中国农业科学 ›› 2018, Vol. 51 ›› Issue (4): 688-696.doi: 10.3864/j.issn.0578-1752.2018.04.008

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

甘蓝型油菜茎秆纤维组分含量和木质素单体G/S 近红外模型构建

陈雪萍1,刘世尧2,尹能文1,荆凌云1,魏丽娟1,林呐1,肖阳1,徐新福1,李加纳1,刘列钊1

 
  

  1. 1西南大学农学与生物科技学院/重庆市油菜工程技术研究中心,重庆400715;2西南大学园艺园林学院,重庆400715
  • 收稿日期:2017-06-21 出版日期:2018-02-16 发布日期:2018-02-16
  • 通讯作者: 刘列钊,E-mail:liezhao2003@126.com
  • 作者简介:陈雪萍,E-mail:1473718700@qq.com
  • 基金资助:
    国家自然科学基金(31371655)、中央高校基本科研业务费专项(XDJK2017A009)、重庆市科委(cstc2014jcyjA0334,cstc2016shmszx0367)

Construction of a Near Infrared Model for Detecting Stem Fiber Component Content and Lignin Monomer G/S in Rapeseed

CHEN XuePing1, LIU ShiYao2, YIN NengWen1, JING LingYun1, WEI LiJuan1, LIN Na1, XIAO Yang1,  XU XinFu1, LI JiaNa1, LIU LieZhao1   

  1. 1College of Agronomy and Biotechnology, Southwest University/Chongqing Engineering Research Center for Rapeseed,  Chongqing 400715; 2College of Horticulture and Landscape Architecture, Southwest University, Chongqing 400715
  • Received:2017-06-21 Online:2018-02-16 Published:2018-02-16

摘要: 【目的】探索近红外光谱分析技术在甘蓝型油菜茎秆纤维组分含量及木质素单体G/S测定中应用的可能性。【方法】采集近红外光谱,根据马氏距离GH(Global H)筛选出103份纤维组分含量材料和75份木质素单体G/S材料作为定标样品,采用Van Soest法和GC-MS法对茎秆纤维组分含量和木质素单体比例进行测定,统计结果表明定标样品化学测定值变异范围较大,3次重复差异较小,可用于近红外模型构建。运用不同光谱预处理方法和化学计量学方法建立校正模型,对比各模型性能参数,筛选出最优定标模型并用检验集对模型进行验证。【结果】采用修正偏最小二乘法(MPLS)建立模型最佳。中性洗涤纤维(neutral detergent fiber,NDF)、酸性洗涤纤维(acid detergent fiber,ADF)、酸性洗涤木质素(acid detergent lignin,ADL)与木质素单体G/S的交叉验证相关系数(1-VR)分别为0.864、0.861、0.872和0.920,定标相关系数(RSQ)分别为0.892、0.891、0.907和0.953。用检验集对模型进行验证,NDF、ADF、ADL及木质素单体G/S模型的外部检验相关系数(RSQ)分别为0.837、0.818、0.870和0.935,其预测标准差(SEP)为0.680、0.636、0.348和0.054。【结论】试验所建模型质量较好,能快速测量茎秆纤维组分含量和木质素单体G/S,可为油菜抗病抗倒伏育种研究提供技术支持。

关键词: 甘蓝型油菜, 纤维组分含量, 木质素单体G/S, 近红外光谱

Abstract: 【Objective】The aim of this study is to explore the feasibility of rapidly detecting the content of fiber composition and monomer G/S with near-infrared spectroscopy (NIRS) in rapeseed(Brassica napus L.). 【Method】 After the NIRS was collected, 103 samples for fiber component content and 75 for monomer G/S in rapeseed were selected by removing outlier and redundant samples according to measure distance. Fiber component content was measured with Van Soest method and lignin monomer G/S was measured with GC-MS. Subsequently, data analysis showed that the little difference for the chemical test, and the range of variation in the calibration samples was wide enough for building the NIRS models. By using the optimum spectrum pretreatment and regression method along with internal cross validation, the calibration models were established, and the model accuracy was tested. 【Result】The best regression method for prediction of fiber component and lignin monomer G/S in rapeseed was modified partial least-squares (MPLS) by using near infrared spectroscopy. The cross-validation correlation coefficient (1-VR) of NIRS model for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL) and monomer G/S model was 0.864, 0.861, 0.872 and 0.920, respectively, and the determination coefficient (RSQ) was 0.892, 0.891, 0.907 and 0.953, respectively; The results of testing the validation set showed that external validation correlation coefficient (RSQ) was 0.837、0.818、0.870 and 0.935, respectively, and square errors of prediction (SEP) was 0.680, 0.636, 0.348 and 0.054, respectively. 【Conclusion】These results indicated that the model established in our research had relatively high accuracy in prediction tests for stem fiber component content and lignin monomer G/S in rapeseed, which could provide support for rapeseed disease and lodging resistance in research and breeding project.

Key words: Brassica napus, fiber component content, lignin monomer G/S, near infrared spectroscopy