Table 3.

Analysis of variance results for different statistical models for: (a) droplet size diameter (d_3.2); (b) DPPH radical scavenging activity (IC₅₀); (c) antimicrobial activity against B. subtilis (CFU/mL); (d) antimicrobial activity against E. coli (CFU/mL).

(a)
Source	Sum of Squares	df	Mean Square	F-Value	p -Value
Model	2.02	7	0.2890	62.30	<0.0001	significant
⁽1⁾ Linear Mixture	1.27	2	0.6342	136.69	<0.0001
AB	0.1415	1	0.1415	30.49	0.0004
AC	0.0764	1	0.0764	16.46	0.0029
BC	0.3179	1	0.3179	68.52	<0.0001
AB(A-B)	0.1404	1	0.1404	30.26	0.0004
BC(B-C)	0.0752	1	0.0752	16.21	0.0030
Residual	0.0418	9	0.0046
Lack of Fit	0.0307	4	0.0077	3.45	0.1033	not significant
Pure Error	0.0111	5	0.0022
Cor Total	2.07	16
(b)
Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	1.74	8	0.2173	120.23	<0.0001	significant
⁽1⁾ Linear Mixture	1.03	2	0.5150	285.04	<0.0001
AB	0.1082	1	0.1082	59.89	<0.0001
AC	0.0609	1	0.0609	33.72	0.0004
BC	0.3769	1	0.3769	208.56	<0.0001
AB(A-B)	0.0736	1	0.0736	40.74	0.0002
AC(A-C)	0.0280	1	0.0280	15.51	0.0043
BC(B-C)	0.0308	1	0.0308	17.03	0.0033
Residual	0.0145	8	0.0018
Lack of Fit	0.0098	3	0.0033	3.46	0.1077	not significant
Pure Error	0.0047	5	0.0009
Cor Total	1.75	16
(c)
Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	5.61 × 1015	7	8.02 × 1014	76.12	<0.0001	significant
⁽1⁾ Linear Mixture	3.24 × 1015	2	1.62 × 1015	153.75	<0.0001
AB	8.81 × 1013	1	8.81 × 1013	8.36	0.0179
AC	4.31 × 1014	1	4.31 × 1014	40.94	0.0001
BC	1.87 × 1015	1	1.87 × 1015	177.29	<0.0001
AC(A-C)	1.06 × 1014	1	1.06 × 1014	10.08	0.0113
BC(B-C)	1.76 × 1014	1	1.76 × 1014	16.73	0.0027
Residual	9.48 × 1013	9	1.05 × 1013
Lack of Fit	7.41 × 1013	4	1.85 × 1013	4.47	0.0660	not significant
Pure Error	2.07 × 1013	5	4.15 × 1012
Cor Total	5.71 × 1015	16
(d)
Source	Sum of Squares	df	Mean Square	F-value	p-value
Model	3.87 × 1018	5	7.73 × 1017	40.80	<0.0001	significant
⁽1⁾ Linear Mixture	2.28 × 1018	2	1.14 × 1018	60.16	<0.0001
AB	1.55 × 1017	1	1.55 × 1017	8.19	0.0155
AC	2.12 × 1017	1	2.12 × 1017	11.17	0.0066
BC	1.40 × 1018	1	1.40 × 1018	74.13	<0.0001
Residual	2.08 × 1017	11	1.90 × 1016
Lack of Fit	1.24 × 1017	6	2.07 × 1016	1.23	0.4180	not significant
Pure Error	8.40 × 1016	5	1.68 × 1016
Cor Total	4.07 × 1018	16

⁽¹⁾ Inference for linear mixtures uses Type I sums of squares; A, B, and C were the input factors (A: EO_CU, B: EO_CA, and C: EO_CO).