr/Hf比值和Y/Ho比值相关图；e—Eu异常Eu/Eu*和Zr/Hf比值相关图；f—Eu异常Eu/Eu*和Ce异常Ce/Ce*相关图。Figure 5. Selected major element variational diagrams (a, b) and trace element ratios variational diagrams (c-f) for titanite. The variation of Zr/Hf, Nb/Ta and Y/Ho ratios of titanite grains range from 21.0 to 31.5, 10.4 to 13.9 and 27.4 to 35.0, respectively. These trace element ratios are consistent with those of normal crust and are not fractionated. Therefore, the trace elements of titanite were completely controlled by ion radius and charge, and not affected by late hydrothermal alteration.元素进入榍石晶格与其形成条件密切相关[33-35]。一般而言，岩浆成因榍石具有低CaO和TiO2含量，高FeO、Na2O和MgO含量，稀土和高场强元素含量较高，稀土元素配分模式呈现出平坦的中-重稀土型式，这些地球化学特征明显有别于热液和变质成因的榍石[36-37, 35]。当有流体参与作用时，矿物中的等价微量元素对Zr-Hf、Nb-Ta和Y-Ho会发生明显分异，偏离地壳岩石的正常范围[38-40]，由于流体作用中，这些元素在矿物和熔体之间的分配不再受电价和离子半径控制[41]。铜山岭花岗闪长岩与铜多金属成矿在时空和成因上密切相关，岩体普遍遭受了强烈的热液蚀变作用[25, 27-28]，热液活动是否对榍石的形成存在影响目前尚不明确。本次研究的榍石具有平坦的中-重稀土元素配分模式(图 3)，与苏鲁大别超高压变质岩中残留岩浆榍石的稀土配分模式完全一致[34]。所有榍石均具有低的CaO、Al2O3和TiO2含量及高的Fe2O3和MgO含量(表 1)，元素的含量也与苏鲁大别超高压变质岩中残留岩浆榍石及三江地区碱性岩中岩浆榍石的元素含量相当[36, 34-35]。这些元素地球化学特征均说明所研究的榍石都属于岩浆成因。而且，铜山岭花岗闪长岩和暗色包体中榍石中Nb/Ta、Zr/Hf和Y/Ho比值变化范围非常小(图 5)，Nb/Ta比值一般小于13.5，Zr/Hf比值一般大于21，Y/Ho比值大于27.4，完全处于离子半径和电价控制的范围。因此，榍石未受热液活动的影响，保持岩浆初始信息，可以用于限定寄主岩石的岩浆性质。
已有实验研究表明，微量元素Zr可以取代榍石中的Ti，其取代量的多少与体系的温度和压力相关，因此，榍石被广泛应用于地质温压条件的估算[42-44]。系统的实验研究证实，榍石中Zr含量与温压条件存在以下关系式[42]：
$$ \begin{aligned} \log \left(\mathrm{Zr}_{\text {榍石 }}\right) & =10.52( \pm 0.10)-7708( \pm 101) / T- \\ & 960( \pm 10) P / T-\log \left(\alpha_{\mathrm{TiO}_2}\right)-\log \left(\alpha_{\mathrm{SiO}_2}\right) \end{aligned} $$ 式中：Zr榍石为榍石中Zr含量(μg/g)；T为温度(K)；P为压力(GPa)，αTiO2和αSiO2分别为Ti和Si的活度。
前人通过角闪石的Al压力计获得了铜山岭花岗闪长岩形成的压力约为2.0GPa[22]。由于铜山岭花岗闪长岩中含有金红石和石英，假定αTiO2和αSiO2均为1，即Ti和Si的活度均为1，根据榍石中Zr含量，计算得到暗色包体中榍石的形成温度为762~956℃，略高于花岗闪长岩中榍石的形成温度743~963℃(表 2)，并明显高于前人通过角闪石、黑云母和斜长石等矿物计算的温度[22]。因此，榍石记录的是初始岩浆温度条件，暗色包体中的榍石形成时间略早于寄主花岗岩闪长中的榍石。根据Chappell等[45]提出的高温和低温花岗岩类分类标准，铜山岭花岗闪长岩属于高温花岗岩类。同时，榍石中Ce和Eu异常通常与岩浆氧化还原状态密切相关，由于不同的氧化还原条件下，Ce可以Ce3+和Ce4+，Eu可以Eu2+和Eu3+存在[46, 35]。还原条件下，Ce主要以低价态的Ce3+形式存在，Ce3+离子半径为1.02Å，与7次配位Ca2+离子半径1.06Å相似，容易置换榍石中的Ca2+进入晶格，从而导致较高的Ce/Ce*比值；而Eu主要以Eu2+形式存在，Eu2+离子半径为1.17 Å，与榍石中7次配位Ca2+离子半径相差较大，难以置换进入榍石晶格，从而具有较低的Eu/Eu*比值[46]。氧化条件下，榍石中Ce/Ce*比值和Eu/Eu*比值则反之。铜山岭花岗闪长岩暗色包体中榍石具有Eu的正异常，而花岗闪长岩中榍石分析点大部分显示出Eu的弱负异常，少量点具有Eu正异常(图 3)，Eu/Eu*比值降低(图 5)，二者的Ce/Ce*比值都大于1.0，且与Eu/Eu*比值变化存在相关性(图 5)。因此，榍石中Eu、Ce异常说明岩浆的初始氧逸度较高，随着岩浆演化，氧逸度有降低趋势。
4.2 榍石Nd同位素对岩浆源区示踪
铜山岭花岗闪长岩具有明显的富钾、高铝特征[47, 28]，全岩初始Sr-Nd同位素变化范围较大，初始87Sr/86Sr变化范围为0.707962~0.710396，εNd(t)值为-2.3~-7.0[47, 28]。基于全岩Sr-Nd同位素和元素特征，前人认为铜山岭花岗闪长岩主要由壳幔物质混合形成或者残留体再造[45-46]。由于花岗质岩石在风化和热液蚀变过程中Sm-Nd同位素体系容易重置，难以限定岩浆源区特征，而榍石抗风化抗热液蚀变能力强，其原位Sm-Nd同位素代表了榍石结晶时岩浆的Nd同位素组成，可以有效地示踪岩浆来源和演化过程物质的变化细节，榍石原位Nd同位素成为了示踪岩浆源区和演化过程一个新的有效手段[15, 14, 35]。铜山岭花岗闪长岩中暗色包体的榍石εNd(t)值为-3.5~-8.9，平均值为-7.2±2.4，花岗闪长岩中榍石εNd(t)值为-5.4~-9.9，平均值为-6.9±2.4，二者变化范围相似(图 4)，而且同一颗粒不同生长环带的Nd同位素组成比较均一，说明在榍石结晶过程中岩浆来源没有发生明显变化，没有明显的岩浆混合特征。
在Nd同位素演化曲线上，铜山岭花岗闪长岩和暗色包体中榍石都具有负的初始Nd同位素组成，靠近华南大陆中下地壳Nd同位素区域，与湘南地区下地壳麻粒岩包体的Nd同位素组成相似[εNd(t)值为-6.59~-7.34][48]，处于元古代麻源群中基性变质岩的范围(图 6)。因此，铜山岭地区的花岗闪长岩很可能由均一的镁铁质中下壳熔融形成。然而，中下地壳什么样的物质能产生富钾、富铝的岩浆？前人通过实验研究发现，角闪岩脱水熔融过程产生的水不饱和岩浆具有高铝、高钾特征，而产生的水饱和岩浆具有高铝、高钙，但亏损铁、镁和钾特征[52-53]，因此，铜山岭岩体很可能由镁铁质角闪岩相中下地壳发生脱水熔融形成的水不饱和岩浆形成。
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图 6 铜山岭榍石Nd同位素演化曲线。铜山岭榍石的初始Nd同位素靠近华南中下地壳Nd同位素演化线，暗示铜山岭花岗闪长质岩石的物质源区是华南中下地壳物质。所有初始同位素比值根据年龄159±1Ma进行校正，华南中下地壳Sr-Nd同位素数据据Yu等[49]和孔华等[48]，元古代中基性变质岩数据据袁忠信等[50]，Nd同位素演化曲线据Chen等[51]Figure 6. Nd isotopic evolution diagrams for titanite from the Tongshanling granodiorite. All titanite grains have negative initial Nd isotopic compositions, which is consistent with the evolution trend of Nd isotopes of the middle-lower continental crust of South China. It is indicated that granodiorites from the Tongshanling pluton were probably formed by the amphibole-dehydration melting of a mafic source in the middle-lower crust beneath South China. All the initial ratios were corrected to 159±1Ma. The Nd isotopic data of middle/lower crust are from Yu, et al[49] and Kong, et al[48]. The data of Proterozoic metamorphic rocks are from Yuan, et al[50]. Nd isotopic evolution diagram was modified after Chen, et al[51].5. 结论
利用LA-ICP-MS和LA-MC-ICP-MS等现代原位分析测试技术，精确测定了铜山岭岩体中镁铁质暗色包体(MME)和寄主花岗闪长岩中副矿物榍石的微量元素和Nd同位素组成，确定了REE与Al和Fe主要通过(Al，Fe3+)+REE=Ti4++O2-方式替换榍石的Ti位和Ca位而进入晶格。榍石中微量元素对Zr/Hf、Nb/Ta、Y/Ho比值变化范围完全受控于离子半径和电荷，不受热液蚀变的影响，保留岩浆初始信息。榍石原位化学组成对示踪岩浆性质和起源具有明显的优势。
榍石微量元素分析结果表明铜山岭花岗闪长质岩浆初始氧逸度高，随岩浆演化有降低趋势。暗色包体和寄主花岗闪长岩中榍石具有均一的、负的Nd同位素组成，变化范围较小，与华南大陆中下地壳Nd同位素演化趋势一致，暗示铜山岭花岗闪长岩很可能由镁铁质角闪岩相中下地壳脱水熔融形成的水不饱和岩浆形成。
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图 1 土壤-植物系统中硒的生物有效性和相关的化学反应(据Dinh等[15]修改)
Figure 1. The bioavailability and associated chemical reactions of selenium in soil-plant systems (The grey-blue parts on the left side presents, from top to bottom, the root soil, the soil solution and the soil solid phase; the blue arrow on the right side indicates the increase in bioavailability of selenium from bottom to top).Modified from Dinh, et al[15].
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图 4 有机酸对土壤硒生物有效性的影响示意图
Figure 4. The impact of organic acids on soil selenium bioavailability.
表 1 土壤硒生物有效性评价研究案例
Table 1 Cases of soil selenium bioavailability assessment
评估方法 土壤类型 地区 作物 影响硒生物有效性因素 参考文献 单一提取法 草甸黏壤土 英国 - 可溶性硒、交换性硒为主要的有效硒组分 [24] 黄褐色土 湖北省恩施市 马铃薯 硒酸盐比亚硒酸盐更能提高块茎硒的生物有效性，但膨大期叶面施用亚硒酸盐适合富硒马铃薯的生产 [43] 水田土，旱地土 湖北省恩施市 水稻 水稻植株的硒含量与有机结合态硒呈显著相关，有机质是影响水稻硒生物有效性的主要因素 [44] 黄土, 砂壤土 陕西省永寿县 玉米 土壤和叶面施加硒均能可靠有效地提高玉米籽粒中硒的含量 [45] 变性土，铁铝土 云南省滇池东岸 - 土壤中的总硒含量对生物有效性硒影响最大，其次是铁/铝氧化物，pH增加时铁/铝氧化物对硒的吸附降低 [46] 富硒土壤，风化石煤 湖北省恩施市渔塘坝 - 弱结合的腐植酸结合态硒在有机结合态硒中占主导地位，且结合越弱越容易转化成生物有效性硒，是生物有效性硒的潜在来源 [47] 泥炭土、壤土，泥炭/壤土混合土 挪威东南部 小麦 有机质含量较低的土壤，硒有效性随pH的增加而增加；有机质含量较高的泥炭土，硒有效性随pH的增加而降低 [48] 顺序提取法 水稻土，旱地土 陕西省紫阳县闹热村 水稻，玉米 旱地中铁锰氧化结合态硒占主导地位，有机结合态释放硒会提高硒的生物有效性 [25] 黄土 陕西省 小白菜 硒酸盐比亚硒酸盐处理的土壤有更高的生物有效性 [32] 黄土，壤土 西北农林科技大学试验田 小麦 亚硒酸盐处理，交换性硒浓度增加；硒酸盐处理，可溶性硒浓度增加；铁锰氧化结合态硒、有机结合态硒浓度均降低；硒生物有效性增加 [33] 大骨节病病区的天然土壤 西藏高原松潘县 青稞 硒的生物有效性与海拔高度呈负相关 [49] 栗钙土，黑土 内蒙古和黑龙江 小白菜 老化使可溶性硒和交换性硒随时间延长而含量降低，硒生物有效性降低 [50] DGT技术 天然富硒土壤 湖北省恩施市 水稻 DGT测定的硒主要来源于可溶性和可交换态硒，可溶性和交换性硒浓度与土壤pH呈显著正相关 [36] 天然富硒土壤 陕西省紫阳县 玉米 残余态硒和铁锰氧化物结合态硒占据优势，交换性硒和碳酸盐结合态硒占比<5%，生物有效性很低 [39] 农场表层土 西北农林科技大学农场 紫甘蓝，西兰花，芥菜，小麦 紫甘蓝和西兰花吸收土壤中最有效的可溶性硒的能力优于芥菜和小麦，DGT适用于表征硒酸盐处理的土壤硒生物有效性 [40] 栗钙土，黑土 内蒙古和黑龙江 小白菜 小白菜根中硒浓度与CDGT-Se呈极显著相关，硒酸盐处理的土壤老化速率低于亚硒酸盐处理的土壤，老化使硒生物有效性均降低 [51] 水培溶液 - 油菜，小麦 油菜对硒的积累速度大约是小麦的三倍 [52] 黄棕壤、砂姜黑土、褐土、海滨土、黑土和潮土 安徽、江苏、辽宁、天津、黑龙江、河北 小白菜 生物有效性：褐土>潮土, 黑土>海滨土, 砂姜黑土>黄棕壤, 土壤类型是影响有效硒的主要因素 [53] 
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