  In this paper, we apply the nonlinear filtering theory to the estimation of
the partially observed dynamics of anthracnose which is a phytopathology. The
signal here is the inhibition rate and the observations are the fruit volume
ant the rotted volume. We propose stochastic models based on the deterministic
models given in the references [21, 22], in order to represent the noise
introduced by uncontrolled variation on parameters and errors on the
measurements. Under the assumption of Brownian noises we prove the
well-posedness the models either they take into account the space variable or
not. The filtering problem is solved for the non-spatial model giving Zakai and
Kushner-Stratonovich equations satisfied respectively by the unnormalized and
the normalized conditional distribution of the signal with respect to the
observations. A prevision problem and a discrete filtering problem are also
studied for the realistic cases of discrete and possibly incomplete
observations. We illustrate the filter behaviour through numerical simulations
corresponding to different scenarios
  KeyWords: Anthracnose modelling, State estimation, Nonlinear filtering.
