Study on the Rapid Determination of Neophytadiene Content in Tobacco by NIR Spectroscopy

Panpan YANG; Wenzhong ZHOU; Folin LI; Changgui QIU; Hui GAO; Longqing ZHAO; Jing LIU

doi:10.12101/j.issn.1004-390X(n).201901011

JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science） > 2019 > 34(6): 994-999. > DOI: 10.12101/j.issn.1004-390X(n).201901011

Panpan YANG, Wenzhong ZHOU, Folin LI, et al. Study on the Rapid Determination of Neophytadiene Content in Tobacco by NIR Spectroscopy[J]. JOURNAL OF YUNNAN AGRICULTURAL UNIVERSITY（Natural Science）, 2019, 34(6): 994-999. DOI: 10.12101/j.issn.1004-390X(n).201901011

Citation:

PDF (1028 KB)

Study on the Rapid Determination of Neophytadiene Content in Tobacco by NIR Spectroscopy

1.
School of Civil Engineering, Southwest Forestry University, Kunming 650224, China
2.
Yunnan Comtestor Detection Technology Co., Ltd., Kunming 650106, China
3.
College of Tobacco Science, Yunnan Agricultural University, Kunming 650201, China

More Information

Received Date: January 03, 2019
Revised Date: September 16, 2019
Available Online: November 27, 2019
Published Date: October 31, 2019

Graphical Abstract

Abstract

Abstract

PurposeTo explore a rapid method for determining the content of neophytadiene in flue cured tobacco leaves which was based on near infrared spectrum (NIR).
MethodNear infrared technology combined with spectral pretreatment (multiple scattering correction + second derivative + Norris smoothing), abnormal sample removal (module iterative singular sample diagnosis), wavelength optimization based on competitive adaptive weighting (CARS) algorithm, and model wavelength variable optimization based on RMSECV with cross-validation root mean square error (RMSECV) were used. A near infrared PLS calibration model for neophytadiene content in flue-cured tobacco leaves was established. The accuracy and stability of the model was verified by internal parameters (R² of calibration model), RMSECV, RMSEC and RMSEP of external verification set and their paired t-test results.
Results(1) The main wavelength ranges of the calibration model are 2 464.58-2 450.60 nm, 1 962.7-1 959.74 nm, 1 767.37-1 763.76 nm, 1 687.98-1 681.41 nm, 1 425.36-1 419.90 nm, 1 412.93-1 409.86 nm, 1 180.66-1 177.98 nm, 1 174.78 -1 173.18 nm, 1 168.95-1 167.37 nm and 1 156.44-1 154.38 nm. (2) The value of RMSEC is 18.602. The value of R² is 0.882 7 were used to calibrate the near infrared calibration model of neophytadiene in flue-cured tobacco leaves. The prediction error of external validation set is 20.995. The paired t-test results between the predicted and measured values of 20 external verification sets show that there is no significant difference between the two groups at the level of alpha 0.05.
ConclusionThe internal parameters and external validation results show that the calibration model has good prediction accuracy. The above results show that the method can quickly and accurately determine neophytadiene in flue-cured tobacco leaves, and has good practical value.
- tobacco,
- neophytadiene,
- near infrared reflectance spectroscopy,
- calibration model

FullText(HTML)

References (28)

References

[1]	韩锦峰, 袁秀秀, 谢晓辉, 等. 同一品种在不同生态区烟叶化学品质的差异[J]. 中国烟草学报, 2016, 22(5): 70. DOI: 10.16472/j.chinatobacco.2016.170.
[2]	王鹏泽, 赵铭钦, 刘鹏飞, 等. 浓香型产区烤烟中性致香成分与生物碱组成及含量[J]. 中国烟草科学, 2014, 35(5): 98. DOI: 10.13496/j.issn.1007-5119.2014.05.019.
[3]	周芳芳, 张晓龙, 詹军, 等. 典型清香型烤烟产地间致香物质含量及组成差异分析[J]. 中国烟草学报, 2016, 22(2): 34. DOI: 10.16472/j.chinatobacco.2014.085.
[4]	李玲燕, 徐宜民, 刘百战, 等. 不同生态区域烤烟烟叶香气物质分析[J]. 中国烟草科学, 2015, 36(3): 1. DOI: 10.13496/j.issn.1007-5119.2015.03.001.
[5]	赵晓丹, 鲁喜梅, 史宏志, 等. 不同烟草类型烟叶中性致香成分和生物碱含量差异[J]. 中国烟草科学, 2012, 33(2): 7. DOI: 10.3969/j.issn.1007-5119.2012.02.002.
[6]	王春凯, 王英俊, 矫海楠, 等. 不同采收成熟度烤后烟叶香气质量评价[J]. 中国烟草科学, 2016, 37(3): 22. DOI: 10.13496/j.issn.1007-5119.2016.03.004.
[7]	王玉, 王保兴, 武怡, 等. 卷烟挥发性成分的聚类分析[J]. 烟草科技, 2007(2): 48. DOI: 10.3969/j.issn.1002-0861.2007.02.013.
[8]	WANG J A, YANG G H, LI C X. Zonal distribution of neutral aroma components in flue-cured tobacco leaves[J]. Phytochemistry Letters, 2018, 24: 125. DOI: 10.1016/j.phytol.2018.01.014.
[9]	褚小立, 陆婉珍. 近五年我国近红外光谱分析技术研究与应用进展[J]. 光谱学与光谱分析, 2014, 34(10): 2595. DOI: 10.3964/j.issn.1000-0593(2014)10-2595-11.
[10]	王加华, 张晓伟, 王军, 等. 基于便携式近红外技术的生鲜乳品质现场评价[J]. 光谱学与光谱分析, 2014, 34(10): 2679. DOI: 10.3964/j.issn.1000-0593(2014)10-2679-06.
[11]	徐霞, 成芳, 应义斌. 近红外光谱技术在肉品检测中的应用和研究进展[J]. 光谱学与光谱分析, 2009, 29(7): 1876. DOI: 10.3964/j.issn.1000-0593(2009)07-1876-05.
[12]	张翼, 杨征宇, 葛炯, 等. 近红外分析技术在烟草中的应用[J]. 计算机与应用化学, 2016, 33(2): 251. DOI: 10.16866/j.com.app.chem201602026.
[13]	邱军, 张怀宝, 宋岩, 等. 近红外光谱分析技术在烟草行业的应用[J]. 中国烟草科学, 2008, 29(1): 55. DOI: 10.3969/j.issn.1007-5119.2008.01.013.
[14]	宾俊, 范伟, 周冀衡, 等. 近红外技术结合SaE-ELM用于烤烟烘烤关键参数的在线监测[J]. 烟草科技, 2016, 49(9): 50. DOI: 10.16135/j.issn1002-0861.2015.0571.
[15]	邢雪霞, 刘国顺, 贾方方, 等. 烤烟叶片色素含量的高光谱预测模型研究[J]. 中国烟草学报, 2014, 20(1): 54. DOI: 10.3969/j.issn.1004-5708.2014.01.010.
[16]	DBT 497—2013. 烟草及烟草制品主要化学成分指标近红外校正模型建立与验证导则[S].
[17]	李劲, 杨盼盼, 唐文旭, 等. 基于波长优选的小柴胡颗粒黄芩苷近红外校正模型建立[J]. 中国实验方剂学杂志, 2016, 22(18): 72. DOI: 10.13422/j.cnki.syfjx.2016180072.
[18]	梁逸曾, 许青松. 复杂体系仪器分析—白、灰、黑分析体系及其多变量解析方法[M]. 北京: 化学工业出版社, 2012.
[19]	LI H D, LIANG Y Z, CAO D S, et al. Model-population analysis and its applications in chemical and biological modeling[J]. TrAC Trends in Analytical Chemistry, 2012(38): 154. DOI: 10.1016/j.trac.2011.11.007.
[20]	LI H D, LIANG Y Z, XU Q S, et al. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration[J]. Analytica Chimica Acta, 2009, 648(1): 77. DOI: 10.1016/j.aca.2009.06.046.
[21]	GB/T 29858—2013. 分子光谱多元校正定量分析通则[S].
[22]	孟祥东, 赵铭钦, 李元实, 等. 不同耕作模式对烤烟常规化学成分、经济指标及香气成分的影响[J]. 云南农业大学学报(自然科学), 2010, 25(5): 642. DOI: 10.3969/j.issn.1004-390X.2010.05.009.
[23]	李晓婷, 荣凡番, 罗云, 等. 典型香型间和地区间烟叶中性致香物质组成与含量差异[J]. 云南农业大学学报(自然科学), 2017, 32(6): 1036. DOI: 10.16211/j.issn.1004-390X(n).2017.06.011.
[24]	胡小曼, 李佛琳, 杨焕文, 等. 丽江烟区烤烟烟叶致香物质和常规化学成分及其相关性研究[J]. 云南农业大学学报(自然科学), 2011, 26(S2): 41. DOI: 10.3969/j.issn.1004-390X(n).2011.z2.007.
[25]	陈兴, 张天栋, 邓国宾, 等. 红大烟花香料挥发性成分分析及其在卷烟中的应用[J]. 云南农业大学学报(自然科学), 2018, 33(4): 663. DOI: 10.12101/j.issn.1004-390X(n).201702004.
[26]	师君丽, 杨虹琦, 宋春满, 等. 云南不同生态烟区烤烟主要挥发性香气物质含量的比较[J]. 云南农业大学学报(自然科学), 2011, 26(6): 790. DOI: 10.3969/j.issn.1004-390X(n).2011.06.011.
[27]	SANTOS C A T D, PÁSCOA R N, LOPO M, et al. Applications of portable near-infrared spectrometers[M]// ROBERT A M. Encyclopedia of analytical chemistry. John Wiley & Sons, Ltd, 2015.
[28]	PASQUINI C. Near infrared spectroscopy: a mature analytical technique with new perspectives - a review[J]. Analytica Chimica Acta, 2018, 1026: 8. DOI: 10.1016/j.aca.2018.04.004.

Cited By

Cited by

Periodical cited type(6)

1.	付光明，高子婷，杨建新，李怀奇，罗菲，梁一凡，严定伟，韦凤杰，常剑波，姬小明. 基于近红外光谱的烤烟油分识别研究. 河南农业大学学报. 2024(04): 583-591 .
2.	李华杰，王道铨，朱叶梅，林志平，张建平，杨盼盼，罗登炎，邱昌桂. 近红外光谱结合模式识别方法所建模型分析卷烟烟丝配方比例. 理化检验-化学分册. 2022(07): 760-767 .
3.	王文伦，汪应华，刘羿男，肖毅为，吴佳，王永平，方亮，汪华国，胡小东. 密集烘烤干筋期最高温度对烟叶致香物质的影响. 安徽农业科学. 2022(16): 130-134 .
4.	胡超，张玎婕，胡志忠，宋凌勇，李志华，务文涛，张峻松. 烟叶新植二烯的提取及热裂解分析. 食品与机械. 2022(10): 178-186 .
5.	蔡庭秀，叶英，乔杨波，刘哲，王进英. 青藏高原狭果茶藨子籽油成分分析及原油三脱工艺优化. 食品工业科技. 2021(22): 212-222 .
6.	王冰，赵乐，余晶晶，蔡君兰，丁美宙，彭斌，赵俊伟，赵晓东，秦亚琼，刘克建，刘绍锋，谢复炜. 不同生态区烟叶新植二烯含量的反吹气相色谱法检测与分析. 中国烟草科学. 2021(06): 66-73 .

Other cited types(1)

Get Citation

PDF

XML

Article views (2207) PDF downloads (23) Cited by(7)

Turn off MathJax

Article Contents

Abstract

References

Study on the Rapid Determination of Neophytadiene Content in Tobacco by NIR Spectroscopy

Abstract

References

Cited by

Periodical cited type(6)

Other cited types(1)

Catalog

Export File

Citation

Format

Content