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Geometric Mean

Geometric Mean

The mean is a measure of the central tendency of a data set. In some data sets, the data is inherently multiplicative, and the arithmetic mean is not useful. For example, the human population multiplies with time, and so does the credit amount of financial investment, as the interest compounds over successive time intervals.
In cases of multiplicative data, the geometric mean is used for statistical analysis. First, the product of all the elements is taken. Then, if there are n elements in the...

Geometric Sequences

Geometric Sequences

In systems where values diminish by a constant proportion at each stage, the resulting sequence follows a geometric structure. Each new value in the sequence is obtained by applying a fixed multiplier to the preceding term. This regular, proportional decline type is often used to represent processes involving gradual loss, such as energy dissipation or reduction in amplitude over time.When analyzing the total effect of such a process across unlimited iterations, the series of values is referred...

Background and Environment Affect Phenotype

Background and Environment Affect Phenotype

Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...

Stereoisomerism

Stereoisomerism

Isomerism in Complexes
Isomers are different chemical species that have the same chemical formula.
Transition metal complexes often exist as geometric isomers, in which the same atoms are connected through the same types of bonds but with differences in their orientation in space. Coordination complexes with two different ligands in the cis and trans positions from a ligand of interest form isomers. For example, the octahedral [Co(NH3)4Cl2]+ ion has two isomers (Figure 1) In the cis...

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

Comparing Mitochondrial, Chloroplast, and Prokaryotic Genomes

The present-day mitochondrial and chloroplast genomes have retained some of the characteristics of their ancestral prokaryotes and also have acquired new attributes during their evolution within eukaryotic cells. Like prokaryotic genomes, mitochondrial and chloroplast genomes neither bind with histone-like proteins nor show complex packaging into chromosome-like structures, as observed in eukaryotes. Unlike mitotic cell divisions observed in eukaryotic cells, mitochondria and chloroplasts...

Coordination Number and Geometry

Coordination Number and Geometry

For transition metal complexes, the coordination number determines the geometry around the central metal ion. Table 1 compares coordination numbers to molecular geometry. The most common structures of the complexes in coordination compounds are octahedral, tetrahedral, and square planar.

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Related Experiment Video

Updated: Feb 8, 2026

Quantification of Orofacial Phenotypes in Xenopus

Quantification of Orofacial Phenotypes in Xenopus

Published on: November 6, 2014

Arabidopsis phenotyping through geometric morphometrics.

Carlos A Manacorda¹, Sebastian Asurmendi^1,2

¹Instituto de Biotecnología, CICVyA, INTA, Nicolas Repetto y de los Reseros s/n, Hurlingham, (1686) Buenos Aires, Argentina.

|June 20, 2018

Summary

Geometric morphometrics offers objective shape analysis for Arabidopsis plants, crucial for understanding viral infections. This method provides reproducible measurements for large-scale phenotyping and genetic studies.

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Area of Science:

Plant biology
Quantitative genetics
Computational biology

Background:

High-throughput plant phenotyping advances enable large-scale genetic and physiological studies using image analysis.
Current Arabidopsis rosette shape analysis lacks objective descriptors, hindering accurate cross-platform comparisons.
Geometric morphometrics provides a robust framework for quantitative shape analysis in phenomics.

Purpose of the Study:

To propose a landmark-based geometric morphometric scheme for analyzing shape variation in Arabidopsis rosettes.
To quantify and visualize shape differences during viral infection processes.
To enable objective and reproducible shape comparisons in plant phenotyping.

Main Methods:

Development of a specific landmark placement scheme on Arabidopsis rosette images.
Application of geometric morphometrics to quantify shape variations.
Statistical analysis to assess shape differences between control and infected plants, and between different viruses.

Main Results:

Quantification and visualization of shape differences between control and virus-infected Arabidopsis plants.
Objective comparison of shape variations induced by two distinct ssRNA+ viruses.
Assessment of the reproducibility of the proposed geometric morphometric method.

Conclusions:

Geometric morphometrics offers an objective and reproducible approach to plant shape analysis.
This method enhances phenotypic feature extraction when combined with automated phenotyping platforms.
The proposed scheme is valuable for studying plant responses to biotic stress, such as viral infections.