Sensitive approach and future perspectives in microscopic patterns of mycorrhizal roots
| Autor: | Florin Păcurar, Vlad Stoian, Mignon Sandor, Ioana Crisan, Roxana Vidican, V. Stoian, Carmen Puia, Ioana Vaida |
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| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0301 basic medicine
Computer science Science Plant Roots Article 03 medical and health sciences Soil 0302 clinical medicine Root length Mycorrhizae Numerical simulations Host plants Colonization Arbuscular mycorrhiza Symbiosis Soil Microbiology Biological data Microscopy Multidisciplinary Digital mapping Models Theoretical Plants 030104 developmental biology Medicine Biological system 030217 neurology & neurosurgery Mycorrhizal colonization |
| Zdroj: | Scientific Reports Scientific Reports, Vol 9, Iss 1, Pp 1-8 (2019) |
| ISSN: | 2045-2322 |
| Popis: | The harmonization of methodologies for the assessment of radicular endophytic colonization is a current necessity, especially for the arbuscular mycorrhizas. The functionality of mycorrhizal symbionts for plants can be described only by indicators obtained based on microscopic analysis. That is the reason for which a unifying methodology will lead to the achievement of highly correlated indicators comparable from one research to another. Our proposed methodology can further digitize the microscopic observations of colonization. The MycoPatt system is developed as a methodological framework for obtaining objective and comparable microscopic observations. The horizontal, vertical and transversal indicators are highly adaptable and allow the tracking of mycorrhizal colonization in root length. All structures developed by symbionts can be traced and the obtained metadata can be compared without any transformation. Mycorrhizal maps have a high degree of applicability in evaluating soil inoculum efficiency. In the future, the application of this method will lead to digital maps with a high degree of accuracy. MycoPatt allows the mathematical expression of colonization patterns, being a complex model that converts biological data into statistically comparable indicators. This will further allow obtaining inferences with applicative importance and similarity spectra for the colonizing fungi and host plants. |
| Databáze: | OpenAIRE |
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