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作 者:彭丹[1] 杨嘉盛 史翠熠 陈名扬 PENG Dan;YANG Jia-sheng;SHI Cui-yi;CHEN Ming-yang(College of Food Science and Engineering,Henan University of Technology,Zhengzhou 450001,Henan,China)
机构地区:[1]河南工业大学粮油食品学院,河南郑州450001
出 处:《粮食与油脂》2022年第8期142-146,共5页Cereals & Oils
基 金:河南省科技攻关项目(212102110341);国家自然科学基金项目(31671818)。
摘 要:采用近红外光谱技术结合化学计量学方法建立葵花籽含油量及水分含量的分析模型,比较不同的光谱预处理方法、波段及建模方法对预测效果的影响。结果表明:含油量和水分含量的光谱范围分别为780~2500 nm和1300~1630 nm,预处理方法均采用多元散射校正(MSC)+正交信号校正(OSC),建模方法均为偏最小二乘法(PLS),模型的交互验证均方根误差(RMSECV)分别为1.9632和0.0796,决定系数R^(2)均大于0.87,分析结果接近常规化学方法,能够满足实际检测需要。The analysis model of oil content and moisture content of sunflower seed was established by using near infrared spectroscopy combined with chemometrics,and the effects of different spectral pretreatment methods,bands and modeling methods on the prediction results were compared.The results showed that the spectral ranges of oil content and moisture content were 780-2500 nm and 1300-1630 nm,respectively.Multiple scatter correct(MSC)+orthogonal signal correction(OSC)was used as pretreatment method,and partial least square(PLS)was used as modeling method.The root mean square error of cross validation(RMSECV)of the model were 1.9632 and 0.0796,respectively,and the determination coefficient(R^(2))was greater than 0.87.The analysis results were close to conventional chemical methods,which could met the actual detection needs.
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