近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量

引用本文: 谢越, 周成, 涂从, 张祖亮, 汪建飞. 近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量[J]. 分析化学, 2017, 45(3): 363-368. doi: 10.11895/j.issn.0253-3820.160773 shu

Citation: XIE Yue, ZHOU Cheng, TU Cong, ZHANG Zu-Liang, WANG Jian-Fei. Quantitative Determination of Ferulic Acid Content in Chrysanthemum Morifolium cv.(Chuju) Continuous Cropping Soil Using Near Infrared Spectroscopy[J]. Chinese Journal of Analytical Chemistry, 2017, 45(3): 363-368. doi: 10.11895/j.issn.0253-3820.160773 shu

近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量

谢越 ^1,2, ,
周成 ^3, ,
涂从 ^2, ,
张祖亮 ^4, ,
汪建飞 ^1,

1.
安徽科技学院资源与环境学院, 凤阳 233100;
2.
Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA;
3.
安徽科技学院生命科学学院, 凤阳 233100;
4.
六安市食品药品检验中心, 六安 237009
基金项目:
本文系国家自然科学基金项目(No.21607002)、安徽省自然科学基金项目(No.1508085QD74)、安徽省高校自然科学研究项目(No.KJ2015A188)、农业部生物有机肥创制重点实验室开放课题(No.BOFC2015KB04)、2016年高校中青年骨干人才重点项目(No.gxfxZD2016182)资助

摘要: 应用近红外光谱(NIRS)技术定量分析连作滁菊土壤样品中阿魏酸的含量。通过标准杠杆值、学生残差和马氏距离判断异常光谱，经二阶导数和Norris平滑滤噪预处理后，在6000~4000 cm^-1范围，最佳因子数为7，采用偏最小二乘法(PLS)构建数学模型。结果表明，模型校正集和验证集与高效液相色谱仪(HPLC)测定的参考值之间均呈现良好相关关系，校正相关系数R_c为0.9914，交叉验证相关系数R_cv为0.9935，校正集误差均方根(RMSEC)为0.484，预测误差均方根(RMSEP)为0.539，交叉验证误差均方根(RMSECV)为0.615。研究结果表明，NIRS分析技术能够实现连作土壤中阿魏酸的快速检测，结果准确可靠。

关键词:

English

Quantitative Determination of Ferulic Acid Content in Chrysanthemum Morifolium cv.(Chuju) Continuous Cropping Soil Using Near Infrared Spectroscopy

1.
College of Resources and Environment, Anhui Science and Technology University, Fengyang 233100, China;
2.
Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA;
3.
College of Life Science, Anhui Science and Technology University, Fengyang 233100, China;
4.
Lu'an Institute for Food and Drug Control Center, Lu'an 237009, China
Received Date: 19 October 2016
Revised Date: 14 December 2016
Fund Project:
This work was supported by the National Natural Science Foundation of China (No.21607002) and the Natural Science Foundation of Anhui Province, China (No.1508085QD74)

Abstract: A near infrared spectroscopy (NIRS) method was used for rapid quality evaluation of ferulic acid content in chrysanthemum morifolium cv. (Chuju) continuous cropping soil. Standard leverage, studentized residual and Mahalanobis distance were calculated to eliminate abnormal samples. After the initial near infrared spectrum was treated by two second derivative and Norris smoothing filter noise, 6000-4000 cm^-1 wave number range and 7 factors were chosen for partial least squares (PLS) calibration model. The results showed that good correlation was presented between the calibration set/validation set and the values determined by high performance liquid chromatography, and the calibration correlation coefficient (R_c) and validation correlation coefficient (R_cv) were 0.9914 and 0.9935, respectively. Root mean square error of calibration (RMSEC), root mean square error of validation (RMSEP) and root mean square error of cross-validation (RMSECV) were 0.484, 0.539 and 0.615, respectively. This method was accurate, reliable, simple, rapid and nondestructive, and could be applied to the fast analysis for ferulic acid in continuous cropping soil.

Key words:

Near infrared transmittance spectroscopy
/ Continuous cropping soil
/ Chrysanthemum morifolium cv.(Chuju)
/ Phenolic acids
/ Ferulic acid

1. [1]
  SHU Jun-Sheng, HUANG Gui-Dong, MAO Jian. Chinese J. Inst. Food Sci. Tech., 2013,13(4):207-213 舒俊生, 黄桂东, 毛健.中国食品学报,2013,13(4):207-213
2. [2]
  XIE Yue, XIAO Xin, ZHOU Yi, CHEN Shi-Yong, LI Xiao-Liang, XING Su-Zhi, WANG Jian-Fei. J. Nanjing Agri. Univ., 2012,06:19-24 谢越, 肖新, 周毅, 陈世勇, 李孝良, 邢素芝, 汪建飞.南京农业大学学报,2012,06:19-24
3. [3]
  XIE Yue, YU Hao, WANG Jian-Fei, ZHANG Zu-Liang, CHEN Si-Yong, XIAO Xin, LI Xiao-Liang. Chinese J. Anal. Chem., 2013,41(3):383-388 谢越, 俞浩, 汪建飞, 张祖亮, 陈世勇, 肖新, 李孝良.分析化学,2013,41(3):383-388
4. [4]
  WANG Xiao-mei, JIAO Long, LIU Xiao-li, LI Hua. Chin. J. Pharm. Anal., 2011,31(6):1016-1019 王小梅, 焦龙, 刘小丽, 李华.药物分析杂志,2011,31(6):1016-1019
5. [5]
  GU Zhi-Rong, ZHANG Ya-Ya, DING Jun-Xia, SUN Yu-Jing. Nat. Prod. Res. Dev., 2015,27:849-853, 889 顾志荣, 张亚亚, 丁军霞, 王亚丽, 孙宇靖.天然产物研究与开发,2015,27:849-853, 889
6. [6]
  CHEN Jia-Le, JIN Ye, CHEN Hong-Ying, LIU Xue-Song, LIU Zhi-Gang, LI Ya-Qiong, LUAN Lian-Jun. Chinese Herbal Med., 2016,47(6):1004-1009 陈佳乐, 金叶, 陈红英, 刘雪松, 刘志刚, 李琼娅, 栾连军.中草药,2016,47(6):1004-1009
7. [7]
  Xie Y F, Bi W W, Wang X J, Zhang X L, Zhang X N, Zhao G X, Liu Q Q. J. Food Process. Preserva., 2016,DOI: 10.1111/jfpp.13119
8. [8]
  Wang J P, Li N B, Luo H Q. Spectrochim. Acta A, 2008,71(1):204
9. [9]
  CHU Xiao-Li, LU Wan-Zhen. Spectroscopy and Spectral Analysis, 2014, 346(10):2595-2605 褚小立, 陆婉珍.光谱学与光谱分析,2014,34(10):2595-2605
10. [10]
  LUAN Lian-Jun, CHEN Na, LIU Xue-Song, WU Yong-Jiang. Chinese J. Anal. Chem., 2012,40(4):626-629 栾连军, 陈娜, 刘雪松, 吴永江.分析化学,2012,40(4):626-629
11. [11]
  FANG Xiao-Rong, ZHANG Hai-Liang, HUANG Ling-Xia, HE Yong. Spectroscopy and Spectral Analysis, 2014, 35(5):1248-1252 方孝荣, 章海亮, 黄凌霞, 何勇.光谱学与光谱分析,2015,35(5):1248-1252
12. [12]
  ZHU Xiang-Rong, LI Gao-Yang, HUANG Lv-Hong, SU Dong-Lin, LIU Wei, SHAN Yang. Chinese J. Anal. Chem.,2015, 43(4):599-603 朱向荣, 李高阳, 黄绿红, 苏东林, 刘伟, 单杨.分析化学,2015,43(4):599-603
13. [13]
  Bin J, Ai F F, Fan W, Zhou J H, Yun Y H, Liang Y Z. RSC Adv., 2016,6, 30353-30361
14. [14]
  LU Yong-Jun, CHEN Hua-Cai, LV Jin, CHEN Xing-Dan. Chinese J. Anal. Chem., 2005,33(6):835-837 芦永军, 陈华才, 吕进, 陈星旦.分析化学,2005,33(6):835-837
15. [15]
  ZHU Xiang-Rong, LI Gao-Yang, HUANG LYU-Hong, SU Dong-Lin, LIU Wei, SHAN Yang. Chinese J. Anal. Chem., 2015,43(4):599-603 朱向荣, 李高阳, 黄绿红, 苏东林, 刘伟, 单杨.分析化学,2015,43(4):599-603
16. [16]
  LU Yong-Hun, QU Yan-Ling, ZHANG Jun, PIAO Ren-Guan. Spectrosc. Spect. Anal., 2004,24(6):744-747 芦永军, 曲艳玲, 张军, 朴仁官.光谱学与光谱分析,2004,24(6):744-747
17. [17]
  Pande R, Mishra H N. Food Chem., 2015,172:880-884
18. [18]
  GENG Shu, CHEN Yong, JIN Ye, LUAN Lian-Jun, LIU Xue-Song, WU Yong-Jiang. Chin. J. Mod. Appl. Pharm., 2016,33(2):144-150 耿姝, 陈勇, 金叶, 栾连军, 刘雪松, 吴永江.中国现代应用药学,2016,33(2):144-150
19. [19]
  Raquel C M, Maria P C, Yash D, Denisio T, Laura A J, Patrick C, Carl S. J. Near Infrared Spec., 2015,23(4):245-253

扫一扫看文章

计量

PDF下载量: 2
文章访问数: 571
HTML全文浏览量: 66

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量

English

Quantitative Determination of Ferulic Acid Content in Chrysanthemum Morifolium cv.(Chuju) Continuous Cropping Soil Using Near Infrared Spectroscopy

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南：你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

计量

通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

近红外光谱技术定量分析连作滁菊土壤中的阿魏酸含量

English

Quantitative Determination of Ferulic Acid Content in Chrysanthemum Morifolium cv.(Chuju) Continuous Cropping Soil Using Near Infrared Spectroscopy

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南： 你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

计量

文章相关

通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

CCS Chemistry：颜徐州、鲍哲南：你的皮肤可能是一片SPMs