Agriculture Reference
In-Depth Information
Disadvantages
1. The number of treatments equals the number
of rows and columns.
2. The layout of the design is not as simple as in
the case of CRD or RBD.
3. The analysis assumes
Advantages
1. In factorial experiments, the effects of more
than one factor at a time can be estimated.
2. In factorial experiments the interaction effects
can be estimated which is not possible in
single-factor experiments.
3. Factorial experiments are resource saving
compared to single-factor experiments; facto-
rial experiments could be set up with lesser
number of replications.
that
there are no
interactions.
4. It requires
mainly
a square number of experi-
mental units.
The LSD is suitable and more advantageous
over CRD and RBD under
specific field
Disadvantages
1. When the number of factors or the levels of
factors or both increase, then the number of
treatment combinations will also increase,
resulting in a requirement of bigger experi-
mental area/units and bigger block/group size.
As the block/group size increases, it is very
difficult to maintain homogeneity among the
plots/units within the block/group. Thus, there
is a possibility of increase in the experimental
error vis-`-vis decrease in precision of
experiment.
2. Factorial experiments are more complicated
than single-factor experiments.
3. Failure in one experiment may result in a loss
of huge amount of information compared to a
single-factor experiment.
conditions.
Factorial Experiment
To save time and other resources and also to
know the interaction effects of different factors
in single factor experiments factorial experi-
ments are set up. These are also suitable for
agricultural field, laboratory, social science, and
other studies in which the impact of more than
one factor is required to be compared. It is our
common experience that a particular variety of
wheat or a crop is responding differentially under
different irrigation schedule, different rates of
fertilizers, different weed management practices,
different crop protection practices etc. and an
experimenter wants to know all the above. More-
over, in this type of experiments, the experi-
menter wants to know not only the level or the
doses of individual factor giving better result
but also wants the combination of the levels of
different factors which is producing the better
result. In a study related to the role of health
drinks and physical exercise, one may be inter-
ested in knowing (1) which health drink is com-
paratively better, (2) what type of exercise is
better, and (3) what combination of health drinks
and exercise provides better health to the grow-
ing children. In socioeconomic studies, one may
be interested in relating the economic status and
educational status of the people in adopting mod-
ern agricultural practices. Factorial experiments
are the methods for answering the questions
related to more than one factor at a time for
their individual effects as well as interaction
effects in a single experiment.
Types of Factorial Experiment
(a)
Based on the number of factors
: Depending
upon the number of factors used in the exper-
iment, a factorial experiment is a
two-factor,
three-factor
...
p-factor
factorial experiment
when the number of factors put under exper-
imentation is 2, 3
...
p
, respectively.
(b)
Based on the level of
: Depending
upon the equality or inequality in the levels
of factors put under experimentation, a facto-
rial experiment is either
factors
symmetrical
asym-
or
metrical
. If the numbers of levels for all factors
are same, it is symmetrical, otherwise asym-
metrical. For example, a two-factor factorial
experiment with five varieties and five differ-
ent doses of nitrogen is a symmetrical factorial
experiment, but a factorial experiment with
five varieties and any number of doses of
nitrogen (not equal to five) is an asymmetrical
