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

SUMMARYData from uniformity trials on healthy and diseased wheat and oat crops showed that the coefficient of variation for yield decreased as plot size increased and became nearer to square in shape. Infection with Septoria leaf blotch of oats and powdery mildew of wheat did not appear to affect yield variability. Plots larger than rod row size (where 16 ft of the centre row of 3 rows is harvested) are recommended to detect differences of 10 per cent in yield between two treatments.

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Non-sward densities for the assessment of yield in Italian ryegrass: II. Convenient plot and block size and shape

The Journal of Agricultural Science ◽

10.1017/s0021859600010923 ◽

1968 ◽

Vol 70 (2) ◽

pp. 105-108 ◽

Cited By ~ 1

Author(s):

F. England

Keyword(s):

Block Size ◽

Italian Ryegrass ◽

The Other ◽

Size And Shape ◽

Plot Size ◽

The Mean ◽

Uniformity Trials

SUMMARYTwo uniformity trials were carried out, one using S. 22 and the other Irish Italian ryegrass. In both trials the plants were grown at 6 in spacing and were harvested in basic units of 1 yd. If no allowance was made for guard rows the smallest plots were the most efficient in that they required a smaller total area of ground and fewer plants to detect a specified difference. For comparative purposes, the size of trial required to detect a difference of 7% of the mean was used. Allowing for 1 guard row round each plot, 2 yd plots were as efficient as those of 1 yd and had the advantage of requiring fewer replications. The effects of plot and block shape were considerable. In general long narrow plots in short wide blocks were more efficient. The choice of plot and block shape is most important. For a given plot size a poor shape may be less than half as efficient as a good one.

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Field Plot Technique Studies with Flue‐Cured Tobacco. I. Optimum Plot Size and Shape 1

Agronomy Journal ◽

10.2134/agronj1963.00021962005500020033x ◽

1963 ◽

Vol 55 (2) ◽

pp. 197-199 ◽

Cited By ~ 1

Author(s):

Julian W. Crews ◽

Guy L. Jones ◽

D. D. Mason

Keyword(s):

Field Plot ◽

Size And Shape ◽

Plot Size ◽

Field Plot Technique

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Automating Uniformity Trials to Optimize Precision of Agronomic Field Trials

Agronomy ◽

10.3390/agronomy11061254 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1254

Author(s):

Marcus Jones ◽

Marin Harbur ◽

Ken J. Moore

Keyword(s):

Web Application ◽

Unit Area ◽

Field Trials ◽

State University ◽

Iowa State University ◽

Plot Size ◽

Maize Field ◽

Process Uniformity ◽

Field Plots ◽

Uniformity Trials

Plot size has an important impact on variation among plots in agronomic field trials, but is rarely considered during the design process. Uniformity trials can inform a researcher about underlying variance, but are seldom used due to their laborious nature. The objective of this research was to describe variation in maize field trials among field plots of varying size and develop a tool to optimize field-trial design using uniformity-trial statistics. Six uniformity trials were conducted in 2015–2016 in conjunction with Iowa State University and WinField United. All six uniformity trials exhibited a negative asymptotic relationship between variance and plot size. Variance per unit area was reduced over 50% with plots 41.8 m2 in size and over 75% when using a plot size >111.5 m2 compared to a 13.9 m2 plot. Plot shape within a fixed plot size did not influence variance. The data illustrated fewer replicates were needed as plot size increased, since larger plots reduced variability. Use of a Shiny web application is demonstrated that allows a researcher to upload a yield map and consider uniformity-trial statistics to inform plot size and replicate decisions.

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Problems in the use of microplots for assessing the fate of urea applied to flooded rice

Australian Journal of Agricultural Research ◽

10.1071/ar9880351 ◽

1988 ◽

Vol 39 (3) ◽

pp. 351 ◽

Cited By ~ 4

Author(s):

ACF Trevitt ◽

JR Freney ◽

JR Simpson ◽

WA Muirhead

Keyword(s):

Solar Radiation ◽

Preliminary Analysis ◽

Ammonia Volatilization ◽

Urea Hydrolysis ◽

Incident Solar Radiation ◽

Size And Shape ◽

Flooded Rice ◽

Ph Values ◽

Plot Size ◽

Heat Penetration

The effects of differences in size of microplot and type of enclosure on the floodwater parameters determining ammonia volatilization were studied. The results show that the use of enclosures can retard urea hydrolysis, suppress the maximum daytime pH values (an effect which is cumulative over a number of days), and significantly reduce the potential for ammonia volatilization. These effects are the consequence of lowered light (and heat) penetration in the enclosed area due to shading of the floodwater by the enclosure walls. The magnitude of these effects varies with plot size and shape, and the material used for construction of the plot wall. A preliminary analysis suggests that, if errors due to shading are acceptable when 90% or more of the incident solar radiation always penetrates to the enclosed floodwater, then square plots with opaque walls must be at least 1.2 m along a side and cylindrical plots must be at least 1.2 m in diameter when wall height is 0.1 m above the floodwater.

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Basic experimental unit and plot sizes for fresh matter of sunn hemp

Ciência Rural ◽

10.1590/0103-8478cr20170660 ◽

2018 ◽

Vol 48 (5) ◽

Cited By ~ 1

Author(s):

Giovani Facco ◽

Alberto Cargnelutti Filho ◽

André Lavezo ◽

Denison Esequiel Schabarum ◽

Gabriela Görgen Chaves ◽

...

Keyword(s):

Experimental Unit ◽

Fresh Matter ◽

Crotalaria Juncea ◽

Evaluation Period ◽

Plot Size ◽

Maximum Curvature ◽

Sunn Hemp ◽

Sowing Season ◽

Uniformity Trials

ABSTRACT: This study aimed to verify the influence of the basic experimental unit (BEU) size in the estimation of the optimum plot size to evaluate the fresh matter of sunn hemp (Crotalaria juncea L.) using the modified maximum curvature method. The fresh matter of sunn hemp was evaluated in uniformity trials in two sowing season in flowering. In each sowing season, 4,608 BEUs of 0.5×0.5m (0.25m2) were evaluated and 36 BEU plans were formed with sizes from 0.25 to 16m2. In each evaluation period for each BEU plan, using fresh matter data, optimum plot size was estimated through the modified maximum curvature method. Estimation of the optimum plot size depends on the BEU size. Assessing fresh matter in BEUs that are as small as possible is recommended in order to use it to estimate the optimum plot size.

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