# Comparison of Biochemical Constituents and Contents in Floral Next of _Castanae_ spp.
## 4 Materials and Methods
### Volatile Organic Compounds (VOCs) Identification  
The volatile profile analysis was performed on a GC-MS 7890B/5977B quadrupole, with electron ionization (Agilent Technologies). The separation was performed on Agilent HP-5 MS analytical column (30 m \(\times\) 0.25 mm, 0.25 \(\upmu\)m) using 99.999% high purity helium as the carrier gas velocity in 36.262 cm sec\({}^{-1}\). SPME fiber was injected into the GC injection port and the volatiles in fiber were desorbed onto the column at 250 \({}^{\circ}\)C for 3 min in splitless mode. The oven temperature was held at 40 \({}^{\circ}\)C for 6 min, increasing at a ratio of 6 \({}^{\circ}\)C min\({}^{-1}\) until 250 \({}^{\circ}\)C at 6 \({}^{\circ}\)C min\({}^{-1}\) (6 min hold). The mass spectrometer operated at 70 eV ionization energy. The ion source temperature was 280 \({}^{\circ}\)C. The identification of VOCs was performed by comparison of mass spectra with those in the mass spectra library (NIST/EPA/NIH 2017 Library) with the MSD Chemstation software (Version F.01.03.2357, Agilent Technologies). Linear retention indices (LRI) were calculated as a parameter for identifying compounds using a series of C8-C20 alkanes (#04070, Sigma Aldrich, St Louis, MO, USA), analyzedunder the same chromatographic conditions. The semi-quantification of VOCs was calculated based on the corresponding calibration curves obtained by an external standard. A linearity ranges from 0.01, 0.1, 0.1 mg/mL of acetophenone (#42163, Sigma-Aldrich) was observed for the external standards (linear regression equation y = 46617x + 2E+06, R\({}^{2}\) = 0.9971). Peak areas were normalized as percentage and used to determine the relative amounts of the VOCs. The data were expressed as mean \(\pm\) standard error of the mean (SEM) of triplicate measurements. One-way analysis of variance (ANOVA) with [PERSON]'s multiple range tests to assess differences in VOCs among five different floral nectar of _Castanea_ spp. using SPSS(r) Statics 25 (IBM, Armonk, NY, USA). Principal component analysis (PCA) was employed to establish relationships between the _Castanea_ spp. and their VOCs using the online software MetaboAnalyst 4.0 ([[http://www.metaboanalyst.ca](http://www.metaboanalyst.ca)]([http://www.metaboanalyst.ca](http://www.metaboanalyst.ca))). The data acquired from GC-MS was scaled with unit variance before all variables were subjected to the PCA. Figures were prepared in GraphPad(r) Prism 8 (GraphPad Software, Inc., La Jolla, CA, USA).  
Conceptualization, M.S.K. and Y.K.K.; data curation, U.Y. and S.L.; investigation, Y.K.K. and S.L.; methodology, Y.K.K. and S.L.; project administration, J.H.S., M.-L. and H.W.K.; resources, J.H.S., M.S.K. and Y.K.K.; software, M.-L.L. and S.L.; supervision, M.J.K. and H.W.K.; validation, J.H.S., M.S.K. and H.W.K.; visualization, S.L.; writing--Original draft preparation, Y.K.K. and S.L.; writing--Review and editing, M.J.K., U.Y., M.S.K. and H.W.K.; All authors have read and agreed to the published version of the manuscript.  
This work was supported by National Institute of Forest Science (FG0403-2017-03-2019). Also, this work was carried out with the support of \"Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ014762)\" Rural Development Administration of Republic of Korea and Research Assistance program (2019) in the Incheno National University.  
The authors declare no conflict of interest.