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茶叶光谱与叶绿素、茶氨酸、茶多酚含量关系分析 被引量:7

Relationship between Tea Spectra and Contents of Chlorophyll,Theanine and Polyphenols
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摘要 利用茶叶反射光谱数据分析茶叶中有机物组分的含量,能够快速、无损地进行茶叶品质鉴定。选择浙江省丽水市松阳县和绍兴市越城区的4个茶叶品种的新叶、成熟叶和老叶的样本,进行了光谱测量和3种有机物组分(叶绿素、茶氨酸和茶多酚)的含量检测。然后利用最佳指数法选出了估算这3种有机物的最佳波段,建立了估算3种有机物含量的多元回归线性模型。最后,比较了多元散射校正变换、标准归一化变换、结合Savitzky-Golay滤波的一阶导数变换这3种不同的光谱数据预处理方法的估算结果的差异,并分析了敏感波段的产生原因。研究结果表明:利用茶叶光谱估算叶绿素含量的效果最好,模拟值与实测值之间R^2大于0.9;估算茶氨酸的效果次之,模拟值与实测值之间R^2约为0.7;估算茶多酚的效果最差,模拟值与实测值之间R^2仅为0.65左右。 It is a fast and nondestructive way to detect the foliar biochemistry of tea using reflectance spec- troscopy.To analyze the relationship between the spectra and the contents of foliar biochemistry,the spec- tra of young leaves, adult leaves and old leaves from four kinds of tea was measured, and corresponding contents of chlorophyll, total tea polyphenols and amino acids were obtained firstly. Then sensitive spec- trum wave bands were determined by Optimum Index Factor and linear models were established to predict the concentrations of the foliar biochemistry by multiple regression. At last, differences of three spectral preprocessing methods (multiple scattering correction, standard normal variation, Savitzky-Golay) in model building were discussed,and probable causes of the sensitive waves were analyzed.The results of this paper indicated that the accuracy was the highest when estimating the contents of chlorophyll, R2 could be as high as 0.9 between the estimated and measured contents of chlorophyll.Followed by the accuracy of theanine, R2 was about 0.7 between the estimated and measured contents. However, R2 was the lowest between the estimated and measured contents of polyphenols,only about 0.65.
作者 余涛 胡波 孙睿 金志凤 王岳飞 张蕾 徐伟燕 刘刚 Yu Tao Hu Bo Sun Rui Jin Zhifeng Wang Yuefei Zhang Lei Xu Weiyan Liu Gang(School of Geography ,Beijing Normal University ,Beijing 100875 ,China State Key Laboratory of Remote Sensing Science ,Beijing 100875 ,China Beijing Key Laboratory of Environmental Remote Sensing and Digital City ,Beijing 100875,China Zhejiang Climate Center, Hangzhou 310017 ,China College of Agriculture & Biotechnology ,Zhejiang University ,Hangzhou 310017 ,China Ningbo Meteorological Bureau, Ningbo 315012, China)
出处 《遥感技术与应用》 CSCD 北大核心 2016年第5期872-878,共7页 Remote Sensing Technology and Application
基金 公益性行业(气象)科研专项(GYHY201306037) 国家自然科学基金项目(41471349)
关键词 茶叶品质 光谱 有机物组分 敏感波段 Tea quality Spectral Foliar biochemistry Sensitive bands
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