期刊
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
卷 67, 期 26, 页码 7530-7537出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jafc.9b02500
关键词
portable gas chromatography; volatile organic compounds; plant emission; plant disease diagnosis; common milkweed (Asclepias syriaca)
资金
- Flux HPC Cluster by the University of Michigan Office of Research and Advanced Research Computing - Technology Services (ARC-TS)
We developed and applied a fully automated portable gas chromatography (GC) device for rapid and in situ analysis of plant volatile organic compounds (VOCs) to examine plant health status. A total of 42 emission samples were collected over a period of 5 days from 10 milkweed (Asclepias syriaca) plants, half of which were infested by aphids. Thirty-five VOC peaks were separated and detected in 8 min. An algorithm based on machine learning, principal component analysis, and linear discriminant analysis was developed to evaluate the GC results. We found that our device and algorithm are able to distinguish between the undamaged control and the aphid-infested milkweeds with an overall accuracy of 90-100% within 48-72 h of the attack. Such rapid in situ detection of insect attack attests to the great potential of VOC monitoring in plant health management.
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