Rapid Prediction of Antioxidant Activity of Coreopsis Tinctoria by Model Established by Near Infrared Spectroscopy with Partial Least Square Regression
摘 要
将10批不同产地的雪菊样品自然干燥,粉碎,过筛,分取0.2 g,加入50 mL 35%(体积分数)甲醇溶液,静置过夜,超声处理30 min,抽滤,收集滤液,采用1,1-二苯基-2-三硝基苯肼(DPPH)法和2,2'-联氮双(3-乙基苯并噻唑啉-6-磺酸)二铵盐(ABTS)法测定雪菊的抗氧化活性(参考值)。利用近红外光谱仪对100个雪菊粉末样品分别进行光谱扫描,采用近红外积分球漫反射模式进行光谱采集,分别采用标准正态变量(SNV)+连续小波变换(CWT)和CWT对原始近红外光谱数据进行预处理,结合偏最小二乘回归(PLSR),在4 767~4 960 cm-1、5 153~6 966 cm-1、7 120~8 813 cm-1波段内建立DPPH抗氧化活性模型,在5 153~7 081 cm-1、7 660~8 624 cm-1波段内建立ABTS抗氧化活性模型。结果表明:DPPH抗氧化活性模型的交叉验证均方根误差(RMSECV)为0.772,相关系数(R)为0.948,预测残差值(RPD)为3.17;ABTS抗氧化活性模型的RMSECV为0.365,R为0.884,RPD为2.52。利用模型预测雪菊样品的DPPH和ABTS抗氧化活性,预测值和参考值基本一致,并且DPPH抗氧化活性模型的预测均方根误差(RMSEP)为0.705,ABTS抗氧化活性模型的RMSEP为0.377。
Abstract
Ten batches of Coreopsis tinctoria samples from different origins were naturally dried, crushed, and screened. An aliquot (0.2 g) was taken and mixed with 50 mL of 35% (volume fraction) methanol solution. The mixture was settled overnight, and treated by ultrasonic for 30 min. After suction filtration, the filtrate was collected. The antioxidant activities (reference values) of Coreopsis tinctoria were determined by 1,1-diphenyl-2-picrohydrazyl (DPPH) method and 2,2'-diazepine (3-ethylbenzothiazolin-6-sulfonic acid) diamammonium salt (ABTS) method. The near infrared spectrometer was used to scan the spectra of 100 Coreopsis tinctoria powder samples, and the near infrared integrating sphere diffuse reflection mode was used to collect the spectra. The antioxidant activity model of DPPH was established combined with partial least square regression (PLSR) in the wavebands of 4 767-4 960 cm-1, 5 153-6 966 cm-1 and 7 120-8 813 cm-1 after the original near infrared spectra data were pretreated by standard normal variate (SNV)+continuous wavelet transform (CWT), and the antioxidant activity model of ABTS was established combined with PLSR in the wavebands of 5 153-7 081 cm-1 and 7 660-8 624 cm-1 after the original near infrared spectra were pretreated by CWT. The results showed that the root mean square error of cross validation (RMSECV), correlation coefficient (R) and predictive residual value (RPD) of antioxidant activity model of DPPH was 0.772, 0.948 and 3.17, respectively, and those of antioxidant activity model of ABTS were 0.365, 0.884 and 2.52, respectively. The antioxidant activities of DPPH and ABTS of Coreopsis tinctoria samples were predicted by the models, giving results of the predicted values were basically consistent with the reference values, and root mean square error of prediction (RMSEP) of the antioxidant activity model of DPPH was 0.705, and that of the antioxidant activity model of ABTS was 0.377.
中图分类号 O657.3 DOI 10.11973/lhjy-hx202307008
所属栏目 专题报道(化学计量学方法在食品药品分析中的应用)
基金项目 国家自然基金项目(21765012);新疆维吾尔自治区高校科研计划自然科学重点项目(XJEDU2020I016);2021年新疆维吾尔自治区研究生创新项目(XJ2021G315)
收稿日期 2022/1/4
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联系人作者楚刚辉(cghks5@126.com)
备注韩想,硕士研究生,研究方向为现代分离分析
引用该论文: HAN Xiang,HE Xiaogang,YU Jiaping,FENG Yulong,CHU Ganghui. Rapid Prediction of Antioxidant Activity of Coreopsis Tinctoria by Model Established by Near Infrared Spectroscopy with Partial Least Square Regression[J]. Physical Testing and Chemical Analysis part B:Chemical Analysis, 2023, 59(7): 792~797
韩想,贺小刚,于佳萍,冯昱龙,楚刚辉. 近红外光谱结合偏最小二乘回归所建模型快速预测雪菊的抗氧化活性[J]. 理化检验-化学分册, 2023, 59(7): 792~797
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【6】伊丽米热·吾甫尔,库热西·玉努斯,王志滨,等.网络药理学技术预测昆仑雪菊总黄酮治疗非小细胞肺癌作用及初步验证研究[J].天然产物研究与开发, 2021,33(11):1936-1945.
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【8】YAN J, HUANG X P, ZHU W W. Simultaneous determination of antioxidant properties and total phenolic content of Siraitia grosvenorii by near infrared spectroscopy[J]. Journal of Food Measurement and Characterization, 2020,14(4):2300-2309.
【9】TAHIR H E, ZOU X B, TINTING S, et al. Near-infrared (NIR) spectroscopy for rapid measurement of antioxidant properties and discrimination of Sudanese honeys from different botanical origin[J]. Food Analytical Methods, 2016,9(9):2631-2641.
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【12】ZHAO L J, LIU W, XIONG S H, et al. Determination of total flavonoids contents and antioxidant activity of Ginkgo biloba leaf by near-infrared reflectance method[J]. International Journal of Analytical Chemistry, 2018,2018:1-7.
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