ArticleApplications in plant sciences2018
GC-MS metabolite profiling for specific detection of dwarf somaclonal variation in banana plants.
Article in Applications in plant sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Effective Methods Based on Distinct Learning Principles for the Analysis of Hyperspectral Images to Detect Black Sigatoka Disease.Plants (Basel, Switzerland) · 2022Article
- Food Waste Management Employing UV-Induced Black Soldier Flies: Metabolomic Analysis of Bioactive Components, Antioxidant Properties, and Antibacterial Potential.International journal of environmental research and public health · 2022Article
- Induced Genetic Variations in Fruit Trees Using New Breeding Tools: Food Security and Climate Resilience.Plants (Basel, Switzerland) · 2021Review
- Early detection of black Sigatoka in banana leaves using hyperspectral images.Applications in plant sciences · 2020Article
- Systems Metabolic Alteration in a Semi-Dwarf Rice Mutant Induced byInternational journal of molecular sciences · 2020Article
- GC-MS metabolite profiling for specific detection of dwarf somaclonal variation in banana plants.Applications in plant sciences · 2018Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
premise of the studyThe production of banana (
methodsThe gas chromatography-mass spectrometry (GC-MS) metabolite profile of dwarf banana variants was investigated and compared to that of normal-healthy (N) and cucumber mosaic virus (CMV)-infected plants using principal components analysis and partial least squares discriminant analysis (PLS-DA).
resultsSignificant differences among the sample groups were observed in 82 metabolites. Rhamnose was exclusively present in dwarf plants but allothreonine and trehalose were present in all but SV samples. Cellobiose was only detected in N plants, while 45 other metabolites, including methyl-glucopyranoside, allopyranose, lactose, phenylalanine, and l-lysine were detected in all but CMV-infected samples. PLS-DA models were able to detect SV, CMV, and N plants with 100% accuracy and specificity. DISCUSSION: The GC-MS metabolite profile can be used for the rapid, specific detection of SV at early plant production stages. This is the first metabolite-based characterization and detection of somaclonal variation in plants.
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