| 近红外光谱技术定量分析玉米杂交种纯度 |
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| 引用本文： | 王 庆,薛卫青,马晗煦,李军会,孙宝启,孙 群.近红外光谱技术定量分析玉米杂交种纯度[J].农业工程学报,2012,28(26):259-264. |
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| 作者姓名： | 王 庆 薛卫青 马晗煦 李军会 孙宝启 孙 群 |
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| 作者单位： | 1. 中国农业大学农学与生物技术学院植物遗传育种学系/农业部基因组学与遗传改良重点实验室/北京市作物遗传改良重点实验室，北京 100193;1. 中国农业大学农学与生物技术学院植物遗传育种学系/农业部基因组学与遗传改良重点实验室/北京市作物遗传改良重点实验室，北京 100194;1. 中国农业大学农学与生物技术学院植物遗传育种学系/农业部基因组学与遗传改良重点实验室/北京市作物遗传改良重点实验室，北京 100195;2. 中国农业大学信息与电气工程学院，北京 100193;3. 北京市农林科学院，北京 100097;1. 中国农业大学农学与生物技术学院植物遗传育种学系/农业部基因组学与遗传改良重点实验室/北京市作物遗传改良重点实验室，北京 100193 |
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| 基金项目： | ational natural science fund project (30971792); The Fundamental Research Funds for the Central Universities (2012JW001); China's 12th Five Year Plan of Xinjiang construction corps formation (2012BB046) |
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| 摘 要： | 摘要：应用近红外光谱分析技术结合定量偏最小二乘法对先玉335杂交种纯度进行了定量分析，将不同年份和来源的杂交种和其母本种子粉碎后混合，按0.5%的梯度获得纯度80～100%范围内的样本123份（每梯度按年份和来源设置3个重复）后采集光谱。结果表明：采用散射校正预处理，4 000～8 000 cm-1光谱范围时建模效果较适宜（建模集∶检验集=3∶1），建模集内部交叉决定系数达96.06%，校正标准差1.18%，平均相对误差1.03%；检验集的决定系数均达到95.02%，校正标准差1.28%，平均相对误差1.12%。采用不同比例的建模样品和检验样品时，建模集和检验集的决定系数均在94%以上，证明了近红外光谱技术定量测定玉米杂交种纯度的可行性以及所建模型的稳定性。
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| 关 键 词： | 近红外光谱，最小二乘法，模型，玉米杂交种，纯度 |
| 收稿时间： | 5/9/2012 12:00:00 AM |
| 修稿时间： | 2012/8/29 0:00:00 |
Quantitative analysis of seed purity for maize using near infrared spectroscopy |
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| Wang Qing,Xue Weiqing,Ma Hanxu,Li Junhui,Sun Baoqi and Sun Qun.Quantitative analysis of seed purity for maize using near infrared spectroscopy[J].Transactions of the Chinese Society of Agricultural Engineering,2012,28(26):259-264. |
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| Authors: | Wang Qing Xue Weiqing Ma Hanxu Li Junhui Sun Baoqi and Sun Qun |
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| Abstract: | A quantitative identification model for testing the purity of Xianyu335 hybrid maize seed was built by near infrared reflectance spectroscopy (NIRS) with quantitative partial least squares (QPLS). By grinding and mixing maize hybrid seeds of different years and sources with their female parent seeds, 123 samples were obtained with a 0.5% gradient and purity within the range of 80%-100% (three replicates of every year and every source in each gradient) and the spectra of the samples were collected. The results showed as following: through implementation of scatter correction pretreatment, the wave number range of 4 000-8 000 cm-1 was appropriate for modeling (calibration sets: validation set = 3:1); the internal cross coefficient of determination (R2) for the calibration set reached 96.06%; the standard error of calibration (SEC) was 1.18%; and the Average absolute relative deviation (AARD) was 1.03%. Further, the R2 for the validation set was 95.02%; the SEC was 1.28%; and the AARD was 1.12%. Results of using different ratios of the modeling samples and testing samples showed that the R2 of the calibration set and validation set were all greater than 94%, indicating the feasibility and the stability of NIRS to quantitatively determine the purity of maize hybrid. |
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| Keywords: | near infrared spectroscopy least squares approximations models hybrid maize seed purity |
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