周婷婷,张仲平,孙文闪,朱萌萌,周 敏,张永志,王川丕.最小偏二乘方法和近红外技术快速测定莲子多糖及抗氧化活性[J].食品安全质量检测学报,2020,11(11):3435-3440
最小偏二乘方法和近红外技术快速测定莲子多糖及抗氧化活性
Rapid determination of polysaccharide content and antioxidant activity of lotus seeds by partial least squares regression and near infrared analytical technique
投稿时间:2020-01-20  修订日期:2020-05-27
DOI:
中文关键词:  莲子多糖  抗氧化性  快速预测模型  偏最小二乘方法
英文关键词:lotus seed polysaccharide  oxidation resistance  fast prediction models  partial least squares regression
基金项目:国家重点研发计划项目(2018YFC1603400)
作者单位
周婷婷 绿城农科检测技术有限公司 
张仲平 浙江奇彩环境科技股份有限公司 
孙文闪 绿城农科检测技术有限公司 
朱萌萌 绿城农科检测技术有限公司 
周 敏 绿城农科检测技术有限公司 
张永志 绿城农科检测技术有限公司 
王川丕 绿城农科检测技术有限公司 
AuthorInstitution
ZHOU Ting-Ting Greentown Agricultural Testing Technology Co., Ltd 
ZHANG Zhong-Ping Zhejiang Qicai ECO Technology Co., Ltd 
SUN Wen-Shan Greentown Agricultural Testing Technology Co., Ltd 
ZHU Meng-Meng Greentown Agricultural Testing Technology Co., Ltd 
ZHOU Min Greentown Agricultural Testing Technology Co., Ltd 
ZHANG Yong-Zhi Greentown Agricultural Testing Technology Co., Ltd 
WANG Chuan-Pi Greentown Agricultural Testing Technology Co., Ltd 
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中文摘要:
      目的 对5个主要产区的莲子多糖含量和抗氧化活性进行测定, 分析比较各省份莲子质量差异, 并进一步采用近红外分析技术构建莲子多糖的快速预测模型。方法 采用苯酚-硫酸法测定莲子多糖的含量; 利用对1, 1-二苯基-2-苦肼基自由基(1, 1-diphenyl-2-picozide radical, DPPH)清除率测定莲子的抗氧化活性; 并利用偏最小二乘方法构建莲子多糖的快速预测模型。结果 实现了5个产地的莲子多糖含量及其抗氧化活性的精确测定; 构建的快速预测模型对多糖含量及抗氧化活性预测准确率较好, 模型的训练集均方根差(root-mean-square error, RMSEC)为0.0185, 测试集均方根差(root-mean-square error of prediction, RMSECP)为0.0236; 训练集和测试集相关系数的平方分别达到了0.9592和0.8516。结论 本文所构建的快速预测模型能够对不同产地的莲子的多糖含量和抗氧化活性进行快速预测, 为评价莲子多糖含量和抗氧化活性提供了科学参考。
英文摘要:
      Objective To determine the content and antioxidant activity of lotus seed polysaccharide in five main producing areas, analyze and compare the quality differences of lotus seed in different provinces, and further establish a rapid prediction model of lotus seed polysaccharide by near infrared analysis technology. Methods The content of lotus seed polysaccharide was determined by phenol-sulfuric acid method. The antioxidant activity of lotus seeds was determined by scavenging rate of 1, 1-diphenyl-2-picozide radical (DPPH). The partial least squares method was used to construct a fast prediction model of lotus seed polysaccharide. Results The content and antioxidant activity of lotus seed polysaccharide from 5 producing areas were accurately determined. The accuracy of the fast prediction model for polysaccharide content and antioxidant activity was good, the root-mean-square error (RMSEC) of the training set was 0.0185, and the root-mean-square error of prediction (RMSEP) of the test set was 0.0236. The squares of the correlation coefficients of the training set and the test set reached 0.9592 and 0.8516, respectively. Conclusion The rapid prediction model constructed in this paper can quickly predict the polysaccharide content and antioxidant activity of lotus seeds from different producing areas, which provides a scientific reference for evaluating the polysaccharide content and antioxidant activity of lotus seeds.
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