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- W2044274335 abstract "Summary Growth curves fitted to factorial data can be modelled using an extrinsic time variate or using the mean responses within the levels of a subset of factors. Where factors can be partitioned into a set of ‘treatment’ factors and a set of ‘environment’ factors, fitting growth curves to the mean effects of environments allows the effects of treatments to be assessed relative to a uniform background growth rate. This leads to a test of a null hypothesis of equal treatment effects in all environments, given that the mean growth rate and stage of development in all environments is equal. The approach is exemplified using data from a glasshouse tomato crop experiment testing variety, nutrient and sowing date factors. Variety and nutrient treatment effects were of direct interest but sowing dates were intended to generalize results by providing a range of growing environments. Treatment effects are analysed by modelling running cumulative yield totals by growth curves and regressing variety and nutrient growth variates on the mean growth variate within each sowing date. In the discussion the case of more than one environmental factor is considered." @default.
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- W2044274335 date "1989-02-01" @default.
- W2044274335 modified "2023-09-25" @default.
- W2044274335 title "Growth curve analysis for treatments-by-environments interaction effects" @default.
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- W2044274335 doi "https://doi.org/10.1017/s0021859600084057" @default.
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