Transfer strategy for near infrared analysis model of holocellulose and lignin based on improved slope/bias algorithm

Abstract

Model transfer techniques in near infrared spectroscopy are important for avoiding duplicate modeling, sharing samples and data resources, and reducing the human and material consumption required for modeling. Use of the slope/bias correction algorithm (S/B) based on screening wavelengths with consistent and stable signals (SWCSS) for model transfer is a new strategy. To enable sharing of near infrared analysis models of pulp holocellulose and lignin content in two different types of spectroscopic instruments, a combined SWCSS-S/B algorithm was proposed. The stable and consistent wavelengths between the spectroscopic instruments screened by the SWCSS method reduced the differences between the instruments, thereby improving the universality and transmission accuracy of the S/B method. The SWCSS-S/B based model transfer method reduced the predicted standard deviation RMSEP of holocellulose and lignin contents of the samples measured on the target spectrometer of the from 5.4686 and 7.6823 to 1.2133 and 1.3494, respectively. This result showed a significant improvement in the transfer effect compared to the SWCSS and S/B correction results alone, and the prediction of holocellulose was better than that of the prediction effect of lignin. The method has fewer wavelength variables involved in model transfer, fast transfer speed, and high prediction accuracy, which provides a new solution for the wide application of NIR analytical models.

Transfer of near infrared calibration for gasoline octane number based on screening consistent wavelengths combined with direct standardization algorithm

“…If the standardization samples set, or transfer set are too small it will lead to less representation of the whole sample trend, while if too large, the operation will be more complicated and it cannot reflect the advantages of model transfer in practical application. Therefore, the Kennard-Stone algorithm was used to select 5,10,15,20,25,30,35 and 40 samples as the transfer set for model transfer. The relationship between the number of samples in the transfer set and the RMSEP was shown in Figure 6.…”

“…Following the steps of the SWCSS method, 30 5, 10, and 20 representative samples were selected from the master samples by the Kennard-Stone method. The absorbance of the selected sample at each wavelength point was taken as a variable, and the ratio of the standard deviation of difference spectra between master and target instruments (SDDSI j ) of the master-target difference spectrum at wavelength j to the standard deviation of precision detection spectra (SDPDS j ) of the master-target precision test spectrum was defined as the consistency parameter, which can be used to discriminate the consistent and stable wavelength of the spectral signals of different instruments and shown as follows:In equation (2), n was the number of spectral wavelength points in the sample.…”

Application of stable consistency wavelength in optimizing gasoline RON near‐infrared analysis model transfer

“…6,7 The commonly used standard sample model transfer methods mainly include direct standardized (DS) algorithm, 8 piecewise direct standardization (PDS) algorithm, and slope/bias (S/B) correction algorithm. 9,10 Salguero-Chaparro L et al realized the transfer of free fatty acid content and moisture content prediction model of olive oil and used S/B algorithm, PDS algorithm, and orthogonal projection algorithm for transfer. 11 Andong Wang et al proposed a new calibration model transfer strategy of direct orthogonal signal correction combined with slope and bias correction (DOSC-SBC) to maintain the prediction ability of the original calibration model for new source batches and improve the applicability of the SBC method.…”

“…Model transfer is an important way to solve the problem that NIR spectral analysis model is not applicable 6,7 . The commonly used standard sample model transfer methods mainly include direct standardized (DS) algorithm, 8 piecewise direct standardization (PDS) algorithm, and slope/bias (S/B) correction algorithm 9,10 . Salguero‐Chaparro L et al realized the transfer of free fatty acid content and moisture content prediction model of olive oil and used S/B algorithm, PDS algorithm, and orthogonal projection algorithm for transfer 11 .…”

Near-infrared lignin model transfer: A study based on SWCSS-CARS coupling algorithm

“…Currently, model transfer research is mostly focused on improving and developing new algorithms to realize model transfer sharing between different models of NIR spectrometers, which often requires a large number of samples to ensure the reliability of the model transfer, and this method is called scaled sample model transfer. In order to solve the problem of requiring a large number of samples for the traditional model transfer method with labeled samples, model transfer using the SWCSS method is a new strategy worthy of study (Ni et al 2018;Zhang et al 2020;Wang et al 2022), whose transfer process is relatively simple and only requires the selection of very few representative samples for screening the consistent wavelengths, which makes the model transfer easier to realize. However, the wavelengths selected by the current SWCSS method for consistency between different spectroscopic instruments may contain no information as well as wavelengths with very little information, which leads to poor SWCSS-PLSR model transfer performance.…”