Rapid Detection of Sorghum Tannin Content Based on Near-Infrared Spectroscopy and Gaussian Process
10.19756/j.issn.0253-3820.231441
- VernacularTitle:基于近红外光谱与高斯过程的高粱单宁含量快速检测
- Author:
Jin-Yi ZHAO
1
;
Zheng-Guang CHEN
;
Shu-Juan YI
Author Information
1. 黑龙江八一农垦大学,信息与电气工程学院,大庆 163000
- Keywords:
Near-infrared spectroscopy;
Chemometrics;
Sorghum tannin;
Gaussian process;
Rapid non-destructive testing
- From:
Chinese Journal of Analytical Chemistry
2024;52(7):1028-1038
- CountryChina
- Language:Chinese
-
Abstract:
The tannin content of sorghum seeds had a significant impact on the wine's quality during the brewing process.Additionally,when used as a feed ingredient,the tannin content had a major impact on feed consumption.Thus the tannin content of sorghum has a substantial impact on its quality and application.To quickly and nondestructively determine the tannin content of sorghum,near-infrared spectroscopy was combined with chemometrics in this study,which eliminated the need for time-consuming and costly conventional approaches.Following the spectra's preprocessing,anomalous samples were removed by using a combination of Gaussian process regression(GPR)and Monte Carlo cross-validation(MCCV).The sample set was then randomly divided into a modeling set and a prediction set,with feature wavelength selection carried out using the elimination of uninformative variables(UVE)method.Subsequently,a GPR model was developed,and its performance was compared with partial least squares regression(PLSR)and support vector machine regression(SVR)models.The results indicated that the GPR model outperformed the PLSR and SVR models in all aspects.The optimized GPR model,generated following pre-processing process such as Detrending and Savitzky-Golay smoothing,elimination of anomalous samples,and selection of feature wavelengths,demonstrated superior performance,with model set determination coefficient(Rc2),prediction set determination coefficient(RP2),and relative percent deviation(RPD)values of 0.9979,0.9529,and 4.8453,respectively.These findings validated the effectiveness of the GPR regression model,which integrated near-infrared spectroscopy with chemometrics,for the rapid and non-destructive detection of sorghum tannins.
