I performed a LDA in R but I'm a bit concerned about how I could present my results.

I didn't do any scaling before the data analysis, is it recommended to do so?

When I do the LDA, I got the following coefficients:

Coefficients of linear discriminants:

LD1

CHP -8.7908674

CD 6.6956730

CH 9.5463453

ESL 22.3475689

SDBottom -392.2736953

SDMiddle 52.2500963

SDTop 40.8531601

SL -0.4170077

TCDiameter -25.2242270

TCHeight 27.4153806

THeight 74.9738324

VFD 22.6521590

VTD -74.1032630

As I didn't scale, these coefficients are hardly interpretable. How could get the variables that are the most influential in the separation of my classes?

Secondly, how could I plot the individuals and the variables (such as biplot in PCA) so it could be simple to interpret for a posterior presentation?

Thanks in advance