A study on the assessment of two-dimensional barcodes on soil sample bags was conducted by former graduate student Jodi M. Gessner. We used the data she collected to further investigate what is the best bar code label to be used on soil samples so it is still able to be read through different damaging environments. The data that has been previously presented on correction levels 4,5 and 6 and was analyzed on 765 samples.

1. ANALYSIS OF DAMAGED BARCODES
Jennifer Das, Steven Hostetler, Faisal Al-Khalidi, Christopher White, Michael Brockly, Mathias Sutton, Stephen Elliott
Overview
A study on the assessment of two-dimensional barcodes on soil sample bags was conducted by former graduate student
Jodi M. Gessner. We used the data she collected to further investigate what is the best bar code label to be used on soil
samples so it is still able to be read through different damaging environments. The data that has been previously presented
on correction levels 4,5 and 6 and was analyzed on 765 samples.
Problem
Determining whether symbology, error correction, location or a combination of the three affects the failure rate of the
barcode’s ability to be scanned.
Initial Data
SYMBOLOGY
ERROR
CORRECTION
LOCATION
TOTAL
ATTEMPT
TOTAL
PASS
TOTAL
FAIL
% PASS % FAIL
LABEL 1 QR CODE LOW FRONT 145 133 12 91.72% 8.28%
LABEL 2 QR CODE LOW SIDE 145 105 40 72.41% 27.59%
LABEL 3 QR CODE MEDIUM FRONT 150 141 9 94.00% 6.00%
LABEL 4 QR CODE MEDIUM SIDE 150 136 14 90.67% 9.33%
LABEL 5 QR CODE HIGH FRONT 140 123 17 87.86% 12.14%
LABEL 6 QR CODE HIGH SIDE 150 117 33 78.00% 22.00%
LABEL 7 PDF417 4 FRONT 150 145 5 96.67% 3.33%
LABEL 8 PDF417 4 SIDE 145 136 9 93.79% 6.21%
LABEL 9 PDF417 5 FRONT 145 145 0 100.00% 0.00%
LABEL 10 PDF417 5 SIDE 150 141 9 94.00% 6.00%
LABEL 11 PDF417 6 FRONT 140 140 0 100.00% 0.00%
LABEL 12 PDF417 6 SIDE 145 131 14 90.34% 9.66%
LABEL 13 DATA MATRIX NONE FRONT 145 130 15 89.66% 10.34%
LABEL 14 DATA MATRIX NONE SIDE 140 128 12 91.43% 8.57%
Procedures
 Null hypothesis
 The proportion of defects for each label is
equal.
 Alternate hypothesis
 At least one proportion is not equal to the rest of
the data.
 From the initial data, the chi-square test was used to
accept or reject the null hypothesis.
Chi-square test:
Chi-square (Observed value) 129.492
Chi-square (Critical value) 22.362
DF 13
p-value < 0.0001
alpha 0.05
 As the computed p-value is lower than the
significance level alpha=0.05, we rejected the null
hypothesis and accepted the alternative hypothesis.
 The Marascuillo procedure was performed to
compare each of the barcodes to one another.
 The p-values were contrasted and then compared to
the critical range to find out if there is a significant
difference in the proportion of failed scans to total
scans for each barcode.
 There were 91 different comparisons
performed, 9 of which showed significance.
p1 0.082759
p2 0.275862
p3 0.06
p4 0.093333
p5 0.121429
p6 0.22
p7 0.033333
p8 0.062069
p9 0
p10 0.06
p11 0
p12 0.096552
p13 0.103448
p14 0.085714
P-values
Conclusion
After performing the Marscuillo procedure, we found nine
different combinations of symbology, error correction, and
locations that are significant. These combinations each
show a higher proportions of defects. We can’t state that p2
and p6 are problematic independently, but when contrasted
with other variables, they seem to negatively affect the
barcode readability.
Contrast Value Critical value Significant
|p(p2) - p(p3)| 0.216 0.198 Yes
|p(p2) - p(p7)| 0.243 0.189 Yes
|p(p2) - p(p8)| 0.214 0.199 Yes
|p(p2) - p(p9)| 0.276 0.176 Yes
|p(p2) - p(p10)| 0.216 0.198 Yes
|p(p2) - p(p11)| 0.276 0.176 Yes
|p(p6) - p(p7)| 0.187 0.174 Yes
|p(p6) - p(p9)| 0.220 0.160 Yes
|p(p6) - p(p11)| 0.220 0.160 Yes
Significant Comparisons
QR Code PDF417 Data Matrix