Table 1 The parameters for the assessment of these models.

From: Study on browning mechanism of fresh-cut eggplant (Solanum melongena L.) based on metabolomics, enzymatic assays and gene expression

No. Model

Type

A

N

R2X(cum)

R2Y(cum)

Q2(cum)

R2

Q2

All

M1

PCA-X

6

32

0.651

 

0.356

  

5 min/CK

M2

PCA-X

3

16

0.62

 

0.416

  

5 min/CK

M3

PLS-DA

2

16

0.502

0.989

0.955

  

5 min/CK

M4

OPLS-DA

1 + 2 + 0

16

0.64

0.998

0.987

0.642

−0.849

3 min/CK

M5

PCA-X

4

16

0.612

 

0.106

  

3 min/CK

M6

PLS-DA

3

16

0.479

0.995

0.889

  

3 min/CK

M7

OPLS-DA

1 + 3 + 0

16

0.595

0.998

0.925

0.795

 − 0.88

3 min/5 min

M8

PCA-X

4

16

0.662

 

0.321

  

3 min/5 min

M9

PLS-DA

3

16

0.562

0.995

0.956

  

3 min/5 min

M10

OPLS-DA

1 + 1 + 0

16

0.466

0.985

0.943

0.522

− 0.741

  1. Note A represents the number of principal components (PC) while each model is constructed, N represents the numbers of samples analyzed, M1-M10 represents Model 1–10, R2X (cum) represents the interpretation rate of each model in the X axis direction in multivariate statistical analysis modeling, R2Y (cum) represents the interpretation rate of each model in Y axis direction in multivariate statistical analysis modeling, Q2 (cum) represents the prediction rate of each model, R2 represents the intercept value of the Y axis and the regression line, which is obtained when Linear regression analysis between the Y matrix of the original classification, the Y matrices of N times’ different permutations and R2Y was conducted during model validation, and Q2 for the intercept value of the Y axis and the regression line, which is obtained when Linear regression analysis between the Y matrix of the original classification, the Y matrices of N times’ different permutations and Q2Y was conducted during model validation. For Q2 in external validation, general requirement is that Q2 < 0, overfitting is avoided. For R2X, general requirement is that R2X > 0.4, the model is good. For R2 in internal validation, general requirement is that R2 > 0.5, the closer to 1, the better the model.
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