Table 3.

Regression coefficients, R², p-value of lack of fit for the final reduced models.

Responses	KTI (Y1, %)		Lectin (Y2, %)		BBI (Y3, %)
Coefficient	HIT1	HIT2	HIT1	HIT2	HIT1	HIT2
β0	10.2620	6.6139*	17.1457*	0.805433	−7.91743*	0.02922
β1	−0.1757	–	−0.1099	−0.025771	0.10420*	−0.06021
β2	0.0381*	−1.2093*	−0.5440*	−0.752982	–	3.38440
β3	0.5045*	−0.7258	0.1543	0.727783	2.64682*	−1.20048
${\beta }_1^2$	0.0004	–	0.0003	0.000225	–	−0.00024
${\beta }_2^2$	0.0005	–	0.0027*	−0.010021	–	−0.07964
${\beta }_3^2$	0.0376	–	−0.0890*	0.081745*	–	−0.09475
β12	0.0020	–	0.0023*	0.011974	–	−0.03554
β13	0.0142	–	−0.0025	−0.011471*	−0.02639*	0.04163*
β23	−0.05585*	0.2469*	0.0290*	–	–	–
R2	0.664	0.368	0.820	0.963	0.607	0.687
p-value	0.023	0.022	0.005	0.028	0.002	0.026
Lack of fit (p-value)	0.003	0.165	0.589	0.567	0.236	0.557

Abbreviation: β₀ is a constant, β_i, β_ii and β_ij are the linear, quadratic and interaction coefficients of the quadratic polynomial equation, respectively. 1: Heating temperature generated via heat irradiation treatment or that generated by heat ionization treatment; 2: Time applied to both treatments; 3: Mass used to heat irradiation treatment or the pH of buffer used to heat ionization treatment.*Significant at p < 0.05.