Table 3.

Summary of the equations of linear regression methods.

Method	Equation
Benesi-Hildebrand a	$\frac{1}{{\Delta }_{\mathrm{i}}}=\frac{1}{{\mathrm{K}}_{\mathrm{f}}\times {\Delta }_{\max }\times {\left[\mathrm{CD}\right]}_{\mathrm{i}}}+\frac{1}{{\Delta }_{\max }}$
Scott b	$\frac{{\left[\mathrm{CD}\right]}_{\mathrm{i}}}{{\Delta }_{\mathrm{i}}}=\frac{1}{{\mathrm{K}}_{\mathrm{f}}}+{\left[\mathrm{CD}\right]}_{\mathrm{i}}$
Scatchard c	$\frac{{\Delta }_{\mathrm{i}}}{{\left[\mathrm{CD}\right]}_{\mathrm{i}}}=-{\mathrm{K}}_{\mathrm{f}}\times {\Delta }_{\mathrm{i}}+{\mathrm{K}}_{\mathrm{f}}\times {\Delta }_{\max }$

^a [63], ^b [64], ^c [65]. Δ_i stands for the experimental variation of the guest absorbance upon CD addition. Δ_max is the experimental variation of the guest absorbance when it is totally encapsulated. [G] is the concentration of the guest. [CD]_i is the concentration of CD at each titration point.