Botany lecture notes

Classification of Gymnosperms by Chamberlain (1934)

Classification of Gymnosperms

Classification of Gymnosperms
The Chamberlain System – 1934

Brief history of the classification of Gymnosperms:

There are many systems for the classification of Gymnosperms in the literature. Robert Brown (1827) for the first time recognized Gymnosperms as a separate group of plants. Bentham and Hooker (1883) placed Gymnosperms between Dicots and Monocots in their classification (General Plantarum). Van Tieghman (1898) gave the status of Major Division to the Gymnosperms. Tieghman also divided the whole Spermatophyta (seed plants) into two divisions namely Gymnosperms (Astigmatae) and Angiosperms (Stigmatae). Coulter and Chamberlain in 1912 divided the division Gymnosperms directly into seven orders namely (1) Cycadofilicales, (2) Bennettitales, (3) Cycadales, (4) Cordaitales, (5) Ginkoales, (6) Coniferales and (7) Gnetales.

Classification of Gymnosperms by Chamberlain (1934)

Ø  Chamberlain (1934) divided the Gymnosperms into TWO classes and each class into orders.

Ø  Gymnosperms were divided into TWO classes:

(1).      Cycadophyta

(2).      Coniferophyta

Chamberlain System of Classification

Class I : Cycadophyta

Ø  Class Cycadophyta includes both fossil and living forms.

Ø  The stem is unbranched and stumpy.

Ø  Leaves are large and pinnately compound.

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Botany lecture notes

Apical Meristem in Shoot: Structure and Organization


Shoot Apical Meristem
Apical Organization of Shoot Meristem

Apical meristem

Ø  Apical meristem is a patch of meristematic tissue present in the apex (tips) of shoot and roots in plants.  

Shoot apex:

Ø  Shoot apex is the growing tip of the stem.

Ø  It is an undifferentiated region with meristematic cells.

Ø  From this region the plant growth proceeds.

Ø  The shoot apex also produces lateral organs such as leaves, branches and flowers.

Ø  Below the apical meristem, different tissue zones are progressively differentiated.


Tissue zones in the shoot apex

Ø  Three main tissue zones are present on the shoot apex of plants, they are:

$.  Protoderm: Protoderm gives rise to the epidermis of the plant.

$.   Procambium: Procambium gives rise to primary vascular tissue (xylem & phloem).

$.   Ground meristem (fundamental meristem): The ground meristem gives rise endodermis, pericycle, cortex, medulla and pith.

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Biostatistics Study Materials

Difference between Primary and Secondary Data: Comparison Table

primary vs secondary data

Primary Data vs Secondary Data – Statistics
(Similarities and Differences between Primary Data and Secondary Data)

The data is a set of values of qualitative or quantitative variables. In statistics, the data are the individual observations. The scientific investigations involve observations on variables. The observations made on these variables are obtained in the form of ‘data’.

Based on the source, the data is categorized into TWO types: (1) Primary Data and (2) Secondary Data.

Primary Data: Data collected for the first time by the original investigator.

Secondary Data: The data used in statistical investigations which have already been collected by some other for their purpose and published.

The present post discusses the Differences between Primary Data and Secondary Data with a Comparison Table.

Similarities between Primary and Secondary Data

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Biostatistics Study Materials

Types of Experimental Designs in Statistics (RBD, CRD, LSD, Factorial Designs)

Experimental design examples

Types of Experimental Designs in Statistics
Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD) – Advantages and Disadvantages

In the previous post, we have discussed the Principles of Experimental Designs. There we discussed the concept of Experimental design in statistics and their applications. In the present post, we will discuss different types of statistical experimental designs, its applications, advantages and limitations.

Learn more: Principles of Experimental Designs

Different types of Experimental Designs

Ø  Experimental designs are broadly classified into TWO categories:

(A).   Single-Factor Experiments

(B).  Multi-factor Experiments

(A). Single-Factor Experiments:

Ø  Single factor experiments are those experiments in which only a single factor varies while all others are kept constant.

Ø  Here the treatments consist exclusively of the different levels of the single variable factor.

Ø  All other factors are applied uniformly to all plots.

Ø  Examples of Single-Factor Experimental Designs:

(1). Completely Randomized Design (CRD)

(2). Randomized Block Design (RBD)

(3). Latin-Square Design (LSD)

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Biostatistics Study Materials

Principles of Experimental Designs in Statistics – Replication, Randomization & Local Control

Experimental Research Design

Experimental Designs in Statistics
(The Principles of Experimental Designs in Research Methodology)

What is a statistical experiment?

Ø  An experiment is a plan for the collection and analysis of data.

Ø  “It is a controlled act through which data are collected according to some pre-determined objective”.

Ø The observations obtained from a carefully planned and well-designed experiment in advance only gives valid inferences.

Ø An experimental design which gives the smallest error is supposed to be the best design for a particular type of investigation.

Experimental unit (Experimental Plot):

Ø  The smallest division of the experimental material to which we apply the treatment and can make the observation on it is called experimental unit or experimental plot


Ø  Treatments are the characteristics which are to be investigated through an experiment.

Ø  The treatments are the objects of comparisons in an experiment.

Ø  Example: effects of different fertilizers, the yield of different varieties of a crop, disease resistance of different cultivars etc.

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