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Using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technology in multiple reaction monitoring mode, a widely targeted metabolomics approach was employed to identify metabolites in five tissues (exocarp, endocarp, segment membrane, pulp, and seeds) of the Shatian pomelo fruit. The differences in metabolite composition and abundance among different tissues were analyzed using multivariate statistical analysis methods. The results showed that a total of 1722 metabolites were identified from the five tissues of the Shatian pomelo, including 413 flavonoids and 277 amino acids and their derivatives. Flavonoid metabolites accumulate the most abundantly in the exocarp and seeds, while amino acids and their derivatives are primarily accumulated in the exocarp and pulp. A total of 649 key differential metabolites were screened, including flavonoids, amino acids, and their derivatives, indicating the presence of tissue-specific accumulation of metabolites in the Shatian pomelo. This study systematically investigated the metabolite distribution in different tissue parts of the Shatian pomelo, and validated the feasibility of widely targeted metabolomics technology in pomelo quality analysis. It provided a theoretical reference for metabolic research on the Shatian pomelo and other citrus fruits, and offered a theoretical basis for the efficient utilization of pomelo resources. [ABSTRACT FROM AUTHOR]

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Using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) technology in multiple reaction monitoring mode, a widely targeted metabolomics approach was employed to identify metabolites in five tissues (exocarp, endocarp, segment membrane, pulp, and seeds) of the Shatian pomelo fruit. The differences in metabolite composition and abundance among different tissues were analyzed using multivariate statistical analysis methods. The results showed that a total of 1722 metabolites were identified from the five tissues of the Shatian pomelo, including 413 flavonoids and 277 amino acids and their derivatives. Flavonoid metabolites accumulate the most abundantly in the exocarp and seeds, while amino acids and their derivatives are primarily accumulated in the exocarp and pulp. A total of 649 key differential metabolites were screened, including flavonoids, amino acids, and their derivatives, indicating the presence of tissue-specific accumulation of metabolites in the Shatian pomelo. This study systematically investigated the metabolite distribution in different tissue parts of the Shatian pomelo, and validated the feasibility of widely targeted metabolomics technology in pomelo quality analysis. It provided a theoretical reference for metabolic research on the Shatian pomelo and other citrus fruits, and offered a theoretical basis for the efficient utilization of pomelo resources.

Copyright of Journal of Southern Agriculture is the property of Journal of Southern Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Shatian pomelo is one kind of high-quality fruits grown in south China. Modern agricultural planting technology for Shatian pomelo closely relates to the rapid identification of its maturity. As surface color reflects the maturity of fruits, quantitative determination on the color indices of L*, a*, and b* is significant for maturity judgment. Chemoinformatic models were applied for quantitative detection of L*, a*, and b* for Shatian pomelo, by using visible and near-infrared (Vis-NIR) spectrometry. To enhance the analytical accuracy and model stability, we proposed the combined use of moving window partial least squares (MWPLS) and modified optical path length estimation and correction (MOPLEC) to search for high-signal wavelength combinations, in fully optimizing the modeling parameters. Results indicated that the chemoinformatics that we proposed performed well for nondestructive evaluations of the maturity of Shatian pomelo. This technology is expected to be utilized for quality evaluations of some other agricultural and planting fruits. [ABSTRACT FROM AUTHOR]