Rapid Measurement of Cellulose, Hemicellulose, and Lignin Content in Sargassum horneri by Near-Infrared Spectroscopy and Characteristic Variables Selection Methods

Abstract

Near-infrared (NIR) spectroscopy and characteristic variables selection methods were used to develop a quick method for the determination of cellulose, hemicellulose, and lignin contents in Sargassum horneri. Calibration models for cellulose, hemicellulose, and lignin in Sargassum horneri were established using partial least square regression methods with full variables (full-PLSR). The PLSR calibration models were established by four characteristic variables selection methods, including interval partial least square (iPLS), competitive adaptive reweighted sampling (CARS), correlation coefficient (CC), and genetic algorithm (GA). The results showed that the performance of the four calibration models, namely iPLS-PLSR, CARS-PLSR, CC-PLSR, and GA-PLSR, was better than the full-PLSR calibration model. The iPLS method was best in the performance of the models. For iPLS-PLSR, the determination coefficient (R2), root mean square error (RMSE), and residual predictive deviation (RPD) of the prediction set were as follows: 0.8955, 0.8232%, and 3.0934 for cellulose, 0.8669, 0.4697%, and 2.7406 for hemicellulose, and 0.7307, 0.7533%, and 1.9272 for lignin, respectively. These findings indicate that the NIR calibration models can be used to predict cellulose, hemicellulose, and lignin contents in Sargassum horneri quickly and accurately.

Pyrolysis of sargassum in a single mode microwave cavity: use of SiC and biochar as microwave absorbers

“…Comparing Table 5 with another species of brown seaweed such as Sargassum horneri whose hemicellulose composition is 16.75-22.64%, 33 cellulose composition is 28.29-39.88%, 33 and lignin is 22.10-27.20%, 33 we observe lower values in our case. Alvarado Flores et al 34 published a compositional analysis of sargassum, specifically of the species fluitans and natans and observed similar values to ours for cellulose content (15.73%) and lignin (13.15%), but different in the hemicellulose content (12.86%).…”

Rapid Determination of Cellulose and Hemicellulose Contents in Corn Stover Using Near-Infrared Spectroscopy Combined with Wavelength Selection

“…However, due to its randomness, CARS must be run multiple times to reduce the instability of the model. Combining the algorithms for WV optimization can effectively improve the model’s performance [ 35 ]. The performance indicators for the BIPLS-CARS, BIPLS-GSA, and CARS-GSA models were better than those of Full-PLS, BIPLS, and CARS.…”

Optimization of Mixed Fermentation Conditions of Dietary Fiber from Soybean Residue and the Effect on Structure, Properties and Potential Biological Activity of Dietary Fiber from Soybean Residue

“…Another absorption peak at 2927 cm −1 corresponds to the -CH 2 (methylene) stretch vibration, belonging to the range of saturated C-H, which comes from the polypropylene group of polysaccharides [ 21 ]. For MF and UF, the absorption peak at 1542 cm −1 is correlated with cellulose [ 22 ]. The adsorption peak intensity of MF at 1417 cm −1 is higher than that of UF, which is mainly due to the disruption of the crystalline region of cellulose by LAB and SC during fermentation, resulting in an improvement in the peak strength; the absorption peak is related to pectin [ 23 ].…”