Binding of Organic Ligands with Al(III) in Dissolved Organic Matter

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Binding of Organic Ligands with Al(III) in Dissolved Organic Matter from Soil: Implications for Soil Organic Carbon Storage Guang-Hui Yu,† Min-Jie Wu,† Guan-Ran Wei,‡ Yi-Hong Luo,† Wei Ran,† Bo-Ren Wang,§ Jian−chao Zhang,† and Qi-Rong Shen*,† †

Jiangsu Key Lab for Organic Solid Waste Utilization, Key Laboratory of Plant Nutrition and Fertilization in Low-Middle Reaches of the Yangtze River, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, People's Republic of China ‡ School of Environmental Sciences and Technology, Shanghai Jiaotong University, Shanghai 200240, People's Republic of China § Key Laboratory of Plant Nutrition and Nutrient Cycling, Ministry of Agriculture of China and Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, People's Republic of China S Supporting Information *

ABSTRACT: The binding characteristics of organic ligands with Al(III) in soil dissolved organic matter (DOM) is essential to understand soil organic carbon (SOC) storage. In this study, two-dimensional (2D) FTIR correlation spectroscopy was developed as a novel tool to explore the binding of organic ligands with Al(III) in DOM present in soils as part of a long-term (21-year) fertilization experiment. The results showed that while it is a popular method for characterizing the binding of organic ligands and metals, fluorescence excitation− emission matrix−parallel factor analysis can only characterize the binding characteristics of fluorescent substances (i.e., protein-, humic-, and fulvic-like substances) with Al(III). However, 2D FTIR correlation spectroscopy can characterize the binding characteristics of both fluorescent and nonfluorescent (i.e., polysaccharides, lipids, and lignin) substances with Al(III). Meanwhile, 2D FTIR correlation spectroscopy demonstrated that the sequencing/ordering of organics binding with Al(III) could be modified by the use of longterm fertilization strategies. Furthermore, 2D FTIR correlation spectroscopy revealed that the high SOC content in the chemical plus manure (NPKM) treatment in the long term fertilization experiment can be attributed to the formation of noncrystalline microparticles (i.e., allophane and imogolite). In summary, 2D FTIR correlation spectroscopy is a promising approach for the characterization of metal−organic complexes.

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INTRODUCTION Fluorescence excitation−emission matrix (EEM) spectroscopy combined with parallel factor (PARAFAC) analysis is a popular method for investigating the complexes between Al(III) and organic ligands in DOM from soil,1−3 water,4,5 and leachates.6 Dissolved organic matter (DOM) in soil is a small but reactive fraction of soil organic matter.7 However, the stability and dynamics of DOM are essential to soil organic carbon storage. Some investigators have shown that noncrystalline microparticles such as allophane [Al2O3(SiO2)1−2(H2O)2.5−4] and imogolite [(OH)3Al2O3SiOH] in soil DOM control soil organic carbon sequestration.7,9 Therefore, it is essential to investigate the formation of complexes between soil DOM and Al(III). Although the fluorescence EEM-PARAFAC method © 2012 American Chemical Society

can characterize complexes of protein-, humic-, and fulvic-like substances with Al(III), one limitation of this method is that it cannot characterize complexes of nonfluorescent substances (i.e., polysaccharides, lipids, and lignin) with Al(III), even though such substances are the predominant components in soil. Fourier transform infrared (FTIR) spectroscopy is a commonly used technique that can distinguish between the principal organics in soil DOM, including both fluorescent and Received: Revised: Accepted: Published: 6102

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nonfluorescent substances.10,11 By determining the FTIR spectra of DOM after the titration of Al(III), it is possible to explore the complexes of organic ligands in DOM and Al(III). However, the peaks in the conventional FTIR spectra often overlap because of the extreme heterogeneity of DOM.12,13 Recent investigations have demonstrated that two-dimensional (2D) correlation spectroscopy can be applied to solve the overlapped peaks problem by distributing the spectral intensity trends within a data set, collected as a function of a perturbation sequence (e.g., time, temperature, or concentration change), over a second dimension. 12−14 More importantly, 2D correlation spectroscopy can be used to probe the specific sequencing/ordering (sometimes referred to as Noda’s rule) of spectral intensity changes through asynchronous analysis.14 To our knowledge, 2D FTIR correlation spectroscopy has not previously been applied to investigate the complexes of organic ligands in soil DOM and metals. The objectives of the present study were (1) to provide more information regarding the binding of organic ligands with Al(III) at the molecular level using 2D FTIR correlation spectroscopy combined with EEM-PARAFAC; (2) to give the sequencing of relative affinities of organic ligands for binding with Al(III) using 2D FTIR correlation spectroscopy; and (3) to explore the mechanisms of soil organic matter (SOM) sequestration by biogeochemical processes in the soil resulting from different fertilization treatments. For these purposes, the effects of three treatments in a long-term (21-year) fertilization experiment were compared on the formation of complexes between organic ligands in soil DOM and Al(III): no fertilization (CK), chemical (NPK) fertilization, and chemical plus pig manure (NPKM) fertilization.

revealed that the clay mineralogy in the three fertilization treatments was similar with each other, including quartz (SiO2), muscovite [KAl2(Si3Al)O10(OH)2], and cronstedtite-2H1 (Fe2+, Fe3+)3(Si, Fe3+)2O5(OH)4 (Figure S1 of the SI). Al(III) Titration and Complexation Modeling. Aliquots of 25 mL of the diluted solution of DOM were titrated in 40mL brown sealed vials with 0.01 mol/L AlCl3 using an automatic syringe. The Al(III) concentrations in the final solutions ranged from 0 to 100 mmol/L in 10 mmol/L steps. To maintain constant pH before and after titration, the metal titrants were adjusted to pH 6.0, and no more than 25 μL of the metal titrant was added during titration. All titrated solutions were shaken for 24 h at 25 °C to ensure complexation equilibrium.6 Then, all titrated solutions were analyzed by fluorescence EEM spectroscopy. After being freeze-dried, they were also analyzed by FTIR spectroscopy. The modified Stern−Volmer equation was used to estimate the conditional stability constant between Al(III) and the PARAFAC-derived components or the FTIR-derived bands:16 F0 1 1 = + F0 − F f ·KM ·CM f

(1)

where F, F0, and f represent the measured fluorescence intensity score or IR intensity, the initial fluorescence intensity score (i.e., no metal addition) or IR intensity, and the fraction of the initial fluorescence intensity score or IR intensity, respectively. KM and CM are the conditional stability constant and the total metal ion concentration, respectively. The parameters f and KM were solved by plotting F0/(F0 − F) against 1/CM. Fluorescence EEM Determination and PARAFAC Analysis. Fluorescence determination is detailed elsewhere.17−19 Fluorescence EEMs were measured on a Varian Eclipse fluorescence spectrophotometer in scan mode. Scanning emission (Em) spectra from 250 to 600 nm were obtained in 2 nm increments by varying the excitation (Ex) wavelength from 200 to 500 nm in 10 nm increments. The spectra were recorded at a scan rate of 1200 nm/min, using excitation and emission slit band widths of 5 nm. Each scan produced an Excel data file composed of 171 Em (row) × 31 Ex (column) wavelengths. PARAFAC analysis is described in detail elsewhere,17,18 and given in the SI. Analysis of FTIR and 2D Correlation Spectroscopy. Samples were prepared as a mixture of 1 mg of freeze-dried DOM or of the DOM-Al(III) complex and 100 mg of potassium bromide (KBr, IR grade), and this mixture was then ground and homogenized.12,13 A subsample was then compressed between two clean, polished iron anvils twice in a hydraulic press at 20 000 psi to form a KBr window. The FTIR spectra were obtained by collecting 200 scans with a Nicolet 370 FTIR spectrometer. The 2D correlation spectra were produced according to the method of Noda and Ozaki.14 In this study, the Al(III) concentration was applied as an external perturbation, and a set of concentration-dependent FTIR spectra was obtained. Let us consider an analytical spectrum I(x, t). The variable x is the index variable representing the FTIR spectra induced by the perturbation variable t. We intentionally use x instead of the general notation used in conventional 2D correlation equations based on the spectral index v. The analytical spectrum I(x, t) at m evenly spaced points in t (between Tmin and Tmax) can be represented as follows:

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MATERIALS AND METHODS Soil Sample and DOM Extraction. Soils were collected from three treatments in a long-term fertilization experiment station: CK-, NPK-, and NPKM-treatments. The long-term fertilization experiment was conducted initially in September 1990 in fields that were double cropped with wheat and corn at the experiment station of the Chinese Academy of Agricultural Sciences, Qiyang (26° 45′ N, 111° 52′ E, 120 m altitude), Hunan Province, southern China. The red soil was classified as Ferralic Cambisol. A detailed description of the long-term fertilization experiment site can be found elsewhere.15 Soil samples at depths of 0−20 cm were collected during September 2011 using a 5-cm internal diameter auger. Each sample was a composite of 10 random cores collected from a single plot. The fresh soil was mixed thoroughly, air-dried, and sieved through 2-mm and 0.25-mm screens for further analysis, respectively. The SOM contents of samples collected from plots receiving the CK-, NPK-, and NPKM-treatments were 14.88 ± 2.02 g/kg (mean ± standard deviation), 18.36 ± 0.16 g/kg, and 25.13 ± 2.02 g/kg, respectively (Table S1 of the Supporting Information, SI). The DOM fraction of soil samples was extracted with deionized water (solid to water ratio of 1: 2.5 w/v) by shaking fresh soil samples for 24 h on a horizontal shaker at room temperature. The DOM was filtered using 0.45 μm polytetrafluoroethylene (PTFE) filters and further diluted until the dissolved organic carbon (DOC) concentration was aliphatic O−H > amide I in proteins in the CK treatment, amide II in proteins > aliphatic O−H > lignin and aliphatic C−H or (amide I in proteins) in the NPK treatment, and aromatic C−H in cellulose > the C−O stretching of polysaccharides > aliphatic O−H (lignin and aliphatic C−H) in the NPKM treatment. Moreover, the asynchronous maps showed that the band at 1690 cm−1 was overlapped by bands at 1700 and 1640 cm−1; the band at 1520 cm−1 was overlapped by bands at 1540 and 1480 cm−1; the band at 1120 cm−1 was overlapped by bands at 1180, 1160, and 1120 cm−1; and the band at 1020 cm−1 was overlapped by bands at 1110, 1010, and 920 cm−1. The calculated log KM values based on the modified Stern− Volmer equation are listed in Table 1. For the CK treatment,

Figure 3. Synchronous and asynchronous2D correlation maps generated from the 1800−900 cm−1 region of the FTIR spectra of dissolved organic matter in the CK-, NPK-, and NPKM-treatments over Al(III). Red represents positive correlation, and blue represents negative correlation; a higher color intensity indicates a stronger positive or negative correlation.

Table 1. Conditional Stability Constants (log KM) for IRDerived Bands Binding to Al(III) as Calculated Using the Modified Stern−Volmer Equation

CK- and NPK-treatments but only one autopeak for NPKM treatment. Note that autopeaks appear at diagonal position and represent the overall susceptibility of the corresponding spectral region to change in spectral intensity as an external perturbation is applied to the system. The change in band intensity followed the order 1120 > 1520 > 1690 cm−1 for the CK treatment and 1120 > 1520 > 1380 cm−1 for the NPK treatment. However, only one autopeak located at 1010 cm−1 varied for the NPKM treatment. The clear peak positions of 1690 cm−1 for the CK treatment and 1380 cm−1 for the NPK treatment could be seen in Figure S6 of the SI. We assigned these bands as follows: the band at 1690 cm−1 was assigned to the CO stretching of amide I in protein compounds, the band at 1520 cm−1 to N−H deformation and CN stretching of amide II in protein compounds, the band at 1380 cm−1 to the CH deformations in lignin and aliphatic groups, the band at 1120 cm−1 to the C−OH stretching of aliphatic O−H, and the band at 1010 cm−1 to the C−O stretching of polysaccharides, the Si−O of silicate impurities, or phosphate groups.10,11,13,22

treatmenta CK

NPK

NPKM

IR absorption bands (cm−1) 1120 1540 1690 1120 1160 1180 1380 1480 1520 1540 920 1010 1020 1110

log KM not modeled 9.37 9.51 not modeled 9.09 not modeled 9.30 not modeled 9.46 9.47 8.69 8.38 8.36 8.57

R2 0.84 0.78 0.59 0.66 0.63 0.63 0.66 0.92 0.91 0.94

a

Note: CK, no fertilization; NPK, chemical fertilization; NPKM, chemical plus manure fertilization.

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the calculated log KM values were 9.37 (R2 = 0.84) and 9.51 (R2 = 0.78) for amide I (1690 cm−1) and amide II (1540 cm−1) in proteins, respectively. For the NPK treatment, log KM values were approximately 9.46 (R2 = 0.63) and 9.09−9.30 (R2 > 0.59) for amide II (1540 and 1520 cm−1) and lipids (1380 and 1160 cm−1), respectively. However, for the NPKM treatment, log KM values were in the range of 8.36−8.69 for polysaccharides or silicates (1110, 1020, 1010, and 920 cm−1). Therefore, only proteins had a strong binding capability with Al(III) in the CK treatment, but both proteins and lipids demonstrated a strong binding capability with Al(III) in the NPK treatment. However, neither polysaccharides nor silicates had a significant binding capability with Al(III) in the CK treatment.

Therefore, combination of 2D FTIR correlation spectroscopy with EEM-PARAFAC method will help to construct a more comprehensive picture of the binding of organic ligands in DOM with metals characterization. Implications for Soil Organic Carbon Storage. Application of organic fertilizer to soil has been shown as a useful way to increase SOM and reduce environmental pollution.15 However, the mechanism of sequestration of soil organic carbon is not completely understood. In this study, we found that a significant amount of OH bonds (3420 cm−1 and 1120 cm−1) from polysaccharides were detected in soil samples from all three treatments, with the highest OH content present in the NPKM treatment (Figures 3 and S2 of the SI). Meanwhile, the results of 2D FTIR correlation spectroscopy further showed that the intrahydrogen bond (>3400 cm−1) in soil polysaccharides played an important role in binding with Al(III) in all the three treatments (Figure S3 of the SI). However, the Si−O stretching of silicate (1010 cm−1) was only detected in the NPKM treatment and not in samples from the other two treatments. The TEM observation (Figure S8 of the SI) clearly revealed that noncrystalline minerals were forming in soils applied with organic manures. The high-resolution transmission electron micrograph (HR-TEM) image and the corresponding energy dispersive X-ray (EDX) spectrum (Figure S9 of the SI) further support that the main elements of noncrystalline minerals were Al, Si, and O. Therefore, it is reasonable to surmise that the noncrystalline minerals such as allophane [Al 2 O 3 (SiO 2 ) 1 − 2 (H 2 O) 2 .5 − 4 ] or imogolite [(OH)3Al2O3SiOH] were formed in soil DOM from the NPKM treatment. Due to the lack of Si−O stretching from silicate in soil DOM, noncrystalline minerals could not be produced in soil DOM from the CK- and NPK-treatments. The previous investigation explored the structure of allophane and imogolite by FTIR spectroscopy, showing the presence of Al− OH and Si−O−Al bonds in the feature peaks (3500, 3440, 1000, 940, and 917 cm−1).26,27 Smalley28 indicated that the Si− O−(Al) absorption bands in the 1100−900 cm−1 region of the FTIR spectra. However, it should be mentioned that the band at 1010 cm−1 is not certainly attributable to the Si−O of silicate impurities, since it may also be assigned to the C−O stretching of polysaccharides or phosphate groups.10,11,13 Therefore, it needs to further confirm the assignment of the band at 1010 cm−1 in the future research using 29Si NMR spectroscopy. The proposed mechanism of sequestration soil organic matter was given in Figure S10 of the SI. In soil aggregates, DOM was the most reactive fraction.7 DOM would be utilized by crops and microorganisms and released greenhouse gas (e.g., CO2, CH4, NH3, N2O). Noncrystalline minerals were formed in soil DOM from the NPKM treatment. The formation of noncrystalline minerals (i.e., allophane and imogolite) could significantly decrease the reactivity and bioavailability of organic matter.8 Torn et al.8 demonstrated that noncrystalline minerals such as allophane and imogolite controlled soil organic carbon storage and turnover. Furthermore, Parfitt29 indicated that under favorable conditions, the turnover of SOM in allophonic soils may persist in tephra beds for at least 250 000 years. However, allophane and imogolite have been shown to be strong absorbents for CO2, CH4, NH3, and N2O.30,31 Globally, approximately 190−332 million tons of C can be sequestrated by silicate minerals each year.32 Therefore, it can be concluded that the mechanism of sequestration of SOM in the NPKM treatment is attributable to the formation of noncrystalline minerals such as allophane and

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DISCUSSION The EEM contours of DOM from the different fertilization strategies had been shown distinct and thus could be used to assess the soil management effects.23 Ohno et al.23 and Zhang et al.24 investigated the effect of fertilizer treatments (10 years) on EEM contours of DOM, and found that proteins in DOM from no fertilization and chemical fertilization were higher than those from organic fertilization. Meanwhile, with the increase of fertilization time, humic- and fulvic-like materials increased while proteins decreased. Their observations were similar to the results presented in this study. The DOM from the CK- and NPK-treatments, rather than NPKM treatment, contained proteins that may be attributable to the priming effect of manure which rapidly depleted easily available proteins and transferred them to more stable humic and fulvic-like materials.25 However, the robust mechanism needs to be elucidated in future investigations. The fluorescence EEM-PARAFAC method could provide information about Al(III) binding characteristics with fluorescent substances such as protein-, humic-, and fulvic-like substances. However, this popular approach has been criticized as being unable to provide information about the binding characteristics of nonfluorescent substances (e.g., polysaccharides, lipids, and lignin) with Al(III). In soil environments, both fluorescent- and nonfluorescent-substances are abundant.10,11 Our results, based on 2D FTIR correlation spectroscopy, clearly demonstrate that this approach can provide information about Al(III) binding with both fluorescent (i.e., 1690 and 1540 cm−1) and nonfluorescent (i.e., 1380, 1120, and 1010 cm−1) substances. The synchronous maps reveal that the binding strength of compounds with Al(III) follows this sequence: lipids (aliphatic O−H) > amide II > amide I in proteins for the CK treatment, lipids (aliphatic O−H) > amide II in proteins > lignin and aliphatic groups for the NPK treatment, and only polysaccharides and silicates bind with Al(III) in the NPKM treatment. Therefore, nonfluorescent substances (i.e., lipids, polysaccharides, and lignin) played an important role in the binding of organic ligands with Al(III), which could not have been detected by the EEM-PARAFAC method. The asynchronous maps further demonstrated that the sequencing of Al(III) binding with organic ligands could be modified by the use of different long-term fertilization strategies. Specifically, proteins followed by lipids were bound with Al(III) in the CK- and NPK-treatments, whereas homopolysaccharides (i.e., cellulose) followed by heteropolysaccharides and lignin were bound with Al(III) in the NPKM treatment. In summary, the 2D FTIR correlation spectroscopy can be complementary to EEM-PARAFAC method in improving the binding of organics in DOM with metals characterization. 6107

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(6) Wu, J.; Zhang, H.; He, P. J.; Shao, L. M. Insight into the heavy metal binding potential of dissolved organic matter in MSW leachate using EEM quenching combined with PARAFAC analysis. Water Res. 2011, 45, 1711−1719. (7) Troyer, I. D.; Amery, F.; Moorleghem, C. V.; Smolders, E.; Merckx, R. Tracing the source and fate of dissolved organic matter in soil after incorporation of 13C labeled residue: A batch incubation study. Soil Biol. Biochem. 2011, 43, 513−519. (8) Torn, M. S.; Trumbore, S. E.; Chadwich, O. A.; Vitousek, P. M.; Hendricks, D. M. Mineral control of soil organic carbon storage and turnover. Nature 1997, 389, 170−173. (9) Mikutta, R.; Kaiser, K. Organic matter bound to mineral surfaces: Resistance to chemical and biological oxidation. Soil Biol. Biochem. 2011, 43, 1738−1741. (10) Artz, R. R. E.; Chapman, S. J.; Robertson, A. H. J.; Potts, J. M.; Laggoun-Defarge, F.; Gogo, S.; Comont, L.; Disnar, J. R.; Francez, A. J. FTIR spectroscopy can be used as a screening tool for organic matter quality in regenerating cutover peatlands. Soil Biol. Biochem. 2008, 40, 5151−527. (11) D’Orazio, V.; Senesi, N. Spectroscopic properties of humic acids isolated from the rhizosphere and bulk soil compartments and fractionated by size-exclusion chromatography. Soil Biol. Biochem. 2009, 41, 1775−1781. (12) Yu, G. H.; Tang, Z.; Xu, Y. C.; Shen, Q. R. Multiple fluorescence labeling and two dimensional FTIR−13C NMR heterospectral correlation spectroscopy to characterize extracellular polymeric substances in biofilms produced during composting. Environ. Sci. Technol. 2011, 45, 9224−9231. (13) Wang, L. P.; Shen, Q. R.; Yu, G. H.; Ran, W.; Xu, Y. C. Fate of biopolymers during rapeseed meal and wheat bran composting as studied by two-dimensional correlation spectroscopy in combination with multiple fluorescence labeling techniques. Bioresour. Technol. 2012, 105, 88−94. (14) Noda, I., Ozaki, Y., Eds. Two-Dimensional Correlation Spectroscopy- Applications in Vibrational and Optical Spectroscopy; John Wiley & Sons: London, 2004. (15) Zhang, H. M.; Wang, B. R.; Xu, M. G.; Fan, T. L. Crop yield and soil responses to long-term fertilization on a red soil in southern China. Pedosphere 2009, 19, 199−207. (16) Hur, J.; Lee, B. M. Characterization of binding site heterogeneity for copper within dissolved organic matter fractions using twodimensional correlation fluorescence spectroscopy. Chemosphere 2011, 83, 1603−1611. (17) Yu, G. H.; He, P. J.; Shao, L. M. Novel insights into sludge dewaterability by fluorescence excitation−emission matrix combined with parallel factor analysis. Water Res. 2010, 44, 797−806. (18) Yu, G. H.; Luo, Y. H.; Wu, M. J.; Tang, Z.; Liu, D. Y.; Yang, X. M.; Shen, Q. R. PARAFAC modeling of fluorescence excitation− emission spectra for rapid assessment of compost maturity. Bioresour. Technol. 2010, 101, 8244−8251. (19) Yu, G. H.; Wu, M. J.; Luo, Y. H.; Yang, X. M.; Ran, W.; Shen, Q. R. Fluorescence excitation-emission spectroscopy with regional integration analysis for assessment of compost maturity. Waste Manage. 2011, 31, 1729−1736. (20) Abdulla, H. A.; Minor, E. C.; Dias, R. F.; Hatcher, P. G. Changes in the compound classes of dissolved organic matter along an estuarine transect: A study using FTIR and 13C NMR. Geochim. Cosmochim. Acta 2010, 74, 3815−3838. (21) Chen, W.; Westerhoff, P.; Leenheer, J. A.; Booksh, K. Fluorescence excitation−emission matrix regional integration to quantify spectra for dissolved organic matter. Environ. Sci. Technol. 2003, 37, 5701−5710. (22) He, Z. Q.; Ohno, T.; Cade-Menun, B. J.; Erich, M. S.; Honeycutt, C. W. Spectral and chemical characterization of phosphates associated with humic substances. Soil Sci. Soc. Am. J. 2006, 70, 1741−1751. (23) Ohno, T.; He, Z. Q.; Tazisong, I. A.; Senwo, Z. N. Influence of tillage, cropping, and nitrogen source on the chemical characteristics of

imogolite in soil DOM, which could decrease the reactivity and bioavailability of organic matter and increase the storage of CO2, CH4, NH3, and N2O. Knowledge of the binding of organic ligands and metals contributes to our understanding of the sequestration process of SOM and provides novel information for fertilization techniques and scientific research.

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ASSOCIATED CONTENT

S Supporting Information *

Detailed descriptions of the chemical characterization assay and PARAFAC analysis; one table listing physiochemical characteristics of bulk soil in the CK-, NPK-, and NPKM-treatments; one table listing TOC and metals concentration in DOM of the CK-, NPK-, and NPKM-treatments; one table presenting conditional stability constants (log KM) for EEM-PARAFACderived components binding to Al(III) as calculated using the modified Stern−Volmer equation; one figure showing fluorescence EEM contours of composts; one figure showing surface plots of three PARAFAC-derived components; one figure presenting synchronous and asynchronous 2D correlation maps generated from the 3600−3200 cm−1 region; and two figures showing TEM images of aluminosilicate minerals in the DOM leaching from soil of the NPKM treatment. This material is available free of charge via the Internet at http:// pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone: +86-25-8439 5212; fax: +86-21-8439 5212; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The work was funded by the National Basic Research Program of China (2011CB100503), the National Natural Science Foundation of China (21007027), the Specialized Research Fund for the Doctoral Program of Higher Education (20100097120015), the China Postdoctoral Science Foundation (20100481156, 201104535, and 1002017B), the Fundamental Research Funds for the Central Universities (KYZ201143), and the Agricultural Ministry of China (2011G27 and 201103004).

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