Sequential mean squares measure how much variation a term or a model explains. The sequential mean squares depend on the order the terms enter the model. Unlike the sequential sums of squares, the sequential mean squares consider the degrees of freedom.
The sequential mean square of the error (also called MSE or s2) is the variance around the fitted values.
Minitab uses the sequential mean square to calculate the p-value for a term. Minitab also uses the sequential mean squares to calculate the adjusted R2 statistic. Usually, you interpret the p-values and the adjusted R2 statistic instead of the sequential mean squares.