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Characterizing root response phenotypes by neural network analysis.

Hatzig SV, Schiessl S, Stahl A, Snowdon RJ - J. Exp. Bot. (2015)

Bottom Line: To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify.Interactive changes in root architecture can be easily captured by individual intersection profiles generated by Sholl analysis.Both genotypes reacted to osmotic stress with a shift in their intersection patterns measured with Sholl analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany sarah.hatzig@agrar.uni-giessen.de.

No MeSH data available.


Related in: MedlinePlus

Principle of root phenotyping by Sholl analysis, in which concentric circles are drawn at regular intervals around the root origin and the number of root-circle intersections was counted for each circle (this figure is available in colour at JXB online).
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Figure 1: Principle of root phenotyping by Sholl analysis, in which concentric circles are drawn at regular intervals around the root origin and the number of root-circle intersections was counted for each circle (this figure is available in colour at JXB online).

Mentions: Total root length (RL), primary root length (PRL), and lateral root length (LRL) were measured manually by tracing the roots with the freehand line tool of the software ImageJ (rsb.info.nih.gov/ij/). Mean length of lateral roots (MLRL) was calculated. The number of lateral roots (NLR) was determined by manual counting. Concentric circles were drawn with a common compass around the root origin (Fig. 1) at intervals of 0.5cm. The first circle was drawn at a distance of 0.5cm from root origin and the outer circle was drawn beyond the outermost root tip.


Characterizing root response phenotypes by neural network analysis.

Hatzig SV, Schiessl S, Stahl A, Snowdon RJ - J. Exp. Bot. (2015)

Principle of root phenotyping by Sholl analysis, in which concentric circles are drawn at regular intervals around the root origin and the number of root-circle intersections was counted for each circle (this figure is available in colour at JXB online).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4585416&req=5

Figure 1: Principle of root phenotyping by Sholl analysis, in which concentric circles are drawn at regular intervals around the root origin and the number of root-circle intersections was counted for each circle (this figure is available in colour at JXB online).
Mentions: Total root length (RL), primary root length (PRL), and lateral root length (LRL) were measured manually by tracing the roots with the freehand line tool of the software ImageJ (rsb.info.nih.gov/ij/). Mean length of lateral roots (MLRL) was calculated. The number of lateral roots (NLR) was determined by manual counting. Concentric circles were drawn with a common compass around the root origin (Fig. 1) at intervals of 0.5cm. The first circle was drawn at a distance of 0.5cm from root origin and the outer circle was drawn beyond the outermost root tip.

Bottom Line: To improve sustainability in low-water environments, breeders of major crops must therefore pay closer attention to advantageous root phenotypes; however, the complexity of root architecture in response to stress can be difficult to quantify.Interactive changes in root architecture can be easily captured by individual intersection profiles generated by Sholl analysis.Both genotypes reacted to osmotic stress with a shift in their intersection patterns measured with Sholl analysis.

View Article: PubMed Central - PubMed

Affiliation: Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany sarah.hatzig@agrar.uni-giessen.de.

No MeSH data available.


Related in: MedlinePlus