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林业资源管理 ›› 2022, Vol. 0 ›› Issue (6): 138-144.doi: 10.13466/j.cnki.lyzygl.2022.06.021

• 技术应用 • 上一篇    下一篇

近红外光谱技术在闽楠叶片氮含量测定中的应用

涂白连1(), 伍艳芳1,2, 刘新亮2, 郑永杰2, 张月婷2, 徐海宁2()   

  1. 1.江西农业大学 林学院,南昌 330045
    2.江西省林业科学院 国家林业草原樟树工程技术研究中心,南昌 330032
  • 收稿日期:2022-09-05 修回日期:2022-09-15 出版日期:2022-12-28 发布日期:2023-01-16
  • 通讯作者: 徐海宁
  • 作者简介:涂白连(1998-),女,江西九江人,在读硕士,研究方向为林木遗传育种。Email:tbl18370106478@163.com
  • 基金资助:
    江西省重点研发计划项目(20203BBF62W010);江西省重点研发计划项目(20202BBF63006);江西省林业科技创新专项(创新专项〔2021〕15号)

Application of Near-infrared Spectroscopy in the Determination of Nitrogen Content of Phoebe bournei Leaves

TU Bailian1(), WU Yanfang1,2, LIU Xinliang2, ZHENG Yongjie2, ZHANG Yueting2, XU Haining2()   

  1. 1. College of Forestry,Jiangxi Agricultural University,Nanchang 330045,China
    2. Jiangxi Academy of Forestry,Camphor Engineering Technology Research Center for National Forestry and Grassland Administration,Nanchang 330032,China
  • Received:2022-09-05 Revised:2022-09-15 Online:2022-12-28 Published:2023-01-16
  • Contact: XU Haining

摘要:

借助近红外光谱技术,以江西省永丰官山林场楠木种子园的64份闽楠叶片为材料,采用传统的化学分析方法测定闽楠叶片样品的氮元素含量作参考值,同时采集闽楠叶粉末样品的近红外光谱图。运用化学计量学软件NIRCal,选定建模方法、建模波段和预处理方法,建立最优测定模型。另随机抽取10份未知样品对模型进行检验,结合配对样本T检验进行评价。结果表明:用主成分回归方法(PCR)建立的模型效果最好,其校正集相关系数Rc为0.912,校正集均方根误差RMSEC为1.098,交互验证集相关系数Rv为0.897,交互验证集均方根RMSEV为1.192。外部验证结果显示,预测值与实测值的相对偏差范围在0.070~0.705之间,且配对样本T检验结果显示P值为0.116,大于0.05,无显著差异。该方法可用于闽楠营养水平和优质选种的大批量快速检测。

关键词: 闽楠, 氮含量, 干叶粉末, 近红外光谱

Abstract:

Using near-infrared spectroscopy,64 leaves of P.bournei in the P.bournei Seed Garden of Guanshan Forest Farm in Yongfeng,Jiangxi Province were used as materials,and the nitrogen content of P.bournei leaf samples was determined by the traditional chemical analysis method as a reference value.At the same time,the near-infrared spectrum of the P.bournei leaf powder samples was collected.Using the chemometric software NIRCal,the optimal determination model was established by selecting the modeling method,modeling band,and pre-treatment method.In addition,10 unknown samples were randomly selected to test the model,and the paired sample T test was used to evaluate the model.The results showed that the model established by the Principal Component Regression (PCR) method had the best effect;its related coefficient of calibration (Rc) was 0.912;the Root Mean Square Error (RMSEC) of calibration was 1.098;the related coefficient of validation (Rv) was 0.897;and the Root Mean Square Error of validation(RMSEV) was 1.192.The external verification results showed that the relative deviation between the predicted value and the measured value ranged from 0.070 to 0.705,and the paired sample T-test results showed that the P value was 0.116,greater than 0.05,and there was no significant difference.It can be used for large-scale rapid detection of the nutrient level and high-quality seed selection of P.bournei.

Key words: P.bournei, nitrogen content, leaf powder, near infrared reflectance spectroscopy

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