An integrated chemical characterization based on FT-NIR, GC-MS and LC-MS for the comparative metabolite profiling of wild and cultivated agarwood

Salty treatment increased bioactive compounds accumulation during agarwood development in Aquilaria sinensis trees

To compare the bioactive compounds in agarwood induced by different methods in Aquilaria sinensis(Lour.) Gilg trees, a two dimensional thin layer chromatograph(2D-TLC) combined with effect directive analysis(EDA) was developed. Three antioxidants were found by 2D-TLC-DPPH and further identified as 2-(2-phenylethyl) chromones(PECs) with LC-MS/MS. The 3 antioxidants decreased along agarwood formation and their compositions in drilling induced agarwood differed with those in microbe culture induced agarwood. Further study showed NaCl treatment promoted antioxidants accumulation in agarwood induced by drilling or hot drilling. Hot drilling combined with salty stimulation was most efficient in some chemicals accumulation, which were identified as PECs with antioxidant, tyrosinase or β-glucosidase inhibiting activities by 2D-TLC-EDA-LC-MS/MS. This study provided a 2D-TLC-EDA-LC-MS/MS method for bioactive compounds screen and qualification of agarwood. Based on this method, non-conventional methods were found to accelerate the accumulation of some bioactive PECs in A. sinensis trees.

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

Rapid screening and characterization of 2-(2-phenylethyl)chromones in agarwood by UHPLC-Q-Exactive Orbitrap-MS

The purpose of this study is to develop an improved comprehensive data filtering strategy, which was implemented primarily through the Microsoft Office platform's Excel software for rapid screening of potential 2-(2-phenylethyl)chromone (PEC) monomers and their dimers (PEC dimers) obtained from agarwood. A total of 108 PEC monomers and 30 PEC dimers in agarwood were characterized. In conclusion, the results obtained in this work could provide useful information for the future utilization of agarwood. In particular, it is the first time to conduct an in-depth analysis of the MS/MS fragmentation behavior of a large number of PEC monomers and PEC dimers, including the identification of substituent positions of them. The proposed data filtering strategy could improve the comprehensive characterization efficiency of complex components in spices.

Comprehensive Comparisons between Grafted Kynam Agarwood and Normal Agarwood on Traits, Composition, and In Vitro Activation of AMPK

Agarwood, a highly valuable resin/wood combination with diverse pharmacological activities but scarce supply, has a long history of being used as a medicine in several medical systems. Grafted Kynam agarwood (GKA) has been cultivated successfully recently and has the qualities meeting the definition of premium Kynam agarwood. However, there are few comprehensive comparisons between GKA and normal agarwood in terms of traits, global composition, and activity, and some key issues for GKA to be adopted into the traditional Chinese medical (TCM) system have not been elaborated. The two types of agarwood samples were evaluated in terms of trait characteristics, physicochemical indicators, key component groups, and global compositional profile. Furthermore, a molecular docking was performed to investigate the active ingredients. In vitro activity assays were performed to evaluate the activation of adenosine 5'-monophosphate (AMP)-activated protein kinase (AMPK) by GKA and normal agarwood. The results revealed that, overall, the traits, microscopic characteristics, chemical composition types, and bioactivity between GKA and normal agarwood were similar. The main differences were the content of resin (ethanolic extract content), the content of key component groups, and the composition of the different parent structural groups of 2-(2-phenethyl) chromones (PECs). The contents of total PEC and ethanol extract content of GKA were significantly higher than those of normal agarwood. The MS-based high-throughput analysis revealed that GKA has higher concentrations of sesquiterpenes and flindersia-type 2-(2-phenylethyl) chromones (FTPECs) (m/z 250-312) than normal agarwood. Molecular docking revealed that parent structural groups of FTPECs activated multiple signaling pathways, including the AMPK pathway, suggesting that FTPECs are major active components in GKA. The aim of this paper is to describe the intrinsic reasons for GKA as a high-quality agarwood and a potential source for novel drug development. We combined high-throughput mass spectrometry and multivariate statistical analysis to infer the different components of the two types of agarwood. Then we combined virtual screening and in vitro activity to construct a component/pharmacodynamic relationship to explore the causes of the activity differences between agarwood with different levels of quality and to identify potentially valuable lead compounds. This strategy can also be used for the comprehensive study of other TCMs with different qualities.

An integrated approach utilizing raman spectroscopy and chemometrics for authentication and detection of adulteration of agarwood essential oils

Agarwood is a precious aromatic plant which has good pharmacological effects such as antidepressant and sedation. It also has good ornamental and collection value. However, due to it is long and complex production process, the output of agarwood essential oils (AEOs) is scarce, so the price is expensive, the quality is uneven, and the adulteration events is endless. From the commercial and pharmaceutical point of view, the authenticity and quality of the commercial products labeled as AEOs is very important. This paper tested the applicability of Raman spectroscopy combined with chemometrics in classification and authenticity identification of AEOs. In this study, Raman spectroscopy and principal component analysis (PCA) combined with partial least square discriminant analysis (PLS-DA) were used to comprehensively evaluate AEOs from different geographical origins and/or extracted by different methods which showed different characteristic bands. The characteristic component of AEOs, chromone derivatives, and two commonly used adulterants were also detected. These characteristic bands provide spectrum information of AEO samples and reference materials, which can be used as Raman spectral markers for the qualitative identification of AEOs. This study can provide a novel, fast and convenient method for identification of AEOs.