[Retracted] Electronic Nose for Differentiation and Quantification of Yeast Species in White Fresh Soft Cheese
Table 2
Results of partial least squares (PLS-1) models for four strains using electronic nose (as matrix) and the concentration of each strain (as matrix) using three sensors (MQ-2, MQ-135, and MQ-138). The different parameters are shown in calibration and validation methods. Full cross-validation was used.
Parameters
Species names
Pichia anomala (PA)
Pichia kluyveri (PK)
Debaryomyces hansenii (DH)
Hanseniaspora uvarum (HU)
Calibration set
0.97
0.95
0.97
0.67
Slope
0.97
0.95
0.97
0.68
RMSE
50.96
67.64
46.17
181.2
RE (%)
5.56
7.65
5.20
20.13
Number of PCs used in the model
2
2
3
2
% of explained
99
93
100
99
% of explained
98
96
98
79
RPD
6.75
5.05
7.49
1.58
Model performance
Acceptable
Acceptable
Acceptable
Rejected
Validation set
0.88
0.86
0.83
0.51
Slope
0.80
0.76
1.04
0.52
RMSE
128.87
144.76
15.89
266.21
RE (%)
14.20
16.18
17.12
29.57
Number of PCs used in the model
2
2
3
2
% of explained
99
93
100
99
% of explained
98
96
98
79
RPD
2.36
2.04
2.63
1.31
Model performance
Acceptable
Acceptable
Acceptable
Rejected
: correlation coefficient; RMSE: root mean square error; RE: relative error (i.e., ); PCs: principal components; RPD: ratio performance deviation ().
