Optimizing the acceleration of Cheddar cheese ripening using response surface methodology by microbial protease without altering its quality features

AMB Express

Table 1 Regression coefficients, R², and probability value of the response surface models

Regression coefficient	pH (Y1)	ADV (Y2)	Moisture (Y3)	a_w (Y4)	SN [(%), Y5]	Fat [(%), Y6]	Overall acceptability (Y7)
b0	3.22	22.156	31.27	0.87167	60.4	41.98	32.3
b1	0.96	− 7.752	3.47	0.04122	− 16.8	− 1.75	− 3.0
b2	102.14	− 438.700	− 277.16	− 1.89539	− 1812.0	− 363.49	− 853.9
b3	− 0.71	7.457	− 0.83	− 0.01209	14.3	− 2.40	− 10.0
b1²	− 0.10	0.652	− 0.43	− 0.00551	2.0	− 0.02	0.1
b2²	− 1629.07	− 764.094	2827.35	− 2.94037	30,030.3	1381.18	14,895.8
b3²	− 0.12	− 0.363	0.19	− 0.00385	0.2	− 0.78	0.5
b12	− 11.58	115.769	32.60	0.34731	60.7	53.63	− 9.3
b13	0.00	− 0.474	− 0.08	0.00204	− 2.5	0.71	1.3
b23	22.96	− 52.445	− 67.11	0.23852	26.1	42.82	78.5
R²	0.99	0.95	0.96	0.94	0.94	0.94	0.92
Regression (P-value)	0.00^a	0.00^a	0.00^a	0.00^a	0.00^a	0.00^a	0.00^a

b0, b1, b2 and b3: the estimated regression coefficient for the main linear effects. b1², b2² and b3²: the estimated regression coefficient for quadratic effects. b12, b13 and b23: the estimated regression coefficient for the interaction effects. 1: purification factor of protease (PF), 2: protease concentration (%); 3: ripening time (month)
^aSignificant (P ≤ 0.05)