Latent variables can be regarded as the real information hiding in the spectra. Too many latent variables can result in an over-fitted model that will not work well on new samples.
When models are created, an optimization process decides how many latent variables will be used in the model. The default range of latent variables is 1-5 (the maximal number of LVs is limited to 20% of the number of samples).
Using the expert mode, you can choose which number of LVs to use in the optimization process by writing a new range using ‘-‘ or discrete values separated by ‘,’.

For example, if you create a simple model for mixtures of material A and material B, one LV for each material should be enough to capture the information hidden in the spectrum.