|
|
|
|
|
|
Rapid Quality Evaluation of Anxi Tieguanyin Tea Based on Genetic Algorithm |
WANG Bing-yu1, SUN Wei-jiang2,3*, HUANG Yan2, YU Wen-quan4, WU Quan-jin1, LIN Fu-ming1, XIA Jin-mei1 |
1. Horticultural College of Fujian Agriculture and Forestry University,Fuzhou 350002,China
2. Anxi Tea College of Fujian Agriculture and Forestry University,Fuzhou 350002,China
3. Tea Industry Technology Development Base of Fujian Province,Fuzhou 350002,China
4. Fujian Academy of Agricultural Sciences,Fuzhou 350003,China |
|
|
Abstract Anxi Tieguanyin tea was collected as the research materials in this study. In order to find a fast and non-destructive method for rapid quality evaluation of Anxi Tieguanyin tea, the Genetic Algorithm (GA) was applied to wavelength selection befoe it is combined with partial least squares (PLS) to construct PLS and GA-PLS calibration model. The results showed that the PLS model displayed the highest prediction performance after the Fourier transform near-infrared (FT-NIR) spectrum being processed by smoothing, the second derivative and normalized methods. Statistic results with PLS: RC=0.921, RMSEC=0.543, RP=0.913, RMSEP=0.665. NIR spectra ranging from 6 670 to 4 000 cm-1 were selected, and 1 557 data volume for building calibration model were reduced to 408 with Genetic algorithm. Statistic results with GA-PLS: RC=0.959, RMSEC=0.413, RP=0.940, RMSEP=0.587. It has shown that the prediction precision of calibration set and validation set of GA-PLS model is better than those of PLS model. According to the results, it can effectively improve the prediction ability of the model when the Genetic Algorithm (GA) is applied to select the wavelengths in a traditional model which is based on the near infrared spectroscopy combined with partial least squares. It can also achieve the innovation of the methodology. Furthermore, the quality evaluation GA-PLS model provides strong reference and possesses promotional value. In addition, it provides valuable reference and new avenue for improving the standard of detection technology of tea quality in China.
|
Received: 2015-11-10
Accepted: 2016-03-19
|
|
Corresponding Authors:
SUN Wei-jiang
E-mail: swj8103@126.com
|
|
[1] XIONG Ying(熊 英). Journal of the Graduates Sun YAT-SEN University·Natural Sciences. Medicine(中山大学研究生学刊·自然科学与医学版),2013,2:16.
[2] WANG Yu-xia, XU Rong-rong, REN Guang-xin, et al(王玉霞,徐荣荣,任广鑫,等). Journal of Tea Science(茶叶科学),2011,4:355.
[3] Fu X S,Xu L,Yu X P,et al. J. Spectrosc.,2013,2013.
[4] Ren G X,Wang S P,Ning J M,et al. Food Research International,2013,53(2):822.
[5] Diniz P H G D,Gomes A A,Pistonesi M F,et al. Food Anal Methods,2014,(7):1712.
[6] Daiki Ono,Takeshi Bamba,Yuichi Oku,et al. Journal of Bioscience and Bioengineering,2011,112(3):247.
[7] Xu L,Shi PT,Fu XS,et al. J. Spectrosc.,2013,2013.
[8] CHENG Quan,YANG Fang,WANG Dan-hong,et al(程 权,杨 方,王丹红,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2014,34(3):656.
[9] ZENG Ri-bo(曾日波). Ordnance Industry Automation(兵工自动化),2005,06:115.
[10] ZHANG Xiao-chao,WU Jing-zhu,XU Yun(张小超,吴静珠,徐 云). Near Infrared Spectroscopy Analysis and Its Application in Modern Agriculture(近红外光谱分析技术及其在现代农业中的应用). Beijing:Publishing House of Electronics Industry(北京:电子工业出版社),2012. 125.
[11] ZHENG Yong-mei,ZHANG Jun,LI Rong-fu,et al(郑咏梅,张 军,李荣福,等). Laser and Infrared(激光与红外),2003,33(2):125. |
[1] |
WANG Wen-xiu, PENG Yan-kun*, FANG Xiao-qian, BU Xiao-pu. Characteristic Variables Optimization for TVB-N in Pork Based on Two-Dimensional Correlation Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2094-2100. |
[2] |
LE Ba Tuan1, 3, XIAO Dong1*, MAO Ya-chun2, SONG Liang2, HE Da-kuo1, LIU Shan-jun2. Coal Classification Based on Visible, Near-Infrared Spectroscopy and CNN-ELM Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2107-2112. |
[3] |
LIU Jin, LUAN Xiao-li*, LIU Fei. Near Infrared Spectroscopic Modelling of Sodium Content in Oil Sands Based on Lasso Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(07): 2274-2278. |
[4] |
YU Hui-ling1, MEN Hong-sheng2, LIANG Hao2, ZHANG Yi-zhuo2*. Near Infrared Spectroscopy Identification Method of Wood Surface Defects Based on SA-PBT-SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1724-1728. |
[5] |
OUYANG Ai-guo, ZHANG Yu, TANG Tian-yi, LIU Yan-de. Study on Density, Viscosity and Ethanol Content of Ethanol Diesel Based on Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1772-1778. |
[6] |
TAO Chao1*, WANG Ya-jin1, ZOU Bin1, 2, TU Yu-long1, JIANG Xiao-lu1. Assessment and Analysis of Migrations of Heavy Metal Lead and Zinc in Soil with Hyperspectral Inversion Model[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1850-1855. |
[7] |
XU Wei-jie1, WU Zhong-chen1, 2*, ZHU Xiang-ping2, ZHANG Jiang1, LING Zong-cheng1, NI Yu-heng1, GUO Kai-chen1. Classification and Discrimination of Martian-Related Minerals Using Spectral Fusion Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(06): 1926-1932. |
[8] |
LI Ying1, LI Yao-xiang1*, LI Wen-bin2, JIANG Li-chun3. Model Optimization of Wood Property and Quality Tracing Based on Wavelet Transform and NIR Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1384-1392. |
[9] |
DU Jian1, 2, HU Bing-liang1*, LIU Yong-zheng1, WEI Cui-yu1, ZHANG Geng1, TANG Xing-jia1. Study on Quality Identification of Macadamia nut Based on Convolutional Neural Networks and Spectral Features[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1514-1519. |
[10] |
WANG Chao, WANG Jian-ming, FENG Mei-chen, XIAO Lu-jie, SUN Hui, XIE Yong-kai, YANG Wu-de*. Hyperspectral Estimation on Growth Status of Winter Wheat by Using the Multivariate Statistical Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1520-1525. |
[11] |
HAN Guang, LIU Rong*, XU Ke-xin. Extraction of Effective Signal in Non-Invasive Blood Glucose Sensing with Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1599-1604. |
[12] |
LIU Huan, LIU Wen, HAN Dong-hai*, WANG Shi-ping*. Three-Dimensional Fluorescence Fingerprint Technique for Milk Quality Evaluation: Antibiotic Residual Detection and Heat-Treated Evaluation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1633-1639. |
[13] |
WANG Shi-fang, LUO Na, HAN Ping*. Application of Energy-Dispersive X-Ray Fluorescence Spectrometry to the Determination of As, Zn,Pb and Cr in Soil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(05): 1648-1654. |
[14] |
WANG Li-shuang, ZHANG Wen-bo*, TONG Li. Studies on Dimensional Stability of Wood under Different Moisture Conditions by Near Infrared Spectroscopy Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1066-1069. |
[15] |
HUANG Hua1, WU Xi-yu2, ZHU Shi-ping1*. Feature Wavelength Selection and Efficiency Analysis for Paddy Moisture Content Prediction by Near Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(04): 1070-1075. |
|
|
|
|