A manual of rice seed health testing - IRRI books - International Rice ...

CHAPTER 4
Samples and sampling
J. Mojica and K.A. Gomez
Proper sampling is vital to assessing
seed quality for planting value, seed
health, and seedling vigor. Seed analysts,
field inspectors, and quarantine
personnel often have to collect
samples or deal with samples provided
to them. Thus, they need to be
aware of the types of samples, of
sampling procedures, and of the reasons
for placing great emphasis on
sampling.
General concept of sampling
Definition and importance
of sampling
Sampling is a procedure of selecting
a fraction of the total population,
about which information is needed,
to represent that population. It is
used when information regarding
one or more characteristics of the
population is needed but measuring
all individuals in that population is
not possible (Snedecor and Cochran
1967).
A sample is a subcollection of objects
(or organisms) selected from a
population of interest, usually chosen
so as to make inferences about
one or more attributes of the population
based on observation made on
the sample. It must be a representative
of the population if it leads to
correct inferences about the population
(Steel and Torrie 1960). If all the
sampling units (say, plants, panicles,
or seeds) in the population are alike,
only one sample is needed to give all
information about the population.
However, sampling units differ from
one another. Also, sampling units
comprising a particular sample may
differ from sample to sample and
this inherent variability from different
samples could give rise to different
results. The differences among
samples is called sampling variation.
Despite sampling variation, appropriate
conclusions about the population
should be reached. Thus, the
process of sampling must be guided
by statistical techniques such as the
use of efficient sampling designs and
appropriate choices of estimation
procedures (Snedecor and Cochran
1967).
A good sampling technique
should have the following features:
a) minimum sampling variation signifying
a high level of precision of
the estimate, b) unbiasedness implying
accuracy of the estimate or the
closeness of the expected values and
the true value of the estimate, and
c) feasibility and cost effectiveness
(Cochran 1977).
Components of a sampling
technique
A sampling technique consists of the
following (Steel and Torrie 1960),
Snedecor and Cochran 1967, Ostle
and Mensing 1975, Cochran 1977,
Gomez and Gomez 1984):
1. Definition of the target population
and choice of sampling unit
The sampling unit is the unit on
which actual measurement is to be
made. A good sampling unit must
be easy to identify, easy to measure,
and fairly uniform.
Examples
Target population Sampling unit
Seeds in a seed lot 1 seed
Plants in a plot
1 hill
Disease severity 1 leaf
in a plant
Rice yield in a plot 5-m 2 area
2. Sample size or the number of sampling
units taken from tha population
Sample size is governed by the
size of the variability among sampling
units and the desired degree of
precision of thc estimate. Sampling
variation, the variability among sampling
units, decreases as samplc size
increases.
3. Sampling design or the method (of
selecting the sample
To obtain a representative sample
of the population, the principle of
randomness should be applied.
Some commonly used sampling designs
applying this principle are:
Simple random sampling. Each unit
in the population is given an equal
chance of being selected into the
sample.
Example. Let the population be a
collection of seeds placed in a bag
(or a seed lot). Each seed in the bag
has an equal chance of being chosen
if a sample of size 100 is drawn randomly
from the bag.
Multistage random sampling. This is
characterized by a series of sampling
stages which involves several types
of sampling units. The selection of
the sample is done separately and
independently at each stage of sampling.