摘要
利用近红外光谱仪采集木薯近红外光谱数据,对数据进行多元散射校正(MSC)进行偏最小二乘法的运算,采用微分法进行求导,确定最佳的校准曲线处理参数,开发出木薯的检测模型。验证表明,检测模型水分标准差SEP值为0.15%,淀粉标准差SEP值为0.56%,准确性、重复性验证结果均能满足标准要求。
Near-infrared spectroscopy（NIRS） was used to collect near-infrared spectroscopy data of cassava. The data were corrected by multivariate scatter calibration（MSC）, partial least square method and differential method were used to derive the best calibration curve parameters,development of a test model for cassava. The results showed that the standard deviation SEP of the model was 0.15% and the standard deviation of starch SEP was 0.56%. The accuracy and repeatability of the test results could meet the standard requirements.
出处
《现代食品》
2018年第1期76-78,共3页
Modern Food
关键词
近红外光谱技术
检测模型
木薯
水分
淀粉
Near infrared spectroscopy
Detection model
Cassava
Water content
Starch
