Rapid non ‐destructive analysis of lignin using NIR spectroscopy and chemo‐metrics

In this paper, we employ NIR spectroscopy combined with synergy interval partial least squares (SiPLS), optimized bootstrapping soft shrinkage method (FRC-BOSS) and partial least square regression (PLSR) to select feature wavelength for rapid and nondestructive analysis of lignin content in ‘Snow’ pears. And then, a comparison of the SiPLS, SiPLS-SPA, SiPLS-CARS, and SiPLS-BOSS variables selection method, the partial least square regression (PLSR) model based on the variables selected by SiPLS-FRCBOSS method has the best prediction ability. It is concluded that the NIR diffuse refl ectance spectroscopy technology combined with FRC-BOSS proved to be a good tool for nondestructive determination of lignin content in ‘Snow’ pears. AbstractLignin plays an important role in the formation of stone cells in pears. However, the accumulation of lignin had adverse impact on the flavor and quality of the fruit. A rapid and accurate method for measuring the lignin content of pears is therefore required. An improved variables selection method called ‘the bootstrapping soft shrinkage combined with frequency and regression coefficient of variables (FRCBOSS)’ was therefore developed based on ‘the bootstrapping soft shrinkage (BOSS)’technique, to identify the characteristic wavelengths of near-infrared (NIR) spectra for non-destructive and rapid analysis of lignin. Sub-models were generated by weighted bootstrap sampling (WBS) in the FRCBOSS method. For the BOSS method, the new...

Source: Food and Energy Security - May 5, 2021 Category: Food Science Authors: Xin Wu, Guanglin Li, Xuwen Liu, Fengyun He Tags: ORIGINAL RESEARCH Source Type: research