Application of Near Infrared Spectroscopy in the Rapid Detection of Total Sugar Content in Lentinula edodes

被引：1
|
作者：
Lu J. [1 ,2 ]
Tian J. [1 ,2 ]
Liang Z. [1 ,2 ]
Wang J. [1 ,2 ]
Kang W. [1 ,2 ,3 ]
Ma C. [1 ,2 ]
Li C. [1 ,2 ]
机构：
[1] National R & D Center for Edible Fungus Processing Technology, Henan University, Kaifeng
[2] Engineering Technology Research Center for Functional Food of Henan Province, Kaifeng
[3] Kaifeng Key Laboratory of Functional Components in Health Food, Kaifeng
来源：
Shipin Kexue/Food Science | 2021年 / 42卷 / 12期
关键词：
Lentinula edodes; Near infrared spectroscopy; Partial least square; Rapid detection method; Total sugar;
D O I：
10.7506/spkx1002-6630-20210115-167
中图分类号：
学科分类号：
摘要：
In order to improve the defects of the method specified in the Chinese national standard to determine the total sugar content in edible fungi (Lentinula edodes), such as long detection time and tedious steps, near infrared spectroscopy(NIR) combined with partial least square (PLS) was adopted to establish a rapid method for determining the total sugar content of L. edodes and the predictive model parameters were optimized. In this study, a total of 106 samples were collected, 13 of which were randomly assigned into the validation set for testing model reliability, while the remaining 93 were assigned into the calibration set.In the calibration set, according to the studentized residuals and leverage value, 65 lots of samples with the typical characteristics of L. edodes were selected to optimize spectral range and the number of PLS factors for the establishment of a quantitative model for predicting the total sugar content in L. edodes. It was found that the optimal spectral preprocessing method was multiplicative scatter correction (MSC) combined with second derivatives (SD), and the predictive model with optimal results was constructed using the spectral range of 4 000-10 000 cm-1 and 10 PLS factors, with a root mean square error of calibration(RMSEC) of 1.393 and a root mean square error of prediction (RMSEP) of 1.557 as well as a correlation coefficient for calibration(R2) up to 0.940 04 and a relative percent deviation (RPD) up to 4.08.Finally, the verification results showed the model-predicted value had a good linear relationship with the experimental value with no significant difference between them (P = 0.993).In conclusion, the NIR prediction model could accurately predict the total sugar content of L. edodes. © 2021, China Food Publishing Company. All right reserved.
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页码：189 / 194
页数：5
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