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Optimization of Headspace Solid-Phase Microextraction Conditions for the Identification of Phytophthora Cinnamomi Rands

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Journal Plant Dis
Specialty Biology
Date 2019 Feb 3
PMID 30708791
Citations 4
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Abstract

A robust technique was developed to identify Phytophthora cinnamomi using headspace solid-phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled to a flame ionization detector (FID) for analyzing volatile organic compounds (VOCs). Six fiber types were evaluated and results indicated that the three-phase fiber 50/30 μm divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) had the highest extraction efficiency for both polar and nonpolar GC columns. The maximum extraction efficiency (equilibrium absorption) was achieved 16 h after fiber exposure in the HS. Absorbed compounds on the fiber were completely desorbed in the GC injector after 5 min at 250°C. Compared with the nonpolar column, the polar column showed optimum separation of VOCs released from P. cinnamomi. Under the optimized HS-SPME and GC/FID conditions, lower detection limits for the four external standards was found to be between 1.57 to 27.36 ng/liter. Relative standard deviations <9.010% showed that the method is precise and reliable. The method also showed good linearity for the concentration range that was analyzed using four standards, with regression coefficients between 0.989 and 0.995, and the sensitivity of the method was 10 times greater than that of the conventional HS method. In this study, the VOC profiles of six Phytophthora spp. and one Pythium sp. were characterized by the optimized HS-SPME-GC method. The combination of the VOCs creates a unique pattern for each pathogen; the chromatograms of different isolates of P. cinnamomi were the same and the specific VOC pattern of P. cinnamomi remained consistently independent of the growth medium used. The chromatograms and morphological studies showed that P. cinnamomi released specific VOCs at different stages of colony development. Using the optimized HS-SPME GC method, identification of P. cinnamomi from 15 in vivo diseased soil samples was as high as 100%. Results from this study demonstrate the feasibility of this method for identifying P. cinnamomi and the potential use of this method for physiological studies on P. cinnamomi.

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