The main effect of time just looks at whether there is significantly more variation between the different levels of time compared to the error term (the interaction between time and participants, i.e., the difference in the effect of time for different participants). It had nothing to do with whether the relationship between the levels is linear, quadratic, cubic, or whatever. It just looks for variations between levels.
The trend analysis is more specific in that it looks for a particular kind of relationship between the levels of time, in your case a quadratic relation (a fitted line that contains a quadratic component). The analysis suggests that your data can be well approximated by a quadratic function, but the question may be 1) if it is the kind of quadratic function you would expect? and 2) if you expected a quadratic function at all? If I strongly expected a quadratic relationship I would be inclined to skip the first analysis of the main effect and head directly for the within-subjects contrasts, but only if I really predicted such a result. It may not make much sense otherwise.