| 光谱学与光谱分析 |
|
|
|
|
|
| Study on the Discrimination of Boletus Edulis from Different Years and Origins with FTIR |
| YANG Tian-wei1, 2, LI Tao3, LI Jie-qing1, ZHANG Xue4, WANG Yuan-zhong2*, LIU Hong-gao1* |
1. College of Agronomy and Biotechnology, Yunnan Agricultural University, Kunming 650201, China
2. Institute of Medicinal Plants, Yunnan Academy of Agricultural Sciences, Kunming 650200, China
3. College of Resources and Environment, Yuxi Normal University, Yuxi 653100, China
4. Yunnan Technician College, Anning 650300, China |
|
|
|
|
Abstract In order to establish a rapid method for discriminating Boletus edulis mushroom, Fourier transform infrared spectroscopy combined with multivariate statistical analysis were used to study B. edulis which were collected from different origins and different years. The original infrared spectra of all the 152 B. edulis samples collected from 2011 to 2014 and 26 different areas of Yunnan Province were optimized with orthogonal signal correction and wavelet compression (OSCW) method. The spectral data that before and after being preprocessed with OSCW were analyzed with partial least squares discriminant analysis (PLS-DA). The classification results of PLS-DA were compared. Then the 152 B. edulis samples were randomly divided into a training set (120) and a validation set (32) to establish the PLS classification prediction model. The results showed that, after OSCW processing, the classification result of PLS-DA was significantly better than the other one which was not processed by OSCW. Principal component score plot can accurately distinguish B. edulis samples collected from different years and different origins. It indicated that OSCW can effectively eliminate the noise of spectra and reduce the unrelated interference information about the dependent variables to improve the accuracy and calculation speed of spectral analysis. Before OSCW preprocessed, the R2 and RMSEE of PLS model of the training set were 0.790 1 and 21.246 5 respectively while R2 and RMSEP of the model of validation set were 0.922 5 and 14.429 2. After OSCW pretreatment, R2 and RMSEE of the training set were 0.852 3 and 17.238 1 while R2 and RMSEP of validation set were 0.845 4 and 20.87. It suggested that OSCW could improve the predictive effect of the training set, but the over-fitting of OSCW-PLS may reduce the predictive ability of validation set. Therefore, it was unsuitable to establish a model with OSCW combined with PLS. In a conclusion, OSCW combined with PLS-DA can eliminate a large amount of spectrum interference information. This method could accurately distinguish B. edulis samples collected from different years and different origins. It could provide a reliable basis for the discrimination and classification of wild edible fungi.
|
|
Received: 2014-09-13
Accepted: 2014-12-25
|
|
|
|
Corresponding Authors:
WANG Yuan-zhong, LIU Hong-gao
E-mail: boletus@126.com; honggaoliu@126.com
|
|
[1] Wang X M, Zhang J, Wu L H, et al. Food Chemistry, 2014, 151: 279.
[2] Wu G, Feng B, Xu J P, et al. Fungal Diversity, 2014, 69: 93.
[3] DENG Bai-wan, CHEN Wen-qiang, LI Xin-sheng(邓百万, 陈文强, 李新生). Food Science(食品科学), 2005, 25(11): 255.
[4] Kalac P. Food Chemistry, 2009, 113(1): 9.
[5] ZHOU Ling-xian, YIN Jian-zhong(周玲仙, 殷建忠). Edible Fungus(食用菌), 2008, (4): 61.
[6] Luo Aoxue, Luo Aoshuang, Huang Jiandong, et al. Molecules, 2012, 17(7): 8079.
[7] LI Shu-hong, ZHAO Yong-chang, YU Fu-qiang, et al(李树红, 赵永昌, 于富强, 等). Edible Fungi of China(中国食用菌), 2011, 30(5): 34.
[8] ZHOU Zai-jin, LIU Gang, REN Xian-pei(周在进, 刘 刚, 任先培). Laser and Infrared(激光与红外). 2010, 40(9): 970.
[9] DAI Yu-cheng, TOLGOR Bau, CUI Bao-kai, et al(戴玉成, 图力古尔, 催宝凯, 等). Illustrations of Medicinal Fungi in China(中国药用真菌图志). Harbin: Northeast Forestry University Press(哈尔滨: 东北林业大学出版社), 2013. 74.
[10] WANG Xiang-hua, LIU Pei-gui, YU Fu-qiang(王向华, 刘培贵, 于富强). Color atlas of wild commercial mushrooms in Yunnan(云南野生商品蘑菇图鉴). Kunming: Yunnan Science and Technology Press(昆明: 云南科技出版社), 2004. 125.
[11] ZHOU Zai-jin, LIU Gang, REN Xian-pei(周在进, 刘 刚, 任先培). Laser and Infrared(激光与红外), 2009, 39(11): 1158.
[12] SUN Su-qin, DU De-guo, LIANG Xi-yun, et al(孙素琴, 杜德国, 梁曦云, 等). Chinese Journal of Analytical Chemistry(分析化学), 2001, 29(3): 309.
[13] YANG Tian-wei, CUI Bao-kai, ZHANG Ji, et al(杨天伟, 崔宝凯, 张 霁, 等). Mycosystema(菌物学报), 2014, 33(2): 262.
[14] WEI Hai-long, LI Hai-bo, WANG Li-ling, et al(魏海龙, 李海波, 王丽玲, 等). Mycosystema(菌物学报), 2014, 33(2): 242.
[15] Mello A, Ghignone S, Vizzini A, et al. Journal of Biotechnology, 2006, 121(3): 318.
[16] Lian B, Zang J P, Hou W G, et al. Electronic Journal of Biotechnology, 2008, 11(3): 102.
[17] ZHOU Ye, ZHANG Qing-wei, LI Pei-fu, et al(周 晔, 张庆伟, 李佩孚, 等). Chinese Journal of Traditional Chinese Medicine(中国中药杂志), 2013, 38(019): 3309.
[18] Alexandrakis D, Downey G, Scannell A G M. Food and Bioprocess Technology, 2012, 5(1): 338.
[19] REN Xian-pei, LIU Gang, ZHOU Zai-jin, et al(任先培, 刘 刚, 周在进, 等). Laser and Infrared(激光与红外), 2009, 39(9): 944.
[20] Tarantilis P A, Troianou V E, Pappas C S, et al. Food Chemistry, 2008, 111(1): 192.
[21] Sun S Q, Chen J B, Zhou Q, et al. Planta Medica, 2010, 76(17): 1987.
[22] Wold S, Antti H, Lindgren F, et al. Chemometrics and Intelligent Laboratory Systems, 1998, 44: 175.
[23] Bylesj M, Rantalainen M, Cloarec O, et al. Journal of Chemometrics, 2006, 20(8-10): 341.
[24] LI Si-hai, PAN Xin-bo, REN Zhen, et al(李四海, 潘新波, 任 真, 等). Chinese Journal of Experimental Traditional Medical Formulae(中国实验方剂学杂志), 2013, 19(12): 132. |
| [1] |
LI Shu-jie1, LIU Jie1, DENG Zi-ang1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Study of Germinated Rice Seeds by FTIR Spectroscopy Combined With Curve Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1832-1840. |
| [2] |
ZHANG Yan-ru1, 2, SHAO Peng-shuai1*. Study on the Effects of Planting Years of Vegetable Greenhouse on the
Cucumber Qualties Using Mid-IR Spectroscopoy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1816-1821. |
| [3] |
SHI Wen-qiang1, XU Xiu-ying1*, ZHANG Wei1, ZHANG Ping2, SUN Hai-tian1, 3, HU Jun1. Prediction Model of Soil Moisture Content in Northern Cold Region Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1704-1710. |
| [4] |
WANG Xue-pei1, 2, ZHANG Lu-wei1, 2, BAI Xue-bing3, MO Xian-bin1, ZHANG Xiao-shuan1, 2*. Infrared Spectral Characterization of Ultraviolet Ozone Treatment on Substrate Surface for Flexible Electronics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1867-1873. |
| [5] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
| [6] |
FENG Rui-jie1, CHEN Zheng-guang1, 2*, YI Shu-juan3. Identification of Corn Varieties Based on Bayesian Optimization SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1698-1703. |
| [7] |
YU Zhi-rong, HONG Ming-jian*. Near-Infrared Spectral Quantitative Analysis Network Based on Grouped Fully Connection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1735-1740. |
| [8] |
XIE Yu-yu1, 2, 3, HOU Xue-ling1, CHEN Zhi-hui2, AISA Haji Akber1, 3*. Density Functional Theory Studies on Structure and Spectra of Salidroside Molecule[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1786-1791. |
| [9] |
MENG Fan-jia1, LUO Shi1, WU Yue-feng1, SUN Hong1, LIU Fei2, LI Min-zan1*, HUANG Wei3, LI Mu3. Characteristic Extraction Method and Discriminant Model of Ear Rot of Maize Seed Base on NIR Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1716-1720. |
| [10] |
PENG Yan-fang1, WANG Jun1, WU Zhi-sheng2*, LIU Xiao-na3, QIAO Yan-jiang2*. NIR Band Assignment of Tanshinone ⅡA and Cryptotanshinone by
2D-COS Technology and Model Application Tanshinone Extract[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1781-1785. |
| [11] |
LI Qing1, 2, XU Li1, 2, PENG Shan-gui1, 2, LUO Xiao1, 2, ZHANG Rong-qin1, 2, YAN Zhu-yun3, WEN Yong-sheng1, 2*. Research on Identification of Danshen Origin Based on Micro-Focused
Raman Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1774-1780. |
| [12] |
TIAN Xue1, CHE Qian1, YAN Wei-min1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Discrimination of Millet Varieties and Producing Areas Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1841-1847. |
| [13] |
MA Fang1, HUANG An-min2, ZHANG Qiu-hui1*. Discrimination of Four Black Heartwoods Using FTIR Spectroscopy and
Clustering Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1915-1921. |
| [14] |
HU Bin1, 2, FU Hao1, WANG Wen-bin1, ZHANG Bing1, 2, TANG Fan3*, MA Shan-wei1, 2, LU Qiang1, 2*. Research on Deep Sorting Approach Based on Infrared Spectroscopy for High-Value Utilization of Municipal Solid Waste[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1353-1360. |
| [15] |
YAN Ling-tong, LI Li, SUN He-yang, XU Qing, FENG Song-lin*. Spectrometric Investigation of Structure Hydroxyl in Traditional Ceramics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1361-1365. |
|
|
|
|
