Evaluation of Quality Parameters of Apple Juices Using Near-Infrared Spectroscopy and Chemometrics
Table 2
Characteristics of the optimal regression models for the prediction of the soluble solids content (SSC), titratable acidity (TA), and ratio of the soluble solids content to the titratable acidity (SSC/TA) of the apple juices under study.
Parameter
Variable selection
Spectral range (cm−1)
Preprocessing
LV
R2
Calibration
RE (%)
R2
Cross-validation
RE (%)
RMSECV
RMSECV
SSC
None
Full range
None
6
0.891
0.257
2.20
0.800
0.360
3.08
Jack-knife
1st derivative
3
0.911
0.232
1.99
0.881
0.277
2.37
NIR
9406–7498; 6224–5350
2nd derivative
10
0.987
0.088
0.75
0.853
0.309
2.65
A, B
10,109–8516; 6137–5334
SNV + 1st derivative
4
0.904
0.242
2.07
0.838
0.324
2.77
TA
None
Full range
None
7
0.804
0.209
3.98
0.512
0.341
6.50
Jack-knife
Smooth + SNV
7
0.862
0.175
3.33
0.733
0.252
4.80
NIR
6224–5350
Smooth
9
0.889
0.157
2.99
0.761
0.239
4.55
A
10,904–10,106; 9314–7722; 6137–5334
Smooth + SNV
6
0.829
0.195
3.71
0.717
0.260
4.95
B
10,109–8516; 6137–5334
Smooth + MSC
10
0.893
0.155
2.95
0.713
0.262
4.99
SSC/TA
None
Full range
None
7
0.902
0.086
3.84
0.707
0.154
6.88
Jack-knife
Smooth
8
0.931
0.073
3.26
0.835
0.116
5.18
NIR
6224–5350
None
8
0.940
0.068
3.04
0.843
0.113
5.04
A, B
6137–5334
None
10
0.941
0.067
2.99
0.828
0.118
5.27
The best model for each of the parameters is italicized; none: spectra without preprocessing; 1st derivative: first-order derivative; 2nd derivative: second-order derivative; smooth: smoothing; SNV: standard normal variate; MSC: multiplicative scatter correction; NIR, A, and B are different versions of the iPLS method.
