Skip to main content

Table 2 Comparison of calibration models and prediction results of the immunoglobulin G (IgG) concentration of 200 bovine serum samples, obtained using different pre-processing approaches for infrared spectra

From: A rapid field test for the measurement of bovine serum immunoglobulin G using attenuated total reflectance infrared spectroscopy

    Calibration (n = 133) Prediction (n = 67)
Pre-processing PLS factors RMMCCV (mg/dL) r RMSEC (mg/dL) r RMSEP (mg/dL) RPD RER
Smoothing (9 points) 14 335 0.97 364 0.92 340 2.6 8.8
Smoothing + normalization (SNV) 14 332 0.97 359 0.93 326 2.7 9.1
Smoothing + vector normalization 14 336 .097 367 0.93 331 2.7 9
1st derivatives (9 points) 6 341 0.95 370 0.91 373 2.4 8
1st derivatives + normalization (SNV) 6 338 0.95 355 0.91 362 2.4 8.2
1st derivatives + vector normalization 6 340 0.96 357 0.91 362 2.4 8.2
2nd derivatives (9 points) 5 363 0.97 382 0.88 424 2.1 7
2nd derivatives + normalization (SNV) 5 358 0.97 376 0.87 429 2 7
2nd derivatives + Vector normalization 6 356 0.97 376 0.89 409 2.1 7.3
  1. PLS, Partial least squares, RMMCCV Root mean squared error of the Monte Carlo cross validation value, r Pearson correlation coefficient, RMSEC Root mean squared error of calibration;, RMSEP Root mean squared error of prediction, RPD (ratio of predictive deviation), SD divided by RMSEP, RER (range error ratio), Range divided by RMSEP; SNV Standard normal variate