Table 4. Linear regression models for predicting the cooking loss of pork loin (experiment 2) with addition of electrical conductivity

pH	CIE L*	CIE a*	CIE b*	Moisture	Protein	EC-40	Intercept	Adj-r2 1)	Adj-r2 2)
–12.63	–0.79				0.32	3.09	130.51	0.513	0.115
–9.74		1.72	–3.06			1.76	120.45	0.468	0.260
–3.39				0.65	0.61	1.66	–14.79	0.276	0.184
–16.98	–0.96	1.08	–2.09			3.52	196.94	0.646	0.420
–12.94	–0.76	–0.36			0.72	3.29	122.85	0.487	0.097
–17.22	–0.93		–1.13		0.24	4.16	180.89	0.606	0.020
–9.84	–0.54			0.42	0.55	2.29	67.24	0.412	0.064
–7.45		1.82	–2.42	1.09		1.79	16.64	0.540	0.314
–9.85		1.49	–3.06		0.39	0.87	115.01	0.436	0.427
–15.33	–0.78	1.31	–2.30	0.35		3.21	155.39	0.639	0.378
–16.70	–0.94	1.08	–2.07		0.07	3.46	192.45	0.629	0.431
–9.14	–0.49	0.08		0.44	0.58	2.22	57.84	0.385	0.173
–12.22	–0.55		–0.61	0.49	0.59	3.00	83.07	0.511	0.118
–6.70		1.70	–2.09	0.97	0.56	1.53	4.51	0.553	0.414

Adj-r²: Adjust-r² value of the regression model including 40 Hz electrical conductivity.
Adj-r²: Adjust-r² value of the regression model excluding 40 Hz electrical conductivity.
EC-40, electrical conductivity measured using an LCR meter at 40 Hz; LCR, inductance (L), capacitance (C), and resistance (R).