Cowpea (Vigna unguiculata (L.) Walp), a legume crop that is grown in the worldwide, provides beneficial proteins for human consumption and animal feeding. In comparison, Rapid N analyzer as traditional method, has bee...Cowpea (Vigna unguiculata (L.) Walp), a legume crop that is grown in the worldwide, provides beneficial proteins for human consumption and animal feeding. In comparison, Rapid N analyzer as traditional method, has been widely used to measure protein content through the percentage of total nitrogen in the seed’s grounded powder. Near-Infrared Reflectance (NIR) has commonly been used to measure protein content in soybean seeds using whole grain without the need of seed grinding, which makes it possible to obtain fast results at a lower cost-per-analysis than the traditional combustion method. The specific objective of this study is to test a rapid method for measuring cowpea seed protein content by the NIR analyzer comparing to the traditional rapid N analyzer. A total of 240 cowpea genotypes were used in this study, including six seed coat colors, black, blackeye, browneye, cream, pinkeye, and red with 40 cowpea genotypes. The results showed that a linear relationship exists between the NIR analyzer and the Rapid N analyzer in the six different color groups. The correlation efficiency (r) between the seed protein contents from NIR and Rapid N was higher for pinkeye seed (r = 0.867), blackeye (0.771), cream (0.729), browneye (0.700), and red (0.623), respectively, but lower for black seeds, indicating that the NIR analyzer can be used to measure protein content for cowpea seeds with the five types of seed coat except black. Overview, the cowpea seed protein content measured from the NIR analyzer showed a little higher seed protein content. A series of regression models with different seed coat color have been built to adjust to protein content of colorful cowpea seeds from the NIR analyzer. But, it is not recommended to use for black color seeds due to a very low correlation efficiency (r) value with 0.184.展开更多
为实现灵芝提取物和云芝提取物的自动化快速鉴别,利用近红外光谱仪对灵芝提取物和云芝提取物进行近红外光谱分析,根据正确率和均值离差平方和(Average of Sum of Differ-ence Square,ASDS)确定最佳预处理方法,建立距离匹配(Distance Mat...为实现灵芝提取物和云芝提取物的自动化快速鉴别,利用近红外光谱仪对灵芝提取物和云芝提取物进行近红外光谱分析,根据正确率和均值离差平方和(Average of Sum of Differ-ence Square,ASDS)确定最佳预处理方法,建立距离匹配(Distance Match,DM)判别分析模型.结果表明:在全波长范围内,采用FD和MSC+FD预处理,在建模集中,对样品的识别率达到90.79%,模型预测效果好;在外部验证中,验证的识别率达到100%,具有很强的应用性.上述结果表明:利用近红外光谱和均值离差平方和,得出经过一阶导数处理的光谱,在DM模型对灵芝和云芝提取物分类中是可行的.展开更多
文摘Cowpea (Vigna unguiculata (L.) Walp), a legume crop that is grown in the worldwide, provides beneficial proteins for human consumption and animal feeding. In comparison, Rapid N analyzer as traditional method, has been widely used to measure protein content through the percentage of total nitrogen in the seed’s grounded powder. Near-Infrared Reflectance (NIR) has commonly been used to measure protein content in soybean seeds using whole grain without the need of seed grinding, which makes it possible to obtain fast results at a lower cost-per-analysis than the traditional combustion method. The specific objective of this study is to test a rapid method for measuring cowpea seed protein content by the NIR analyzer comparing to the traditional rapid N analyzer. A total of 240 cowpea genotypes were used in this study, including six seed coat colors, black, blackeye, browneye, cream, pinkeye, and red with 40 cowpea genotypes. The results showed that a linear relationship exists between the NIR analyzer and the Rapid N analyzer in the six different color groups. The correlation efficiency (r) between the seed protein contents from NIR and Rapid N was higher for pinkeye seed (r = 0.867), blackeye (0.771), cream (0.729), browneye (0.700), and red (0.623), respectively, but lower for black seeds, indicating that the NIR analyzer can be used to measure protein content for cowpea seeds with the five types of seed coat except black. Overview, the cowpea seed protein content measured from the NIR analyzer showed a little higher seed protein content. A series of regression models with different seed coat color have been built to adjust to protein content of colorful cowpea seeds from the NIR analyzer. But, it is not recommended to use for black color seeds due to a very low correlation efficiency (r) value with 0.184.
文摘为实现灵芝提取物和云芝提取物的自动化快速鉴别,利用近红外光谱仪对灵芝提取物和云芝提取物进行近红外光谱分析,根据正确率和均值离差平方和(Average of Sum of Differ-ence Square,ASDS)确定最佳预处理方法,建立距离匹配(Distance Match,DM)判别分析模型.结果表明:在全波长范围内,采用FD和MSC+FD预处理,在建模集中,对样品的识别率达到90.79%,模型预测效果好;在外部验证中,验证的识别率达到100%,具有很强的应用性.上述结果表明:利用近红外光谱和均值离差平方和,得出经过一阶导数处理的光谱,在DM模型对灵芝和云芝提取物分类中是可行的.
