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Transcript and Metabolite Profiling for the Evaluation of Tobacco Tree and Poplar as Feedstock for the Bio-based Industry
Published on: May 16, 2014
Quantitative Morphological Profiling and Isolate-Specific Insensitivity of Cacao Pathogens to Novel Bio-Based
Ezekiel Ahn1, Masoud Kazem-Rostami2, Sunchung Park1
1Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD 20705, USA.
Novel bio-based fatty amides show promise against cacao fungal pathogens like Colletotrichum gloeosporioides. One compound, PhSOAM, effectively inhibited growth and altered fungal morphology, demonstrating isolate-specific efficacy for sustainable crop protection.
Area of Science:
- Agricultural Science
- Mycology
- Biochemistry
Background:
- Fungal pathogens such as Colletotrichum gloeosporioides and Pestalotiopsis spp. pose significant risks to global cacao production.
- Developing sustainable strategies requires understanding pathogen responses to new antifungal agents.
Purpose of the Study:
- To investigate the isolate-specific sensitivity and morphological responses of cacao pathogens to novel bio-based phenolic-branched fatty acids and amides.
- To evaluate the potential of these compounds as sustainable antifungal agents for crop protection.
Main Methods:
- Tested four novel bio-based phenolic-branched fatty acids and amides against three cacao pathogen isolates (one Pestalotiopsis sp., two C. gloeosporioides).
- Utilized quantitative image analysis to assess morphological changes in fungal colonies.
- Employed multivariate analyses and machine learning models for response classification and prediction.
Main Results:
- Observed high isolate-specific susceptibility, with one compound (PhSOAM) showing potent inhibition against two isolates.
- Identified significant intraspecific variation, as one C. gloeosporioides isolate was insensitive to all tested compounds.
- PhSOAM uniquely increased the length-to-width ratio of fungal colonies, suggesting disruption of polarized growth.
- Machine learning models achieved R² up to 0.74 in classifying pathogen-compound interaction outcomes.
Conclusions:
- Bio-based amides, particularly PhSOAM, demonstrate potential as effective antifungal agents against specific cacao pathogens.
- The study highlights significant intraspecific variation in pathogen response, crucial for targeted control strategies.
- A combined approach of morphological profiling and predictive modeling offers a powerful framework for studying complex fungal-antifungal interactions.
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