Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246494
Title: Cross prediction studies on spring barley
Author: Tapsell, Christopher Robert.
ISNI:       0000 0001 3499 1963
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 1983
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Abstract:
The genetical and environmental control of a number of characters of agronomic importance in barley has been investigated by triple test cross (TTC) and linear model-fitting analyses. Additive and dominance genetic effects are observed for height, maturity, yield and yield component characters with the exception of tiller number, which was found to be almost totally controlled by environmental factors. Epistasis was found to be important only for grain number, although it was observed in other characters (notably neck length). Other analyses on the same data set have also been made to detect the presence of genotype x environment interactions and linkage in the above characteristics, together with phenotypic and genotypic correlations between them. Only height at harvest and 1000 grain weight appeared to have potential for early generation selection. As a result, efficient prediction of the potential of a particular cross for the majority of characters of agronomic importance is shown to be necessary and important. The second part of this work involved testing the effectiveness of cross-prediction methods based on the results of the genetical analyses. It is shown that the potential of a cross to produce superior inbred lines can be successfully predicted from TTC and model-fitting analyses. The prediction methods have been shown to be successful in identifying the cross from a number of crosses with the greatest potential in respect of both single characters and pairs of characters. It is shown that yield itself can be studied successfully in this way, as well as those characters with high heritability such as height and 1000 grain weight. Furthermore it is shown that an estimate of the additive genetic variance necessary for making the predictions, of similar accuracy to that obtained from the TTC, can be Je<-ive
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.246494  DOI: Not available
Keywords: Biometrics Biomedical engineering Biochemical engineering Agronomy Plant diseases Horticulture
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