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| A Combination of Hyperspectral Imaging With Two-Dimensional Correlation Spectroscopy for Monitoring the Hemicellulose Content in Lingwu Long Jujube |
| LI Yue1, LIU Gui-shan1*, FAN Nai-yun1*, HE Jian-guo1, LI Yan1, SUN You-rui1, PU Fang-ning2 |
1. School of Agriculture Department of Food, Ningxia University, Yingchuan 750021, China
2. School of Physics and Electronic Engineering, Ningxia University, Yingchuan 750021, China
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Abstract In this paper, hemicellulose content in Lingwu long jujube was determined by hyperspectral imaging and two-dimensional correlation spectroscopy (2D-COS) combined with stoichiometry. A quantitative bruising device was used to obtain the level 0，Ⅰ，Ⅱ，Ⅲ and Ⅳbruising model of jujube. Hyperspectral images and hemicellulose content of samples were obtained by hyperspectral and spectrophotometer, respectively. After the outliers were eliminated by the Monte Carlo cross-validation method, sample sets were divided into corrected and prediction sets by random sampling (RS)，kennard-stone method (KS)，sample set partitioning based on joint X-Y distances (SPXY) and 3∶1 partitioning method, respectively. The original spectrum of long jujube was preprocessed by baseline calibration, de-trending and normalising, and then a partial least square regression model was established to determine the optimal sample set division method and spectral pretreatment method.The spectral signal was extended to the second dimension by 2D-COS, and sensitive wavelength areas related to hemicellulose content were searched in the full spectral range. Competitive adaptive reweighted sampling (CARS), bootstrapping soft shrinkage (BOSS), interval variable iterative space shrinkage approach (iVISSA), variables combination population analysis (VCPA), iVISSA+BOSS, iVISSA+CARS and iVISSA+VCPA combination methods were used to extract characteristic wavelengths in the 2D-COS sensitive wavelength areas, and establish PLSR model based on characteristic wavelengths.The results showed that the PLSR model of full band established after the sample set was divided by 3∶1 and Baseline preprocessed was optimal. Therefore, the optimal sample set division method is 3∶1, and the spectral pretreatment method is Baseline, which isused for the subsequent characteristic wavelength modeling. Three autocorrelation peaks containing 401, 641 and 752 nm were found by 2D-COS analysis, respectively. The BOSS, CARS, iVISSA, VCPA, iVISSA+BOSS, iVISSA+CARS, iVISSA+VCPA methods were applied to selected 14, 26, 39, 12, 15, 22 and 11 corresponding characteristic wavelengths from 2D-COS spectra, accounting for 18.9%, 35.1%, 52.7%, 16.2%, 20.2%, 29.7%, 14.8% of the total wavelength, respectively. Comparedwith the PLSR model established by 2D-COS and characteristic waves, the 2D-COS+iVISSA-PLSR model had the best performance, with R2C=0.747 9, R2P=0.604 7, RMSEC=0.043 8, RMSEP=0.060 3. The results showed that hyperspectral imaging technology combined with 2D-COS could be used to detect hemicellulose content in Lingwu long jujube quickly.
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Received: 2021-09-06
Accepted: 2022-03-02
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Corresponding Authors:
LIU Gui-shan, FAN Nai-yun
E-mail: liugs@163.com；fny0606@163.com
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