Evaluation of germination and vigor in corn seeds using the Hill function

Abstract

The seeds are complex biological structures that result from the struggle for the survival of the plants, constituting the most important agricultural input. Germination is one of the first events that occurs in the occupation of a new habitat, pertinent to the distribution in time/space at different rates. And one of the ways to understand this process with greater detail, is through regression studies as a function of time, for this we can apply non-linear regressions. Thus, the objective of this work was to verify the adjustment of h nonlinear equations to test the following hypotheses in form general, seeking to determine the lot of higher physiological quality: (a) H0: the h equations are identical, that is, we can use a common equation as an estimate of the equations h involved; and (b) H0: a given number of parameters is equal in the h groups. Germination data were obtained from two corn lots that were modeled by the four parameter Hill function. The best fit hypothesis (square root of the maximum likelihood estimate of the residual variance) was chosen to represent the germination of the corn lots. It is concluded that the use of non-linear regressions through the test of equality of parameters and identity of models can be used in the comparison of germination of different seed lots.

Keywords

• germination, physiological potential, nonlinear regression, likelihood.