|
|
|
|
|
|
| Discrimination of Millet Varieties and Producing Areas Based on Infrared Spectroscopy |
| TIAN Xue1, CHE Qian1, YAN Wei-min1, OU Quan-hong1, SHI You-ming2, LIU Gang1* |
1. School of Physics and Electronic Information, Yunnan Normal University, Kunming 650500, China
2. School of Physics and Electronic Engineering, Qujing Normal University, Qujing 655011, China
|
|
|
|
|
Abstract There are significant differences in taste and nutritional value among different varieties and producing areas of millet. Therefore, it is of reference significance for consumers to distinguish different kinds of millet. In this paper, Fourier transforms infrared (FT-IR) spectroscopy, two-dimensional correlation infrared (2D-IR) spectroscopy combined with curve fitting, principal component analysis (PCA) was used to distinguish varieties and origins of millet. The results showed that the original spectra of millet were similar, which were mainly composed of carbohydrates, proteins and lipids. The obvious differences in intensity were observed near 3 012, 2 962, 2 928, 2 856, 1 748 and 1 548 cm-1 in SD-IR. The numbers, positions and intensities of auto-peaks and cross-peaks were different in the range of 1200~860 and 1700~1180 cm-1. The curve fitting results showed that the ratio of the sub-peak areas of millet in the range of 1 700~1 600 cm-1 was different, which indicated that the protein content of millet was different among different varieties, to realize the identification of millet varieties. The range of 1 800~800 cm-1 in the derivative spectra was used for PCA analysis. The results showed that the cumulative contribution rate of the first three principal components was 97%, and millet from different producing areas was correctly classified. The study demonstrates that IR combined with statistical analysis methods could be effectively used to identify and analyze varieties and producing areas of millet.
|
|
Received: 2021-05-12
Accepted: 2021-08-24
|
|
|
|
Corresponding Authors:
LIU Gang
E-mail: gliu66@163.com
|
|
[1] LI Xing, WANG Hai-huan, SHEN Qun(李 星, 王海寰, 沈 群). Chinese Journal of Food Science(中国食品学报), 2017, 17(7): 248.
[2] Wafula W N, Korir N K, Ojulong H F, et al. Agronomy Journal, 2018, 8(2): 24.
[3] LIANG Ke-hong, ZHU Da-zhou, SUN Jun-mao(梁克红, 朱大洲, 孙君茂). Food Industry(食品工业), 2017, 38(4): 192.
[4] FENG Nai-hong, HOU Dong-hui, YANG Cheng-yuan, et al(冯耐红, 侯东辉, 杨成元，等). Food Industry Technology (食品工业科技), 2020, 448(8): 230.
[5] Bai J, Yue P, Dong Q, et al. Scientific Reports, 2021, 11(1): 1.
[6] LI Xiu-ping, LI Jie-qing, LI Tao, et al(李秀萍, 李杰庆, 李 涛, 等). Mycosystema(菌物学报), 2019, 38(4): 494.
[7] WANG Xin-rui, LIU Zhen-fang, LI Feng, et al(王鑫瑞, 刘振芳, 李 峰，等). Lishizhen Medicine and Materia Medica Research(时珍国医国药), 2020, 31(9): 2152.
[8] Ma L, Gao R, Han H J, et al. Optik, 2020, 224: 165712.
[9] Chen L, Huang J F, Qin Y Z, et al. Spectrochim. Acta A: Mol. Biomol. Spectrosc., 2018, 199: 271.
[10] Wu H, Wei Y, Yang R, et al. Journal of Molecular Structure, 2020, 1218: 128471.
[11] SUN Su-qin, ZHOU Qun, CHEN Jian-bo(孙素琴, 周 群, 陈建波). Infrared Spectrum Analysis and Identification of Traditional Chinese Medicine(中药红外光谱分析与鉴定). Beijing: Chemical Industry Press(北京: 化学工业出版社), 2010: 72.
[12] WENG Shi-fu, XU Yi-zhuang(翁诗甫, 徐怡庄). Fourier Transform Infrared Spectroscopy(傅里叶变换红外光谱分析). 3rd Edition(第3版). Beijing: Chemical Industry Press(北京: 化学工业出版社), 2016. 373.
[13] Tian F, Tan F, Li H. Vibrational Spectroscopy, 2020, 107(C): 103017.
[14] Neves M, Poppi R J. Talanta, 2020, 219: 121338.
[15] Gu D C, Zou M J, Guo X X, et al. Food Chemistry, 2017, 229: 458.
[16] Paul G, WU Hai-long, KANG Chao(Paul G, 吴海龙, 康 超). Practical Guide to Stoichiometry(化学计量学实用指南). Beijing: Science Press(北京：科学出版社), 2012. 77.
|
| [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] |
LI Jin-hua1, 2, ZHANG Min-juan1, 2, WANG Zhi-bin1, 2, LI Shi-zhong1, 2*. The Effect of Instrument Resolution on Passive Ranging of Oxygen A Band[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1974-1978. |
| [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] |
MIAO Shu-guang1, SHAO Dan1*, LIU Zhong-yu2, 3, FAN Qiang1, LI Su-wen1, DING En-jie2, 3. Study on Coal-Rock Identification Method Based on Terahertz
Time-Domain Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1755-1760. |
| [11] |
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. |
| [12] |
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. |
| [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] |
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. |
| [15] |
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. |
|
|
|
|
