Quantitative structure-retention relationship studies of aroma components from pineapple based on neural network

Authors

QIN Zheng-long, College of Chemistry and Materials Science, Jiangsu Normal University, Xuzhou, Jiangsu 221116, China
FENG Chang-jun, College of Chemistry & Chemical Engineering, Xuzhou Institute of Technology, Xuzhou, Jiangsu 221008, China

Abstract

In order to study chromatographic retention time (RT) of aroma components from pineapple, molecular valence connectivity index (^mX^V_t), molecular shape index (ⁿK) and electrotopological state index (E_i) of 44 aroma components were calculated. ²X^V_p and ⁴X^V_c of the molecular valence connectivity indices, and ¹K and ²K of the molecular shape indices, E₈ and E₁₃ of the electrotopological state indices were optimized. The six parameters were used as input variables of neural network and the chromatographic retention time was used as output variable，and the 6∶3∶1 network structure was adopted and BP neural network method was used to establish a satisfying QSRR prediction model. The total correlation coefficient was 0.995. The predicted values by the model were in agreement those of the experiment values. A good nonlinear relationship between the chromatographic retention time and the six molecular structure parameters was found. The model could better elucidate the changing rule of chromatography retention time of the aroma components.

Publication Date

1-28-2021

First Page

30

Last Page

33

DOI

10.13652/j.issn.1003-5788.2021.01.003

Recommended Citation

Zheng-long, QIN and Chang-jun, FENG (2021) "Quantitative structure-retention relationship studies of aroma components from pineapple based on neural network," Food and Machinery: Vol. 37: Iss. 1, Article 3.
DOI: 10.13652/j.issn.1003-5788.2021.01.003
Available at: https://www.ifoodmm.cn/journal/vol37/iss1/3

References

[1] 姜永超, 李柳基, 袁源, 等. 不同酿酒酵母对菠萝果汁发酵特性的比较[J]. 食品科技, 2018, 43(11): 90-97.
[2] 刘延波, 王娜, 赵志军, 等. 响应面法优化菠萝梨酒的发酵工艺[J]. 食品研究与开发, 2020, 41(8): 124-129, 159.
[3] 张庆庆, 郑天柱, 汤文晶, 等. 红曲菠萝酒发酵及香气成分的分析[J]. 食品工业科技, 2015, 36(19): 209-301, 317.
[4] 王花俊, 张峻松, 刘利锋. 菠萝挥发性成分的GC-MS分析[J]. 食品研究与开发, 2009, 30(12): 134-137.
[5] 魏长宾, 刘胜辉, 陆新华, 等. 菠萝果实香气成分多样性研究[J]. 热带作物学报, 2016, 37(2): 418-426.
[6] 刘胜辉, 孙伟生, 陆新华, 等. 6个菠萝品种成熟果实香气成分分析[J]. 热带作物学报, 2015, 36(6): 1 179-1 185.
[7] 张钰乾. 菠萝芳香物质组成及影响因子研究[D]. 南宁: 广西大学, 2013: 11-43.
[8] 曹明宇, 杨志豪, 罗凌, 等. 基于神经网络的药物实体与关系联合抽取[J]. 计算机研究与发展, 2019, 56(7): 1 432-1 440.
[9] 胡欣颖, 李洪军, 李少博, 等. 对比研究响应面法和BP神经网络—粒子群算法优化调理松板肉加工工艺[J]. 食品与发酵工业, 2019, 45(24): 179-187.
[10] 万赐晖, 贾文珅, 王纪华, 等. 基于人工神经网络算法的电子鼻系统在食品无损检测中的应用[J]. 食品与机械, 2016, 32(10): 221-225.
[11] 石佳超, 罗坤, 樊建人, 等. 基于CMAQ与前馈神经网络的区域大气污染物浓度快速响应模型[J]. 环境科学学报, 2018, 38(11): 4 480-4 489.
[12] 杨志锐, 郑宏, 郭中原, 等. 基于网中网卷积神经网络的红枣缺陷检测[J]. 食品与机械, 2020, 36(2): 140-145, 181.
[13] 张婷, 梁逸曾, 赵晨曦, 等. 基于分子结构预测气相色谱程序升温保留指数[J]. 分析化学, 2006, 34(11): 1 607-1 610.
[14] 秦文斌, 冷检, 秦正龙, 等. 金莲花挥发性组分色谱保留值的构效关系研究[J]. 日用化学工业, 2014, 44(12): 680-682.
[15] 孙运佳, 张荣荣, 施宇靖, 等. 新型苯并噻(噁)唑酮衍生物抑制黄瓜炭疽菌活性的QSAR研究[J]. 化学研究与应用, 2016, 28(6): 818-823.
[16] 许禄, 邵学广. 化学计量学方法[M]. 北京: 科学出版社, 2004: 287.
[17] 冯长君. 物质构效学与应用[M]. 徐州: 中国矿业大学出版社, 2017: 3.