Quantitative Detection of Ethanol Solid-State Fermentation Process Parameters Based on Near Infrared Spectroscopy

2017 ◽  
Vol 54 (2) ◽  
pp. 023002
Author(s):  
张航 Zhang Hang ◽  
刘国海 Liu Guohai ◽  
江辉 Jiang Hui ◽  
梅从立 Mei Congli ◽  
黄永红 Huang Yonghong
Keyword(s):  
Infrared Spectroscopy ◽  
Solid State ◽  
Near Infrared Spectroscopy ◽  
Process Parameters ◽  
Solid State Fermentation ◽  
Fermentation Process ◽  
Near Infrared ◽  
Quantitative Detection

Rapid Estimation of Xanthan and Biomass Concentration during Xanthan Production under Solid State Fermentation on Polyurethane Foam with Near–Infrared Spectroscopy

2012 ◽  
Vol 482-484 ◽  
pp. 1515-1519
Author(s):  
Zhi Guo Zhang ◽  
Hong Zhang Chen
Keyword(s):  
Infrared Spectroscopy ◽  
Solid State ◽  
Polyurethane Foam ◽  
Near Infrared Spectroscopy ◽  
Solid State Fermentation ◽  
Near Infrared ◽  
External Validation ◽  
Biomass Concentration ◽  
Inert Support ◽  
Xanthan Production

Recently, some solid state fermentation (SSF) processes of xanthan production were studied. However, quantitative analysis of the concentration of xanthan and biomass is more complicated than that of submerged fermentation. To facilitate the analysis of these components, near–infrared spectroscopy (NIRS) was used. A NIRS calibration models for rapidly estimating xanthan and biomass concentration in xanthan fermentation on inert support of polyurethane foam was established. The wavenumber and spectral pretreatment method were optimized. The data of cross validation and external validation shows that NIRS was suitable for rapid and accurate quantification of the concentration of xanthan and biomass in solid state fermentation on inert support. This method will provide much convenience for the research of solid state fermentation on inert support.

scholarly journals Application of Near-Infrared Spectroscopy to Quantitatively Determine Relative Content of Puccnia striiformis f. sp. tritici DNA in Wheat Leaves in Incubation Period

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Yaqiong Zhao ◽  
Yilin Gu ◽  
Feng Qin ◽  
Xiaolong Li ◽  
Zhanhong Ma ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Incubation Period ◽  
Stripe Rust ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Puccinia Striiformis ◽  
Quantitative Detection ◽  
Support Vector ◽  
Infected Leaf ◽  
Wheat Leaves

Stripe rust caused by Puccinia striiformis f. sp. tritici (Pst) is a devastating wheat disease worldwide. Potential application of near-infrared spectroscopy (NIRS) in detection of pathogen amounts in latently Pst-infected wheat leaves was investigated for disease prediction and control. A total of 300 near-infrared spectra were acquired from the Pst-infected leaf samples in an incubation period, and relative contents of Pst DNA in the samples were obtained using duplex TaqMan real-time PCR arrays. Determination models of the relative contents of Pst DNA in the samples were built using quantitative partial least squares (QPLS), support vector regression (SVR), and a method integrated with QPLS and SVR. The results showed that the kQPLS-SVR model built with a ratio of training set to testing set equal to 3 : 1 based on the original spectra, when the number of the randomly selected wavelength points was 700, the number of principal components was 8, and the number of the built QPLS models was 5, was the best. The results indicated that quantitative detection of Pst DNA in leaves in the incubation period could be implemented using NIRS. A novel method for determination of latent infection levels of Pst and early detection of stripe rust was provided.

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