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