Variability in seed testing results, factors affecting the variability, application and use of tolerance tables and seed standards and Sequential sampling

1. Presented by,
Usha Pedireddi
Scientist, DSST

2.  As a rule, the seed testing results must be accurate and
reproducible within comparable limits.
 However, the results obtained at two different seed testing
laboratories may vary, although the same rules are followed.
 Various factors affecting variability are as follows:
1. Heterogeneity of seed lots.
2. Sampling and Equipment.
3. Experience of seed analyst.
4. Experimental conditions
Testing method itself
Lab environment etc…

3. Heterogeneity of seed lots:
 This is the most important cause of variation.
 No two samples taken from the same container or the same lot
of seeds are likely to be identical.
 Inadequate mixing or blending interferes with random
distribution and therefore lowers the chances of getting a
representative sample from seed lot.
 Tendency towards stratification of particles due to varying
densities during filling, stacking and transportation of seed
containers can lead to sample variations.

4. Heterogeneity is calculated by using the formula
H= V%W -1
V=actual variance of the samples in respect of the
attribute tested.
W=expected variance of the sample
W=x (100-x) % n
X= measurement in any bag sample of the attribute under
test, e,g. purity per cent, germination per cent.
X= mean of x value (=Σx % n).
n= number of bag samples taken.
V= n(Σx2
) - (Σx)2
%n(n-1)

5.  Also, genetic heterogeneity, variability in soil and
degree of pest and disease incidence during seed
maturation combined with variations in operations
during harvesting, drying and conditioning.
 These are some of the major causes of heterogeneity
in a seed lot.
 Utmost care in seed sampling is therefore of crucial
importance.

6.  Detective sampling, substandard equipment and
uncontrolled differences in the application of test
procedures are the other important sources of
variation in test results.
 If larger the sample size, smaller the random-
sampling variation.

7.  Expertise of analysts making and/or reporting the test
results vary. This may also lead to variation.
 It should be the endeavor of all seed analysts in the
seed laboratory to stick to the procedure prescribed in
the rules of seed testing.
 This would help in bringing uniformity, accuracy and
reproducibility in test results

8. The Seed Standards consists of the following:
a) The minimum percentage of pure seed, and weed
seeds have been prescribed for ensuring good
physical purity of seeds.
b) The maximum permissible limits for objectionable
weeds have been prescribed to ensure relative
freedom from these very harmful weed species.
c) The maximum permissible limits for seeds infected
by seed-borne diseases have been fixed to ensure
good seed health.

9. d) The maximum permissible limits of the seeds of
other distinguishable varieties have been prescribed
to ensure minimum standards of genetic purity.
In the case of hybrid seeds, produced by methods
employing hand pollination, or in certain crops the
genetic purity verification requirements through a
grow-out test have also been prescribed to ensure
minimum genetic purity standards.

10. In case of seedless watermelon, determination of
ploidy level by ploidy test has been prescribed to
ensure seedless watermelon.
e) The maximum permissible limits for moisture
content have been prescribed for the safe storage of
seeds.

11. Crop Pure
Seed
Min.
(%)
Inert
matter
(%)
Maximum permissible level Minimum
Permissible
Limit
Germin
ation
count
days
Germ
inatio
n
Moisture
O.C.S.
(No.s/k
g)
O.D.V
(No.s/kg)
O.W.S.
(No.s/k
g)
F C F C F C CB VP 1st 2n
d
Paddy 98 2 10 20 0.05 0.2 10 20 80 13 8 5 14
Jowar 98 2 5 10 10 20 5 10 75 12 8 4 10
Maize
Hybrids
98 2 - 10 - 10 - - 90 12 8 - -
Single
crosses
98 2 5 - 5 - - - 80 12 8 4 7
Inbreds,
compos
98 2 5 - 5 - - - 80 12 8 - -

12. Bajra 98 2 10 20 - - 10 20 75 12 8 3 7
Redgram 98 2 5 10 10 20 5 10 75 9 8 4 10
Greengram 98 2 5 10 10 20 5 10 75 9 8 3 7
Blackgram 98 2 5 10 10 20 5 10 75 9 8 5 8
Bengalgram 98 2 - 5 5 10 - - 85 9 8 - -
Cowpea 98 2 - 10 5 10 - 10 75 9 8 - -
Castor 98 2 - - 5 10 - - 70 8 5 14 -
Groundnut 96 4 - -- - - - - 70 9 5 - -
Sunflower 98 2 - - - - 5 10 70 7 7 - -
Safflower 98 2 5 10 - - - - 80 9 7 4 14
Sesamum 97 3 10 20 10 20 10 20 80 9 5 3 6
Soybean 98 2 - 10 10 40 5 10 70 12 7 5 8
Cotton
hybrids
98 2 5 10 - - 5 10 75 10 6 4 12

13. Cotton
varieties
98 2 5 10 - - 5 10 70 10 6 4 12
Jute 97 3 10 20 10 20 10 20 80 9 7 3 7
Bhendi 99 1 - 5 10 20 - - 65 10 8 4 21
Brinjal 98 2 - - - - - - 70 8 6 4 14
Tomato 98 2 5 10 - - - - 70 8 6 5 14
Capsicu
m &
chilli
98 2 5 10 - - 5 10 60 8 6 7 14
Cluster
bean
98 2 10 20 10 20 - - 70 9 8 4 14
Bottlega
urd
98 2 - - - - - - 60 7 6 4 14
Waterme
lon
98 2 - - 5 10 - - 60 7 6 4 14
Mestha 98 2 10 20 - - - - 75 10 8 - -
Sunhemp 98 2 10 20 - - - - 80 9 8 - -

14. Definition:
A tolerance is the maximum difference between two test results.
When carrying out more than one purity or germination test, using
different replicates or samples of the same lot of seed one would
not expect the result of each test to be exactly same.
Such variation between individual tests of observations made on
biological material & to a certain extent is quite acceptable.
The difference is may be due to errors in sampling and/or testing.

15. The tolerance limits vary depending on:
The type of test (e.g. purity or germination)
The type of seed (e.g. chaffy vs non-chaffy seed)
The number of tests
The level of purity or germination

16. : Application of Tolerances:
The various tolerances used in connection with the
rules for seed testing are:
1. Comparison of two tests of the same submitted
sample in the laboratory.
2. Comparison of two tests of the same submitted
sample in different laboratories.
3. Comparison of two tests in the same laboratory of
two different submitted samples from the same lot
4. Comparison of tests in different laboratories of two
different samples from the same lot.

17. Procedure of using Tolerances:
Calculate the average of two results to be compared(only 2 results –
purity test, 4 replicate results-germination test)
Find the average value in the first column and the tolerance will be
found opposite in the column corresponding to the type of test (e.g.
in purity tests chaffy vs non-chaffy ;or the number of tests) (in
germination tests 3or 4 replicates).
If the difference between any 2 tests is greater than the tolerance
shown in the table, the results are out of tolerance.

22. Importance:
 It is important to mention here that the tolerances should not
be confused with allowances (permissible limits) for labeling
of seeds.
 The tolerances are provided to take care of the unavoidable
variation in seed testing results and they are not to be applied
prior to labeling by adding them to the results found by test.
 The tolerance should never be used for the purpose of
permitting labelling to show higher quality than is actually
found by the test.

23. Definition:
 A sampling plan in which an undetermined number of samples
are tested one by one, accumulating the results until a decision
can be made.
 Sequential sampling is a non-probability sampling technique
wherein the researcher picks a single or a group of samples in
a given time interval, conducts his study, analyzes the results
then picks another group of samples if needed and so on.
 This sampling technique gives the researcher limitless chances
of fine tuning his research methods and gaining a vital insight
into the study that he is currently pursuing.

24.  If we are to consider all the other sampling techniques
in research, we will all come to a conclusion that
the experiment and the data analysis will either boil
down to accepting the null hypothesis or disproving the
null hypothesis while accepting the alternative
hypothesis.
 In sequential sampling technique, there exists another
step, a third option.

25.  The researcher can accept the null hypothesis, accept
his alternative hypothesis, or select another pool of
samples and conduct the experiment once again.
 This entails that the researcher can obtain limitless
number of samples before finally making a decision
whether to accept his null or alternative hypothesis.

26.  The researcher has a limitless option when it comes to sample
size and sampling schedule. The sample size can be relatively
small of excessively large depending on the decision making
of the researcher.
 Sampling schedule is also completely dependent to the
researcher since a second group of samples can only be
obtained after conducting the experiment to the initial group
of samples.
 As mentioned above, this sampling technique enables the
researcher to fine-tune his research methods and results
analysis.

27.  Due to the repetitive nature of this sampling method,
minor changes and adjustments can be done during the
initial parts of the study to correct and done the
research method.
 There is very little effort in the part of the researcher
when performing this sampling technique.
 It is not expensive, not time consuming and not
workforce extensive.

28.  This sampling method is hardly representative of the
entire population.
 Its only hope of approaching representativeness is
when the researcher chose to use a very large sample
size significant enough to represent a big fraction of the
entire population.
 The sampling technique is also hardly randomized.

29.  This contributes to the very little degree
representativeness of the sampling technique.
 Due to the aforementioned disadvantages, results from
this sampling technique cannot be used to create
conclusions and interpretations pertaining to the
entire population.

30.  Poorly-, intermediate- and well-mixed batches of lucerne (Medicago sativa) and rape
seed were tested for heterogeneity with respect to indicator seeds (seeds identical to
the principal seed but marked for easy detection).
 Lucerne seed was also tested for heterogeneity with respect to seeds of curled dock
(Rumex crispus), wild mustard (Brassica kaber) and prostrate pigweed (Amaranthus
graecizans).
 Two controllable variables were critical to the outcome of a heterogeneity test. Small
numbers in either category can lead to wrong declarations of homogeneity in lots that
are truly heterogeneous.
 It is suggested that indicator seed heterogeneity test results can be used as a reliable
predictor of heterogeneity.
Niffenegger et.al.
 Title: Factors affecting the outcome and usefulness of seed heterogeneity tests.
Source: Journal of Seed Technology. 1989. 13: 2, 150-168. 21 ref.

31. conclusion
In practice, even if bulking and mixing are done carefully it is
virtually impossible to obtain a completely homogeneous seed lot, so
sampling variation can occur. For this tolerances are fixed for each
attribute( to be tested) which will ensure the acceptance of certain
samples up to the level tolerance. So that the seed analyst should
take utmost care during seed testing at every stage will the reduce
the variation in seed testing results.