Implications Concerning the Frequency of Control Plots in Wheat Breeding Nurseries

Briggs, K. G.; Shebeski, L. H.

doi:10.4141/cjps68-027

Cited by 27 publications

(21 citation statements)

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“…Baker and McKenzie (1967) concluded that there is no advantage to the use of control plots unless f;mith's coemcient of soil heterogeneity (Smith 1938 Knott (1972) (unadjusted) and Ve (moving mean) in Table 1). In all four of these trials the correlation coefficients are much lower than those reported by Briggs and Shebeski (1968). …”

Section: Introductioncontrasting

confidence: 68%

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Use of Moving Means in Wheat Yield Trials

Townley‐Smith¹,

Hurd²

1973

Can. J. Plant Sci.

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Section: Introductioncontrasting

confidence: 68%

“…Briggs and Shebeski (1968) (1935). Briggs and Shebeski (1968) (J!lV 1973) .001) between F" yields expressed as a percentage of the adjacent control and the means of their respective li5's.…”

Section: Introductionmentioning

confidence: 99%

Use of Moving Means in Wheat Yield Trials

Townley‐Smith¹,

Hurd²

1973

Can. J. Plant Sci.

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“…The results of this study agree in general with those of similar studies concerning grain yield (BRIGGS & SHEBESKI, 1968). In both studies a high correlation was obtained for adjacent plots, which rapidly decreased as the distance between the plots increased.…”

Section: Number Of Control Plots In Screening Nurseriessupporting

confidence: 82%

“…Answers to a questionnaire sent to wheat breeders all over the world indicated that the frequency of control plots in screening nurseries for grain yield varies from one in every third plot to one in 200 plots, with an average of about one control in every 50 plots (BRIGGS ~ SHEBESKI, 1968). The same authors using the Triticurn aestivum wheat var.…”

Section: Introductionmentioning

confidence: 99%

Frequency of control plots in screening nurseries for protein content

Hadjichristodoulou

Della

1976

Euphytica

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Correlation coefficients were calculated in two seasons, between protein content of control plots of "Kyperounda' durum wheat and 'Athenais" barley sown at distances of from 0.6 m to 68.4 m. Simple correlation coefficients were high (0.737, 0.710 and 0.311) and significant at the 1 ~ level of probability for plots 0.6 m apart, but decreased rapidly with increasing distances between plots. The correlation in four nurseries was significant for plots 7.2 m, 4.2m, 4.2 m and 1.8 m apart. It was concluded that a control plot provides a fairly good measure of the protein content of adjacent plots.

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“…This means that for the next step of selection the last 44 genotypes can be recommended. Briggs and Shebeski, 1967;Zimmerman and Harville, 1991;Brownie and Gumpertz, 1997;Martin, 1986;Gołaszewski, 1999Gołaszewski, , 2002. In another approach, to recognize the spatial variability of the environment (soil), check plots are distributed over all experimental units.…”

Section: Mejza and Marczyńska 2011)mentioning

confidence: 99%

Check plots in field breeding experiments

Mejza

2013

Biometrical Letters

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SUMMARYThis paper deals with the problems of selection in the early stages of a breeding program. During the improvement process, it is not possible to use an experimental design that satisfies the requirement of replicating all the treatments, because of the large number of genotypes involved, the small amount of seed and the low availability of resources. Hence unreplicated designs are used. To control the real or potential heterogeneity of experimental units, control (check) plots are arranged in the trial.There are many methods of using the information resulting from check plots. All of the usually applied adjusting methods for unreplicated experiments are appropriate for some specific structure of soil fertility. Their disadvantage is the fact that, before and also after the experiment, we usually do not know what a kind of soil structure is present in the experiment. Hence we cannot say which of the existing methods is appropriate for a given experimental situation. The method of inference presented below avoids this disadvantage. It is always appropriate, because of the fact that a trend of soil variability is identified and estimated. In the paper the main tool used to explore this information will be based on a response surface methodology. To begin with we will try to identify a response surface characterizing the experimental environments. We assume that observed yield (or another trait) results directly from two components, one of them due to soil fertility and the other due to the genotype effect. This means that difference between observed yield and forecast can be treated as the estimate of a genotype effect. The obtained response surface will then be used to adjust the observations for genotypes. Finally, the data so adjusted are used for inferences concerning the next stage of the breeding program. The theoretical considerations are illustrated with an example involving yields of spring barley.

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Implications Concerning the Frequency of Control Plots in Wheat Breeding Nurseries

Cited by 27 publications

References 0 publications

Use of Moving Means in Wheat Yield Trials

Use of Moving Means in Wheat Yield Trials

Frequency of control plots in screening nurseries for protein content

Check plots in field breeding experiments

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