检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
机构地区:[1]西北农林科技大学食品科学与工程学院,陕西杨凌712100
出 处:《食品科学》2014年第2期164-167,共4页Food Science
基 金:"十二五"国家科技支撑计划项目(2012BAD36B04)
摘 要:为实现中宁枸杞子产地的自动化快速鉴别,利用近红外光谱仪对不同产地42个枸杞子样品进行扫描,对枸杞子近红外光谱分别进行距离判别分析和聚类分析,建立枸杞子产地判别模型。结果表明:在6500-5200cm-1波数范围内,采用多元散射校正和标准正态变量变换预处理,对样品的识别率均达到100%,模型预测效果好;采用马氏距离结合离差平方和法,枸杞子可分为宁夏中宁枸杞和非宁夏中宁枸杞两大类群,样品判别率达到96.9%。利用近红外光谱对中宁枸杞子产地判别分析是可行的。To develop an automatic and quick method to discriminate the geographical origin of Chinese wolfberry from Zhongning, 42 Chinese wolfberry samples from different regions in China were scanned with a near infrared spectrometer (NIR). The NIR spectral data of wotfberry samples were analyzed with distance discriminant analysis (DDA) and cluster analysis to discriminate their geographical origins. The DDA analysis indicated that good prediction results were achieved with 100% recognition rate for the origin of wolfberry based on the multiplicative scatter correction and standard normal variate transformation of spectral data ranging from 6 500 to 5 200 cm-1. The wolfberry samples could be clustered into two groups using the Mahalanobis distances in combination with the Ward's method: one group consisting of those from Zhongning, Ningxia and the other from other regions. The recognition rate was 96.9%. In conclusion, it is feasible to apply NIR to discriminate the geographical origin of Chinese wolfberry from Zhongning.
分 类 号:TS255.2[轻工技术与工程—农产品加工及贮藏工程]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.249