Statistical modeling of sugar cane potential bud sprouting within the context of a 3x3x2 factorial experiment

the aim of this study was to model sugarcane potential bud sprouting temporal evolution within the context of a 3x3x2 factorial experiment. statistical modeling was accomplished by means of a three-parameter logistic model using nonlinear mixed models. the trial was carried out with seed cane from three varieties (lcp 85-384, cp 65-357 and cp 48-103), considering three harvesting dates (may, august, and october) and two seed cane origins (micropropagation and hot water treatment). experimental units were distributed in a 3x3x2 completely randomized factorial arrangement with two replicates. the number of sprouts was recorded from the day after plantation up to the 21st day. the selection of effects associated with a particular parameter was made by means of backward selection. once the significant effects were selected, the need for the corresponding random effect was tested. the same procedure was followed with the rest of the parameters. heteroscedasticity was corrected using a power variance function and autocorrelation of residuals was included as an order 1 autoregressive model. after statistical modeling, the conclusion to be drawn is that the methodology of nonlinear mixed models is an adequate and powerful tool when analyzing data obtained from factorial experiments, where repeated measurements over a period of time have been recorded.