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Study of Germinated Rice Seeds by FTIR Spectroscopy Combined With Curve Fitting |
LI Shu-jie1, LIU Jie1, DENG Zi-ang1, 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
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Abstract Seed germination is one of the main components of the seed life course. Agricultural production needs to understand the physiological and biochemical changes in seed germination and accurately determine the vigor of seeds. Therefore, it is of great significance to study seed germination. In order to explore the mobilization of storage materials during seed germination, Fourier transforms infrared spectroscopy (FTIR) combined with curve fitting was used to study rice seeds with different germination days. The rice seeds with different germination times were studied by original infrared spectra, second derivative spectra, two-dimensional correlation infrared spectra and curve fitting. The results showed that the original infrared spectra were overall similar. The spectra reflected that the main storage substances of rice seeds were starch, protein and fat. The absorption peak intensity ratios of A1 659/A1 019, A1 740/A1 019, A1 157/A1 019 and A1 157/A1 081 decreased with germination time. The results of two-dimensional correlation infrared spectroscopy in the range of 814~1 000 and 1 028~1 340 cm-1 showed that the number of auto-peaks, and the position and intensity of the strongest auto-peaks changed with the increase of seed germination time, indicating that carbohydrate and protein changed during seed germination. The second derivative spectra showed seven peaks in the range of 1 200~950 cm-1. The 988 cm-1 peaks shifted to the higher wavenumber with the increase in germination time, while the peaks at 1 053 and 1 158 cm-1 were shifted to a lower wavenumber, which indicated that the structure and content of polysaccharides in rice seeds changed during germination. Nine peaks appeared in the range of 1 700~1 600 cm-1, among which the peaks at 1 641 and 1 692 cm-1 moved to lower wavenumber with the increase in germination time, indicating that the protein structure and content of rice seeds may have changed during germination. In the range of 1 800~1 700 cm-1, only two peaks at 1 712 and 1 744 cm-1. There are observed in the second derivative spectra, which 1 744 cm-1 is caused by the C═O stretching vibration of the lipid substance. In order to further explore the specific changes of storage substances during the germination of rice seeds, curve fitting analysis was carried out in the regions of 1 200~950 and 1 800~1 600 cm-1 of original infrared spectra based on the location and number of sub-peaks determined by the second derivative spectra. The curve fitting results showed that with the increase of germination time, the relative polysaccharide and protein content showed a downward trend, while the relative content of fat first decreased and then increased. The results show that FTIR combined with curve fitting can be an effective method for seed germination study.
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Received: 2020-09-30
Accepted: 2021-03-03
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Corresponding Authors:
LIU Gang
E-mail: gliu66@163.com
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[1] Zhang Y F, Chen C, Chen Y, et al. Food Hydrocolloids, 2019, 91(1): 136.
[2] Basnet P, Amarasiriwardena D, et al. Microchemical Journal, 2016, 127: 152.
[3] LI Qian-feng, YU Jia-wen, LU Jun, et al(李钱峰, 余佳雯, 鲁 军, 等). Jiangsu Agricultural Sciences(江苏农业科学), 2018, 46(4): 60.
[4] ZHANG Hong-sheng, HU Jin(张红生, 胡 晋). Seed Science(Second edition)(种子学(第2版)). Beijing: Science Press(北京: 科学出版社), 2015. 128.
[5] Ma Z G, Bykova N V, Igamerdiev A U. The Crop Journal, 2017, 5(6): 459.
[6] Liu Y, Han C X, Deng X, et al. Journal of Plant Physiology, 2018, 229(6): 63.
[7] Han C X, Zhen S M, Zhu G R, et al. Plant Physiology and Biochemistry, 2017, 115(4): 320.
[8] Zhou Y M, Wang H, Cui L L, et al. Food Chemistry, 2015, 186(3): 224.
[9] Gordon R, Chapman J, Power A, et al. Journal of Cereal Science, 2019, 85(11): 41.
[10] de la Rosa-Millan J, Heredia-Olea E, Perez-Carrillo E, et al. LWT—Food Science and Technology, 2019, 102: 330.
[11] Wang X, Sheng D P, Zhu Z J, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 141(1): 94.
[12] REN Jing, LIU Gang, OU Quan-hong, et al(任 静, 刘 刚, 欧全宏, 等). Chinese Agricultural Science Bulletin(中国农学通报), 2015, 31(17): 58.
[13] YANG Wei-mei, LIU Gang, LIN Hao-jian, et al(杨卫梅, 刘 刚, 林浩坚, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2018, 38(10): 3041.
[14] HUANG Guo-ping(黄国平). Food and Nutrition in China(中国食物与营养), 2005,(12): 25.
[15] WENG Shi-fu, XU Yi-zhuang(翁诗甫, 徐怡庄). FULIYE BIANHUAN HONGWAI GUANGPU FENXI(傅里叶变换红外光谱分析). Beijing: Chemical Industry Press(北京: 化学工业出版社), 2016. 373.
[16] WANG Te, XUE Yong-chang(王 特, 薛永常). China Food Additives(中国食品添加剂), 2011,(2): 105.
[17] ZHAO Ming, ZHANG Hong-xiang, YAN Hong, et al(赵 明, 张红香, 颜 宏, 等). Soils and Crops(土壤与作物), 2018, 7(2): 189.
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