光谱学与光谱分析 |
|
|
|
|
|
Measuring Fatty Acid Concentration in Maize Grain by Near-Infrared Reflectance Spectroscopy |
YANG Xiao-hong, GUO Yu-qiu, FU Yang, HU Jie-yun, CHAI Yu-chao, ZHANG Yi-rong, LI Jian-sheng* |
National Maize Improvement Center of China, Key Lab of Crop Genetics and Breeding of Beijing, China Agricultural University,Beijing 100094, China |
|
|
Abstract The fatty acid concentrations in maize grain were analyzed with a set of 294 samples including normal inbred lines, high-oil inbred lines and high-oil recombinant inbred lines (RIL). The method of partial least squares (PLS) regression with internal cross validation was employed to develop the measuring models of near-infrared reflectance spectroscopy (NIRS) for concentrations of four major fatty acids, palmitic, stearic, oleic and linoleic acids, as well as oil concentration in maize grain. The NIRS models were accurate for oleic acid, linoleic acid and oil concentrations. The determination coefficients of these models in cross validation were 0.89, 0.88 and 0.91, respectively; the determination coefficients in external validation were 0.86, 0.84 and 0.92, respectively; and the ratio of standard deviation (SD) to root mean square error of validation (RMSEV) in both calibration and external validation sets (RSC(P)) was higher than 2.5. But the models for palmitic and stearic acid concentrations were not accurate enough with determination coefficients in cross validation and external validation lower than 0.80, and RSC(P) lower than 2.5. Further practical validation showed that the predicted results by using NIRS models for oleic acid, linoleic acid and oil concentrations were accurate and reliable, which will be a useful approach to the measurement of a large number of breeding samples during genetic improvement of oil quality and quantity in maize.
|
Received: 2007-09-12
Accepted: 2007-12-05
|
|
Corresponding Authors:
LI Jian-sheng
E-mail: lijiansheng@cau.edu.cn
|
|
[1] Lambert R. High-Oil Corn Hybrids, in Special Corn, Ed by Hallau A R. CRC Press Inc, Boca Raton, Florida, 2001. 131. [2] Mattson F H, Grundy S M. Journal of Lipid Research, 1985, 26: 194. [3] WEI Liang-ming, JIANG Hai-ying, LI Jun-hui, et al(魏良明, 姜海鹰, 李军会, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2005, 25(9): 1404. [4] BI Jing-cui, ZHANG Wen-wei, XIAO Ying-hui, et al(毕京翠,张文伟,肖应辉,等). Acta Agronomica Sinica(作物学报), 2006, 32(5): 709. [5] XIAO Xin, XIE Xin-hua, CHEN Yi, et al(肖 昕,谢新华,陈 奕,等). Scientia Agricultura Sinica(中国农业科学), 2004, 37(11): 1709. [6] González-Martín I, Hernández-Hierro J M, Bustamante-Rangel M, et al. Analytical and Bioanalytical Chemistry, 2006, 386: 1553. [7] BAI Qi-lin, CHEN Shao-jiang, DONG Xiao-ling, et al(白琪林, 陈绍江, 董晓玲, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(2): 271. [8] Velasco L, Becker H C. Euphytica, 1998, 101: 221. [9] WU Jian-guo, SHI Chun-hai, ZHANG Hai-zhen(吴建国, 石春海, 张海珍). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(2): 259. [10] Kim K S, Park S H, Choung M G, et al. Journal of Crop Science and Biotechnology, 2007, 10: 15. [11] Satoa T, Mawb A A, Katsutac M. Journal of the American Oil Chemists’ Society, 2003, 80(12): 1157. [12] Kovalenko I V, Rippke G R, Hurburgh C R. Journal of the American Oil Chemists’ Society, 2006, 83(5): 421. [13] Sukhija P S, Palmquist D L. Journal of Agricultural and Food Chemistry, 1988, 36: 1202. [14] Murray I. Forage Analysis by Near Infrared Spectroscopy, in Sward Measurement Handbook, 2nd edn, Ed by Davies A, Baker R D, Grant S A, et al. The British Grassland Society, 1993. 285.
|
[1] |
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. |
[2] |
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. |
[3] |
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. |
[4] |
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. |
[5] |
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. |
[6] |
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. |
[7] |
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. |
[8] |
WANG Li-qi1, YAO Jing1, WANG Rui-ying1, CHEN Ying-shu1, LUO Shu-nian2, WANG Wei-ning2, ZHANG Yan-rong1*. Research on Detection of Soybean Meal Quality by NIR Based on
PLS-GRNN[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1433-1438. |
[9] |
FU Yan-hua1, LIU Jing2*, MAO Ya-chun2, CAO Wang2, HUANG Jia-qi2, ZHAO Zhan-guo3. Experimental Study on Quantitative Inversion Model of Heavy Metals in Soda Saline-Alkali Soil Based on RBF Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1595-1600. |
[10] |
LI Jia-yi1, YU Mei1, LI Mai-quan1, ZHENG Yu2*, LI Pao1, 3*. Nondestructive Identification of Different Chrysanthemum Varieties Based on Near-Infrared Spectroscopy and Pattern Recognition Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1129-1133. |
[11] |
CHEN Chu-han1, ZHONG Yang-sheng2, WANG Xian-yan3, ZHAO Yi-kun1, DAI Fen1*. Feature Selection Algorithm for Identification of Male and Female
Cocoons Based on SVM Bootstrapping Re-Weighted Sampling[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1173-1178. |
[12] |
LI Xue-ying1, 2, LI Zong-min3*, CHEN Guang-yuan4, QIU Hui-min2, HOU Guang-li2, FAN Ping-ping2*. Prediction of Tidal Flat Sediment Moisture Content Based on Wavelet Transform[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1156-1161. |
[13] |
ZHANG Xiao-hong1, JIANG Xue-song1*, SHEN Fei2*, JIANG Hong-zhe1, ZHOU Hong-ping1, HE Xue-ming2, JIANG Dian-cheng1, ZHANG Yi3. Design of Portable Flour Quality Safety Detector Based on Diffuse
Transmission Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1235-1242. |
[14] |
ZHENG Kai-yi1, ZHANG Wen1, DING Fu-yuan1, ZHOU Chen-guang1, SHI Ji-yong1, Yoshinori Marunaka2, ZOU Xiao-bo1*. Using Ensemble Refinement (ER) Method to OptimizeTransfer Set of Near-Infrared Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1323-1328. |
[15] |
CHENG Jie-hong1, CHEN Zheng-guang1, 2*, YI Shu-juan2. Wavelength Selection Algorithm Based on Minimum Correlation Coefficient for Multivariate Calibration[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 719-725. |
|
|
|
|