In a data, there are 9 columns and first 8 columns give various measured properties of wine, as floating point numbers, and the final column is a factor (categorical variable) representing the perceived quality of the wine.

Is it appropriate to fit a linear regression model to predict the quality of a wine, given its other properties which are numeric (columns 1 to 8)?

logistic regression is the good choice for this but I wanted to know will the linear regression work either by converting factor into numeric (or) it is not a possible thing because the quality of wine is not numeric to predict (or) linear regression can be used anyway( without converting) because linear models fit in any classification problems ?