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Differentiation of Pectobacterium and Dickeya spp. phytopathogens using infrared spectroscopy and machine learning analysis
- Source :
- Journal of biophotonicsREFERENCES. 13(5)
- Publication Year :
- 2019
-
Abstract
- Pectobacterium and Dickeya spp. are soft rot Pectobacteriaceae that cause aggressive diseases on agricultural crops leading to substantial economic losses. The accurate, rapid and low-cost detection of these pathogenic bacteria are very important for controlling their spread, reducing the consequent financial loss and for producing uninfected potato seed tubers for future generations. Currently used methods for the identification of these bacterial pathogens at the strain level are based mainly on molecular techniques, which are expensive. We used an alternative method, infrared spectroscopy, to measure 24 strains of five species of Pectobacterium and Dickeya. Measurements were then analyzed using machine learning methods to differentiate among them at the genus, species and strain levels. Our results show that it is possible to differentiate among different bacterial pathogens with a success rate of ~99% at the genus and species levels and with a success rate of over 94% at the strain level.
- Subjects :
- Pectobacterium
Pectobacteriaceae
General Physics and Astronomy
Dickeya
Machine learning
computer.software_genre
medicine.disease_cause
01 natural sciences
General Biochemistry, Genetics and Molecular Biology
010309 optics
Machine Learning
Enterobacteriaceae
0103 physical sciences
medicine
General Materials Science
Agricultural crops
Plant Diseases
Alternative methods
biology
business.industry
Strain (biology)
Spectrum Analysis
010401 analytical chemistry
General Engineering
food and beverages
Pathogenic bacteria
General Chemistry
biology.organism_classification
0104 chemical sciences
Artificial intelligence
business
computer
Subjects
Details
- ISSN :
- 18640648
- Volume :
- 13
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Journal of biophotonicsREFERENCES
- Accession number :
- edsair.doi.dedup.....327c6c12f44d54b14d29f35d47da963e