INTRODUCTION: Plant volatiles (PVOCs) are important targets for studies in natural products, chemotaxonomy and biochemical ecology. The complexity of PVOC profiles often limits research to studies targeting only easily identified compounds. With the availability of mass spectral libraries and recent growth of retention index (RI) libraries, PVOC identification can be achieved using only gas chromatography coupled to mass spectrometry (GCMS). However, RI library searching is not typically automated, and until recently, RI libraries were both limited in scope and costly to obtain. OBJECTIVE: To automate RI calculation and lookup functions commonly utilised in PVOC analysis. METHODOLOGY: Formulae required for calculating retention indices from retention time data were placed in a spreadsheet along with lookup functions and a retention index library. Retention times obtained from GCMS analysis of alkane standards and Koeberlinia spinosa essential oil were entered into the spreadsheet to determine retention indices. Indices were used in combination with mass spectral analysis to identify compounds contained in Koeberlinia spinosa essential oil. RESULTS: Eighteen compounds were positively identified. Total oil yield was low, with only 5 ppm in purple berries. The most abundant compounds were octen-3-ol and methyl salicylate. The spreadsheet accurately calculated RIs of the detected compounds. CONCLUSION: The downloadable spreadsheet tool developed for this study provides a calculator and RI library that works in conjuction with GCMS or other analytical techniques to identify PVOCs in plant extracts.
INTRODUCTION: Plant volatiles (PVOCs) are important targets for studies in natural products, chemotaxonomy and biochemical ecology. The complexity of PVOC profiles often limits research to studies targeting only easily identified compounds. With the availability of mass spectral libraries and recent growth of retention index (RI) libraries, PVOC identification can be achieved using only gas chromatography coupled to mass spectrometry (GCMS). However, RI library searching is not typically automated, and until recently, RI libraries were both limited in scope and costly to obtain. OBJECTIVE: To automate RI calculation and lookup functions commonly utilised in PVOC analysis. METHODOLOGY: Formulae required for calculating retention indices from retention time data were placed in a spreadsheet along with lookup functions and a retention index library. Retention times obtained from GCMS analysis of alkane standards and Koeberlinia spinosa essential oil were entered into the spreadsheet to determine retention indices. Indices were used in combination with mass spectral analysis to identify compounds contained in Koeberlinia spinosa essential oil. RESULTS: Eighteen compounds were positively identified. Total oil yield was low, with only 5 ppm in purple berries. The most abundant compounds were octen-3-ol and methyl salicylate. The spreadsheet accurately calculated RIs of the detected compounds. CONCLUSION: The downloadable spreadsheet tool developed for this study provides a calculator and RI library that works in conjuction with GCMS or other analytical techniques to identify PVOCs in plant extracts.
Authors: Christopher Charles Presley; Ana Lisa Valenciano; Maria L Fernández-Murga; Yongle Du; Narasimhamurthy Shanaiah; Maria B Cassera; Michael Goetz; Jason A Clement; David G I Kingston Journal: J Nat Prod Date: 2017-10-19 Impact factor: 4.050
Authors: D M Magalhães; M Borges; R A Laumann; C M Woodcock; J A Pickett; M A Birkett; Maria Carolina Blassioli-Moraes Journal: J Chem Ecol Date: 2016-04-22 Impact factor: 2.626
Authors: Oleg B Shevelev; Alisa A Seryapina; Evgenii L Zavjalov; Lyudmila A Gerlinskaya; Tatiana N Goryachkovskaya; Nikolay M Slynko; Leonid V Kuibida; Sergey E Peltek; Arcady L Markel; Mikhail P Moshkin Journal: Data Brief Date: 2018-03-26