The influence of ripening stage and region on the chemical compounds in mulberry fruits (Morus atropurpurea Roxb.) based on UPLC-QTOF-MS

https://doi.org/10.1016/j.foodres.2017.08.023Get rights and content

Highlights

  • 43 compounds classified into nine groups were identified in mulberry fruits (MFs).

  • Caffeoylquinic acids and anthocyanins could be regarded as markers for MFs ripening.

  • Organic acids are responsible for the differentiation of samples in two regions.

Abstract

Mulberries (Morus atropurpurea Roxb.) are rich in beneficial nutrients and secondary metabolites. Dramatic climate differences between western and eastern China lead to differences among the fruiting habits of mulberries grown in these regions. In this study, Xinjiang and Jiangsu, two regions in western and eastern China, respectively, were selected as sites where mulberry fruits (MFs) at different ripening stages were sampled. Their individual components, including both targeted and non-targeted chemical compounds, were detected by rapid ultra performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS). Multivariate statistical analyses, including principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to compare MFs during ripening from these two regions. Potential biomarkers, which significantly contributed to the differentiation of the samples, were further identified or tentatively identified to determine the effects of ripening stages and regions on the chemical compounds in MFs. The results show that 43 compounds classified into nine different groups were identified in the MF samples from both the Xinjiang and Jiangsu regions. Among the compounds, all anthocyanins, carbohydrates and dihydroflavonols increased while phenolic acids and hydroxycoumarins decreased during ripening. Caffeoylquinic acids and some of anthocyanins could be regarded as important markers for MF ripening, and the accumulation of organic acids differentiated the samples from the two regions. Together, UPLC-QTOF-MS coupled with multivariate statistical analyses may be effective for metabolite profiling and identification of ripening degrees and cultivation regions.

Introduction

The mulberry (Morus atropurpurea Roxb.) is widely cultivated in China, especially in the south for its leaves and fruits. Mulberry fruits (MFs) have historically been used in traditional Chinese medicine to reduce the risk of human cancer, liver disease, obesity, diabetes, and cardiovascular disease (Huang et al., 2013, Song et al., 2009). Modern research has revealed that the biological actions of MFs are largely due to their nutrients and bioactive components, including phytochemicals, such as polyphenols (Haminiuk, Maciel, Plata-Oviedo, & Peralta, 2012).

As the functional components of MFs have gradually been reported, consumer demand for these fruits has increased, and MFs are usually eaten fresh or processed as jam, jelly, marmalade, etc. (Vijayan et al., 2014). However, fresh, fully ripened MFs are rarely commercialized because of their susceptibility to spoilage and instability in commonly used storage conditions (Tchabo, Ma, Engmann, & Zhang, 2015). Additionally, the development of MFs is usually completed within one month, and it is not uncommon to find the green, red (ripening stage) or the over-mature MFs on sale. For the processing industry, a majority of the unripened MFs are wasted during quality control. Thus, it is necessary to identify the chemical ingredients and marker compounds whose contents vary dramatically during the mulberry development stages, which enables processing companies to maximize the use of rejected fruits and also provides basic knowledge to optimize harvests (Gibson, Rupasinghe, Forney, & Eaton, 2013).

However, current literature is mainly focused on the analysis of one or several classes of compounds, such as polyphenols and polysaccharides, instead of a comprehensive identification of the chemical components in MFs (Bae and Suh, 2007, Jin et al., 2015). MFs at their maximum ripeness have been broadly studied, but there are only a few reports associated with unripe MFs (Lou et al., 2012, Mahmood et al., 2012). Liquid chromatography-mass spectrometry (LC-MS) has been used for structure elucidation and characterization of low molecular mass organic molecules in these reports; however, the LC-MS-based workflow can be time-consuming and requires human intervention at almost every step (Zhang, Li, et al., 2016). With the advantages of high resolution, high sensitivity, and accurate mass measurement, ultra performance liquid chromatography (UPLC) combined with time-of-flight (TOF) mass spectrometry (MS) has become an alternate choice for unbiased compound screening and has been used to analyze natural fruits, vegetables and herbal medicines (Stark et al., 2015, Zhang et al., 2016 & Zhang, Zhang, et al., 2016). In addition, Progenesis QI (Nonlinear Dynamics, Newcastle, UK), a small molecule discovery analysis software, provides an informatics platform to reliably identify compounds even without reference standards, which alleviates workload (Zhang, Yang, et al., 2016). By performing alignment, peak-picking, and mining of metabolomics data, this new software platform can be used to identify important molecular alterations among sample groups (Arapitsas, Langridge, Mattivi, & Astarita, 2016). Several studies have used this platform for both in vivo and in vitro experiments to identify and quantify metabolites in their multisamples (Geenen et al., 2013, Hua et al., 2016, Jing et al., 2017)

Therefore, our first aim was to quickly identify the chemical constituents in the Dashi cultivar of MFs at different ripening stages from two regions in China utilizing UPLC-QTOF-MS coupled with Progenesis QI data analysis software. Then, we used principal component analysis (PCA) to build a predicting model using orthogonal partial least squares discriminant analysis (OPLS-DA) to screen for potential marker compounds that would differentiate samples based on ripening stage and cultivation region.

Section snippets

MF samples

Two regions (Xinjiang and Jiangsu) were selected as sampling sites due to their large production of MFs. Their meteorological conditions during collection are summarized in Table 1. MFs without injury and apparent contamination were collected according to color uniformity. In total, 9 different samples from the Jiangsu region (4 ripening stages) and the Xinjiang region (5 ripening stages) were picked randomly from twenty to forty trees at each site. Each sample weighed approximately 1–3 kg. All

Metabolic profiling analysis

Once the data in negative and positive mode were separately processed on the Progenesis QI platform, all the matching components were listed for further verification. Fig. 1 displays the negative and positive ion base peak intensity (BPI) chromatographic profiles of MFs (Dashi) at Stage 5 (ST5) from the Xinjiang region. Other comparisons of the chromatographic profiles of unripe and ripened MFs from various cultivars and regions are presented in Appendix Supplementary Fig. S2 and Fig. S3.

Conclusions

In this work, we identified individual chemical compounds from nine different groups (phenolic acids, flavonols, hydroxycoumarins, dihydroflavonols, anthocyanins, organic acids, amino acids, carbohydrates, and vitamins) in MFs from two different regions during ripening based on UPLC-QTOF-MS data. We also evaluated the data for potential markers that differentiate MFs at different ripening stages and from different cultivation regions using multivariate statistical analysis models (the

Acknowledgement

We would like to thank the National Natural Science Foundation of China for financial support (No. 31571840).

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