1. Application of near infrared spectroscopy for rapid determination the geographical regions and polysaccharides contents of Lentinula edodes
- Author
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Shui-Han Zhang, Xie Yi, Chen-xi Zhao, Luqi Huang, Hua-Lin Xie, Yi Yu, Rongrong Zhou, and Jianhua Huang
- Subjects
Time Factors ,Materials science ,Shiitake Mushrooms ,02 engineering and technology ,Polysaccharide ,Biochemistry ,Chemometrics ,Root mean square ,03 medical and health sciences ,Structural Biology ,Calibration ,Spectroscopy ,Molecular Biology ,030304 developmental biology ,chemistry.chemical_classification ,0303 health sciences ,Spectroscopy, Near-Infrared ,Chromatography ,Geography ,biology ,Near-infrared spectroscopy ,Fungal Polysaccharides ,General Medicine ,021001 nanoscience & nanotechnology ,biology.organism_classification ,Lentinula ,chemistry ,Nir spectra ,0210 nano-technology - Abstract
In this study, a calibration model based on Near-infrared spectroscopy (NIR) technique and chemometrics method was developed for rapid and non-destructive detecting the polysaccharide contents of lentinula edodes samples collected from different regions. The polysaccharide contents of these samples were firstly determined by standard phenol-sulphruic acid method. Then, NIR spectra of these samples were collected by using Fourier transform infrared spectrometry. Based on these experimental data, a random forest method was further used to distinguish the regions of these samples, with a classification accuracy of 96.6%. After that, a rapid, accurate, and quantitative model was established for predicting the polysaccharide contents of these samples. In the model establishing process, some signal pre-treatment methods were optimized, and the validation results with highest determination coefficient (R2) and low root mean square errors of prediction (RMSEP) were, 0.925 and 0.720, respectively. These results showed that combined NIR technique with chemometrics was an effective and green method for lentinula edodes quality control.
- Published
- 2019