x Environment Interactions Oregon State 基因型与环境的相互作用俄勒冈州ppt课件.pptVIP

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x Environment Interactions Oregon State 基因型与环境的相互作用俄勒冈州ppt课件.ppt

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x Environment Interactions Oregon State 基因型与环境的相互作用俄勒冈州ppt课件

乙方有义务提供相应的执业资格证、执业印章等配合甲方工程招投标、承担的工程项目报建及建设施工过程中各类手续办理。 PBG 650 Advanced Plant Breeding Module 13: Breeding for Diverse Environments Genotype x Environment Interactions Genotype by environment interaction Genotypes respond differently across a range of environments i.e., the relative performance of varieties depends on the environment GXE, GEI, G by E, GE Genotype by environment interactions are common for most quantitative traits of economic importance Advanced breeding materials must be evaluated in multiple locations for more than one year MET = multi-environment trials P = G + E + GE Types of GEI Interaction may be due to: heterogeneity of genotypic variance across environments imperfect correlation of genotypic performance across environments noncrossover crossover The GEI challenge Environmental effect is the greatest, but is irrelevant to selection (remember 70-20-10 rule, E: GE: G) Many statistical approaches consider all of the phenotypic variation (i.e., means across environments), which may be misleading Need analyses that will help you to characterize GEI GE Interaction is not merely a problem, it is also an opportunity (Simmonds, 1991). Specific adaptations can make the difference between a good variety and a superb variety The GEI challenge Some environmental variation is predictable can be attributed to specific, characteristic features of the environment e.g., soil type, soil fertility, plant density Some variation is unpredictable e.g., rainfall, temperature, humidity Questions a breeder may ask How do I choose suitable environments for testing? How do I allocate resources (number of testing sites vs replicates within sites)? In general, increasing environments does more to reduce the standard error of genotype means than increasing replications ? Conventional ANOVA Ratios of Sums of Squares (SS) can be used to estimate the contribution of interactions to the total SS Can also estimate variance components due to GXE Mixed Models for anal