HYHonglian Ye

Honglian Ye

*This is an algorithmically generated author record based on publicly available information.

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Previous Organizations / Institutes

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Honglian Ye has a total of 9 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    The Sink–Source Relationship Regulated Camellia oleifera Flower Bud Differentiation by Influencing Endogenous Hormones and Photosynthetic Characteristics

    by Yuanyuan Si, Yue Wen, Honglian Ye, Tingting Jia, Zhichao Hao, Shuchai Su, Xiangnan Wang

    To explore the reasons for the differences in flower bud differentiation in Camellia oleifera under different sink–source relationships, different types of new shoots (T1 and T2) were selected to represent different sink–source relationships (new shoots with one fruit borne alongside at the bottom of the new shoots-T1; new shoots without one fruit borne alongside at the bottom of the new shoots-T2), and the flower bud differentiation rate, endogenous hormones and photosynthetic characteristics were determined. With the increase in the sink, the flower differentiation rate decreased significantly and the IAA and GA3 content in the leaves and ABA content in the buds increased significantly, while the GA3 and ZT content in the buds decreased significantly, which were significantly and positively correlated with the flower differentiation rate, with correlation coefficients of 0.777 and 0.817, respectively. Furthermore, an increase in the number of sinks contributed significantly to the increase in soluble sugar and starch content in leaves, while the soluble sugar and starch content in flower buds decreased significantly with the increase in sinks, with maximum differences of 3.45 mg·g−1 (soluble sugar in leaves), 4.09 mg·g−1 (soluble sugar in flower buds), 7.08 mg·g−1 (starch in leaves) and 4.87 mg·g−1 (starch in flower buds), and the high soluble sugar and starch content in flower buds at preflower bud differentiation with correlation coefficients of 0.854 and 0.837, respectively. The chlorophyll content and net photosynthetic rate increased with increasing sinks. In the presence of fruit at the base of the new shoot, more 13C assimilates were allocated to fruit and less to flower buds, resulting in a decrease in the rate of flower bud differentiation. The 13C assimilate allocated to the flower buds of T1 (6.71 mg·g−1) was significantly lower than the 13C assimilate allocated to the flower buds of T2 (10.26 mg·g−1) during late bud differentiation, and the difference between T1 and T2 was greatest during this period. Our work demonstrated that the sink–source relationship regulated Camellia oleifera flower bud differentiation by influencing endogenous hormones and photosynthetic characteristics. To achieve stable production of Camellia oleifera in successive years in the future, the ratio of the number of new shoots of the two types in relation to the different sink–source relationships should be reasonable.


  • Open Access

    Automatic Assignment of Molecular Ion Species to Elemental Formulas in Gas Chromatography/Methane Chemical Ionization Accurate Mass Spectrometry

    by Shunyang Wang, Luis Valdiviez, Honglian Ye, Oliver Fiehn

    Gas chromatography–mass spectrometry (GC-MS) usually employs hard electron ionization, leading to extensive fragmentations that are suitable to identify compounds based on library matches. However, such spectra are less useful to structurally characterize unknown compounds that are absent from libraries, due to the lack of readily recognizable molecular ion species. We tested methane chemical ionization on 369 trimethylsilylated (TMS) derivatized metabolites using a quadrupole time-of-flight detector (QTOF). We developed an algorithm to automatically detect molecular ion species and tested SIRIUS software on how accurate the determination of molecular formulas was. The automatic workflow correctly recognized 289 (84%) of all 345 detected derivatized standards. Specifically, strong [M − CH3]+ fragments were observed in 290 of 345 derivatized chemicals, which enabled the automatic recognition of molecular adduct patterns. Using Sirius software, correct elemental formulas were retrieved in 87% of cases within the top three hits. When investigating the cases for which the automatic pattern analysis failed, we found that several metabolites showed a previously unknown [M + TMS]+ adduct formed by rearrangement. Methane chemical ionization with GC-QTOF mass spectrometry is a suitable avenue to identify molecular formulas for abundant unknown peaks.