Why in sometimes the 1st component explains less variance than the 2nd component in PLS-DA?

Yes, it is possible. PLS-DA maximizes the covariance between X (data) and Y (group). The variance displayed in the plot above is the explained variance for X . Covariance and x-variance may not agree with each other in some cases. For instance, the 1st component may not explain more X-variance than the 2nd component. In summary:

  1. The first component still explain the most co-variance between X and Y (most predictive)
  2. There are other factors (in addition to Y) contributing to the variance in the data X