Solid-state NMR Spectroscopic Analysis of Sweet Cherry Leaves under Different Cultivation Patterns

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  • 1 Institute for Forest Resources and Environment of Guizhou/College of Forestry, Guizhou University, Guiyang 550025, China
  • 2 School of Architectural Engineering, Kaili University, Kaili 556011, Guizhou, China
  • 3 Guangxi Key Laboratory of Superior Timber Trees Resource Cultivation, Guangxi Zhuang Autonomous Regton Forest Research Institute, Nanning 530002, China
  • 4 College of Chemistry and Materials, Ningde Normal University, Ningde 352100, China
  • 5 School of Architectural Engineering, Kaili University, Kaili 556011, Guizhou, China

Solid-state 1H-NMR and 13C-NMR spectroscopy were used to investigate the chemical components of sweet cherry tree leaves under rain-shelter cultivation (RS) and open-field cultivation (CK). The 1H-NMR spectral chemical shifts of RS and CK showed differences in height and integral value. The δ 1–3, δ 3–4, δ 4–6, and δ 6–10 regions were attributed to the hydrogen signals of aliphatic compounds, unsaturated carbohydrate compounds, and aromatic compounds, respectively. Among the four regions, the percentage of signal strength and the integral value of hydrogen signals of RS and CK were 34.25% and 28.34%, 11.64% and 12.26%, 26.71% and 31.06%, 27.4% and 28.34%, respectively. The 13C-NMR results showed that the CK sample had slightly stronger spectral lines and contained slightly more carbon atoms than the RS sample. Sweet cherry leaves contain aromatic and carboxyl carbons, mainly from carboxylic acids, esters, and amides. The alkyl carbons exhibited the lowest ratio, whereas the alkyl and alkoxy carbons were mainly derived from carbohydrates (cellulose, polysaccharides).

Abstract

Solid-state 1H-NMR and 13C-NMR spectroscopy were used to investigate the chemical components of sweet cherry tree leaves under rain-shelter cultivation (RS) and open-field cultivation (CK). The 1H-NMR spectral chemical shifts of RS and CK showed differences in height and integral value. The δ 1–3, δ 3–4, δ 4–6, and δ 6–10 regions were attributed to the hydrogen signals of aliphatic compounds, unsaturated carbohydrate compounds, and aromatic compounds, respectively. Among the four regions, the percentage of signal strength and the integral value of hydrogen signals of RS and CK were 34.25% and 28.34%, 11.64% and 12.26%, 26.71% and 31.06%, 27.4% and 28.34%, respectively. The 13C-NMR results showed that the CK sample had slightly stronger spectral lines and contained slightly more carbon atoms than the RS sample. Sweet cherry leaves contain aromatic and carboxyl carbons, mainly from carboxylic acids, esters, and amides. The alkyl carbons exhibited the lowest ratio, whereas the alkyl and alkoxy carbons were mainly derived from carbohydrates (cellulose, polysaccharides).

Sweet cherry (Prunus avium L.) fruits are popular among consumers for their thick pulp, mild flavor and high nutritional value. In recent years, after cherry trees were widely introduced in southern China, the phenomena of low fruiting rate, serious fruit drop and cracking have caused great economic loss (Kaufmann and Blanke, 2017; Nastić et al., 2020). These issues are mainly caused by rainfall during the harvest season and are related to osmotic factors and fruit water permeability. For this reason, sweet cherry cultivation in many southern regions has generally adopted RS to reduce losses. However, the environmental changes caused by RS will inevitably affect the physiological and biochemical indexes of sweet cherry leaves (Kafle et al., 2016; Li et al., 2014). At present, there are many studies on the photosynthetic characteristics, diseases, insect pests, fruit quality, and enzyme activities of sweet cherry trees in RS (Serrano et al., 2005a, 2005b). However, the differences in the chemical composition of sweet cherry leaves under different cultivation patterns using Nuclear magnetic resonance (NMR) have not been reported. NMR is a powerful and sophisticated technique with a wide range of applications, such as materials science, plant physiology and development, biodiversity, medicinal materials, gene function, and metabolism (Cloarec et al., 2005; Schripsema, 2010). Since its discovery, NMR has become an effective method for studying the structure of organic compounds due to its advantages, such as the small number of samples required, relatively simple sample pretreatment, and the large amount of information it can provide. Compared with other chemical methods, NMR is a nondestructive testing technology that does not destroy the internal structure of the sample being tested. 13C-NMR can qualitatively and quantitatively analyze the carbon structure framework of organic matter without changing the original structure of plants (Jiang et al., 2009). Previous studies have shown that xylan and cellulose interactions, the molecular architecture of softwood, lignin–polysaccharide interactions in plant secondary cell walls, etc., could be revealed by solid-state NMR (Dalvi et al., 2019; Geo et al., 2018; Terrett et al., 2019).

The identification of chemical constituents and structures in plants by traditional chemical extraction methods usually requires pyrolysis of the samples, which results in the destruction of the structural information of the samples (Mo et al., 1995). In this study, solid-state NMR spectroscopy was used to directly analyze the functional group composition in plant samples without the need for pretreatment, such as dissolution, heating, and extraction of the sample, thereby avoiding the structural changes caused by the extraction process. This technique has the advantage of simultaneous qualitative and quantitative analysis of the chemical composition of organic substances, which can reflect relatively comprehensive original sample information, and the identification results are close to the real situation (Cross et al., 2018; Glatz et al., 2019). In this experiment, solid-state NMR was used to analyze and identify the chemical composition and content of sweet cherry tree leaves under RS and CK, which provides a scientific basis for the comprehensive utilization of sweet cherry resources.

Materials and Methods

Plant material and growth conditions.

The leaves of the sweet cherry (Prunus avium L.) cultivar “Summit” were collected from the Baiyi fruit tree experimental base of Guiyang Wudang, Guizhou Institute of Fruit Tree Science (lat. 27°03′3.89″N, long. 106°25′47.23″E), and the samples were collected in July 2019. The rain-shelter facilities were 4 span rain-shelters built in April 2014. The Summit trees were 5 years old and were grafted on ‘Gisela 6’ rootstocks and planted under rain-shelter and open field conditions in Mar. 2015. All the trees were managed with the same practical techniques. Three trees with normal growth and relatively consistent growth potential were selected randomly from RS and CK, and 20 leaves (well-developed leaves from the base of the shoots) from four directions were harvested from each tree. To fully retain the chlorophyll, carotenoids, and phenolic substances in the leaves, heat treatment of sweet cherry leaves was selected in the experiment, but heat treatment may also cause the degradation of some heat-sensitive substances in the leaves. After being washed with distilled water, the fresh leaves were oven dried at 105 °C for 30 min and then dried at 80 °C to constant weight.

NMR spectroscopic analysis.

Conventional solid-state NMR experiments were performed on a standard bore 18.8-T spectrometer or a 9.4-T spectrometer, both of which were equipped with a Bruker Avance III HD console (Bruker, Hamburg, Germany). DNP-enhanced solid-state NMR experiments were performed on a Bruker 9.4-T 500-MHz/263-GHz solid-state NMR spectrometer equipped with a Bruker Avance III console. A Bruker 3.2-mm triple resonance DNP probe configured in HCN triple resonance mode was used for acquisition of all spectra.

The dried samples were ground with a mini-pulverizer, and 40 to 60 mesh powder was isolated as the raw material for the test. A powder sample (80 μL) was transferred to a 4-mm zirconia (ZrO2) rotary tube for testing. The rotation speed was 5 kHz, the compensation time was 20 ms, the contact time was 1 ms, and the delay between two pulses was 3 ms.

Results and Discussion

Solid-state 1H-NMR spectroscopic analysis.

The chemical shifts and relative strengths of the signal peaks in the 1H-NMR spectrum reflect the types and relative contents of the chemical components in the sweet cherry leaves, as shown in Figs. 1 and 2. 1H-NMR mainly provides chemical environment, hydrogen distribution, and internuclear relationship data (Kim et al., 2005). Moreover, 1H-NMR cannot give a resonance signal without hydrogen groups, it is difficult to identify alkanes with similar chemical environments, and spectral lines often overlap (Zhi et al., 2012). Comparing the 1H-NMR, the types of metabolites of RS and CK samples were observed. The chemical displacements at 5.28, 5.10, 4.47, 2.74, 2.03, 1.64, 1.55, 1.25, 0.93, and 0.87 ppm showed significant differences in terms of the signal strength and integral value of different metabolites. The double-bond protons on fatty acids may be represented at δ 5.4–5.0. Hydrogens of saturated compounds on oxygen atoms observed at δ 5.0–3.0 may have been generated by sterol, glycerol resin, etc., and δ 2.4–0.8 signals represent aliphatic hydrogens.

Fig. 1.
Fig. 1.

1H-NMR spectra of sweet cherry tree leaves under rain-shelter cultivation.

Citation: HortScience horts 56, 2; 10.21273/HORTSCI15346-20

Fig. 2.
Fig. 2.

1H-NMR spectra of sweet cherry tree leaves under open-field cultivation.

Citation: HortScience horts 56, 2; 10.21273/HORTSCI15346-20

The 1H-NMR spectrum can reflect many chemical components in sweet cherry leaves, and the size of a peak can reflect the content. The relative strength ratio of each signal peak can be obtained by integrating the corresponding signal interval of sweet cherry leaves. The δ 1–3 interval contained hydrogen signal peaks of aliphatic hydrocarbons (aliphatic compounds include long-chain aliphatic alkanes, unsaturated fatty acids, ethyl linoleate, sterols, terpenes, etc.). The large proportion of the integral value indicated that the content of aliphatic compounds in the leaves was large (Hazekamp et al., 2004). The proportions of RS and CK were 34.25% and 28.34%, respectively. The δ 3–4 interval contained hydrogen signals of sugars (monosaccharides, oligosaccharides, glycosides, etc.). The ratios of the integral values of RS and CK was 11.64% and 12.26%, respectively. The δ 4–6 region contained hydrogen signal peaks of unsaturated compounds (unsaturated fatty acids, terpenes, etc.). The ratios of RS and CK were 26.71% and 31.06%, respectively. The peaks at δ 4.47 and δ 5.10 were attributed to the hydrogens of sugars on glycosides, including saponins, carotene, etc. (Charisiadis et al., 2011). The signal at δ 5.28 was attributed to hydrogens of unsaturated compounds such as unsaturated fatty acids. The δ 6–10 interval contained peaks of the hydrogens of aromatic compounds, aldehydes, hydroxyls on benzene rings, etc. The ratios of the integral values of RS and CK were 27.4% and 28.34%, respectively.

Solid-state 13C-NMR spectroscopic analysis.

It can be seen in Figs. 3 and 4 that the peaks of the CK sample were more low-field than those of the RS sample, indicating that the former had a slightly higher moisture content than that of the latter (Jingya et al., 2016; Liang et al., 2018). The signal peak intensities at 60 to 110 ppm in Figs. 3 and 4 indicate that the CK sample had higher carbohydrate, hemicellulose, and cellulose contents than the RS sample (Duchesne et al., 2001). According to the analysis of the chemical shifts of the main carbon groups of organic compounds in the 13C-NMR spectra based on existing studies, the carbon chemical shifts of organic compounds are divided into four regions (Hult et al., 2000): δC 0–50 ppm is the alkyl region, δC 50–110 ppm is the alkoxy region, δC 110–165 ppm is the aromatic region, and δC 165–210 ppm is the carbonyl region. The 13C-NMR spectra of RS and CK were basically the same, and the main absorption peaks were located at 71.92 ppm and 104.66 ppm in the alkoxy region of 50–110 ppm. The intensity of the spectral line of CK was slightly higher than that of RS, indicating that the former contains more carbon atoms than the latter (Longobardi et al., 2013). Qualitative analysis shows that in the alkyl region, methyl carbons (21.17, 24.98 ppm) and amorphous (CH2)n long-chain carbons (29.83, 32.53, 39.45, 48.02 ppm) were mainly connected to aromatic rings. In the alkoxy region, there were mainly absorption peaks of C2 to C6 structures, i.e., carbohydrates (62.46–64.68, 71.92, 82.61–88.02 ppm), and the absorption peak of acetal carbons in polysaccharides was observed at 104.66 ppm. Among the observed peaks, those at 62.46–64.68 ppm and 71.92 ppm were the carbon absorption peaks of primary alcohol and secondary alcohol groups in carbohydrates, respectively. These carbons were mainly derived from carbohydrates of cellulose. In the aromatic region, the signal peaks of syringl ligninunit were at 154.59 ppm (C-3/C-5), 147.44 ppm (C-3/C-5), 138.51 ppm (C-4), 135.15 (C-1), and 104.66 ppm (C-2/C-6). The peaks of the carbon signal at 115.65–116.64 ppm were mainly aromatic compounds containing carboxyl or carboxymethyl groups. The signal at 128.02–129.78 ppm was attributed to aromatic carbons associated with O and N. The signal at 144.09 ppm was attributed to phenolic compound carbons. The results of studies by Bardet et al. (2012) and Nogueira et al. (2004) show that the 56 ppm and 147–148 ppm signals were from lignin. The intensity of the signals near these two chemical shifts in the RS spectrum were higher than those in the CK spectrum. The former had a higher lignin content than the latter. This was consistent with the findings of Ke et al. (2011). The carbon signal peak at 172.82 ppm in the spectrum may be derived from the carbonyl groups of the ester bonds or the carboxyl groups of the fatty acids. The peak signal of the carbonyl region only appeared at 172.82 ppm, and no peak signal appeared in other regions, indicating that the CK sample mainly contained carbonyl and carboxyl carbons, mainly from carboxylic acids, esters and amides, but no carbonyl carbons from aldehydes, ketones, and anthracene compounds were observed (Fan et al., 2001; Holmes et al., 2006).

Fig. 3.
Fig. 3.

13C-NMR spectra of sweet cherry tree leaves under rain-shelter cultivation.

Citation: HortScience horts 56, 2; 10.21273/HORTSCI15346-20

Fig. 4.
Fig. 4.

13C-NMR spectra of sweet cherry tree leaves under open-field cultivation.

Citation: HortScience horts 56, 2; 10.21273/HORTSCI15346-20

From Table 1, RS and CK organic matter had the highest signal proportion in the aromatic region (52.79% and 56.25%, respectively), followed by the carboxyl region (29.33% and 26.04%, respectively), alkoxy region (9.68% and 10.5%, respectively), and alkyl region (8.21% and 7.55%, respectively).

Table 1.

Carbon group distribution in sweet cherry leaves/%.

Table 1.

Using solid-state 13C-NMR technology to study the main carbon groups in sweet cherry leaves, it was found that the carbon groups of sweet cherry leaves in the two cultivation groups were mainly aromatic compounds and carboxyl compounds, indicating that the lignin content in the leaves was relatively high. Alkyl compounds and alkoxy compounds are mainly derived from carbohydrates (cellulose and polysaccharides, etc.) (Li et al., 2009). Qualitative and quantitative analysis showed that rain-shelter cultivation would affect the carbon structure and aromatic compound content of sweet cherry leaves. The proportion of alkyl compounds in the RS sample was higher than that in the CK sample, whereas that of alkoxy carbons was lower. According to 13C-NMR spectral characteristics and carbon chemical shift assignment, it was determined that the carboxyl compounds in sweet cherry leaves mainly come from carboxylic acids, esters, and amides (Girelli et al., 2016).

Structural characterization of sweet cherry leaf metabolites.

13C-NMR can directly measure the carbon skeleton and information about the chemical structures and molecular movement, such as the number of carbon atoms in the molecule and the specific group, and it can also distinguish primary, secondary, tertiary, and quaternary carbon atoms. According to the preliminary research conclusions of our team (Zhang et al., 2020), the eight main components in a sweet cherry leaf extract were 4-hydroxycoumarin, chlorogenic acid, D-(-)-mannitol, DL-malic acid, quercetin-3β-D-glucoside, rutin, α,α-trehalose, and β-carotene (Nos. 1 to 8 in Table 2). Combining NMR spectra and MS, the main structural units in sweet cherry leaves are shown in Table 2.

Table 2.

13C-NMR spectral data and analysis of sweet cherry leaves.

Table 2.Table 2.

Conclusion

The chemical composition of sweet cherry leaves under two cultivation conditions was confirmed from solid-state NMR (1H-NMR and 13C-NMR). The chemical shift positions of RS and CK in 1H-NMR or 13C-NMR did not change extensively, but there were some differences in signal intensity, and the types of metabolites were similar. On the basis of the change in the relative peak area of the characteristic signal peak, there were differences in the structure and content of the metabolites of sweet cherry leaves cultivates under the two systems. The results provide solid-state NMR data and method guidance for the discovery and structural identification of metabolites in sweet cherry leaves.

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Contributor Notes

This research was supported by grants from the Research Project of Young and Middle-aged Teachers in Ningde Normal University (2017Q103), Natural Science Research Project [2017]011 of Education Department of Guizhou Province, P. R. China and Scientific Research Project for Guangxi Science and Technology Major Project (AA17204087-6).

H.L. and Q.L. are corresponding authors. E-mail: linhui@ndnu.edu.cn or liquan-8@163.com.

  • View in gallery

    1H-NMR spectra of sweet cherry tree leaves under rain-shelter cultivation.

  • View in gallery

    1H-NMR spectra of sweet cherry tree leaves under open-field cultivation.

  • View in gallery

    13C-NMR spectra of sweet cherry tree leaves under rain-shelter cultivation.

  • View in gallery

    13C-NMR spectra of sweet cherry tree leaves under open-field cultivation.

  • Bardet, M., Gerbaud, G., Doan, C., Giffard, M., Hediger, S., De Paëpe, G. & Trân, Q.K. 2012 Dynamics property recovery of archaeological-wood fibers treated with polyethylene glycol demonstrated by high-resolution solid-state NMR Cellulose 19 1537 1545

    • Search Google Scholar
    • Export Citation
  • Charisiadis, P., Primikyri, A., Exarchou, V., Tzakos, A. & Gerothanassis, I.P. 2011 Unprecedented ultra-high-resolution hydroxy group 1H-NMR spectroscopic analysis of plant extracts J. Nat. Prod. 74 2462 2466

    • Search Google Scholar
    • Export Citation
  • Cloarec, O., Dumas, M.E., Craig, A., Barton, R.H., Trygg, J., Hudson, J. & Nicholson, J. 2005 Statistical total correlation spectroscopy: An exploratory approach for latent biomarker identification from metabolic 1H-NMR data sets Anal. Chem. 77 1282 1289

    • Search Google Scholar
    • Export Citation
  • Cross, T., Paulino, J., Qin, H., Shin, Y., Escobar, C., Zhang, R. & Hung, I. 2018 Unique Insights into the structural and functional biology of membrane proteins from solid state NMR spectroscopy Biophys. J. 114 207a

    • Search Google Scholar
    • Export Citation
  • Dalvi, L.C., Laine, C., Virtanen, T., Liiti, T. & Tamminen, T. 2019 Study of xylan and cellulose interactions monitored with solid-state NMR and QCM-D Holzforschung 74 1 11

    • Search Google Scholar
    • Export Citation
  • Duchesne, I., Hult, E., Molin, U., Daniel, G., Iversen, T. & Lennholm, H. 2001 The influence of hemicellulose on fibril aggregation of kraft pulp fibres as revealed by FE-SEM and CP/MAS 13C-NMR Cellulose 8 103 111

    • Search Google Scholar
    • Export Citation
  • Fan, T.W.M., Lane, A.N., Shenker, M., Bartley, J.P., Crowley, D. & Higashi, R.M. 2001 Comprehensive chemical profiling of gramineous plant root exudates using high-resolution NMR and MS Phytochemistry 57 209 221

    • Search Google Scholar
    • Export Citation
  • Geo, P., Chiara, B., Ilaria, B., Maurizio, C., Giorgio, G. & Enrica, G. 2018 Combined solid-state NMR, FT-IR and computational studies on layered and porous materials Chem. Soc. Rev. 47 5684

    • Search Google Scholar
    • Export Citation
  • Girelli, C.R., De Pascali, S.A., Del Coco, L. & Fanizzi, F.P. 2016 Metabolic profile comparison of fruit juice from certified sweet cherry trees (Prunus avium L.) of Ferrovia and Giorgia cultivars: A preliminary study Food Res. Intl. 90 281 287

    • Search Google Scholar
    • Export Citation
  • Glatz, P., Comte, M., Montagne, L., Doumert, B. & Cormier, L. 2019 Quantitative determination of the phosphorus environment in lithium aluminosilicate glasses using solid-state NMR techniques Phys. Chem. Chem. Phys. 21 18370 18379

    • Search Google Scholar
    • Export Citation
  • Hazekamp, A., Choi, Y.H. & Verpoorte, R. 2004 Quantitative analysis of cannabinoids from Cannabis sativa using 1H-NMR Chem. Pharm. Bul. 52 718 721

  • Holmes, E., Tang, H., Wang, Y. & Seger, C. 2006 The assessment of plant metabolite profiles by NMR-based methodologies Planta Med. 72 771 785

  • Hult, E.L., Larsson, P.T. & Iversen, T. 2000 A comparative CP/MAS 13C-NMR study of cellulose structure in spruce wood and kraft pulp Cellulose 7 35 55

    • Search Google Scholar
    • Export Citation
  • Jiang, N., Pu, Y., Samuel, R. & Ragauskas, A.J. 2009 Perdeuterated pyridinium molten salt (ionic liquid) for direct dissolution and NMR analysis of plant cell walls Green Chem. 11 1762 1766

    • Search Google Scholar
    • Export Citation
  • Jingya, R., Chang, Z., Lu, Q., Yanxia, L., Lifeng, H. & Haiyang, Y. 2016 Plant resources (13)C-NMR spectral characteristic and pharmacological activities of dammarane-type triterpenoids Molecules 21 1047

    • Search Google Scholar
    • Export Citation
  • Kafle, G.K., Khot, L.R., Zhou, J., Bahlol, H.Y. & Si, Y. 2016 Towards precision spray applications to prevent rain-induced sweet cherry cracking: Understanding calcium washout due to rain and fruit cracking susceptibility Scientia Hort. 203 152 157

    • Search Google Scholar
    • Export Citation
  • Kaufmann, H. & Blanke, M. 2017 Changes in carbohydrate levels and relative water content (RWC) to distinguish dormancy phases in sweet cherry J. Plant Physiol. 218 1 5

    • Search Google Scholar
    • Export Citation
  • Ke, S., Keiluweit, M., Kleber, M., Pan, Z.Z. & Xing, B.S. 2011 Sorption of fluorinated herbicides to plant biomass-derived biochars as a function of molecular structure Bioresource Technol. 102 21 270 276

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