Numerical Taxonomy: Principles, Merits, Demerits and Applications

Numerical Taxonomy is the technique of classifying organisms using numerical methods. This method firmly clarifies as well as displays the degree of link among the species. Organisms are classified into taxa according to their similarities and differences. Numerical Taxonomy is at present a very essential part of current systematics. Numerical Taxonomy is also known as Taximetrics; however, presently it is more commonly referred to as Phenetics. It is the Numerical evaluation of the similarities or affinities of taxonomic units, which are typically classified into taxa based on their affinities. 

Also read: Taxonomic Hierarchy of Plants and Animals

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Key Terms: Taxa, Electrophoretic patterns, Mitochondrial, DNA, RFLP, Phytochemical data

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History of Numerical Taxonomy

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Heywood's definition of the Numerical Taxonomy is the Numerical evaluation of the similarity of groups of organisms and the ordering of these groups into higher-ranked taxa on the basis of these similarities.

• The original methods and concepts of Numerical Taxonomy were created between 1957 and 1961. 
• Michel Adanson, a French botanist, assigned Numerical ratings to organisms' similarities.
• He also noted that while identifying plants, all traits should be given equal weightage.
• The classifications he created were known as Adansonian classifications since he considered as many characters as possible.
• Sneath and Sokal, on the other hand, were significantly responsible for the development and popularization of the Numerical Taxonomy in 1963.

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Aspects of Numerical Taxonomy

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Following are the two important aspects involved in Numerical Taxonomy,

1. Construction of taxonomic groups: Individuals are chosen as well as their characteristics are spotted to construct taxonomic categories. This aspect says, the greater the amount of characters, the better is the approach. Then, using character analysis, similarities between the individuals are determined.
2. Taxonomic group discrimination: If the taxonomic groups chosen for the study have overlapping traits, it is always better to use discrimination to choose them.

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Principles of Numerical Taxonomy

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The principles of Numerical Taxonomy that were put forward by Sneath and Sokal are as follows – 

1. The greater the content of information in the taxa, and the more the characters are taken into consideration, the better a given classification system will be.
2. Every character should be given equal weightage in creating new taxa.
3. The overall similarity between any two entities is considered for the purpose of comparison.
4. The correlation of characters differs in the groups of organisms under study. Thus distinct taxa can be recognized.
5. Phylogenetic conclusions can be drawn from the taxonomic structure of a group and from character correlations, assuming some evolutionary pathways and mechanisms.
6. The science of taxonomy is viewed and practiced as an empirical science.
7. The phenetic similarity is the base of classifications.

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Merits of Numerical Taxonomy

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The advantages of Numerical Taxonomy according to Sneath and Sokal are given below -

1. The data of conventional taxonomy is improved by Numerical Taxonomy as it uses more numbers and better-described characters.
2. The data are collected from a variety of sources, such as morphology, chemistry, physiology, etc.
3. As Numerical methods are more sensitive for delimiting taxa, the data obtained can be efficiently used in the construction of better classification systems and keys.
4. Numerical Taxonomy has in fact suggested several fundamental changes in the conventional classification systems.
5. The number of existing biological concepts has been reinterpreted in the light of Numerical Taxonomy.
6. Numerical Taxonomy allows more taxonomic work to be done by the workers that ate not much skilled.

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Demerits of Numerical Taxonomy

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The demerits of numerical taxonomy are as follows – 

1. The Numerical methods come along with phenetic classifications and not phylogenetic classifications.
2. The determined limits held by these techniques may not be accepted by the proponents of the “biological” species concept.
3. In this method, the greatest disadvantage is character selection. If characters selected for comparison are not enough, the statistical methods may not give the expected solution.
4. Different taxometric procedures may conclude in different results, according to Steam. A crucial difficulty is to choose a process for the requirement and the number of traits necessary in order to get expected results from these mechanical aids.
5. It is also very important to ascertain whether a large number of traits would really conclude with much-expected results than those using a smaller number of traits.

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Applications of Numerical Taxonomy

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The applications of numerical taxonomy are – 

• Numerical Taxonomy is found to be successful in the study of various Angiosperms such as Apocynum, Oenothera, Salix, Zinnia, Chenopodium, Crotalaria, Cucurbita, Wheat cultivars, and Maize cultivars, etc.
• With the assistance of Numerical Taxonomy similarities and affinities in bacteria, there can be studies held on various other microorganisms also.
• Mitochondrial DNA RFLP and Phytochemical data from seed protein studies have been Numerically examined to learn the variations that are interspecific.
• Several Angiosperms including Oryza, Sarcostemma Solarium, and other groups comprising Farinosae of Engler along with other groups have achieved delimitation.
• According to the Sokal & sneath and Romero Lopes et al. method, the degree of pairing affinity i.e. PA or similarity index is calculated by the following given formula. This is mainly based on the results of electrophoretic patterns.

Also read: Plant Kingdom MCQs

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Things to Remember

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• Numerical Taxonomy is the technique of classifying organisms using Numerical methods. Numerical Taxonomy is also known as Taximetrics; however, presently it is more commonly referred to as Phenetics.
• The concept of Numerical Taxonomy was first developed in 1963 by Robert R. Sokal and Peter H. A. Sneath.
• Numerical Taxonomy is the Numerical evaluation of the similarities or affinities of taxonomic units, which are typically classified into taxa based on their affinities.
• This is assisted by mathematical or automated methods to analyze various taxonomic data types.
• There are two different aspects of Numerical Taxonomy. They are (i) Construction of taxonomic groups and (ii) Taxonomic group discrimination.
• According to the Sokal & sneath and Romero Lopes et al. method, the degree of pairing affinity i.e. PA or similarity index is calculated by the following given formula. This is mainly based on the results of electrophoretic patterns.

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Previous Year Questions

1. The scientist widely regarded as the triple crown of biology X is…[AMUEEE 2015]
2. Evolutionary history of an organism is known as… [NEET 2006]
3. Reason of diversity in living being is….[NEET 2001]
4. The living organisms can be unexceptionally distinguished from the non-living things on the basis of their ability for….​[NEET 1988]
5. Rauwolfia - serpentina belongs to..........family.​...​[KCET 2007]
6. Edaphology is​...[KCET 2007]
7. Read the statements given below and identify the incorrect statement.​...[KCET 2012]
8. Which of the following taxonomic category of housefly is wrongly matched?​...[KEAM]

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