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Check plots in field breeding experiments

100%

Mejza S. , Mejza I.

Biometrical Letters

2013

tom 50

nr 2

137-149

This 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.

Comparison of phenotypic and genetic selections in Scots pine (Pinus sylvestris L.) single tree plot half-sib progeny tests

63%

Kowalczyk J.

Dendrobiology

2005

tom 53

45-56

The study was carried out in three Scots pine (Pinus sylvestris L.) single tree plot half-sib progeny tests planted in 1984–86. Phenotypic selection was done in two ways: F about 0.5% to 1% of the total number of trees were chosen by the author on the basis of their appearance only, and Fbis on the basis of diameters at breast height and heights measurements and observations scored for individual trees. The best trees were selected on the basis of the index value weighing traits by their economic value. Genetic selection was performed based on both family index value (Wf) and tree index value (WT), weighing traits by heritability and economic value. This was done in four different ways: (A) The best trees were selected only on the basis of their index value (WT) with no attention paid to the family; (B) About 10 to 12 trees were selected in the best families, (both (Wf) and (WT) were taken into consideration); (C) The best 30% of the families (Wf) were selected and then equal numbers of best trees were selected (WT); (D) The same number families (Wf) as in the phenotypic selection were selected and within these families equal numbers of best trees (WT). The number of trees that were genetically selected was always the same as the number of phenotypically selected ones (selection type F). The selections were compared using a calculated expected genetic gain and the relative loss of effective population size. As expected, phenotypic selection resulted in the lowest genetic gain. Phenotypic selection generally conserved genetic variability, while genetic selection reduced it, especially when genetic gain was maximised. Phenotypic selection type F generally identifies the good families. The agreement of genetic selection with the phenotypic selection is low (0% to 19%) at the individual tree level. This is slightly better with phenotypic selections using measurements data (Fbis). Phenotypic selection is recommended only where information concerning pedigrees is not available. It can provide a simple and cheap way of obtaining material for future selection. Genetic selection method (A) where best trees were selected without any restrictions provided highest genetic gain and cause the greatest loss of genetic diversity.