A new method for the analysis of germination and emergence data of weed species

Due to their peculiar characteristics, seed germination and emergence assays may pose problems for data analysis, due to non-normal error distribution and serial correlation between the numbers of seeds counted on different dates from the same experimental unit (Petri dish, pot, plot). Furthermore, it is necessary to consider viable seeds that have not germinated/emerged at the end of an experiment (censored observations), as well as late germination/emergence flushes, that relate to genotypic differences within natural occurring seed populations. Traditional methods of data analysis may not be optimal for dealing with these problems. Therefore, survival analysis may represent an appropriate alternative. In this analysis, the time course of germination/emergence is described by using a non-parametric step function ('germination function') and the effect of factors and covariates on 'germination functions' is assessed by Accelerated Failure Time regression and expressed in terms of 'time ratios'. These parameters measure how a change in the explanatory variables changes (prolongs/shortens) the time to germination of a seed lot. This paper presents four examples of the application of survival analysis on seed germination/emergence studies. Results are discussed and compared with those obtained with more traditional techniques.