Paper · 2014 · Fayoum Journal of Agricultural Research and Development /Fayoum Journal of Agricultural Research and Development

UTLIZATION OF UNIFORMITY TRIALS TO ESTIMATE THE OPTIMUM PLOT SIZE AND SHAPE AND THE NUMBER OF REPLICATIONS IN WHEAT YIELD TRIALS

S.K.A. Ismail; Sahar A. Farag

11
claims
28
verbatim quotes
0
citations
2
research areas
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Open access · cc-by

Abstract

In the present work, two uniformity trials were carried out during thefirst and the second winter seasons of 2011/2012 and 2012/2013 in theExperimental farm Demo, Faculty of Agriculture, Fayoum University. Themain objectives were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial. The cultivated area of each field trial was divided into 12 strips;each of which consisted of 100 rows, 0.2 m width and 3.0 m long. Twostatistical methods including soil variability index and maximum curvaturewere used to estimate the optimum plot size and shape using the yield data of1200 basic units (each of 0.6 m2). The data were subjected to two proceduresof statistical analysis to estimate the optimum plot size, when the cost ofconducting the experiment is not taken into consideration and to evaluate theeffect of changing the plot shape on the variability. The first statistical methodwas that of maximum curvature which is based on the exponentialrelationship between plot size and the coefficient of variability. The secondmethod was that developed by smith’s method (1938). Bartlett's test forhomogeneity of variances, as outlined by Steel and Torrie (1980), was usedto study the effect of changing plot shape. The obtained results could besummarized as follows: Increasing the plot size decreased the variance perbasic unit and the coefficient of variability. However, the reduction was not inproportion with the increase in plot size. The index of soil variability rangedfrom 0.6433 to 0.6018 as an average for the 1st and the 2nd seasons,respectively. The relationship between the coefficient of variability (C.V.)and plot size (X) were mathematically expressed by the following equationC.V. = 19.21 X-0.2595 for the 1st season and C.V. = 19.60 X – 0.2725 for the 2ndone. Accordingly, using the soil variability index, the optimum plot size was2 basic units (1/3500 fed.) for the two seasons, while it was 4 basic units(1/1750 fed.) in both seasons when the maximum curvature method wasapplied. The required number of replications for the optimum plot size usingSmith method detecting a 15% difference among treatment means varied 13and 14 in the 1st and the 2nd seasons, respectively. But, for detecting a 20%difference among treatment means, 7 replications in the 1st season and 8replications in the 2nd one were found necessary. Optimum plot size estimatedusing the maximum curvature method detecting a 15% difference amongtreatment means varied 7 and 8 in the 1st and the 2nd seasons, respectively. But, for detecting a 20% difference among treatment means, 4 replications inthe 1st and 2nd season's one were found necessary. Generally, the plot shapedid not affect on the precision of wheat yield trial in most cases in the twogrowing seasons.

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Claims 11

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The soil variability index gave an optimum wheat plot size of 2 basic units (1/3500 fed.).

Outcome
optimum plot sizee1
Value
2 basic units (1/3500 fed.)e1

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e1

“using the soil variability index, the optimum plot size was2 basic units (1/3500 fed.) for the two seasons”

✓ located verbatim in the source · abstract, characters 1870–1976 · show in text ↑
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The maximum curvature method gave an optimum wheat plot size of 4 basic units (1/1750 fed.).

Outcome
optimum plot sizee1
Value
4 basic units(1/1750 fed.)e2
Qualifier
maximum curvature methode2

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e1

“using the soil variability index, the optimum plot size was2 basic units (1/3500 fed.) for the two seasons”

✓ located verbatim in the source · abstract, characters 1870–1976 · show in text ↑
e2

“4 basic units(1/1750 fed.) in both seasons when the maximum curvature method wasapplied”

✓ located verbatim in the source · abstract, characters 1991–2078 · show in text ↑
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Smith method needed 13 and 14 replications, in the 1st and 2nd seasons, to detect a 15% difference among treatment means.

Outcome
number of replicationse3
Value
13and 14e3
Qualifier
detecting a 15% difference among treatment meanse3

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e3

“The required number of replications for the optimum plot size usingSmith method detecting a 15% difference among treatment means varied 13and 14 in the 1st and the 2nd seasons”

✓ located verbatim in the source · abstract, characters 2080–2255 · show in text ↑
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Smith method needed 7 replications in the 1st season and 8 in the 2nd season to detect a 20% difference among treatment means.

Outcome
replicationse4
Value
7 replications in the 1st season and 8replications in the 2nd onee4
Qualifier
detecting a 20% difference among treatment meanse4

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e4

“for detecting a 20% difference among treatment means, 7 replications in the 1st season and 8replications in the 2nd one were found necessary”

✓ located after whitespace/quote normalisation · abstract, characters 2276–2415 · show in text ↑
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The maximum curvature method needed 7 and 8 replications, in the 1st and 2nd seasons, to detect a 15% difference among treatment means.

Outcome
replicationse3
Value
7 and 8e5
Qualifier
maximum curvature methode5

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e3

“The required number of replications for the optimum plot size usingSmith method detecting a 15% difference among treatment means varied 13and 14 in the 1st and the 2nd seasons”

✓ located verbatim in the source · abstract, characters 2080–2255 · show in text ↑
e5

“using the maximum curvature method detecting a 15% difference amongtreatment means varied 7 and 8 in the 1st and the 2nd seasons”

✓ located verbatim in the source · abstract, characters 2444–2572 · show in text ↑
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

The maximum curvature method needed 4 replications, in the 1st and 2nd seasons, to detect a 20% difference among treatment means.

Outcome
replicationse6
Value
4 replicationse6
Qualifier
maximum curvature methode5

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e5

“using the maximum curvature method detecting a 15% difference amongtreatment means varied 7 and 8 in the 1st and the 2nd seasons”

✓ located verbatim in the source · abstract, characters 2444–2572 · show in text ↑
e6

“for detecting a 20% difference among treatment means, 4 replications inthe 1st and 2nd season's one were found necessary”

✓ located verbatim in the source · abstract, characters 2593–2713 · show in text ↑
Observationobservedoriginal resultmeasured

Claim · model-written summary

The index of soil variability ranged from 0.6433 to 0.6018 across the two seasons.

Outcome
index of soil variabilitye7
Value
0.6433 to 0.6018e7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e7

“The index of soil variability rangedfrom 0.6433 to 0.6018 as an average for the 1st and the 2nd seasons”

✓ located verbatim in the source · abstract, characters 1519–1622 · show in text ↑
Associationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

In the 1st season, the coefficient of variability was related to plot size (X) by C.V. = 19.21 X-0.2595.

Treatment
plot size (X)e6
Outcome
coefficient of variabilitye6
Value
C.V. = 19.21 X-0.2595e5

Not reportedDirection

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e5

“C.V. = 19.21 X-0.2595 for the 1st season”

✓ located verbatim in the source · abstract, characters 1772–1812 · show in text ↑
e6

“The relationship between the coefficient of variability (C.V.)and plot size (X) were mathematically expressed”

✓ located verbatim in the source · abstract, characters 1637–1746 · show in text ↑
Associationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

In the 2nd season, the coefficient of variability was related to plot size (X) by C.V. = 19.60 X – 0.2725.

Treatment
plot size (X)e6
Outcome
coefficient of variabilitye6
Value
C.V. = 19.60 X – 0.2725e5

Not reportedDirection

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e5

“C.V. = 19.60 X – 0.2725 for the 2ndone”

✓ located verbatim in the source · abstract, characters 1817–1855 · show in text ↑
e6

“The relationship between the coefficient of variability (C.V.)and plot size (X) were mathematically expressed”

✓ located verbatim in the source · abstract, characters 1637–1746 · show in text ↑
Associationobservedoriginal resultno effectmeasured

Claim · model-written summary

Plot shape did not affect the precision of wheat yield trials in most cases in the two seasons.

Treatment
plot shapee7
Outcome
precision of wheat yield triale7
Direction
did not affecte7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e7

“the plot shapedid not affect on the precision of wheat yield trial in most cases in the twogrowing seasons”

✓ located verbatim in the source · abstract, characters 2726–2832 · show in text ↑
Associationobservedoriginal resultmeasured

Claim · model-written summary

Increasing plot size decreased the variance per basic unit and the coefficient of variability of wheat yield trials.

Treatment
plot sizee6
Outcome
variance perbasic unit and the coefficient of variabilitye6
Direction
decreasede6
Qualifier
not inproportion with the increase in plot sizee7

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“were to estimate the optimum plot size, plot shape andnumber of replicates for wheat yield traits using the variety Sakha 93 as plantmaterial”

✓ located verbatim in the source · abstract, characters 225–366 · show in text ↑
e6

“Increasing the plot size decreased the variance perbasic unit and the coefficient of variability”

✓ located verbatim in the source · abstract, characters 1345–1441 · show in text ↑
e7

“However, the reduction was not inproportion with the increase in plot size”

✓ located verbatim in the source · abstract, characters 1443–1517 · show in text ↑