Effect-of-dissolved-organic-matter-from-Guangzhou-landfill-leachate-on-sorption-of-phenanthrene-by-M

土壤有机碳激发效应英文回答：Soil organic carbon (SOC) plays a crucial role in maintaining the productivity and health of terrestrial ecosystems. Enhancing SOC content has emerged as a promising strategy to improve soil quality and mitigate the effects of climate change. This phenomenon, known as the "priming effect," involves the acceleration of decomposition of native soil organic matter (SOM) upon the addition of fresh organic matter inputs.The priming effect is driven by the microbial response to the increased availability of labile carbon from the fresh organic matter. Microbes utilize this labile carbon as an energy source, releasing enzymes that degrade both the fresh organic matter and native SOM. The extent of the priming effect varies depending on the quality of the added organic matter, the soil microbial community composition, and environmental conditions.Several mechanisms have been proposed to explain the priming effect. One theory suggests that the addition of fresh organic matter stimulates the growth of microbial populations, leading to increased enzyme production and decomposition of both the fresh and native SOM. Another mechanism involves the selective utilization of labile carbon by microbes, leaving behind more recalcitrant compounds that are more resistant to decomposition. This process can result in the accumulation of recalcitrant organic matter, which can have long-term effects on soil carbon dynamics.The priming effect can have both positive and negative implications for soil health and ecosystem functioning. On the one hand, it can accelerate the release of nutrients from SOM, making them available for plant uptake. This increased nutrient availability can boost plant growth and productivity. On the other hand, the priming effect can also lead to the loss of stable SOC, which is an important component of soil carbon storage and a major contributor to the global carbon cycle.Managing the priming effect is crucial for sustainable soil management practices. One approach involves the use of organic matter amendments that are high in labile carbonand low in recalcitrant compounds. This can help tominimize the loss of stable SOC while still stimulating microbial activity and nutrient release. Additionally, maintaining a diverse soil microbial community can promote the balanced decomposition of organic matter and reduce the risk of excessive priming.中文回答：土壤有机碳（SOC）在维持陆地生态系统的生产力和健康方面发挥着至关重要的作用。

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浙江大学硕士论文
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２．２．１大棚内Ｃ０２的发酵装置……．．．……………………。………………………………１５ ２．２．２番茄植株生长指标的测定……………………………………………………．１５ ２．２．３番茄植株结果数和果实产量的测定……………。…．．．………………………１６ ３结果与分析…………………………………………………………………………．．１６ ３．１ Ｃ０２施肥对番茄植株株高的影响…………………………．．．…… ¨１６ ３．２ Ｃ０２施肥对番茄单株结果数的影响………………………………………………．１７ ４讨论……………………………………． ５结论……。 第三章Ｃ０２施肥对番茄果实品质的影响 ……………………．…………………………．．１７
……………………．．．．．……．．：１６ ………．．．…………．．．．………３７
浙江大学硕士论文
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Heterogeneous AOTs –
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•
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University of Alberta Department of Civil and Environemental Engineering Edmonton, AB Canada; Email jb3@ualberta.ca
Advanced Oxidation Technologies
• Advanced Oxidation Technologies (AOTs)
• The most efficient and most widely studied
substance is the anatase form of TiO2.
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•
最高效和广泛研究的物质是锐钛矿（ TiO2 ）。 ecb- + hvb+ OH + H+ O2-
•
Homogeneous AOTs –
UV/H2O2 Process
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range. 过氧化氢可以吸收 200-300 nm的紫外光。 H2O2 + hν 2 •OH Φ = 1.0

江福林，卢云浩，何强. 茶多酚对植物乳杆菌、金黄色葡萄球菌和大肠杆菌生长的双向调节作用[J]. 食品工业科技，2023，44（22）：152−159. doi: 10.13386/j.issn1002-0306.2023040081JIANG Fulin, LU Yunhao, HE Qiang. Dual-directional Regulation of Tea Polyphenols on the Growth of Lactobacillus plantarum ,Staphylococcus aureus , and Escherichia coli [J]. Science and Technology of Food Industry, 2023, 44(22): 152−159. (in Chinese with English abstract). doi: 10.13386/j.issn1002-0306.2023040081· 生物工程 ·茶多酚对植物乳杆菌、金黄色葡萄球菌和大肠杆菌生长的双向调节作用江福林1，卢云浩2，何　强1,*（1.四川大学轻工科学与工程学院，四川成都 610065；2.成都大学食品与生物工程学院，四川成都 610106）摘　要：增强益生菌产品中益生菌的活力，同时抑制食源性致病菌及腐败菌的生长能够提升产品品质稳定性。

在单培养及共培养条件下，采用传统计数法和高通量测序比较研究了不同浓度的茶多酚对益生菌植物乳杆菌、致病菌金黄色葡萄球菌和大肠杆菌生长的影响。

单培养结果显示，随着茶多酚浓度增加，植物乳杆菌活菌数先增加后降低，在浓度为2.0 mg/mL 时活菌数最多，而两株致病菌的存活率不断降低，其中金黄色葡萄球菌更为明显。

在共培养体系中（金黄色葡萄球菌/大肠杆菌-植物乳杆菌），随着培养时间延长，植物乳杆菌的生物量不断增加，而致病菌数量和培养基pH 不断降低。

remove organic matter 英文缩写Organic matter, often abbreviated as OM, is a vital component of soil that plays a crucial role in maintaining soil health and fertility. It encompasses all living and once-living materials derived from plants, animals, and microorganisms, including decaying leaves, roots, manure, and other decomposing organic substances. Removing organic matter from soil can have significant implications for soil quality, plant growth, and the overall ecosystem. In this essay, we will explore the importance of organic matter and the potential consequences of its removal.Organic matter serves as a reservoir of essential nutrients for plant growth, including nitrogen, phosphorus, and sulfur. As organic matter decomposes, these nutrients are gradually released into the soil, making them available for uptake by plant roots. Without organic matter, soils would rapidly become depleted of these crucial elements, leading to reduced plant productivity and the need for increased fertilizer applications. Moreover, organic matter improves soil structure by binding soil particles together, creating a crumbly texture that allows for better water infiltration, aeration, and root growth. This improved soil structure also enhances water-holding capacity, reducing the risk of erosion and nutrient leaching.The removal of organic matter can disrupt the delicate balance of soil ecosystems. Soil microorganisms, such as bacteria, fungi, and protozoa, rely on organic matter as a source of energy and nutrients. These microorganisms play vital roles in decomposing organic matter, cycling nutrients, and maintaining soil fertility. Removing organic matter can lead to a decline in microbial populations, potentially impacting nutrient cycling and plant growth. Additionally, organic matter serves as a habitat and food source for soil fauna, including earthworms and arthropods, which contribute to soil aeration, nutrient cycling, and the breakdown of organic matter.Furthermore, organic matter acts as a natural buffer against soil pH fluctuations, helping to maintain a stable soil pH range that is conducive to plant growth and nutrient availability. Its removal can lead to increased soil acidity or alkalinity, potentially limiting plant growth and nutrient uptake. Organic matter also plays a role in carbon sequestration, helping to mitigate the effects of climate change by storing carbon in the soil for extended periods.While certain agricultural practices, such as intensive tillage and monoculture cropping systems, can lead to the depletion of organic matter, there are several strategies that can be implemented to maintain or increase its levels in soil. These include the incorporation of cover crops, crop rotation, and the application of organicamendments like compost or manure. Conservation tillage practices, which minimize soil disturbance, can also help to preserve organic matter by reducing its oxidation and breakdown.In conclusion, organic matter is a vital component of soil that plays numerous roles in supporting plant growth, soil fertility, and ecosystem health. Its removal can have far-reaching consequences, including nutrient depletion, reduced soil structure, decreased microbial activity, and disruptions to nutrient cycling. To maintain healthy and productive soils, it is essential to implement sustainable agricultural practices that prioritize the preservation and replenishment of organic matter. By doing so, we can ensure the long-term viability of our agricultural systems and promote the overall health of our soil ecosystems.。

第19卷　第1期2007年3月 塔　里　木　大　学　学　报Journal of Tari m UniversityVol.19No.1Mar.2007① 文章编号:1009-0568(2007)01-0001-03甘草多糖清除自由基活性的研究杨玲1　汪河滨2　罗锋2(1　塔里木大学文理学院,新疆阿拉尔　843300)(2　新疆生产建设兵团塔里木盆地生物资源保护与利用重点实验室,新疆阿拉尔　843300)摘要　本文利用超声-微波协同萃取法提取甘草多糖,并用分光光度法检测甘草多糖对DPPH自由基、羟自由基(・OH)和超氧阴离子自由基(O2-・)的清除能力。

结果表明,甘草多糖溶液对DPPH自由基、・OH和O2-・均具有较好的清除作用。

关键词　甘草多糖;DPPH自由基,羟自由基(・OH);超氧阴离子自由基(O2-・)中图分类号:R285.5 文献标识码:AStudy on Scaveng i n g Free Rad i ca l Acti v ity w ithPolys acchar i des i n Glycyrrh i za Ura lcn sis F ischYang L ing1　W ang Hebin2　Luo Feng2(1College of A rts and Science,Tari m University,A lar,Xinjiang843300) (2Key Laborat ory of Pr otecti on&U tilizati on of B i ol ogical Res ource in Tari m Basin of Xinjiang Pr oducti on and Constructi on Gr oup s,Tari m University,A lar,Xinjiang843300)Abstract　The study uses ultras onic-m icr owave synergistic extracti on technique t o extract polysaccharides of Glycyrrhiza uralcnsis Fisch and tests the scavenging quality of polysaccharides on DPPH free radical,hydr oxyl free radical(・OH)and super oxide free radi2 cal(O2-・)by s pectr ophot ometry.The result shows that polysaccharides has good scavenging effect on DPPH・,・OH and O2-・. Key words　polysaccharides in Glycyrrhiza uralcnsis Fisch;DPPH free radical;hydr oxyl free radical;super oxide free radical 甘草(Glycyrrhiza u ralcnsis F isch.)系豆科(Legu2 m inosae)甘草属多年生草本植物,是最常用而很有用的中药材[1]。

Plant and Soil241:155–176,2002.©2002Kluwer Academic Publishers.Printed in the Netherlands.155 ReviewStabilization mechanisms of soil organic matter:Implications forC-saturation of soilsJ.Six1,R.T.Conant,E.A.Paul&K.PaustianNatural Resource Ecology Laboratory,Colorado State University,Fort Collins,CO80523,U.S.A.1Corresponding author∗Received3January2001.Accepted in revised form13February2002AbstractThe relationship between soil structure and the ability of soil to stabilize soil organic matter(SOM)is a key element in soil C dynamics that has either been overlooked or treated in a cursory fashion when developing SOM models. The purpose of this paper is to review current knowledge of SOM dynamics within the framework of a newly proposed soil C saturation concept.Initially,we distinguish SOM that is protected against decomposition by various mechanisms from that which is not protected from decomposition.Methods of quantification and characteristics of three SOM pools defined as protected are discussed.Soil organic matter can be:(1)physically stabilized,or protected from decomposition,through microaggregation,or(2)intimate association with silt and clay particles, and(3)can be biochemically stabilized through the formation of recalcitrant SOM compounds.In addition to behavior of each SOM pool,we discuss implications of changes in land management on processes by which SOM compounds undergo protection and release.The characteristics and responses to changes in land use or land management are described for the light fraction(LF)and particulate organic matter(POM).We defined the LF and POM not occluded within microaggregates(53–250µm sized aggregates as unprotected.Our conclusions are illustrated in a new conceptual SOM model that differs from most SOM models in that the model state variables are measurable SOM pools.We suggest that physicochemical characteristics inherent to soils define the maximum protective capacity of these pools,which limits increases in SOM(i.e.C sequestration)with increased organic residue inputs.IntroductionMost current models of SOM dynamics assumefirst-order kinetics for the decomposition of various con-ceptual pools of organic matter(McGill,1996;Paus-tian,1994),which means that equilibrium C stocks are linearly proportional to C inputs(Paustian et al., 1997).These models predict that soil C stocks can, in theory,be increased without limit,provided that C inputs increase without limit,i.e.there are no as-sumptions of soil C saturation.While these models have been largely successful in representing SOM dynamics under current conditions and management practices(e.g.Parton et al.,1987,1994;Paustian et ∗FAX No:+1-970-491-1965.E-mail:johan@ al.,1992;Powlson et al.,1996),usually for soils with low to moderate C levels(e.g.<5%),there is some question of their validity for projecting longer term SOM dynamics under scenarios of ever increasing C inputs(e.g.Donigian et al.,1997).Such scenarios are particularly relevant with the development of new technology designed to promote soil C sequestration through increasing plant C inputs.Native soil C levels reflect the balance of C inputs and C losses under native conditions(i.e.productivity, moisture and temperature regimes),but do not neces-sarily represent an upper limit in soil C stocks.Empir-ical evidence demonstrates that C levels in intensively managed agricultural and pastoral ecosystems can ex-ceed those under native conditions.Phosphorous fer-tilization of Australian pasture soils can increase soil C by150%or more relative to the native condition156(Barrow,1969;Ridley et al.,1990;Russell1960). Soil C levels under long-term grassland(‘near native’) vegetation have also been exceeded in high productiv-ity mid-western no-tillage(NT)systems(Ismail et al., 1994)as well as in sod plots with altered vegetation (Follett et al.,1997).Hence,native soil C levels may not be an appropriate measure of the ultimate C sink capacity of soils.There are several lines of evidence that suggest the existence of a C saturation level based on physiochem-ical processes that stabilize or protect organic com-pounds in soils.While many long-termfield experi-ments exhibit a proportional relationship between C inputs and soil C content across treatments(Larson et al.,1972;Paustian et al.,1997),some experiments in high C soils show little or no increase in soil C content with two to three fold increases in C inputs (Campbell et al.,1991;Paustian et al.,1997;Solberg et al.,1997).Various physical properties(e.g.silt plus clay content and microaggregation)of soil are thought to be involved in the protection of organic materials from decomposer organism.However,these proper-ties and their exerted protection seem to be limited by their characteristics(e.g.surface area),which is con-sistent with a saturation phenomenon(Hassink,1997; Kemper and Koch,1966).A number of soil organic matter models have been developed in the last30years.Most of these mod-els represent the heterogeneity of SOM by defining several pools,typically three tofive,which vary in their intrinsic decay rates and in the factors which control decomposition rates(see reviews by McGill, 1996;Parton,et al.,1994;Paustian,1994).Alternat-ive formulations,whereby specific decomposition rate varies as a function of a continuous SOM quality spec-trum(i.e.instead of discrete pools),have also been developed(e.g.Bosatta and Agren,1996).However, in either case,the representation of the model pools (or quality spectrum)is primarily conceptual in nature. While such models can be successfully validated us-ing measurements of total organic carbon and isotopic ratios of total C(e.g.Jenkinson and Rayner,1977), the individual pools are generally only loosely associ-ated with measurable quantities obtained with existing analytical methods.Consequently,it is not straight-forward to falsify or test the internal dynamics of C transfers between pools and changes in pool sizes of the current SOM models with conceptual pool defin-itions because a direct comparison to measured pool changes is not possible.A closer linkage between theoretical and measur-able pools of SOM can be made by explicitly defining model pools to coincide with measurable quantities or by devising more functional laboratory fractiona-tion procedures or both.The phrases‘modeling the measurable’and‘measuring the modelable’have been coined as representing the two approaches towards a closer reconciliation between theoretical and experi-mental work on SOM(Christensen,1996;Elliott et al.,1996).Various attempts have been made to correlate ana-lytical laboratory fractions with conceptual model pools,with limited success.Motavalli et al.(1994) compared laboratory measurements of C mineraliza-tion with simulations by the Century model(Parton et al.,1994)for several tropical soils.When the active and slow pools in the model were initialized using laboratory determinations of microbial+soluble C for the active pool and light fraction for the slow pool,C mineralization was consistently underestim-ated,although all fractions were highly significantly correlated to C mineralization in a regression ana-lysis.Magid et al.(1996)unsuccessfully attempted to trace14C labeled plant materials using three size-density fractionation methods to define an‘active’pool.Metherell(1992)found that the slow pool in Century was much larger than the particulate organic matter(POM)fraction isolated from a Haplustoll by Cambardella and Elliott(1992).However,Balesdent (1996)found that POM isolated after mild disrup-tion corresponds to the plant structural compartment (RPM)of the Rothamsted carbon model(Jenkinson and Rayner,1997).Acid hydrolysis has been used to estimate Century’s passive C pool(Paul et al.,1997a; Trumbore,1993),but it seems to slightly overestimate the size(Paul et al.,1997a;Trumbore,1993),though not the C turnover rate,of the passive pool(Trumbore, 1993).Nevertheless,Paul et al.(1999)used extended laboratory incubations in combination with acid hy-drolysis to define an active,slow and passive pool of C and were successful in modeling the evolution of CO2in thefield based on these pools.These studies suggest that attempting to measure the modelable has had minimal success to date.There have been a few recent attempts to more closely integrate models and measurements of physi-cochemically defined pools by‘modeling the measur-able’,although Elliott et al.(1996)and Christensen (1996)have presented conceptual models for this ap-proach.Arah(2000)proposed an approach based on analytically defined pools and measurements of13C157Figure1.The protective capacity of soil(which governs the silt-and clay protected C and microaggregate protected C pools),the biochemically stabilized C pool and the unprotected C pool define a maximum C content for soils.The pool size of each fraction is determined by their unique stabilizing mechanisms.and15N stable isotope tracers to derive parameters for a model with measurable pools.The approach con-siders all possible transformations between measured C and N pools and devises a system of equations using observed changes in total C and N and13C and15N for each fraction to solve all model unknowns.Necessary requirements of such an approach are that the analyt-ical fractions are distinct and together account for the total carbon inventory.The objective of this review paper is to summar-ize current knowledge on SOM dynamics and sta-bilization and to synthesize this information into a conceptual SOM model based on physicochemically defined SOM pools.This new model defines a soil C-saturation capacity,or a maximum soil C storage potential,determined by the physicochemical proper-ties of the soil.We propose that the conceptual model developed from this knowledge may form the basis for a simulation model with physicochemically measur-able SOM pools as state variables rather than with the biologically defined pools by Paul et al.(1999).Protected SOM:Stabilization mechanisms, characteristics,and dynamicsThree main mechanisms of SOM stabilization have been proposed:(1)chemical stabilization,(2)phys-ical protection and(3)biochemical stabilization (Christensen,1996;Stevenson,1994).Chemical sta-bilization of SOM is understood to be the result of the chemical or physicochemical binding between SOM and soil minerals(i.e.clay and silt particles).Indeed, many studies have reported a relationship between stabilization of organic C and N in soils and clay or silt plus clay content(Feller and Beare,1997; Hassink,1997;Ladd et al.,1985;Merckx et al., 1985;Sorensen,1972).In addition to the clay con-tent,clay type(i.e.2:1versus1:1versus allophanic clay minerals)influences the stabilization of organic C and N(Feller and Beare,1997;Ladd et al.1992; Sorensen,1972;Torn et al.,1997).Physical protection by aggregates is indicated by the positive influence of aggregation on the accumulation of SOM(e.g.Ed-wards and Bremner,1967;Elliott,1986;Jastrow, 1996;Tisdall and Oades,1982;Six et al.,2000a). Aggregates physically protect SOM by forming phys-ical barriers between microbes and enzymes and their substrates and controlling food web interactions and consequently microbial turnover(Elliott and Coleman, 1988).Biochemical stabilization is understood as the stabilization of SOM due to its own chemical com-position(e.g.recalcitrant compounds such as lignin and polyphenols)and through chemical complexing processes(e.g.condensation reactions)in soil.For our analyses,we divide the protected SOM pool into three pools according to the three stabilization mechanisms described(Figure1).The three SOM pools are the silt-and clay-protected SOM(silt and clay defined as <53µm organomineral complexes),microaggregate-protected SOM(microaggregates defined as53–250µm aggregates),and biochemically protected SOM. Chemical stabilization:Silt-and clay-protected SOM The protection of SOM by silt and clay particles is well established(Feller and Beare,1997;Hassink, 1997;Ladd et al.,1985;Sorensen,1972).Hassink (1997)examined the relationship between SOM frac-tions and soil texture and found a relationship between the silt-and clay-associated C and soil texture,though he did notfind any correlation between texture and amount of C in the sand-sized fraction(i.e.POM C).Based on thesefindings,he defined the capacity158Table1.Regression equations relating silt plus clay proportion to silt and clay associated CSize class a Ecosystem Intercept Slope r20–20µm Cultivated 4.38±0.68b0.26±0.010.41Grassland 2.21±1.940.42±0.080.44Forest−2.51±0.550.63±0.010.550–50µm Cultivated7.18±3.040.2±0.040.54Grassland16.33±4.690.32±0.070.35Forest16.24±6.010.24±0.080.35Size class Clay type Intercept Slope r20–20µm1:1 1.22±0.370.30±0.010.742:1 3.86±0.490.41±0.010.390–50µm1:1 5.5±5.930.26±0.130.382:114.76±2.370.21±0.030.07a Two size classes for silt and clay were reported in the literature.b Value±95%confidence interval.of soil to preserve C by its association with silt and clay particles.Studies investigating the retention of specific microbial products(i.e.amino sugars)cor-roborate the proposition of Hassink(1997)that C associated with primary organomineral complexes arechemically protected and the amount of protection in-creased with an increased silt plus clay proportion of the soil(Chantigny et al.,1997;Guggenberger et al., 1999;Puget et al.,1999;Sorensen,1972).Puget et al.(1999)reported an enrichment of microbial derived carbohydrates in the silt plus clay fraction compared to the sand fraction of no-tilled and conventional tilled soils.However,the amount stabilized by silt and clay differs among microbial products.For example,Gug-genberger et al.(1999)reported a higher increase of glucosamine than muramic acid under no-tillage at sites with a high silt plus clay content.A reexamin-ation of the data presented by Chantigny et al.(1997) leads to the observation that the glucosamine/muramic acid ratio was only higher in perennial systems com-pared to annual systems in a silty clay loam soil and not in a clay loam soil.The silty clay loam soil had a higher silt plus clay content.We expanded the analysis of Hassink(1997)of the physical protection capacity for C associated with primary organomineral complexes(Figure2)across ecosystems(i.e.forest,grassland,and cultivated sys-tems),clay types(i.e.1:1versus2:1),and size ranges for clay and silt(0–20µm and0–50µm;see Ap-Figure 2.The relationship between silt+clay content(%)and silt+clay associated C(g silt+clay C kg−1soil)for grassland,forest and cultivated ecosystems.A differentiation between1:1clay and 2:1clay dominated soils is also made.The relationships indicate a maximum of C associated with silt and clay(i.e.C saturation level for the clay and silt particles),which differs between forest and grassland ecosystems and between clay types.Two size boundaries for silt+clay were used(A)0–20µm and(B)0–50µm. pendices for details).Following the methodology of Hassink(1997)we performed regressions(Figure2 and Table1)between the C content associated with silt and clay particles(g C associated with silt and clay particles kg−1soil;Y axis)and the proportion of silt and clay particles(g silt plus clay g−1soil;X axis).All regressions were significant(P<0.05)and comparison of regression lines revealed that the influ-ence of soil texture on mineral-associated C content differed depending on the size range used for clay and silt particles.Consequently,we did regressions for two different size classes of silt and clay particles(i.e.0–20µm and0–50µm;Figure2and Table1).The intercept for the0–50µm silt and clay particles was significantly higher than for the0–20µm silt and clay particles(Table1).This difference in intercept was159probably a result of the presence of larger sized(20–50µm)silt-sized aggregates in the0–50µm than in the 0–20µm silt and clay particles.These larger silt-sized aggregates have more C per unit material because ad-ditional C binds the primary organomineral complexes into silt-sized aggregates(Tisdall and Oades,1982). However the difference in intercept might also be the result of POM particles of the size20–50µm as-sociated with the0–50µm fraction(Turchenek and Oades,1979).Intercepts for cultivated and forest eco-systems were significantly different for the0–50µm particles,but were only marginally significantly dif-ferent(P<0.06)for the0–20µm particles.Slopes for grassland soils(0–20µm particles)were signi-ficantly different than those for forest and cultivated soils.The differences between grasslands and cultiv-ated lands are likely due to differences in input and disturbance,which causes a release of SOM and con-sequently increased C availability for decomposition. An explanation for the significantly different slopes for grassland and forest soils(Table1)is not imme-diately apparent.Especially that the slope is higher for forest than grassland slopes.This is in contrast to the suggestion that grassland-derived soils have a higher potential of C stabilization than forest-derived because of their higher base saturation(Collins et al.,2000; Kononova,1966).Consequently,this difference in C stabilization by silt and clay particles between forest and grassland systems should be investigated further.In contrast to Hassink(1997),we found signific-antly different relationships for1:1clays versus2:1 clays regressions and for the cultivated versus grass-land regressions(Figure2and Table1)for the0–20µm particles.The effect of clay type was also signific-ant for the0–50µm particles.This lower stabilization of C in1:1clay dominated soils is probably mostly re-lated to the differences between the clay types(see be-low).However,the effect of climate can not be ignored in this comparison because most1:1clay dominated soils were located in(sub)tropical regions.The higher temperature and moisture regimes in(sub)tropical re-gions probably also induce a faster decomposition rate and therefore contributes to the lower stabilization of C by the1:1clays.Nevertheless we believe that the type of clay plays an important role because different types of clay(i.e.1:1and2:1clays)have substantial differences in CEC and specific surface(Greenland, 1965)and should,consequently,have different ca-pacities to adsorb organic materials.In addition,Fe-and Al-oxides are most often found in soils domin-ated by1:1minerals and are strongflocculants.By being strongflocculants,Fe-and Al-oxides can re-duce even further the available surface for adsorption of SOM.We are not certain why soils examined by Hassink(1997)did not follow this reduced capacity to adsorb organic materials;few soils dominated by 1:1clays,however,were included in the data set used by Hassink(1997)and most of them had a low car-bon content.Nevertheless,the difference between the two studies might also be a result of the contrast-ing effect the associated Fe-and Al-oxides can have. The strongflocculating oxides can reduce available surface(see above)but they might also co-flocculate SOM and consequently stabilize it.Therefore,it ap-pears that mechanisms with contrasting effects on SOM stabilization exist and the net effect still needs to be investigated.The different regression lines for grassland and cultivated systems are in accordance with Feller et al.(1997).They also found a signific-ant lower slope for the regression line between the amount of0–2µm particles and the C contained in the0–2µm fraction of cultivated soils compared to non-cultivated soils.The lack of influence of cultiv-ation on the silt and clay associated C observed by Hassink(1997)was probably a result of the low pro-portion of silt and clay and high SOM contents of the soils used.The silt-and clay-associated C formed a small fraction of the total C in his soils.Consequently, sand-associated C accounted for the majority of total soil C.Given this dominance of sand-associated C and its greater sensitivity to cultivation than silt-and clay-associated C(Cambardella and Elliott,1992),in which C is transferred from the sand associated fraction to the silt-and clay-associated fractions during decom-position(Guggenberger et al.,1994),a loss of silt-and clay-associated C upon cultivation is likely to be minimal.In summary,we found,as Hassink(1997)did,a direct relationship between silt plus clay content of soil and the amount of silt-and clay-protected soil C, indicating a saturation level for silt and clay associated C.This relationship was different between different types of land use,different clay types,and for differ-ent determinations of silt plus clay size class.Also, the silt-and clay-associated soil organic matter was reduced by cultivation.Physical protection:Microaggregate-protected SOM The physical protection exerted by macro-and/or mi-croaggregates on POM C is attributed to:(1)the compartmentalization of substrate and microbial bio-160mass(Killham et al.,1993;van Veen and Kuikman, 1990),(2)the reduced diffusion of oxygen into macro-and especially microaggregates(Sexstone et al.,1985) which leads to a reduced activity within the aggregates (Sollins et al.,1996),and(3)the compartmentalization of microbial biomass and microbial grazers(Elliott et al.,1980).The compartmentalization between sub-strate and microbes by macro-and microaggregates is indicated by the highest abundance of microbes on the outer part of the aggregates(Hattori,1988)and a substantial part of SOM being at the center of the aggregates(Elliott and Coleman,1988;Golchin et al., 1994).In addition,Bartlett and Doner(1988)repor-ted a higher loss of amino acids by respiration from the aggregate surfaces than from within aggregates. Priesack and Kisser-Priesack(1993)showed that the rate of glucose utilization decreased with distance into the aggregate.The inaccessibility of substrate for mi-crobes within aggregates is due to pore size exclusion and related to the water-filled porosity(Killham et al., 1993).Many studies have documented a positive influ-ence of aggregation on the accumulation of SOM(An-gers et al.,1997;Besnard et al.,1996;Cambardella and Elliott,1993;Franzluebbers and Arshad,1997; Gale et al.,2000;Golchin et al.,1994,1995;Jastrow, 1996;Monreal and Kodama,1997;Paustian et al., 2000;Puget et al.,1995,1996;Six et al.,1998,1999, 2000a).Cultivation causes a release of C by break-ing up the aggregate structures,thereby increasing availability of C.More specifically,cultivation leads to a loss of C-rich macroaggregates and an increase of C-depleted microaggregates(Elliott,1986;Six et al.,2000a).The inclusion of SOM in aggregates also leads to a qualitative change of SOM.For example, Golchin et al.(1994)reported significant differences in chemical structure between the free and occluded (i.e.within aggregates)light fraction.The occluded light fraction had higher C and N concentrations than the free light fraction and contained more alkyl C(i.e. long chains of C compounds such as fatty acids,lipids, cutin acids,proteins and peptides)and less O-alkyl C(e.g.carbohydrates and polysaccharides).These data suggest that during the transformation of free into intraaggregate light fraction there is a selective decomposition of easily decomposable carbohydrates (i.e.O-alkyl C)and preservation of recalcitrant long-chained C(i.e.alkyl C)(Golchin et al.,1994).Golchin et al.(1995)also found that cultivation decreased the O-alkyl content of the occluded SOM.They sugges-ted that this difference is a result of the continuous disruption of aggregates,which leads to a faster min-eralization of SOM and a preferential loss of readily available O-alkyl C.Hence,the enhanced protection of SOM by aggregates in less disturbed soil results in an accumulation of more labile C than would be maintained in a disturbed soil.Recent studies indicate that the macroaggreg-ate(>250µm)structure exerts a minimal amount of physical protection(Beare et al.,1994;Elliott, 1986;Pulleman and Marinissen,2001),whereas SOM is protected from decomposition in free(i.e.not within macroaggregates)microaggregates(<250µm) (Balesdent et al.,2000;Besnard et al.,1996;Skjem-stad et al.,1996)and in microaggregates within mac-roaggregates(Denef et al.,2001;Six et al.,2000b). Beare et al.(1994)and Elliott(1986)found an increase in C mineralization when they crushed macroaggreg-ates,but the increase in mineralization only accounted for1–2%of the C content of the macroaggregates.In addition,no difference in C mineralization between crushed and uncrushed macroaggregates has been ob-served(Pulleman and Marinissen,2001).In contrast, C mineralization of crushed free microaggregates was three to four times higher than crushed macroaggreg-ates(Bossuyt et al.,2002).Gregorich et al.(1989) observed a substantial higher C mineralization when microaggregates within the soil were disrupted than when lower disruptive energies were used that did not break up microaggregates.Jastrow et al.(1996),us-ing13C natural abundance technique,calculated that the average turnover time of C in free microaggreg-ates was412yr,whereas the average turnover time for macroaggregate associated C was only140yr in the surface10cm.These studies clearly indicate that C stabilization is greater within free microaggregates than within macroaggregates.Further corroborating evidence for the crucial role microaggregates play in C sequestration were reported by Angers et al.(1997), Besnard et al.(1996),Gale et al.(2000)and Six et al.(2000b).Angers et al.(1997)found in afield in-cubation experiment with13C and15N labeled wheat straw that wheat-derived C was predominantly stored and stabilized in free microaggregates.Gale et al. (2000)reported similar C stabilization within free mi-croaggregates in an incubation study with14C-labeled root material.Upon conversion of forest to maize cul-tivation,Besnard et al.(1996)found a preferential accumulation of maize-and forest-derived POM-C in microaggregates compared to other soil fractions. Six et al.(1999)observed a decrease infine intra-macroaggregate-POM(i.e.53–250µm sized POM161(fine iPOM)predominantly stabilized in microaggreg-ates within macroaggregates(Six et al.,2000b))under plough tillage compared to no-till.However,there was no difference in coarse intra-macroaggregate POM (i.e.250–2000µm POM not stabilized by the micro-aggregates within macroaggregates)between tillage systems at three of the four sites studied.They con-cluded that the incorporation and stabilization offine POM-C into microaggregates within macroaggregates and free microaggregates under no-tillage is a dom-inant factor for protection of thefine-sized fraction of POM.Nevertheless,the dynamics of macroaggreg-ates are crucial for the sequestration of C because it influences the formation of microaggregates and the sequestration of C within these microaggregates(Six et al.,2000b).That is,rapid turnover of macroaggreg-ates reduces the formation of microaggregates within macroaggregates and the resulting stabilization of C within these microaggregates(Six et al.,1998,1999, 2000b).Though the incorporation of POM into microag-gregates(versus bonding to clay surfaces;i.e.chem-ical mechanism)seems to be the main process for protection of POM,the clay content and type of soil exert an indirect influence on the protection of POM-C by affecting aggregate dynamics.Franzluebbers and Arshad(1997)suggested that physical protec-tion of POM within aggregates increases with clay content since mineralization of POM-C relative to whole-SOM-C after dispersion and aggregation both increased with increasing clay content(Franzluebbers and Arshad,1996).Different clay types lead to differ-ent mechanisms involved in aggregation(Oades and Waters,1991)and will therefore influence differently the protection of POM through microaggregation. Within the2:1clay minerals,clay minerals with a high CEC and larger specific surface,such as montmoril-lonite and vermiculite,have a higher binding potential than clay minerals with a lower CEC and smaller spe-cific surface,such as illite(Greenland,1965).In con-trast to the2:1minerals,kaolinite and especially Fe-and Al-oxides have a highflocculation capacity due to electrostatic interactions through their positive charges (Dixon,1989;Schofield and Samson,1954).Even though,different mechanisms prevail in soils with dif-ferent clay types,soils seem to have a maximum level of aggregate stability.Kemper and Koch(1966)ob-served that aggregate stability increased to a maximum level with clay content and free Fe-oxides content. Since the physical protection of POM seems to be mostly determined by microaggregation,we hypothes-ize that the maximum physical protection capacity for SOM is determined by the maximum microaggrega-tion,which is in turn determined by clay content,clay type.Biochemical stabilization:Biochemically-protected SOMIn this review,a detailed description of the influ-ence of biochemical stabilization on SOM dynamics will not be given,we refer to an excellent review on this subject by Cadisch and Giller(1997).Nev-ertheless,biochemical stabilization of SOM needs to be considered to define the soil C-saturation level within a certain ecosystem(Figure1).Biochemical stabilization or protection of SOM occurs due to the complex chemical composition of the organic mater-ials.This complex chemical composition can be an inherent property of the plant material(referred to as residue quality)or be attained during decomposition through the condensation and complexation of decom-position residues,rendering them more resistant to subsequent decomposition.Therefore the third pool in our model(Figure1)is a SOM pool that is stabilized by its inherent or acquired biochemical resistance to decomposition.This pool is akin to that referred to as the‘passive’SOM pool(Parton et al.,1987)and its size has been equated to the non-hydrolyzable frac-tion(Leavitt et al.,1996;Paul et al.,1995;Trumbore 1993).Using14C dating,it has been found that,in the surface soil layer,the non-hydrolyzable C is ap-proximately1300years older than total soil C(Paul et al.,1997a,2001).Several studies have found that the non-hydrolyzable fraction in temperate soils includes very old C(Anderson and Paul,1984;Paul et al., 1999;Trumbore,1993;Trumbore et al.,1996)and acid hydrolysis removes proteins,nucleic acids,and polysaccharides(Schnitzer and Khan,1972)which are believed to be more chemically labile than other C compounds,such as aromatic humified compon-ents and wax-derived long chain aliphatics(Paul et al.,1997a).The stabilization of this pool and con-sequent old age is probably predominantly the result of its biochemical composition.However,Balesdent (1996)did notfind any great differences in dynam-ics between the non-hydrolyzable and hydrolyzable C fraction and therefore questioned the relationship between biodegradability and hydrolyzability.Never-theless,we chose the hydrolysis technique to differen-tiate an older and passive C pool,because we think it is the simplest and best available technique to define。

通过做转变层和RAFT技术聚合来制备独立的分子印迹膜并在高效液相色谱中使用摘要独立的分子印迹膜（SS-MIFS）已经通过转变层结构由可逆加成-断裂链转移自由基（RAFT）聚合法来准备。

这个结构，组成和分子印迹的选择性以及质量传递的机理通过电子显微镜，X光照射，傅里叶变换红外光谱仪，比表面积区域分析，热重分析和高效液相色谱进行表征。

分析表明样品具有比表面积高80.5 m2.g−1。

是原始多孔阳极氧化铝基板的几乎9倍以上。

热重分析还表明，样品的热稳定温度高达350 °C。

用高效液相色谱法研究分离能力，揭示了目标分子对可可碱选择性分离的能力。

分离系数为5.37。

关键词：分子印迹膜层状双氢氧化物RAFT聚合化学分离介绍分子印迹膜具有分子印迹和膜技术的特点，现在已成为一种广泛应用于各个领域的技术，如分离，化学传感器，生物受体模型等。

在早期的研究中，分子印迹膜的制备是热或紫外线引发自由基聚合。

这些过程具有简单和容易控制的反应条件，但结果大多有大的颗粒尺寸，不规则形状，从而降低分子印迹效率。

近年来，可控自由基聚合合成超精细、超薄、纳米结构的分子印迹薄膜已成为分子印迹领域的一个重要发展方向。

通过制备方法控制自由基聚合，在分子印迹薄膜样品的活性成分-分子印迹层可以得到稳定性的改善，更均匀和稳定的识别位点，以及较高的分子识别效率。

然而，分子印迹膜的制造方法要么以薄层相邻支撑表面和/或接枝- 从载体材料的反应的选择性启动。

分子印迹层之间的结合的相互作用是弱的范德华力或通过复杂的化学氧化还原或辐射接枝获得的共价键。

此外，这些分子印迹膜的支撑膜是灵活的有机薄膜并不能独立的发挥作用。

因此，无机独立分子印迹膜（SSMIFs）是近年来发展起来的。

例如，杨的团队报道了分子印迹的多孔阳极氧化铝膜的自立建设（PAAO）的内部孔壁直接通过一个浅显的溶胶凝胶过程形成–的印迹层膜。

对多孔薄膜利用刚性基板产生的分子印迹膜具有良好的自支撑结构。

BIOCHAR VOLATILE MATTER CONTENT EFFECTS ON PLANT GROWTH AND NITROGEN TRANSFORMATIONS IN A TROPICALSOILJonathan L. Deenik, A.T. McClellan and G. UeharaDepartment of Tropical Plant and Soil Sciences, University of Hawaii, Honolulu, HI ABSTRACTBiochars made from modern pyrolysis methods have attracted widespread attention as potential soil amendments with agronomic value. A series of greenhouse experiments and laboratory incubations were conducted to assess the effects of biochar volatile matter (VM) content on plant growth, nitrogen (N) transformations, and microbial activities in an acid tropical soil. High VM biochar inhibited plant growth and reduced N uptake with and without the addition of fertilizers. Low VM charcoal supplemented with fertilizers improved plant growth compared with the fertilizer alone. The laboratory experiments showed that high VM biochar increased soil respiration and immobilized considerable quantities of inorganic N. This research shows that biochar with high VM content may not be a suitable soil amendment in the short-term. INTRODUCTIONThe use of biochar as a soil amendment is modeled on the C-rich anthropogenic soils known as “Terra Preta do Indio” (Indian black earth) found in Amazonia and associated with habitation sites of pre-contact Amerindian populations dating as far back as 7,000 cal yr BP (Glaser, 2007). The defining characteristic of Terra Preta soils is the presence of large quantities of charcoal in the soil organic matter to depths of 1 m or greater (Glaser et al., 2000; Sombroek et al., 1993). These soils are remarkable because they have remained fertile and enriched in soil C compared with adjacent forest soils despite centuries of cultivation.Recent efforts to replicate the “Terra Preta” phenomenon using biochars created from modern pyrolysis techniques show that charcoal additions can have an ameliorating effect on highly weathered, infertile tropical soils by increasing CEC and plant nutrient supply, reducing soil acidity and aluminum toxicity, and improving fertilizer efficiency due to reduced nutrient leaching (Glaser at al., 2002; Lehmann et al., 2003). Plant growth response to charcoal amended soils has been variable with both negative and positive results reported in the scientific literature (Glaser at al., 2002). Several studies have reported that plant growth responses are largest when charcoal and fertilizers are combined suggesting a synergistic relationship (Chan et al., 2007; Lehmann et al., 2003; Steiner et al., 2007). Gundale and Deluca (2007) observed that laboratory produced charcoal from ponderosa pine and Douglas-fir had a negative effect on plant growth whereas the same charcoal created from wildfires showed a positive effect on plant growth. The authors speculated that the low temperature charring method used to create the charcoal in the laboratory either created toxic compounds that inhibited plant growth or acted as a source of labile carbon (C) stimulating microbial growth and N immobilization. The objectives of the present research were to determine the effects of charcoal volatile matter content on plant growth and N transformations in a tropical acid soil. We hypothesized that biochar created at low temperatures with high VM would increase microbial activity resulting in a decrease in plant available N due to immobilization.MATERIALS AND METHODSTwo greenhouse bioassays and two laboratory incubations were conducted to test the effects of biochar VM content on plant growth and N transformations. The soil was an infertile, acid Leilehua series (very-fine, ferruginous, isothermic, ustic kanhaplohumults) collected from the 30-80 cm depth at the Waiawa Correctional Facility, Mililani, Oahu Island (N21°26’53”, W157° 57’ 52”). The charcoal feedstock used in our experiments was macadamia nut shells. The charcoal was made using a flash carbonization process developed at the Natural Energy Institute at the University of Hawaii (Antal et al., 2003). Selected chemical properties of the soil and biochars used in the different experiments are presented in Table 1. Total C and N content of the biochars were determined by dry combustion on a LECO CN-2000. Biochar pH was measure in 1:1 slurry of charcoal to deionized water. Base cations were extracted with 1M ammonium acetate at pH 7 and Al+++ was extracted with 1M KCl and measured in solution by inductive coupled plasma spectrophotometer. The effective cation exchange capacity (ECEC) of the biochars and soil was determined by summing the exchangeable cations.Table 1. Selected chemical properties of the Leilehua soil, and the biochars used in the greenhouse and laboratory experiments (LVM = low VM content and HVM = high VM content).VM Ash OC TN pH P K Ca Mg Na Al ECEC%kg-1 cmol c kg-1mgSoilLeilehua 4.28 0.12 4.70 2.22 0.09 0.720.520.29 1.61 3.22 CharcoalLVM6.30 4.18 88.7 0.45 8.1617.2 1.25 3.7 0.31 0.011 22.5MacNutHVM22.5 3.33 85.2 0.45 5.7218.5 0.740.7 0.15 0.032 20.2MacNutIn the first greenhouse bioassay we imposed five treatments consisting of a control (unamended soil), soil+lime, soil+biochar, soil+lime+NPK and soil+biochar+lime+NPK arranged in randomized block design with four replications. The biochar contained 22.5 % VM and was considered a high VM biochar. Biochar was applied to achieve 10% (w/w), lime to achieve 2 T ha-1, N as NH4NO3 at a rate of 200 mg N kg-1, P as Ca(H2PO4)2 to achieve a rate of 750 mg P kg-1, K and Mg were added in solution at a rate equivalent to 200 and 100 kg ha-1 respectively, and the micronutrients Cu, Mn, and Zn were added in solution at a rate of 10 kg ha-1. We used corn (Zea mays, var super sweet #9) as the test crop. Eight corn seeds were planted into each pot and thinned to four plants after emergence. The second greenhouse bioassay consisted of five treatments (unamended soil, soil+lime+NPK, soil + high VM biochar, soil + low VM biochar, soil + low VM biochar + NPK) installed in a complete randomized block design with four replicates. Lime and fertilizers were applied at the same rates as in the first experiment and corn was the test crop. At harvest time, above-ground biomass was cut at the soil surface dried at 70°C for 72 hours, weighed and tissue analyzed for nutrient content according to standard procedures (Hue et al., 2000).We conducted two laboratory studies to evaluate the effect of biochar VM content on net N mineralization rates and on CO2 respiration. Both experiments consisted of three treatments, a control (untreated Leilehua soil) and the Leilehua soil amended with high and low VM macadamia nut biochar applied at the same rate as in the greenhouse experiment. For the Nstudy, the biochar was mixed thoroughly with 50 g (oven dry equivalent) of soil followed by the addition of the appropriate volume of deionized water required to bring the soil to 75% of water holding capacity. The soils were placed in 100 mL beakers, weighed at the outset of the incubation, covered with perforated parafilm, and incubated at constant temperature (28°C) and moisture. Soils were sampled and analyzed for inorganic N, protease activity, and K 2SO 4 extractable organic C and TN after 2, 7, and 14 days. The soluble C fraction of the biochar was determined by shaking 3 g of biochar in 30 mL deionized water for 1 hour and filtering through a 45 μm nylon membrane. For the CO 2 respiration study, we used the alkali adsorption method where 50 g of treated and untreated soils and 50 ml of 0.05 M NaOH were sealed in airtight 1 L mason jars and incubated at 28°C for 14 days (Alef, 1995). The beaker containing the NaOH solution was removed from the mason jar at 48 hour intervals and titrated with 0.05 M HCl following the addition of 0.5 M BaCl 2. Four mason jars with the 0.05 M NaOH solution, but without soil were used as controls.RESULTS AND DISCUSSIONThe high VM biochar used in the first greenhouse bioassay had a significant negative effect on corn growth compared to the control (Fig. 1). Amending the soil with conventional inorganic fertilizers (lime+NPK) produced significant increases in corn growth, but the beneficialcombining charcoal with the fertilizer therewas an approximately 50% decline in corn showed very low N, P and K concentrations in the tissue (data not shown). Tissue N and fertilizers significantly increased tissue N, P, and K concentrations and the accompanying significant rise in dry matter production indicated that the Leilehua soil was severely deficient in N, P, and K. The biochar in combination with fertilizers, however,significantly decreased tissue N, P, and K concentrations compared to the fertilizer control treatment. Our observations were in disagreement with a recent greenhouse experiment reporting that biochar significantly improved N fertilizer use efficiency by radish plants (Chan et al., 2007). We speculated that the relatively high VM content of the biochar used in this experiment may have played a role in inhibiting corn growth. Figure 1. Treatment effects on above ground corn dry matter production in an infertile Leilehua soil amended with high VM biochar and fertilizer (S = soil, S+C = soil + biochar, S+L = soil + lime, S+F+L = soil + NPK + lime, S+C+F = soil + biochar + NPK).The results of the second greenhouse experiment showed that biochar VM content had significant effects on plant growth. High VM biochar significantly reduced shoot dry matter compared with the control whereas low VM biochar had no significant effect on dry mattercharcoal treatment than in the high VMcharcoal treatment. The low VM biocharproduction compared with the fertilizeralone treatment. The high VM biochar reduced N uptake by 50% compared withthe control. On the other hand, the low VM biochar did not reduce N uptake intreatment. Although the low VM biochar with fertilizer treatment did not show ashigh an increase in plant growth nor a significant increase in N uptake compared with the fertilizer treatment as in the results reported by Chan and his group(2007), our results provide evidence that the VM content of the biochar is an important factor affecting its agronomic value as a soil amendment. We suspected that high VM charcoal is a source of labile C for soil microorganisms, and the high C:N ratio of the C source stimulated immobilization of the plant available Nin the soil causing N deficiency in the growing plants. A recent experimentreported similar results showing thatcharcoal produced at low temperature(350°C) had a negative effect on plantgrowth (Gundale and DeLuca, 2007), and the researchers speculated that thedecline in plant growth was caused byphenols in the charcoal, which servedas a high C:N carbon source for soilmicroorganisms.Results from the two incubation VM exerts a strong influence on N mineralization and microbial respiration. The untreated soil showedan initial drop in soil NH 4+-N after twodays from 39.4 to 31.7 mg kg -1 followed by a slow increase to 45.3 and 43.4 mg kg -1 after seven Figure 2. Treatment effects on above ground corn dry matter production in an infertile Leilehua soil amended withhigh and low VM biochar and fertilizer (S = soil, HVM = high VM biochar, LVM = low VM biochar). Figure 3. Biochar effects on soil NH 4+-N in a 14 - day incubation.and fourteen days respectively (Fig. 3). The soil amended with high VM biochar, however, showed a dramatic decline in soil NH 4+-N that persisted throughout the fourteen day incubation. The low VM biochar had a much smaller effect on soil NH 4+-N decreasing it to around 30 mg kg -1. In the CO 2 respiration study, the high VM biochar amendment caused a steep increase in respiration reaching a peak at four days followed by a gradual decline through the 12th day (Fig.4). At day 2 and day 6 the high VMbiochar treatment showed a respiration rate threefold higher than the control, which remained at least twice as high as the control throughout the remainder ofrespiration at day 2 followed by a rapiddecline matching the control values bythe eighth day. The relatively high CO 2 dramatic decline in soil NH 4+-Nconcentration observed in the high VM biochar treatment is strong evidence that biomass was an important factor explaining the observed decline in plant growth and N uptake in the high VMbiochar treatments. The high water extractable C content of the high VM biochar (265 mg C kg -1) compared with the low VM biochar (53 mg kg -1) provided a labile source of C fueling the observed stimulation of microbial activity in the high VM treatment. With the high C:N ratio of the biochar, the microbial biomass was forced to scavenge soil N inducing N deficiency in the growing plants.Figure 4. Biochar effects on CO2 respiration in a 12-day incubation.SUMMARYThis research shows that biochar VM content, or the degree of carbonization, can play a critical role in determining its agronomic value as a soil amendment. Our results provide clear evidence that biochars that are high in VM content (i.e., a typical barbecue charcoal) would not be good soil amendments because they can stimulate microbial activity and immobilize plant available N in the short-term. On the other hand, more fully carbonized biochars with lower VM content containing a smaller labile C component have a smaller effect on soil microbial activity and N immobilization. While our research provides one explanation for why some biochars have a negative effect on plant growth, it still remains unclear why low VM biochars in combination with fertilizer appear to have a beneficial effect on plant growth. Despite our findings elucidating the role of VM content in inhibiting N mineralization, research at the field scale is required to truly assess the agronomic value of biochars as soil amendments.REFERENCESAlef, K. 1995. Soil Respiration, p. 214-216, In K. Alef and P. Nannipieri, eds. Methods inapplied soil microbiology and biochemistry. Academic Press, London.Antal, M.J., K. Mochidzuki, and L.S. Paredes. 2003. Flash carbonization of biomass. Industrial & Engineering Chemistry Research 42:3690-3699.Chan, K.Y., L. Van Zwieten, I. Meszaros, A. Downie, and S. Joseph. 2007. Agronomic values of greenwaste biochar as a soil amendment. Australian Journal of Soil Research 45:629-634. Glaser, B. 2007. Prehistorically modified soils of central Amazonia: a model for sustainable agriculture in the twenty-first century. Philosophical Transactions of the Royal Society B-Biological Sciences 362:187-196.Glaser, B., E. Balashov, L. Haumaier, G. Guggenberger, and W. Zech. 2000. Black carbon in density fractions of anthropogenic soils of the Brazilian Amazon region. Organic Geochemistry 31:669-678.Glaser, B., J. Lehmann, and W. Zech. 2002. Ameliorating physical and chemical properties of highly weathered soils in the tropics with charcoal - a review. Biology and Fertility of Soils 35:219-230.Gundale, M.J., and T.H. DeLuca. 2007. Charcoal effects on soil solution chemistry and growth of Koeleria macrantha in the ponderosa pine/Douglas-fir ecosystem. Biology and Fertility of Soils 43:303-311.Hue, N.V., R. Uchida, and M.C. Ho. 2000. Sampling and analysis of soils and plant tissues. pp.23-30, In J. A. S. a. R. S. Uchida, ed. Plant Nutrient Management in Hawaii Soils. College of Tropical Agriculture and Human Resources, University of Hawaii, Honolulu. Lehmann, J., J.P. da Silva, C. Steiner, T. Nehls, W. Zech, and B. Glaser. 2003. Nutrient availability and leaching in an archaeological Anthrosol and a Ferralsol of the Central Amazon basin: fertilizer, manure and charcoal amendments. Plant and Soil 249:343-357. Sombroek, W.G., F.O. Nachtergaele, and A. Hebel. 1993. Amounts, dynamics and sequestering of carbon in tropical and subtropical soils. Ambio 22:417-426.Steiner, C., W. Teixeira, J. Lehmann, T. Nehls, J. de Macêdo, W. Blum, and W. Zech. 2007.Long term effects of manure, charcoal and mineral fertilization on crop production and fertility on a highly weathered Central Amazonian upland soil. Plant and Soil 291:275-290. ACKNOWLEDGEMENTSWe thank Dr. Michael Antal for providing biochar samples along with proximate analysis data and Yudai Tsumiyoshi and Jocelyn Liu for assistance with laboratory analysis. Funding for this research came in part from USDA HATCH project 863H.。

© 2013 American Chemical Society
The DSCs efficiency is the product of the short-circuit photocurrent density (Jsc), the open circuit voltage (Voc), and the cell fill-factor (FF) divided by the intensity of the incident light (Is):
Paolo Salvatori,†,‡ Gabriele Marotta,†,‡ Antonio Cinti,†,‡ Chiara Anselmi,† Edoardo Mosconi,*,† and Filippo De Angelis*,†
†
Computational Laboratory for Hybrid/Organic Photovoltaics (CLHYO), Istituto CNR di Scienze e Tecnologie Molecolari (ISTM-CNR), Via elce di Sotto 8, I-06213, Perugia, Italy ‡ Department of Chemistry, University of Perugia, Via elce di Sotto 8, I-06213, Perugia, Italy
Article /JPCC
Supramolecular Interactions of Chenodeoxycholic Acid Increase the Efficiency of Dye-Sensitized Solar Cells Based on a Cobalt Electrolyte

溶剂化效应英语Solvent EffectThe solvent effect, also known as solvation, refers to the influence that a solvent has on the physical and chemical properties of a dissolved substance. When a solute is dissolved in a solvent, the solvent molecules surround the solute particles and interact with them. The nature of these interactions can significantly impact the behavior of the solute.In many chemical reactions, the solvent plays a crucial role by providing an environment that can stabilize or destabilize the reactants and products. One of the most well-known examples of the solvent effect is the solubility of polar and nonpolar compounds. Polar solvents, such as water, have a high dielectric constant, which allows them to dissolve ionic and polar substances by forming favorable electrostatic interactions. On the other hand, nonpolar solvents, such as hexane, cannot dissolve polar compounds due to their low dielectric constant.The solvent effect can also influence the rate of chemical reactions. In solution, reactant molecules must collide with each other to form products. The presence of a solvent can increase the frequency of molecular collisions by decreasing the viscosity of the solution and increasing themobility of the solute particles. Additionally, solvents can participate in the reaction itself, either as reactants or as intermediates, leading to new reaction pathways and altering the overall reaction rate.Furthermore, the solvent effect can affect the stability and reactivity of ions in solution. In water, for example, the hydration of ions is responsible for their stability and the ability to form complexes with other species. The solvent effect can also influence the acidity and basicity of compounds. In polar solvents, the solvent molecules can stabilize or destabilize the charged species, leading to the enhancement or suppression of acid-base reactions.In summary, the solvent effect is a fundamental concept in chemistry that describes how the properties and behavior of solute molecules are influenced by the surrounding solvent molecules. Understanding the solvent effect is crucial for predicting and controlling the outcomes of chemical reactions, designing efficient separation methods, and developing new materials with tailored properties.。

布朗硼氢化反应英语The Brown hydroboration reaction, discovered by Herbert C. Brown in the 1950s, revolutionized organic synthesis by offering a versatile method for selectively adding hydroxyl groups to alkenes. This reaction, which involves the addition of borane complexes to alkenes followed by oxidation, has found widespread applications in pharmaceuticals, materials science, and fine chemical manufacturing.The key to the Brown hydroboration reaction lies in its ability to provide anti-Markovnikov selectivity, where the hydroxyl group attaches to the less substituted carbon of the double bond. This selectivity contrasts with traditional acid-catalyzed hydration reactions, which typically follow Markovnikov's rule, favoring attachment to the more substituted carbon.The mechanism of the reaction proceeds in two mainstages. Initially, the alkene coordinates with the borane molecule to form a cyclic transition state, facilitating the addition of boron to the double bond. This step occurs rapidly and selectively due to the electron-deficient nature of borane. Subsequently, oxidation with hydrogen peroxide or other oxidants converts the borane complex into a hydroxyl group, yielding the final alcohol product.The Brown hydroboration reaction offers several advantages over alternative methods. Firstly, it provides a straightforward route to synthesizing alcohols with predictable regioselectivity, which is crucial in the pharmaceutical industry for controlling biological activity. Secondly, the reaction tolerates a wide range of functional groups, including esters, ketones, and nitriles, enhancing its utility in complex molecule synthesis. Additionally, the mild reaction conditions and high functional group tolerance make it compatible with sensitive substrates,reducing side reactions and improving yield.Applications of the Brown hydroboration reaction abound in drug discovery and development. It has been instrumental in the synthesis of pharmaceutical intermediates and natural product derivatives, where precise control over stereochemistry and regiochemistry is paramount. Furthermore, its versatility extends to the preparation of polymers and advanced materials, where tailored functional groups are essential for optimizing material properties.In conclusion, the Brown hydroboration reaction represents a cornerstone of modern organic chemistry, offering chemists a powerful tool for synthesizing complex molecules with high selectivity and efficiency. Its impact spans from fundamental research to industrial applications, driving innovation in fields as diverse as medicine, materials science, and beyond. As research continues to refine reaction conditionsand expand substrate scope, the Brown hydroboration reaction remains at the forefront of organic synthesis, poised to shape the future of chemical innovation.。

第9卷第1期2011年1月生 物 加 工 过 程Ch i nese Journa l o f B ioprocess Eng i neer i ng V o.l 9N o .1Jan .2011do:i 10.3969/.j issn .1672-3678.2011.01.006收稿日期:2010-07-14作者简介:唐远谋(1986 ),男,四川南充人,硕士研究生,研究方向:食品营养与安全;焦士蓉(联系人),副教授,硕士生导师,E-m ai:lj s -rong2004@163.co m响应面法优化芦荟中抗氧化活性成分的提取工艺唐远谋1,焦士蓉1,冷 鹂2,唐鹏程1,刘 佳1,冯 慧1(1.西华大学生物工程学院,成都610039;2.四川大学生命科学学院,成都610064)摘 要:对芦荟中抗氧化活性物质提取工艺及其成分进行研究,通过单因素实验和响应面优化,以提取物对DPPH 自由基的清除率为抗氧化的考察指标,得到芦荟中抗氧化活性成分的提取工艺条件:提取温度29 、料液比(g /mL)1 33、提取时间107s 、微波功率500W,微波辅助水提,此条件下得到的提取物对DPPH 自由基的清除率达91 414%。

提取物活性成分分析表明:提取物中芦荟甙含量为1 5m g /g 、黄酮为1 13mg /g 、多酚为4 33m g /g 、多糖为126 36mg /g 。

关键词:芦荟;抗氧化物质;DPPH 自由基;提取;响应曲面法中图分类号:TS201.1 文献标志码:A 文章编号:1672-3678(2011)01-0024-05Opti m izati on of process para m eters of extraction antioxi dantsfro m A loe usi ng response surface m ethodol ogyTANG Yuan m ou 1,JI A O Sh irong 1,LENG L i 2,TANG Pengcheng 1,LI U Jia 1,FENG Hu i1(1.Schoo l o f B i oeng i neer i ng,X i hua U niversity ,Chengdu 610039,China ;2.Schoo l o f L ife Sc i ences ,Sichuan U ni v ers it y ,Chengdu 610064,Chi na)Abst ract :The process para m eters for extraction o f antiox i d ants fro m Aloe w ere opti m ized and the co m po -nents w ere analyzed .The opti m al process conditi o ns w ere attained by sing le factor m ethod and response surface m e t h odogy .Anti o x idant ab ilicy w as evalvated on the scaveng ing rate o fDPP H free radica.l M icro -w ave assisted ex traction(MAE )by w ater w as chosed and t h e solid -li q u i d ratio w as 1 33,m icro w ave po w -er w as 500W at 29 for 107s .Under t h ese conditi o ns ,the re m ova l rate of DPP H w as 91 414%.The resu lts o f co m ponent analysis for antiox idants show ed that the y ie l d of a l o in ,flavono i d s ,po l y pheno ls ,and po l y sacchari d e w ere 1 5m g /g ,1 13m g /g ,4 33m g /g ,and 126 36m g /g ,respectively .K ey w ords :A loe ;anti o x i d ants ;DPP H free rad ica;l extracti o n ;response surface m ethod 芦荟系百合科(L iliaceae )芦荟属(A loe )多年生的常绿、肉质草本植物,原产于非洲[1]。

C H A P T E R O N EDissolved Organic Matter:Biogeochemistry,Dynamics,and Environmental Significance in SoilsNanthi S.Bolan,*,†Domy C.Adriano,‡Anitha Kunhikrishnan,*,†Trevor James,§Richard McDowell,}and Nicola Senesi #Contents1.Introduction32.Sources,Pools,and Fluxes of Dissolved Organic Matter in Soils 53.Properties and Chemical Composition of Dissolved Organic Matter in Soils133.1.Structural components133.2.Fulvic acid—The dominant component 153.3.Elemental composition204.Mechanisms Regulating Dynamics of Dissolved Organic Matter in Soils204.1.Sorption/complexation 234.2.Biodegradation 274.3.Photodegradation 284.4.Leaching295.Factors Influencing Dynamics of Dissolved Organic Matter in Soils 305.1.Vegetation and land use 315.2.Cultivation325.3.Soil amendments 335.4.Soil pH366.Environmental Significance of Dissolved Organic Matter in Soils 376.1.Soil aggregation and erosion control 376.2.Mobilization and export of nutrients386.3.Bioavailability and ecotoxicology of heavy metals43Advances in Agronomy,Volume 110#2011Elsevier Inc.ISSN 0065-2113,DOI:10.1016/B978-0-12-385531-2.00001-3All rights reserved.*Centre for Environmental Risk Assessment and Remediation (CERAR),University of South Australia,Australia {Cooperative Research Centre for Contaminants Assessment and Remediation of the Environment (CRC CARE),University of South Australia,Australia {University of Georgia,Savannah River Ecology Laboratory,Drawer E,Aiken,South Carolina,USA }AgResearch,Ruakura Research Centre,Hamilton,New Zealand }AgResearch,Invermay Agricultural Centre,Mosgiel,New Zealand #Department of Agroforestal and Environmental Biology and Chemistry,University of Bari,Bari,Italy 12Nanthi S.Bolan et al.6.4.Transformation and transport of organic contaminants506.5.Gaseous emission and atmospheric pollution587.Summary and Research Needs607.1.Macroscale(landscape to global)617.2.Microscale(water bodies and soil profile)617.3.Molecular scale(carbon fractions,organic acids,andmicroorganisms)61 Acknowledgments62 References62“Dissolved organic matter comprises only a small part of soil organicmatter;nevertheless,it affects many processes in soil and water includ-ing the most serious environmental problems like soil and waterpollution and global warming.”(Kalbitz and Kaiser,2003)AbstractDissolved organic matter(DOM)is defined as the organic matter fraction in solution that passes through a0.45m m filter.Although DOM is ubiquitous in terrestrial and aquatic ecosystems,it represents only a small proportion of the total organic matter in soil.However,DOM,being the most mobile and actively cycling organic matter fraction,influences a spectrum of biogeochemical pro-cesses in the aquatic and terrestrial environments.Biological fixation of atmo-spheric CO2during photosynthesis by higher plants is the primary driver of global carbon cycle.A major portion of the carbon in organic matter in the aquatic environment is derived from the transport of carbon produced in the terrestrial environment.However,much of the terrestrially produced DOM is consumed by microbes,photo degraded,or adsorbed in soils and sediments as it passes to the ocean.The majority of DOM in terrestrial and aquatic environ-ments is ultimately returned to atmosphere as CO2through microbial respira-tion,thereby renewing the atmospheric CO2reserve for photosynthesis.Dissolved organic matter plays a significant role in influencing the dynamics and interactions of nutrients and contaminants in soils and microbial functions, thereby serving as a sensitive indicator of shifts in ecological processes.This chapter aims to highlight knowledge on the production of DOM in soils under different management regimes,identify its sources and sinks,and integrate its dynamics with various soil processes.Understanding the significance of DOM in soil processes can enhance development of strategies to mitigate DOM-induced environmental impacts.This review encourages greater interactions between terrestrial and aquatic biogeochemists and ecologists,which is essential for unraveling the fundamental biogeochemical processes involved in the synthesis of DOM in terrestrial ecosystem,its subsequent transport to aquatic ecosystem, and its role in environmental sustainability,buffering of nutrients and pollutants (metal(loid)s and organics),and the net effect on the global carbon cycle.Dissolved Organic Matter31.IntroductionThe total organic matter(TOM)in terrestrial and aquatic environ-ments consists of two operationally defined phases:particulate organic matter(POM)and dissolved organic matter(DOM).For all practical purposes,DOM is defined as the organic matter fraction in solution that passes through a0.45m m filter(Thurman,1985;Zsolnay,2003).Some workers have used finer filter paper(i.e.,0.2m m)in an effort to separate “true”DOM from colloidal materials,but0.45m m filtration appears to be standard(Buffle et al.,1982;Dafner and Wangersky,2002).In some litera-ture,the term dissolved organic carbon(DOC)is used,which represents total organic carbon in solution that passes through a0.45m m filter (Zsolnay,2003).Since carbon represents the bulk of the elemental compo-sition of the organic matter(ca.67%),DOM is often quantified by its carbon content and referred to as DOC.In the case of studies involving soils,the term water-soluble organic matter(WSOM)or water-extractable organic matter(WEOM)is also used when measuring the fraction of the soil organic matter(SOM)extracted with water or dilute salt solution(e.g.,0.5 M K2SO4)that passes through a0.45m m filter(Bolan et al.,1996;Herbert et al.,1993).Recently,the distinction between POM and DOM in the marine environment is being replaced by the idea of an organic matter continuum of gel-like polymers,replete with colloids and crisscrossed by “transparent”polymer strings,sheets,and bundles,from a few to hundreds of micrometers—referred to as oceanic“dark matter”(Dafner and Wangersky,2002).Dissolved organic matter is ubiquitous in terrestrial and aquatic ecosys-tems,but represents only a small proportion of the total organic matter in soil(McGill et al.,1986).However,it is now widely recognized that because DOM is the most mobile and actively cycling organic matter fraction,it influences a myriad of biogeochemical processes in aquatic and terrestrial environments as well as key environmental parameters (Chantigny,2003;Kalbitz et al.,2000;McDowell,2003;Stevenson, 1994;Zsolnay,2003).Dissolved organic carbon has been identified as one of the major components responsible for determining the drinking water quality.For example,DOM leads to the formation of toxic disinfection by-products(DBPs),such as trihalomethanes,after reacting with disinfectants (e.g.,chlorine)during water treatment.Similarly,DOM can be related to bacterial proliferation within the drinking water distribution system.There-fore,the control of DOM has been identified as an important part of the operation of drinking water plants and distribution systems(Volk et al., 2002).In aquatic environments,the easily oxidizable compounds in the DOM can act as chemical and biological oxygen demand compounds, thereby depleting the oxygen concentration of aquifers and influencing4Nanthi S.Bolan et al. aquatic biota(Jones,1992).Dissolved organic carbon can act as a readily available carbon source for anaerobic soil organisms,thereby inducing the reduction of nitrate(denitrification)resulting in the release of green house gases,such as nitrous oxide(N2O)and nitric oxide(NO),which are implicated in ozone depletion(Siemens et al.,2003).Organic pesticides added to soil and aquifers are partitioned preferentially onto DOM,which can act as a vehicle for the movement of pesticide residues to groundwater (Barriuso et al.,1992).Similarly,the organic acids present in the DOM can act as chelating agents,thereby enhancing the mobilization of toxic heavy metals and metalloids[metal(loid)s](Antoniadis and Alloway,2002).The release and retention of DOM are the driving forces controlling a number of pedological processes including podzolization(Hedges,1987).Biological fixation of atmospheric CO2by higher plants during photo-synthesis is the primary driver of global carbon cycle.A major portion of the carbon in aquatic environments is derived from the transport of carbon produced on land.It has been estimated that worldwide about210Mt DOM and170Mt POM are transported annually to oceans from land. Carbon in the ocean is recognized as one of the three main reservoirs of organic material on the planet,equal to the carbon stored in terrestrial plants or soil humus(Hedges,1987).The terrestrially produced DOM is subject to microbial-and photodegradation and adsorption by soil and sediments.The majority of DOM in terrestrial and aquatic environments is returned to the atmosphere as CO2through microbial respiration,thereby ultimately replenishing the atmospheric CO2reserve for photosynthesis and reinvi-gorating the global carbon cycle.Dissolved organic carbon can be envisioned both as a link and bottle-neck among various ecological bined with its dynamic nature,this enables DOM to serve as a sensitive indicator of shifts in ecological processes,especially in aquatic systems.Recently,the significance of DOM in the terrestrial environment has been realized and attempts have been made to extend this knowledge to DOM dynamics in aquatic envir-onments.However,DOM dynamics on land are fundamentally different from those in water,where biomass of primary producers is relatively small, allochthonous sources of DOM are dominant,the surface area of reactive solid particles(i.e.,sediments)is smaller,and the fate of DOM is strongly influenced by photolysis and other light-mediated reactions.In contrast,the dynamics of DOM on land are largely controlled by its interactions with abiotically and biotically reactive solid components.Although there have been a number of reviews on the individual components of DOM in soils(e.g.,sources and sink—Kalbitz et al. (2000);microbial degradation—Marschner and Kalbitz(2003);sorption by soils—Kaiser et al.(1996)),there has been no comprehensive review linking the dynamics of DOM to its environmental significance.This chapter aims to elaborate on the production and degradation of DOM inDissolved Organic Matter5 soils under different landscape conditions,identify its sources and sinks,and integrate its dynamics with environmental impacts.Understanding the long-term control on DOM production and flux in soils will be particularly important in predicting the effects of various environmental changes and management practices on soil carbon dynamics.Improved knowledge on the environmental significance of DOM can enhance the development of strategies to mitigate DOM-induced environmental impacts.It is hoped that this chapter will encourage greater interaction between terrestrial and aquatic biogeochemists and ecologists and stimulate the unraveling of fundamental biogeochemical processes involved in the synthesis and trans-port of DOM in terrestrial and aquatic ecosystems.2.Sources,Pools,and Fluxes of DissolvedOrganic Matter in SoilsNearly all DOM in soils comes from photosynthesis.This represents the various C pools including recent photosynthates,such as leaf litter, throughfall and stemflow(in the case of forest ecosystems),root exudates, and decaying fine roots,as well as decomposition and metabolic by-pro-ducts and leachates of older,microbiologically processed SOM(Figure1) (Guggenberger,et al.,1994a;McDowell,2003;McDowell,et al.,1998). The majority of DOM in soils and aquifers originates from the solubilization of SOM accumulated through vegetation and the addition of biological waste materials(Guggenberger,et al.,1994b;McDowell,2003;McDowell, et al.,1998;Tate and Meyer,1983).The addition of biological waste materials,such as poultry and animal manures and sewage sludges,increases the amount of DOM in soils either by acting as a source of DOM or by enhancing the solubilization of the SOM.Most biological waste materials of plant origin contain large amounts of DOM(Table1)and the addition of certain organic manures such as poultry manure increases the pH and thereby enhances the solubilization of SOM(Schindler et al.,1992).The concentrations of DOM in soils and aquifers are highly susceptible to changes induced by humans,such as cultivation,fire,clear-cutting, wetland drainage,acidic precipitation,eutrophication,and climate change (Kreutzweiser et al.,2008;Laudon et al.,2009;Martinez-Mena et al.,2008; Mattsson et al.,2009;Yallop and Clutterbuck,2009).Dissolved organic matter in environmental samples,such as soils and manures,is often extracted with water or dilute aqueous salt solutions.Various methods have been used to measure the concentration of DOM in extracts (Table2).These methods are grouped into three categories(Moore, 1985;Sharp et al.,2004;Stewart and Wetzel,1981;Tue-Ngeun et al., 2005).The most frequently used method involves the measurement ofabsorption of light by the DOM using a spectrophotometer (Stewart and Wetzel,1981).The second method involves wet oxidation of samples containing DOM and the subsequent measurement of the CO 2released or the amount of oxidant consumed (Ciavatta et al.,1991).This method is often referred to as chemical oxygen demand (COD).Dichromates or permanganates are the most common oxidizing agents used in the wet oxidation of DOM,and the amount of oxidant consumed in the oxidation of DOM is measured either by titration with a reducing agent or by calorimetric methods.The third method involves dry oxidation of DOM to CO 2at high temperature in the presence of a stream of oxygen.The amount of CO 2produced is measured either by infrared (IR)detector or by titration after absorbing in an alkali,or by weight gain after absorbing in ascarite (Bremner and Tabatabai,1971).The most commonly used dry combustion techniques include LECO TM combustion and total organic carbon (TOC)analyzer.B horizonA horizonDOMDOMLitter layer Crop residueC horizonAquiferAgricultural soilForest soil 1111101099886677CO 2CO 2PhotosynthesisPhotosynthesis554433212Parent/geologicmaterialFigure 1Pathways of inputs and outputs of dissolved organic matter (DOM)in forest and agricultural soils.Inputs:1,throughfall and stemflow;2,root exudates;3,microbial lysis;4,humification;5,litter/and crop residue decomposition;6,organic amendments;outputs;7,microbial degradation;8,microbial assimilation;9,lateral flow;10,sorp-tion;11,leaching.6Nanthi S.Bolan et al.Plant litter and humus are the most important sources of DOM in soil,which is confirmed by both field and laboratory (including greenhouse)studies (Kalbitz et al.,2000;Kalbitz et al.,2007;Muller et al.,2009;Table 1Sources of dissolved organic matter input to soilsSourcesTotal organic matter (g C kg À1)Dissolvedorganic matterReference(g C kg À1)(%of total organic matter)Pasture leys Brome grass 13.30.0410.31Shen et al .(2008)Clover 15.10.0390.26Shen et al .(2008)Crowtoe10.40.0360.35Shen et al .(2008)Lucerne Cv.Longdong 11.40.0380.32Shen et al .(2008)Lucerne Cv.Saditi 10.90.0360.33Shen et al .(2008)Sainfoin 13.80.0400.29Shen et al .(2008)Sweet pea 10.20.0340.33Shen et al .(2008)SoilForest soil—litter leachate 60.00.0260.04Jaffrain et al.(2007)Arable soil12.00.150 1.25Gonet et al.(2008)Soil under bermuda grass turf 8.100.300 3.70Provin et al.(2008)Pasture soil 32.0 1.02 3.18Bolan et al.(1996)Pasture soil82.5 3.12 3.80Bolan et al.(1996)Organic amendments Sewage sludge 420 2.420.58Hanc et al.(2009)Sewage sludge 321 6.00 1.87Bolan et al.(1996)Paper sludge 2817.19 2.56Bolan et al.(1996)Poultry manure 4258.18 1.92Bolan et al.(1996)Poultry litter a37775.720.1Guo et al.(2009)Mushroom compost 3857.10 1.84Bolan et al.(1996)Fresh spent mushroom substrate28813346.2Marin-Benito et al.(2009)Composted spentmushroom substrate 27443.415.8Marin-Benito et al.(2009)Separated cow manure 4569.80 2.15Zmora-Nahuma et al.(2005)Poultry manure 4258.18 1.92Bolan et al.(1996)Pig manure2966.132.07Bolan et al.(1996)aBisulfate amended,phytase-diet Delmarva poultry litter.Dissolved Organic Matter 7Table2Selected references on methods of extraction and analysis of DOM in environmental samplesSamples Extraction of DOM Measurement of DOM ReferenceVolcanic ash soils Soil solutions collected by centrifugation ofcores at7200rpm;filtration(0.45m mfilters)DOC by Shimadzu TOC-5000analyzerKawahigashi et al.(2003)Peat—moorsh soil Soil samples were crushed an passed througha1mm sieve,then heated in a redistilledwater at100 C for2h under a reflexcondenser;filtration(0.45m mfilters)DOC by Shimadzu TOC5050A analyzerSzajdak et al.(2007)Soils(medial,amorphic thermic,Humic Haploxerands)Extraction with0.5mol LÀ1K2SO4solution1:5(w/v);filtration(AdvantecMFS Nº5C paper).TOC by combustion at675 Cin an analyzer(Shimadzu—model TOC-V CPN)Undurraga et al.(2009)Moss,litter and topsoil (0–5cm)Aqueous samples were estimated for DOCby oxidation of the sample with asulfochromic mixture(4.9g dmÀ3K2Cr2O7and H2SO4,1:1,w/w)withcolorimetric detection of the reduced Cr3þColorimeter KFK-3at590nm Prokushkin et al.(2006)Soil solutions from forested watersheds of North Carolina Samples werefiltered through a WhatmanG/F glassfiberfilters.Wet combustion persulfatedigestion followed byTOC analyzerQualls and Haines(1991)Organic fertilizer Extracted DOC by0.01M CaCl2solutionwith a solid to solution ratio of1:10(w/v),mixed for30min at200rpm;filtration(0.45m mfilter)Shimadzu TOC-5000ATOC analyzerLi et al.(2005)Soil solution and stream waters along a natural soil catena Soil solution collected by tension-freelysimetersDOC by infrared detectionfollowing persulfateoxidationPalmer et al.(2004)Liquid and solid sludge,farm slurry,fermented straw,soil, and drainage water Water extraction followed by centrifugation(40,000Âg)andfiltration(0.45m mfilter)Dry combustion(DhormannCarbon Analyzer DC-80)Barriuso et al.(1992)Soils,peat extract,sludge,pig and poultry manure and mushroom compost Extracted with water(1:3solid:solution ratio);centrifugation(12,000rpm)andfiltration(0.45m mfilter)Wet chemical oxidation withdichromate followed byback titrationBaskaran et al.(1996)Soil(Entic Haplothord)Extraction with deionized water(1:10solid:solution ratio);filtered through0.45m mpolysulfore membrane Dry combustion(TOCanalyzer Shimadzu5050)Kaiser et al.(1996)Pig manure Extracted with water(1:3solid:solution ratio);shaken at200rpm for16h at4o C;centrifugation(12,000rpm)andfiltration(0.45m mfilter)DOC by Shimadzu TOC-5000A TOC analyzerCheng and Wong(2006)Cow manure slurryfiltered through0.45m m polysulforemembrane TOC analyzer using UVabsorbanceAguilera et al.(2009)Sewage sludge DOC was extracted in a soil:water ratio of1:10(w/v)after1h agitation.Wet combustion withchromate followed by backtitrationGasco´and Lobo(2007)River water Natural water from riverfiltered by0.22m mfilter DOC by wet oxidation TOCanalyzerKrachler et al.(2005)Peat water Peat waterfiltered through0.45m mmembranefilters DOC was analyzed using ahigh-temperature catalyticoxidation method(Dohrman DC-190analyzer)Rixen et al.(2008)River water Filtered through0.7m m glassfiberfilter In situ optical technologyusingfluorescenceSpencer et al.(2007)(continued)Table2(continued)Samples Extraction of DOM Measurement of DOM ReferenceSea water Filtered through0.45m m polysulforemembrane High-temperaturecombustion instrument tomeasure isotopecomposition of DOCLang et al.(2007)Freshwater Filtered through0.7m m glassfiberfilter Acid-peroxydisulfatedigestion and high-temperature catalyticoxidation(HTCO)withUV detectionTue-Ngeun et al.(2005) Effluent water–In situ UV spectrophotometer Rieger et al.(2004)Groundwater,lake water, and effluent –High-performance liquidchromatography-sizeexclusion chromatography-UVAfluorescence systemHer et al.(2003)Sea water and effluent Filtered through0.7m m glassfiberfilter Measurement of carbonatomic emission intensity ininductively coupled plasmaatomic emissionspectrometry(ICP-OES)Maestre et al.(2003)Lake water Water samplesfiltered using precombustedGF/Ffilters TOC analyzer(TOC5000;Shimadzu)Ishikawa et al.(2006)Soil solution and stream water from forested catchments Samples werefiltered through0.45m mfiltersDOC by Shimadzu TOC5050A analyzerVestin et al.(2008)Dissolved Organic Matter11 Sanderman et al.,2008).In forest ecosystems,which are the most intensively studied with regard to C cycling and its associated DOM dynamics,the canopy and forest floor layers are the primary sources of DOM(Kaiser et al., 1996;Kalbitz et al.,2007;Park and Matzner,2003).However,it is still unclear whether DOM originates primarily from recently deposited litter or from relatively stable organic matter in the deeper part of the organic horizon(Kalbitz et al.,2007).In a temperate,deciduous forest,the source of DOM leaching from the forest floor(O layer)is generally a water-soluble material from freshly fallen leaf litter and throughfall(Kalbitz et al.,2007;Qualls et al.,1991).Appar-ently all of the DOM and dissolved organic N(DON)could have origi-nated from the Oi(freshly fallen litter)and Oe(partially decomposed litter) horizons.They further observed that,while about27%of the freshly shed litter C was soluble,only18.4%of the C input in litterfall was leached in solutions from the bottom of the forest floor.Virtually all the DOM leached from the forest floor appeared to have originated from the upper forest floor,with none coming from the lower forest floor—an indication of the role of this litter layer as a sink.The role of freshly deposited litter as DOM source was further corroborated by laboratory studies(Magill and Aber, 2000;Moore and Dalva,2001;Muller et al.,2009;Sanderman et al.,2008). Michalzik and Matzner(1999)found high fluxes of DOM from the Oi layer than from the Oe and Oa layers and indicated that the bottom organic layers acted instead as a sink rather than as a source of DOM.Logically,however, because of the more advanced state of decomposition,the bottom litter layers could produce more DOM than the surface layer.Indeed,Solinger et al.(2001)measured greater DOM fluxes out of the Oa than out of the Oi layer.Recently,Froberg et al.(2003)and Uselman et al.(2007)confirmed with14C data that the Oi layer is not a major source of DOM leached from the Oe layer.In a comprehensive synthesis of42case studies in temperate forests, Michalzik et al.(2001)observed that,although concentrations and fluxes differed widely among sites,the greatest concentrations of DOM(and DON)were generally observed in forest floor leachates from the A horizon and were heavily influenced by annual precipitation.However,somewhat surprisingly,there were no meaningful differences in DOM concentrations and fluxes in forest floor leachates between coniferous and hardwood sites. The flux of soluble organic compounds from throughfall and the litter layer could amount to1–19%of the total litterfall C flux and1–5%of the net primary productivity(Froberg et al.,2007;McDowell and Likens,1988; Qualls et al.,1991).Nearly one-third of the DOM leaving the bottom of the forest floor originated from throughfall and stemflow(Qualls et al.,1991; Uselman et al.,2007).Values for the potential solubility of litter in the field and in laboratory studies are in the5–25%range of the litter dry mass and 5–15%of the litter C content(Hagedorn and Machwitz,2007;McDowell12Nanthi S.Bolan et al. and Likens,1988;Muller et al.,2009;Sanderman et al.,2008;Zsolnay and Steindl,1991).In typical soils,DOM concentrations may decrease by50–90%from the surface organic layers to mineral subsoils(Cronan and Aiken,1985;Dosskey and Bertsch,1997;Worrall and Burt,2007).Similarly,fluxes of DOM in surface soil range from10to85g C mÀ2yrÀ1,decreasing to2–40g C mÀ2 yrÀ1in the subsoils(Neff and Asner,2001).In cultivated and pastoral soils,plant residues provide the major source of DOM,while in forest soils,litter and throughfall serve as the major source (Ghani et al.,2007;Laik et al.,2009).In forest soils,DOM represents a significant proportion of the total C budget.For example,Liu et al.(2002) calculated the total C budgets of Ontario’s forest ecosystems(excluding peat lands)to be12.65Pg(1015g),including1.70Pg in living biomass and10.95 Pg in DOM in soils.Koprivnjak and Moore(1992)determined DOM concentrations and fluxes in a small subarctic catchment,which is composed of an upland component with forest over mineral soils and peat land in the lower section.DOM concentrations were low(1–2mg LÀ1)in precipita-tion and increased in tree and shrub throughfall(17–150mg LÀ1),the leachate of the surface lichens and mosses(30mg LÀ1),and the soil A horizon(40mg LÀ1).Concentrations decreased in the B horizon(17mg LÀ1)and there was evidence of strong DOM adsorption by the subsoils.Khomutova et al.(2000)examined the production of organic matter in undisturbed soil monoliths of a deciduous forest,a pine plantation,and a pasture under constant temperature(20 C)and moisture.After20weeks of leaching with synthetic rain water at pH5,the cumulative values of DOM production followed:coniferous forest>deciduous forest>pasture,the difference being attributed to the nature of carbon compounds in the original residues.The residues from the coniferous forest were found to contain more labile organic components.Among ecosystems types,Zsolnay(1996)indicated that DOM tends to be greater in forest than agricultural soils:5–440mg LÀ1from the forest floor compared with0–70mg LÀ1from arable soils.Other studies have also indicated greater concentrations of DOM and concentrations in grasslands than in arable soils(Ghani et al.,2007;Gregorich et al.,2000;Haynes, 2000).In general,DOM concentration decreases in the order:forest floor> grassland A horizon>arable A horizon(Chantigny,2003).The rhizosphere is commonly associated with large C flux due to root decay and exudation(Muller et al.,2009;Uselman et al.,2007;Vogt et al., 1983).Microbial activity in the rhizosphere is enhanced by readily available organic substances that serve as an energy source for these organisms (Paterson et al.,2007;Phillips et al.,2008).Because of their turnover,soil microbial biomass is also considered as an important source of DOM in soils (Ghani et al.,2007;Steenwerth and Belina,2008;Williams and Edwards, 1993).Thus,microbial metabolites may represent a substantial proportionDissolved Organic Matter13 of the soil’s DOM.It may well be that the rate of DOM production and extent of DOM dynamics in soil is regulated by the rate of litter/residue incorporation in soils,kinetics of their decomposition,and various biotic and abiotic factors(Ghani et al.,2007;Kalbitz et al.,2000;Michalzik and Matzner,1999;Zech et al.,1996).In summary,the various C pools in an ecosystem represent the sources of DOM in soils.Due to their abundance,recently deposited litter and humus are considered the two most important sources of DOM in forest soils. Similarly,recently deposited crop residues and application of organic amendment such as biosolids and manures are the most important sources of DOM in arable soils.However,the role of root decay and/or exudates and microbial metabolites cannot be downplayed in both forested and arable ecosystems.3.Properties and Chemical Composition ofDissolved Organic Matter in Soils3.1.Structural componentsBecause DOM is a heterogeneous composite of soluble organic compounds arising from the decomposition of various carbonaceous materials of plant origin,including soluble microbial metabolites from the organic layers in the case of forest ecosystem,DOM constituents can be grouped into “labile”DOM and“recalcitrant”DOM(Marschner and Kalbitz,2003). Labile DOM consists mainly of simple carbohydrate compounds(i.e., glucose and fructose),low molecular weight(LMW)organic acids,amino sugars,and LMW proteins(Guggenberger et al.,1994b;Kaiser et al.,2001; Qualls and Haines,1992).Recalcitrant DOM consists of polysaccharides (i.e.,breakdown products of cellulose and hemicellulose)and other plant compounds,and/or microbially derived degradation products(Marschner and Kalbitz,2003)(Table3).Soil solution DOM consists of LMW carbox-ylic acids,amino acids,carbohydrates,and fulvic acids—the first comprising less than10%of total DOM in most soil solutions and the last(i.e.,fulvic acid)being typically the most abundant fractions of DOM(Strobel et al., 1999,2001;Thurman,1985;van Hees et al.,1996).Dissolved organic matter is separated into fractions based on solubility, molecular weight,and sorption chromatography.Fractionation of DOM by molecular size and sorption chromatography separate DOM according to properties(hydrophobic and hydrophilic)which regulate its interaction with organic contaminants and soil surfaces.The most common technique for the fractionation of aquatic DOM is based on its sorption to non-ionic and ion-exchange resins(Leenheer,1981).。

研究La2−x Ca x CuO4钙钛矿对低温水汽转换反应的影响S.S. Maluf a, P.A.P. Nascente a, C.R.M. Afonso a, E.M. Assaf b,∗a Universidade Federal de São Carlos, Departamento de Engenharia de MateriaiCEP 13565-905, São Carlos, SP, Brazilb Universidade de São Paulo, Instituto d e Química de São Carlos, CEP 13560-970,São Carlos, SP, Brazil摘要：微量的钙对钙钛矿的结构和催化性质的影响已经被研究。

这种样品已经可以用沉淀的方法合成。

钙钛矿氧化物使用X放射线、热塑线、X射线吸收近边结构、电子扫描显微镜、透射显微镜进行表征。

在290摄氏度，在管式反应器内进行的水汽转换反应催化测试表明：表面积在6～18 m2g-1的所有样品具有良好的钙钛矿结构。

用钙取代部分的镧增强了钙钛矿的稳定性和提高了他们的压缩温度。

对于水汽转换反应有催化活性的所有钙钛矿催化剂中，催化活性最好的是组成为La1.85Ca0.15CuO4的催化剂，但是样品中含有5%和10%的钙时具有对反应具有最好的选择性。

这些结果可能与钙的促进作用，大的表面积以及具有还原性的铜和一价铜有关。

关键词：水汽转化反应钙钛矿催化剂1．简介氢被认为是未来的一种重要的清洁能源，因为它可以用作各种各样的高效能的燃料电池原料，并且可以由各种各样的可循环和不可循环原料制得[1]。

对碳氢化合物、碳水化合物、乙醇燃料的催化改性是生产质子交换膜所需氢的一种具有吸引力的选择。

通过改性这些燃料生产氢的一个主要难题是：合成大量的一氧化碳（10—15%）[2-4]，当一氧化碳在改性气中的含量超过30ppm，就会是燃料电池正极催化剂中毒。

第30卷第4期2011年8月红外与毫米波学报J．Infrared Millim．WavesVol．30，No．4August ，2011文章编号：1001－9014（2011）04－0316－06收稿日期：2010-05-30，修回日期：2010-10-17Received date ：2010-05-30，revised date ：2010-10-17基金项目：国家“973”计划项目（2007CB407203）；国家自然科学基金项目（30872073）；“十一五”国家科技支撑计划重大项目（2006BAD09B0603）作者简介：刘炜（1978-），男，陕西咸阳人，博士研究生，主要从事遥感与GIS 应用研究，E-mail ：york5588@nwsuaf．edu．cn．*通讯作者：E-mail ：chqr@nwsuaf．edu．cn．不同尺度的微分窗口下土壤有机质的一阶导数光谱响应特征分析刘炜1，常庆瑞1*，郭曼1，邢东兴1，2，员永生1（1．西北农林科技大学资源环境学院，陕西杨凌712100；2．咸阳师范学院资源环境系，陕西咸阳712000）摘要：使用高光谱仪ASD Field Spec 在波长范围400 1000nm 内采集有机质含量不同的土壤反射光谱数据并作对数变换处理；之后在不同尺度的微分窗口下求取其一阶导数（一阶导数光谱）并进行小波阈值去噪；从一阶导数光谱中提取特征参数表征有机质含量变化．结果表明，微分窗口尺度w =1 5时，土壤一阶导数光谱中含有大量噪声，对一阶导数光谱曲线形态和有机质吸收特征的识别造成严重干扰；微分窗口尺度w =6 15时，土壤一阶导数光谱中的噪声得到一定程度的去除，但仍无法准确判别有机质的吸收特征；微分窗口尺度w =16 30时，土壤一阶导数光谱中的噪声被有效去除，其中当w =19时，从一阶导数光谱中提取的特征参数MD 19s 与土壤有机质含量的相关系数为－0．803．MD 19s 能够较为准确地指示有机质含量变化，而且运算简单，易于实现，为在精准农业中采用可见/近红外反射光谱分析技术快速检测土壤有机质提供了新的途径．关键词：可见/近红外光谱；土壤有机质；一阶导数光谱；小波去噪；特征增强；特征提取中图分类号：S15文献标识码：AAnalysis on derivative spectrum feature for SOMunder different scales of differential windowLIU Wei 1，CHANG Qing-Rui 1*，GUO Man 1，XING Dong-Xing 1，2，YUAN Yong-Sheng 1（1．College of Resources and Environment ，Northwest A＆F University ，Yangling 712100，China ；2．Department of Resources Environment ，Xian yang Normal College ，Xianyang 712000，China ）Abstract ：The hyper-spectral reflectance of soil was measured by a ASD FieldSpec within 400 1000nm ，then treated withlogarithmic transformation．First derivative of soil spectra with different scales of differential window were acquired and de-noised by the threshold denoising method based on wavelet transform．From the first derivative of soil spectra ，feature pa-rameters used as indicators for soil organic matter content were extracted．Results show that ：（1）When the number of the scale of differential window was set as W =1 5，it is difficult to identify the spectrum contour and response feature in first derivative of soil spectra because of much noise．（2）When W =6 15，noise in first derivative of soil spectra is partly removed ，and spectrum contour is identified roughly．However spectral response feature resulted from different organic con-tent levels can not be identified clearly．（3）When W =16 30，noise in first derivative of soil spectrua is removed effec-tively．The coefficient of correlation between organic matter content and feature parameter MD 19s is 0．803．MD 19s can be used as one of the best indicators for soil organic matter content．Key words ：VIS /NIR spectrum ；soil organic matter （SOM ）；first derivative of spectrum ；wavelet denoising ；feature enhancement ；feature extraction PACS ：42．72．Ai引言传统的土壤有机质（Soil Organic Matter ，SOM ）化学测定方法，虽然测定精度较高，但耗时、费力、成本高，而且还存在着有害、污染、测点数量和范围有限等问题．因而无法满足精准农业、变量施肥技术对4期刘炜等：不同尺度的微分窗口下土壤有机质的一阶导数光谱响应特征分析详细掌握土壤养分时空变异状况的需求．现代可见/近红外反射光谱分析技术，能够充分利用全谱段或多波长光谱数据进行定性或定量分析，并且具有速度快、成本低、效率高、测量方便、测试重现性好等特点，近年来，已经被越来越广泛地应用于食品工业、石油化工、农业、制药等多个领域［1-3］．以往大量研究表明，可见/近红外光谱段400 1000nm是土壤有机质最主要的光谱响应区域，具有对有机质含量进行定量分析的潜力［4-6］．一些研究［7-8］还表明对土壤高光谱数据进行导数变换，可以在一定程度上减弱土壤类型、样品粒度等因素的影响，有助于挖掘有机质的吸收特征．大量试验结果表明，当采用不同尺度的微分窗口对土壤高光谱数据进行导数变换时，所获取的土壤一阶导数光谱的形态会因光谱中高频噪声干扰程度的不同而产生较大差异．实际上，对高光谱数据进行导数变换，并不完全等同于从数学意义上对连续、可微函数进行求导运算，而是在一定尺度的微分窗口下，通过一阶差商实现对一阶求导的近似代替［9-11］．当微分窗口取较小的尺度时，导数变换在提供精细的光谱形态变化信息的同时，也会放大光谱中的高频噪声，对光谱曲线上反射峰、吸收谷的识别、定位及相关计算造成严重干扰；当微分窗口取较大的尺度时，导数变换具有一定的平滑去噪功能（差分运算本质上也是一种加权数字平滑［1］），并且微分窗口尺度越大，曲线平滑效果越好．然而，在较大尺度的微分窗口下进行导数变换，也会对一阶导数光谱曲线上的极值点和拐点进行平滑，因而在降噪的过程中，也损失掉了光谱曲线上锐变尖峰成分可能携带的重要信息，导致光谱分析能力下降．因此，选取合适的微分窗口尺度，是从土壤一阶导数光谱中提取特征参数定量检测有机质含量的一个重要前提．试验在不同尺度的微分窗口下对土壤高光谱数据进行导数变换，并从一阶导数光谱中提取特征参数表征有机质含量变化，之后，分析微分窗口尺度变化对特征参数的影响．试验旨为在精准农业中采用可见/近红外光谱反射光谱分析技术定量检测土壤有机质，以及提高高光谱参数准确性和实用性方面提供依据．1材料与方法1．1样品采集与制备土壤样品采自陕西省眉县，采样区土壤为褐土，质地为壤质粘土，土层深厚．试验依据土壤剖面发生层次，分层采集土壤样品，采样深度为0 60cm．为了从光谱数据中消除或降低土壤水分、土壤粒度等因素的对土壤有机质吸收特征的影响，试验将土壤样品置于实验室内自然风干，之后用木棍滚压，并去除沙砾石块及植物残体，接下来研磨、过筛（100目尼龙筛）．试验获取土壤样品36个，每个土壤样品分成两份，一份采用重铬酸钾法测定土壤有机质含量，另一份用来测量光谱数据．36个样本中，有机质含量的最大值为43．91g*kg－1，最小值为2．11g* kg－1，平均值为13．72g*kg－1．1．2光谱测量使用高光谱仪ASD Field Spec在波长范围350 1050nm内，连续测量经预处理后的土壤样品的反射光谱数据，光谱采样间隔1．4nm，重采样间隔1nm．测量光谱前将土壤样品放置在直径16cm，深度3cm 的盛样皿上，调整盛样皿使其处于水平位置，平整土样表面使样品厚度均匀．暗室内测试光源为能够提供平行光的1000W的镁光灯，距土壤表层中心70cm，光源照射方向与垂直方向的夹角为15ʎ．经多次实验后光纤探头的视场角选定为7．5ʎ，置于离土样表面40cm的垂直上方接收光谱数据．测试前以白板定标，每个土壤样品采集10条光谱数据，然后将其算术平均值作为该土壤样品的实际光谱反射数据．1．3数据处理可见/近红外光谱段400 1000nm是土壤有机质最主要的光谱响应区域．然而，该波长范围内土壤光谱反射率水平整体较低，有机质含量不同的各条光谱曲线之间距离较近，没有显著的峰谷特征，不利于特征参数提取［1］．为此，试验在波长范围400 1000nm内对土壤原始光谱进行对数变换和导数变换，以增强有机质含量变化引起的光谱响应差异．对数变换采用的计算公式为［10-12］A（λ）=Ln［1/R（λ）］，（1）式中：λ代表波长位置，取值区间为400 1000nm；R（λ）代表波长位置λnm处的土壤原始光谱反射率；A（λ）是经对数变换处理后的光谱值．导数变换采用的计算公式为［1］D（λ）=［A（λ）–A（λ+w）］/w，（2）式中w代表微分窗口尺度；D（λ）代表波长位置λnm处土壤光谱反射率的一阶导数；λ的取值区间为400 1000nm．2结果与分析2．1对数变换对土壤有机质一阶导数光谱响应特713红外与毫米波学报30卷征的影响图1（a ）显示了波长范围400 1000nm 内，有机质含量不同（25．67，9．37，7．31，4．20g /kg ）的土壤反射光谱曲线；图1（b ）是对它们进行对数变换处理后的结果．从图1（b ）中可以看出，在沿着波长增加的方向上，经对数变换处理后的光谱值大致以线性趋势从2．70下降至0．80，变动区间较原始光谱有所增加；对于不同的有机质含量水平，光谱曲线整体上随有机质含量水平的提高而提高，表现出正相关性；各条光谱曲线之间的距离较图1（a ）中的也有所加大．整体而言，400 1000nm 内，土壤有机质含量的变化可以从图1（b ）光谱曲线的分异表现中得到一定程度的反映，但有机质含量不同的各条光谱曲线仍大致以线性趋势变化，并且没有反映样品信息突出的反射峰、吸收谷．图1对数变换对土壤光谱反射率的影响Fig．1Effect of logarithmic transformation on soil spec-tra under different organic matter content levels2．2不同尺度的微分窗口对土壤有机质一阶导数光谱响应特征的影响在不同尺度的微分窗口下（w =1，2，…，30），求取对数变换后的土壤光谱的一阶导数（一阶导数光谱），结果如图2所示；图3则显示了一阶导数光谱与有机质含量之间的相关系数．结合图2与图3可以看出，随着微分窗口尺度的逐渐增大，导数变换的平滑效果越来越明显．w =1 5时，微分窗口的尺度较小，导数变换的平滑作用较为有限，一阶导数光谱曲线上仍保留有大量噪声，致使曲线轮廓以及因有机质含量变化引起的响应特征受到遮蔽干扰，难以识别，敏感波段无法提取，光谱质量较差；并且在对应的微分窗口尺度下，波长范围400 1000nm 内，相关系数曲线振荡强烈，频率高、幅度大，表现很不稳定．w =6 15时，随着微分窗口尺度的逐渐增大，导数变换的平滑作用有所提升，光谱噪声得到了一定程度的去除，土壤一阶导数光谱曲线的大致轮廓能够被识别出来；但波长范围400 1000nm 内，因有机质含量变化引起的光谱响应特征仍受到较强噪声的干扰，无法准确判别；对应微分窗口尺度下的相关系数曲线，仍然振荡频繁、起伏较大，不利于敏感波段提取．图2不同尺度的微分窗口对土壤一阶导数光谱响应特征的影响Fig．2First derivative of soil spectra under different soil matter organic content levels and different scales of differ-ential window8134期刘炜等：不同尺度的微分窗口下土壤有机质的一阶导数光谱响应特征分析图3不同尺度的微分窗口对土壤一阶导数光谱与有机质含量相关系数的影响Fig．3Correlation coefficients between organic matter contents and first derivative of soil spectra under differ-ent scales of differential windoww =16 30时，随着微分窗口尺度的不断增大，导数变换对光谱曲线的平滑作用进一步加强，土壤一阶导数光谱中的噪声得到有效去除，曲线轮廓更加清晰．从图2（c ）中还可以发现，波长范围450 600nm 内，有机质含量不同的各条光谱曲线均存在一个“凸”状的特征峰；其中在“凸”状特征峰的核心区域，波长范围500 570nm 内，一阶导数光谱值维持在一个较高的平台上小幅振荡；对于不同的有机质含量水平，该波长范围内的光谱值随有机质含量的增加整体呈下降趋势，相对于其它波长位置，该波长范围内的光谱值表现出了较为一致、显著的响应特征．从图3（c ）中还可以看出，波长范围500 570nm 内相关系数值小幅波动，表现较为稳定．鉴于w =16 30时，波长范围500 570nm 内的土壤一阶导数光谱值相互之间比较接近，而且波动程度不大；对有机质含量变化，整体上也表现出了较为一致、显著的响应特征，试验考虑以该波长范围内光谱值的平均值作为特征参数表征有机质含量变化．采用的计算公式为MD w s=171·∑570λ=500D w s（λ），（3）式中，λ代表波长位置；w 代表微分窗口尺度，w =1，2，…，30；D w s （λ）代表经对数变换处理后，微分窗口尺度为w ，波长位置λnm 处的土壤一阶导数光谱值；MD w s 则是波长范围500 570nm 内D ws （λ）的平均值．接下来，试验进一步计算了当微分窗口取不同的尺度时，MD w s 与土壤有机质含量之间的相关系数，结果如图4（a ）所示．从图中可以看出，随着微分窗口尺度的逐渐扩展，相关系数曲线先下降、后上升，大体上呈开口向上的“凹”状波形；其中，在“凹”状波形的前段，当微分窗口取较小的尺度时，相关系数曲线有一定的起伏波动；当微分窗口尺度w =16 20时，相关系数值处于“凹”状波形的底部区域，基本保持在－0．800 －0．805之间，变化趋势十分稳定；其中，w =19时，相关系数取得负的最小值－0．803．显然，在所有的微分窗口尺度中，当w =19时得到的MD 19s 更适合用作特征参数指示有机质含量变化．2．3不同尺度的微分窗口对小波去噪后一阶导数光谱响应特征的影响为了进一步分析微分窗口尺度变化对土壤有机质一阶导数光谱响应特征的影响，试验对各个微分窗口尺度下的土壤一阶导数光谱，进行了小波阈值去噪处理（以“sym8”作为小波母函数，分解尺度J =3，选择“Heursure ”阈值选取规则和“sln ”阈值调整方法［13，14］），结果如图5所示．从中可以看出，经小波阈值去噪处理后，各个微分窗口尺度下的土壤一阶导数光谱的曲线轮廓，都变得十分清晰、光滑；波长范围450 600nm 内的“凸”状特征峰在不同的有机质含量水平下的分异表现也较为明显．同样，为了表征土壤有机质含量变化，试验在不同尺度的微分窗口下，求取波长范围500 570nm 内经小波去噪后的一阶导数光谱值的平均值MD wd 作为特征参数，采用的计算公式为MD w d=171·∑570λ=500D w d（λ），（4）式中λ代表波长位置；w 代表微分窗口尺度，w =1，913红外与毫米波学报30卷图4不同尺度的微分窗口对特征参数的相关系数的影响Fig．4Correlation coefficients between organic mat-ter contents and feature parameters under differentscales of differential window2，…，30；D wd（λ）代表经对数变换及小波阈值去噪处理后，微分窗口尺度为w的土壤一阶导数光谱值．MD wd 则是波长范围500 570nm内D wd（λ）的平均值．试验计算了MD wd与土壤有机质含量之间的相关系数，结果如图4（b）所示．从图中可以看出，当微分窗口尺度逐步扩展时，相关系数曲线呈开口向上、十分光滑的“凹”状波形，其整体变化趋势与图4（a）中相关系数曲线的整体变化趋势大体一致；但波动程度明显降低，曲线形态十分光滑；相对于图4（a），图（4）b中相关系数曲线的整体变动区间有所收窄，在－0．797 －0．753之间；当微分窗口尺度w =15 21时，相关系数值处于“凹”状波形的底部区域；其中，当w=20时，相关系数取得了负的最小值－0．797．对比MD19s 和MD20d，可以看出二者的微分窗口尺度值相差不大，对应的相关系数值也较为接近，但MD19s的表现更好一些；同时，其相关计算较MD20d也更容易实现、易于掌握、推广．故试验认为MD19s更适合用作特征参数指示有机质含量变化．3讨论可见/近红外光谱段400 1000nm是土壤有机图5不同尺度的微分窗口对去噪后的土壤一阶导数光谱响应特征的影响Fig．5Denoised first derivative of soil spectrum under different soil matter organic content levels and different scales of differenti-al window质最主要的光谱响应区域．然而，在该波长范围内，土壤光谱反射率水平整体较低，有机质含量不同的各条光谱曲线之间距离较近，没有显著的峰谷特征，不利于特征参数提取［1］．为此，试验对土壤原始光谱进行对数变换，以增强有机质含量变化引起的光谱响应差异．除对数函数外，还可以选取其它具有较强放大增益的函数，如正切函数、指数函数等作为变换函数对有机质的响应特征进行增强处理．此外，还可以考虑针对能够反映有机质吸收特性的敏感波段，给变换函数的自变量赋以一定的偏移量，以尽可能地将敏感波段置于具有最佳放大增益效果的对应的自变量的取值区间，进一步提升某些特定敏感波段在解释有机质含量变化中的作用．在可见/近红外反射光谱分析技术中，利用导数变换可以获取精细的光谱形态变化信息，并能够增强局部位置（如极值点、拐点等）光谱反射率对目标物质含量变化的响应差异．对于土壤高光谱数据，除一阶导数变换外，还可以在选取具有合适尺度的微分窗口的前提下，考虑采用二阶或三阶等更高阶次导数变换，以进一步挖掘因有机质吸收引起的峰谷特征；之后，根据反射峰（吸收谷）的形态，选择合适的吸收特征描述方法，以提取稳定性更强，敏感程度也好的特征参数表征有机质含量变化．4结论试验对土壤原始光谱进行了对数变换，导数变0234期刘炜等：不同尺度的微分窗口下土壤有机质的一阶导数光谱响应特征分析换以及小波阈值去噪处理；之后，在不同尺度的微分窗口下分析土壤一阶导数光谱对有机质含量变化的响应特征，并提取特征参数MD ws 和MD wd．试验得到的结论如下：（1）微分窗口尺度w=1 5时，土壤一阶导数光谱中含有大量噪声，致使光谱曲线的形态和有机质的吸收特征难以识别，敏感波段无法提取，光谱质量较差．（2）微分窗口尺度w=6 15时，土壤一阶导数光谱中的噪声得到了一定程度的去除，光谱曲线的大致轮廓能够被识别出来，但因有机质含量变化引起的光谱响应差异仍无法得到准确判别．（3）微分窗口尺度w=16 30时，土壤一阶导数光谱中的噪声得到了有效地去除；波长范围450 600nm内呈现出“凸”状的特征峰；其中，在“凸”状特征峰的核心区域，波长范围500 570nm内，一阶导数光谱值对有机质含量变化整体表现了出较为一致、显著的响应特征．（4）特征参数MD19s与土壤有机质含量的相关系数为－0．803，相对于MD20d ，MD19s可以更好地用来指示有机质含量变化．波长范围400 1000nm内，土壤有机质吸收引起的光谱曲线的变化比较微弱，一般均先要求对土壤原始光谱进行某种变换，以增强光谱响应差异，之后提取特征参数检测有机质．在光谱特征增强的数学变换方法中，对数变换，指数函数变换、导数变换等都应用较多．可以针对光谱形态和有机质的吸收特性，对各种增强方法进行更加细致地调整、改进，或者加以综合运用，并选取恰当的吸收特征描述方法［1］，以提取稳定性更强、敏感程度更好的特征参数，为采用可见/近红外反射光谱分析技术快速检测土壤有机质，提供更实用、有效的途径，这将是下一步研究工作重点．REFERENCES［1］LI Min-Zan，HAN Dong-Hai，WANG Xiu．Spectral analysis technology and its application［M］．Beijing：Science Press （李民赞，韩东海，王秀．光谱分析技术及其应用．北京：科学出版社），2006：115-279．［2］HE Yong，SONG Hai-Yan，Pereira A G，et al．Measure-ment and analysis of soil nitrogen and organic matter content using near-infrared spectroscopy techniques［J］．Journal of Zhejiang University SCIENCE，2005，6B（11）：1081-1086．［3］BAO Yi-Dan，HE 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