This document discusses numerical taxonomy, which involves grouping and classifying taxonomic units using numerical methods and quantitative analysis. It defines numerical taxonomy as the grouping of taxonomic units based on numerical evaluations of their affinity or similarity. The document outlines several approaches to numerical taxonomy and notes that it aims to identify, name, and classify plants in a more objective manner than traditional taxonomy by considering multiple character states numerically. It provides examples of how morphological character data from operational taxonomic units can be coded and analyzed using similarity matrices and cluster analysis to construct taxonomic relationships.

2.  Saira Mehar.
 Roll#13
 BS-Botany
 5th-Semester

3. Brief introduction.
Classification of Taxa could not
provide satisfactory degree of
correlative dissimilarity.

4. Keen analysis of phylogeny of plants
complicate the concept of
classification.
Taxonomic structure based on
Morphological Principles.
Cytological,anatomical,physiological
,biochemical
evidences,palaeobotanical evidences
for assessment of the status of any
taxon

5. Defination: grouping of
taxanomic units by numerical
methods.
OR
Numerical evaluation of
affinity or similarity b/w
taxanomic units.

6. Ordering of units into taxa
on the basis of affinities.
Conversion of taxonomic
entities>numerical
quantities.

7. 1. Numerical systematics(Wanger)
2. Mathematical taxanomy(Sibson)
3. Multivariate
morphometrics(Blackith)
4. Taxometrics(Mayer)
5. Taximetrics(Roger)
6. Numerical Taxanomy(Sneath &
Sokal)

8.  Adanson(1763),French
botanist >assign numerical
values to similarity b/w
organism.
 Used many possible
characters for classification.

9.  Present concept concerned with
methods & techniques employed
for classification of plants.
 Aim of numerical taxanomy is;
1. Identification
2. Nomenclature
3. Classification of plants.

10. all characters considered
to equal taxonomic
value>no one character
weighed more or less than
any other.

11. The taxonomic units or
entities are called operational
taxonomic units(OTU).
 EXAMPLE.
 (1,0) or (+,-) any character present or
absent.

12. Orthodox taxonomy
(conventional/traditional)
depends on taxanomic
characters.
All characters cosidered to be of
equal importance.

13. Atleast 60 characters are
selected.
Characters broken into unit
characters.
EXAMPLE: corolla lobe
lenghth,width,spotting,lobe &
tube ratio etc.

14. Characters of OTU divided into
2-state or 3-state. e.g;calyx
lobe apex 1)emarginate
2)obtuse/acute.
Uniform coding is
necessary,(+,+),(-,-), (+,-).

15. 1. Emarginate: heaving a margin interrupted
by notch.
2. Obtuse: blunt-rounded shape.
3. Acute: sharp-ended leaf.

19. Character which cannot be
compared is given NC.
Data matrix called(t x
n)table.
T=taxa
n=character

20.  Similarity(S) is calculated by;
 S = NS x 100
 NS+ND
NS=number of common characters in 2-OTUs
ND=character +ve in one OTU,-ve in other OTU.
Similarities are shown in the
form of matrix in (txt) table.

24. Groups of OTUs called Clusters.
Affinities of different OTUs are
determined.
OTUs of Similar affinities
grouped together in different
taxa.

25. Taxonomic system
constructed>resemblances
& differences b/w clusters.
Cluster analysis
arranged>dendrogram.

26. Matrix is subsequently analyzed.
In cluster analysis structure &
degree of relationship among
OTUs is revealed.
Cluster of OTUs arranged in a
tree diagram or Dendrogram.

28. Phenons; groups of similar
organisms recognized by
numerical method.
Phenons=taxonomic groups
Phenon is not synonym of
taxon.

29. Phenon may or may not equal to
ranks of Numerical Taxonomy,
such as
species,genus,tribe,family,etc
In dendrogram;
1. 1) 1 2) 7 3) 3,5,6
4)4,9,10 5)2,8

31. 3 groups are delimited.
1. Azalea
2. Lepidotae
3. Elepidotae.
 No distinguish character to
separate Azalae group from
Lepidotae & Elepidatae.

32.  Numerically Azalae is a distinct
group.
 Cluster-1 represent Azalae.
 Cluster-2 ……. Lepidotae.
 Cluster-3 ……. Elepidotae.
 Group 2 & 3 are more closely
related

33. R. rubiginosa (B) & R.
cinnabarinum (I) closely
related to one another.
These are only
polypoloid(2n=72)

34. Remaining species are
diploid(2n=24)
Highest % similarity
related to polypoloid
nature.

36. Sneath & Sokal (1973) mentioned
following advantages;
1. Data collected from variety of
sources, such as
morphology,physiology,chemistry,a
mino acid sequences or
proteins,etc.

37. 2)Taxonomic work can be done
by less highly skilled
workers.
3) Numerical data easily used
for creation of
keys,maps,descriptions,catl
ogues,etc

38. 4. Provide better keys and
classification system.
5. Quality of conventional
taxonomy improved by
numerical taxonomy.

39. 6. Suggested several fundamental
changes in conventional
principles of taxonomy.
7. Number of existing biological
concepts reinterpreted in the
light of numerical taxonomy.